DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claim 1 is cancelled.
Claims 2-21 are newly added.
Claims 2-21 are currently pending and examined on the merits.
Priority
The instant application is a CON of 16/757,267 filed on 4/17/2020 which claims priority to U.S. Provisional Application 62/574,364 filed on 10/19/2017. At this point in examination, the effective filing date of claims 2-21 is 10/19/2017.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 10/24/2023 and 3/17/2026 are in compliance with the provisions of 37 CFR 1.97. A signed copy of the corresponding 1449 form has been included with this Office Action.
Claim Objections
Claim 4 is objected to because of the following informalities:
In claim 4, line 3, "correspond" should read "corresponding".
Appropriate correction is required.
Claim Interpretation - 35 USC § 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
A: "a preparation module, stored in the computer memory, wherein the preparation module is programmed to receive information identifying a plurality of candidate ligands and a template ligand-biomolecule structure comprising a template ligand and a biomolecule" in claims 15 and 18-19.
B: “a pharmacophore matcher module, stored in the computer memory, wherein the pharmacophore matcher module is programmed to identify a pharmacophore match between the template ligand and each of the plurality of candidate ligands by comparing the pharmacophore model of the template ligand to the pharmacophore model of a corresponding candidate ligand of the plurality of candidate ligands” in claims 15 and 19.
C: “a docking module, stored in computer memory, wherein the docking module is programmed to predict, for the corresponding candidate ligand, a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule” in claims 15-16 and 18-19.
D: “a ranking module, stored in the computer memory, wherein the ranking module is programmed to rank each altered ligand-biomolecule structure using a scoring function and output the ranked list” in claim 15.
E: “a biomolecule modification module, stored in the computer memory, wherein the biomolecule modification module is programmed to modify atomic coordinates of the biomolecule to reduce clashes between the docked ligand position's atomic coordinates and the biomolecule's atomic coordinates, thereby creating an altered ligand-biomolecule structure having an altered biomolecule and a docked candidate ligand” in claims 17-18.
The limitations use generic placeholder “module” coupled with functional language “programmed to”, without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier. A module of a system can be interpreted as either a software or hardware element. Use of the terms “preparation”, “pharmacophore matcher”, “docking”, “ranking”, and “biomolecule modification”, nor the functional language of the claims recite sufficient description to clarify the structure necessary to perform the claimed function in the instant claims.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f), they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
Para. [0056] of the instant specification indicates that the modules are computer-implemented. MPEP 2181.II.B. indicates that for computer-implemented means-plus-function limitations, the structure is an algorithm coupled with a microprocessor or computer. The above paragraph provides support for the processor or computer. The individual algorithms for each 112(f) invocation are detailed as follows:
A: “a preparation module” – para. [0057]-[0061] of the instant specification describes components of the preparation module that allows the preparation module to receive information identifying candidate ligands and a template ligand-biomolecule structure. For example, it comprises of a conformational sampling module that samples viable three-dimensional conformations of the template ligand-biomolecule complex. Therefore, the instant specification discloses the specific steps of an algorithm that performs receiving information identifying candidate ligands and a template ligand-biomolecule structure. Thus, the description in the specification for the preparation module has adequate corresponding structure.
B: “a pharmacophore matcher module” – para. [0062]-[0064] of the instant specification describes using a pharmacophore generator to generate pharmacophores for a template ligand and a target ligand, and using a pharmacophore match detector comprising any number of algorithms to detect common pharmacophores between the models of the template ligand and the target ligand. Therefore, the instant specification discloses specific steps of an algorithm that performs identifying a pharmacophore match between a template ligand and candidate ligands. Thus, the description in the specification for the pharmacophore matcher module has adequate corresponding structure.
C: “a docking module” – The instant specification does not disclose the specific steps of an algorithm that predicts a docked ligand position by overlapping the pharmacophore models of the candidate ligand and the template ligand while the template ligand is in the binding site of the biomolecule. Thus, the description in the specification for the claimed docking module does not satisfy the requirements under 35 U.S.C. 112(a) and (b); see below.
D: “a ranking module” – The instant specification does not disclose the specific steps of an algorithm that ranks each altered ligand-biomolecule structure using a scoring function and outputting the ranked list. Thus, the description in the specification for the claimed ranking module does not satisfy the requirements under 35 U.S.C. 112(a) and (b); see below.
E: “a biomolecule modification module” – para. [0067]-[0069] of the instant specification talks about components used to alleviate or resolve clashes between a target ligand and a biomolecule. For example, it comprises of a minimizer, which alleviates clashes by performing energetic minimization using classical molecular mechanics forcefields to move the specific atoms in the biomolecule that clash with the target ligand. Therefore, the instant specification discloses the specific steps of an algorithm that performs modifying atomic coordinates of the biomolecule to reduce clashes between the docked ligand and the biomolecule. Thus, the description in the specification for the biomolecule modification module has adequate corresponding structure.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f), applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f).
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 15-16 and 18-19 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor at the time the application was filed, had possession of the claimed invention.
Claims
Claim 15 recites “a ranking module, stored in the computer memory, wherein the ranking module is programmed to rank each altered ligand-biomolecule structure using a scoring function and output the ranked list” which has been interpreted to invoke 35 U.S.C. 112(f).
For a computer-implemented 35 U.S.C. 112(f) claim limitation, the specification must disclose an algorithm for performing the claimed specific computer function, or else the claim is indefinite under 35 U.S.C. 112(b). When a claim containing a computer-implemented 35 U.S.C. 112(f) claim limitation is found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure (e.g., the computer and the algorithm) in the specification that performs the entire claimed function, it will also lack written description under 35 U.S.C. 112(a). See MPEP § 2163.03, subsection VI.
In this case, para. [0056] of the instant specification indicates that the modules are computer-implemented. This suggests that modules such as the docking module (claims 15-16 and 18-19) and ranking module (claim 15) are associated with a computer or processor to carry out its functions. However, the specific steps of the algorithm to perform the functions are not recited in the specification.
While one of ordinary skill in the art could be capable of writing software for an algorithm which predicts a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule (claims 15-16 and 18-19) and ranks each altered ligand-biomolecule structure using a scoring function and outputs the ranked list (claim 15), the understanding of one skilled in the art does not relieve the patentee of the duty to disclose sufficient structure to support means-plus-function claim terms.
For the reasons discussed above, the specification does not provide a sufficient disclosure of the limitations of “predict, for the corresponding candidate ligand, a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule” recited in claims 15-16 and 18-19, and “rank each altered ligand-biomolecule structure using a scoring function and outputs the ranked list” recited in claim 15 to demonstrate to one of ordinary skill in the art that the inventor possessed the invention at the time the application was filed. For more information regarding the written description requirement, see MPEP §2161.01 - §2164.07(b).
Because dependent claims 17 and 20-21 incorporate the unsupported limitations of independent claims 15 and 19 and do not include further limitations that correct the issue, they are likewise rejected under 35 U.S.C. 112(a).
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 15-16 and 18-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The following claim limitations invoke 35 U.S.C. 112(f):
Claims 15-16 and 18-19 recite “a docking module, stored in computer memory, wherein the docking module is programmed to predict, for the corresponding candidate ligand, a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule”.
Claim 15 recites “a ranking module, stored in the computer memory, wherein the ranking module is programmed to rank each altered ligand-biomolecule structure using a scoring function and output the ranked list”.
However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function.
As described above, para. [0056] of the instant specification indicates that the modules are computer-implemented. This suggests that modules such as the docking module (claims 15-16 and 18-19) and ranking module (claim 15) are associated with a computer or processor to carry out its functions. However, the specific steps of the algorithm to perform the functions are not recited in the specification.
Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b).
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 2-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1: Claims 2-14 are directed to a rational drug design method (process). Claims 15-18 are directed to a system (machine). Claims 19-21 are directed to a non-transitory computer-readable storage medium (machine). Therefore, these claims are encompassed by the categories of statutory subject matter, and thus satisfy the subject matter eligibility requirements under Step 1.
[Step 1: YES]
Eligibility Step 2A: First, it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A, Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth described in the claim.
Claims 2, 5-9, 11, and 14-21 recite the following steps which fall within the mental processes and/or mathematical concepts groups of abstract ideas, as noted below.
Independent claim 2 further recites:
identifying a plurality of candidate ligands for bonding to a biomolecular target, the target ligands being candidates for a drug associated with modifying a function of the biomolecular target (i.e., mental processes);
comparing, using the computer system, a pharmacophore model of the template ligand to a pharmacophore model of the corresponding candidate ligand (i.e., mental processes);
overlapping, using the computer system, the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecular target (i.e., mental processes);
predicting the docked position of the corresponding candidate ligand in the binding site of the biomolecular target based on a position of the pharmacophore model of the corresponding candidate ligand when overlapped with the pharmacophore model of the template ligand (i.e., mental processes).
Dependent claim 5 further recites:
wherein predicting the docked position of the corresponding candidate ligand in the binding site of the biomolecule comprises ignoring at least one clash between the corresponding candidate ligand conformations' atomic coordinates and the biomolecule's atomic coordinates (i.e., mental processes).
Dependent claim 6 further recites:
for each candidate ligand conformation, modifying atomic coordinates of the biomolecule to reduce clashes between the docked candidate ligand conformations' atomic coordinates and the biomolecule's atomic coordinates, thereby creating an altered ligand-biomolecule structure comprising the docked candidate ligand and an altered biomolecule (i.e., mental processes).
Dependent claim 7 further recites:
predicting a re-docked position of each candidate ligand conformation by predicting each candidate ligand conformation's position in the binding site of the altered biomolecule (i.e., mental processes);
for each candidate ligand conformation, modifying atomic coordinates of the altered biomolecule to reduce clashes between the atomic coordinates of the candidate ligand conformation's re-docked position and the atomic coordinates of the altered biomolecule, thereby creating a re-altered ligand-biomolecule structure comprising a re-docked candidate ligand and a re-altered biomolecule (i.e., mental processes).
Dependent claim 8 further recites:
wherein providing the ranked list comprises ranking each altered and re-altered ligand-biomolecule structure using a scoring function (i.e., mental processes).
Dependent claim 9 further recites:
wherein the providing the ranked list comprises identifying, using the computer system, a subset of high-ranking candidate ligands corresponding to candidate ligands having a threshold value for an empirical activity (i.e., mental processes).
Dependent claim 11 further recites:
selecting, based on the ranked list, one or more of the plurality candidate ligands for synthesis and assaying (i.e., mental processes).
Dependent claim 14 further recites:
identifying a clinical candidate from the ranked list of candidate ligands based on the at least one assay (i.e., mental processes).
Independent claim 15 further recites:
a pharmacophore matcher module, stored in the computer memory, wherein the pharmacophore matcher module is programmed to identify a pharmacophore match between the template ligand and each of the plurality of candidate ligands by comparing the pharmacophore model of the template ligand to the pharmacophore model of a corresponding candidate ligand of the plurality of candidate ligands (i.e., mental processes);
a docking module, stored in computer memory, wherein the docking module is programmed to predict, for the corresponding candidate ligand, a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule (i.e., mental processes);
a ranking module, stored in the computer memory, wherein the ranking module is programmed to rank each altered ligand-biomolecule structure using a scoring function and output the ranked list (i.e., mental processes).
Dependent claim 16 further recites:
wherein the docking module is programmed to ignore at least one clash between the corresponding candidate ligand's atomic coordinates and the biomolecule's atomic coordinates when predicting the docked ligand position (i.e., mental processes).
Dependent claim 17 further recites:
a biomolecule modification module, stored in the computer memory, wherein the biomolecule modification module is programmed to modify atomic coordinates of the biomolecule to reduce clashes between the docked ligand position's atomic coordinates and the biomolecule's atomic coordinates, thereby creating an altered ligand-biomolecule structure having an altered biomolecule and a docked candidate ligand (i.e., mental processes).
Dependent claim 18 further recites:
wherein the preparation module is programmed to enumerate a plurality of potential candidate ligand structural conformations for the at least one candidate ligand, and each of the enumerated potential candidate ligand structural conformations is processed by the docking module and the biomolecule modification module (i.e., mental processes).
Independent claim 19 further recites:
identifying a pharmacophore match between the template ligand and the corresponding candidate ligand, using a pharmacophore matcher module stored in the computer memory and coupled to at the least one computer processor, wherein the identifying of the pharmacophore match further comprises comparing a pharmacophore model of the template ligand to a pharmacophore model of the corresponding candidate ligand (i.e., mental processes);
predicting a docked ligand position of the target ligand, using a docking module stored in the computer memory and coupled to the at least one computer processor, wherein the docking module predicts the docked position of the corresponding candidate ligand in the binding site of the biomolecule based on a position of the pharmacophore model of the corresponding candidate ligand when overlapped with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule (i.e., mental processes).
Dependent claim 20 further recites:
wherein selecting the plurality of candidate ligands comprises comparing the pharmacophore model of the template ligand to a pharmacophore model of each respective one of the plurality of candidate ligands (i.e., mental processes).
Dependent claim 21 further recites:
wherein the step of predicting an initial docked position comprises ignoring at least one clash between the corresponding candidate ligand's atomic coordinates and the biomolecule's atomic coordinates (i.e., mental processes).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. Dependent claim 4 recites information further limiting the judicial exceptions indicated above.
Therefore, claims 2, 5-9, 11, and 14-21 recite an abstract idea.
[Step 2A, Prong One: YES]
Eligibility Step 2A, Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that, when examined as a whole, integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A, Prong One are not integrated into a practical application because of the reasons noted below.
Claim 10 recites synthesizing one or more target ligands from the ranked list. Claim 12 recites synthesizing the one or more selected candidate ligands to provide one or more synthesized candidate ligands. Synthesizing ligands is considered a well-understood, routine, and conventional activity. Data gathering steps are extra-solution activity as they collect the data needed to carry out the JE. It does not impose any meaningful limitation on the JE or how the JE is performed (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.). Therefore, the claimed additional elements do not integrate the abstract ideas into a practical application.
Claim 13 recites performing at least one assay of the one or more synthesized candidate ligands. Performing an assay is a well-understood, routine, and conventional activity. Data gathering steps are extra-solution activity as they collect the data needed to carry out the JE. It does not impose any meaningful limitation on the JE or how the JE is performed (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.). Therefore, the claimed additional elements do not integrate the abstract ideas into a practical application.
Claims 2-3, 15, and 19 recite the additional non-abstract elements of data gathering:
receiving, by the computer system, a template ligand-biomolecule structure, the template ligand-biomolecular structure comprising a template ligand docked in the binding site of the biomolecular target (claim 2);
providing, using the computer system, a ranked list of the plurality of candidate ligands (claim 2);
receiving a plurality of template ligand-biomolecule structures, each template ligand-biomolecule structure having a different template ligand docked in the binding site of the biomolecule (claim 3);
generating the pharmacophore model of the template ligand by combining information from each of the template ligands from the plurality of template ligand-biomolecule structures (claim 3);
a preparation module, stored in the computer memory, wherein the preparation module is programmed to receive information identifying a plurality of candidate ligands and a template ligand-biomolecule structure comprising a template ligand and a biomolecule (claim 15);
receiving information identifying a corresponding ligand of the plurality candidate ligands and a template ligand-biomolecule structure, using a preparation module stored in computer memory and coupled to at least one computer processor, the template ligand-biomolecule structure comprising a template ligand docked in the binding site of the biomolecule (claim 19).
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data needed to carry out the JE. The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception. (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.).
Claims 15 and 19 recite the additional non-abstract element (EIA) of a general-purpose computer system or parts thereof:
a system comprising a processor and a memory (claim 15);
a non-transitory computer readable storage medium (claim 19).
The EIA do not provide any details of how specific structures of the computer elements are used to implement the JE. The claims require nothing more than a general-purpose computer to perform the functions that constitute the judicial exceptions. The computer elements of the claims do not provide improvements to the functioning of the computer itself (as in DDR Holdings, LLC v. Hotels.com LP); they do not provide improvements to any other technology or technical field (as in Diamond v. Diehr); nor do they utilize a particular machine (as in Eibel Process Co. v. Minn. & Ont. Paper Co.). Hence, these are mere instructions to apply the JE using a computer, and therefore the claim does not recite integrate that JE into a practical application.
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 2-21 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application. Claims 2-3, 10, 12-13, 15, and 19 contain additional elements that would not integrate a judicial exception into a practical application and are further probed for inventive concept in Step 2B.
[Step 2A, Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
With respect to claims 2-3, 15, and 19: The limitations identified above as non-abstract elements (EIA) related to data gathering do not rise to the level of significantly more than the judicial exception. Activities such as data gathering do not improve the functioning of a computer, or comprise an improvement to any other technical field. The limitations do not require or set forth a particular machine, they do not affect a transformation of matter, nor do they provide an unconventional step (citing McRO and Trading Technologies Int’l v. IBG). Data gathering steps constitute a general link to a technological environment. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp.,).
With respect to claims 15 and 19: The limitations identified above as non-abstract elements (EIA) related to general-purpose computer systems do not rise to the level of significantly more than the judicial exception. These elements do not improve the functioning of the computer itself, or comprise an improvement to any other technical field (Trading Technologies Int’l v. IBG, TLI Communications). They do not require or set forth a particular machine (Ultramercial v. Hulu, LLC., Alice Corp. Pty. Ltd v. CLS Bank Int’l), they do not affect a transformation of matter, nor do they provide an unconventional step. Simply appending well understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp., CyberSource v. Retail Decisions, Parker v. Flook, Versata Development Group v. SAP America).
The additional elements of synthesizing one or more target ligands from the ranked list (claim 10) and synthesizing the one or more selected candidate ligands to provide one or more synthesized candidate ligands (claim 12) are conventional. Evidence for conventionality is shown by Kasting et al. (Journal of Chemical Education, 2015, 92(6), 1103-1109). Kasting et al. reviews “Organic chemistry students prepare a series of amine-bis(phenols) via a Mannich reaction” (pg. 1103, Abstract, lines 3-5). Also, further reviews that “the ligand synthesis experiment is typically carried out toward the end of a second-year organic chemistry course (pg. 1105, col. 1, para. 1, lines 1-4). This shows synthesizing ligands, which makes it a conventional practice in the art.
The additional element of performing at least one assay of the one or more synthesized candidate ligands (claim 13) is conventional. Evidence for conventionality is shown by Anderson (Chemistry & Biology, 2003, 10(9), 787-797); refer to as Anderson [A]. Anderson [A] reviews “purchase or synthesize lead and test for binding in biochemical assays” (pg. 788, Figure 1). Also, further reviews “Structure-based drug design methods increase the chance that a “hit” will be found in the top-ranked ligands” (pg. 794, col. 2, para. 3, lines 16-18). This shows performing an assay on synthesized ligand compounds, which makes it a conventional practice in the art.
[Step 2B: NO]
Therefore, claims 2-21 are patent ineligible under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 2, 4, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bemis et al. [US7826979B2], in view of Anderson (Methods in Molecular Biology, 2013, 823, 359-366); refer to as Anderson [B].
With respect to claim 2:
Regarding the recited identifying a plurality of candidate ligands for bonding to a biomolecular target, the target ligands being candidates for a drug associated with modifying a function of the biomolecular target, Bemis et al. discloses providing query ligands, which can be modeled with a target macromolecule in a complex formation at different stages of ligand design such as modeling structures of query ligands having chemical properties suitable for drug development (pg. 17, col. 1, lines 35-39 and line 63; pg. 20, col. 8, lines 30-35). The query ligand can also be an inhibitor of the target macromolecule (pg. 17, col. 1, lines 58-59). This teaches candidate ligands for bonding to a biomolecular target that could be candidates for a drug associated with modifying a function of the biomolecular target.
Regarding the recited predicting, using a computer system, a plurality of target ligand-biomolecule structures each comprising a corresponding candidate ligand of the plurality of candidate ligands and the biomolecular target with the corresponding candidate ligand being in a docked position in a binding site of the biomolecular target, Bemis et al. discloses modeling the scaffold or pharmacophore of query ligands with target macromolecules, where the query ligands can be docked into the binding site of the target macromolecule of interest (pg. 19, col. 6, lines 23-31; pg. 22, col. 11, lines 25-35). This teaches predicting ligand-biomolecule structures, which comprises candidate ligands in docked positions in a binding site of the biomolecular target.
Regarding the recited receiving, by the computer system, a template ligand-biomolecule structure, the template ligand-biomolecular structure comprising a template ligand docked in the binding site of the biomolecular target, Bemis et al. discloses a set of 3D structural models, each comprising a comparison ligand and a comparison macromolecule (pg. 17, col. 2, lines 60-65). Ligand frameworks extracted from protein-ligand complexes structurally related to the target complex are employed as ligand templates for model building (pg. 19, col. 6, lines 14-17 and lines 31-33). This teaches comparison ligand-biomolecule structures comprising comparison ligands docked in their respective biomolecular targets.
Regarding the recited comparing, using the computer system, a pharmacophore model of the template ligand to a pharmacophore model of the corresponding candidate ligand, Bemis et al. discloses comparing the scaffolds of query ligands to scaffolds of known ligands, where the scaffolds can be pharmacophores (pg. 19, col. 6, lines 37-42; pg. 25, col. 17, lines 32-39). This teaches comparing pharmacophore models between a template ligand and a candidate ligand.
Regarding the recited overlapping, using the computer system, the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecular target, Bemis et al. discloses superimposing the scaffold of the query ligand onto the scaffold of the comparison ligand, where the scaffolds can be pharmacophores (pg. 19, col. 6, lines 37-48; pg. 23, col. 13, lines 14-16). Also, further discloses the comparison ligand can be docked into the target macromolecule of interest (pg. 19, col. 6, lines 47-48). This teaches overlapping pharmacophore models of the candidate ligand with the template ligand while the template ligand is bound to the target macromolecule.
Regarding the recited predicting the docked position of the corresponding candidate ligand in the binding site of the biomolecular target based on a position of the pharmacophore model of the corresponding candidate ligand when overlapped with the pharmacophore model of the template ligand, Bemis et al. discloses assigning atomic coordinates from the mapped scaffolds between the query ligand and the comparison ligand to the corresponding atoms of the query ligand, which are then used to position the query ligand in the target protein kinase (pg. 19, col. 6, lines 37-48; pg. 23, col. 13, lines 14-16; pg. 25, col. 17, lines 50-56). This teaches predicting the docked position of a candidate ligand in a biomolecular target based on the overlapped pharmacophore models between the candidate ligand and the template ligand.
Bemis et al. does not disclose providing, using the computer system, a ranked list of the plurality of candidate ligands.
However, Anderson [B] discloses identifying binding modes of ligands in the structure of a target and scoring their docked positions, producing a ranked list of ligands (pg. 359-360, para. 2, lines 3-7). This teaches a ranked list of candidate ligands.
It would have been prima facie obvious to one of ordinary skill in the art to combine predicting target ligand-biomolecule structures disclosed by Bemis et al. with providing a ranked list of ligands disclosed by Anderson [B]. One would be motivated to combine prediction of ligand-biomolecule structures with a ranked list of ligands because Anderson [B] discloses that the speed of structure-based drug design (SBDD) is rapid relative to in vitro screening and the cost of the process is relatively low (pg. 359, para. 1, lines 5-9). This means predicting ligand-biomolecule structures will be rapid and less costly when combined with generating a ranked list of ligands. There is a likelihood of success, since both methods taught are of molecular docking or design, which are well known techniques in the field of computational chemistry.
With respect to claim 4:
Anderson [B] does not disclose wherein at least one of the plurality of candidate ligands has more than one structural conformation in its unbound state, and the docked position of the correspond candidate ligand in the binding site of the biomolecule is predicted by enumerating a set of potential candidate ligand conformations.
However, Bemis et al. discloses defining a set of fixed and flexible bonds of a query ligand and performing a conformational search to model various 3D conformations of the query ligand (pg. 22, col. 12, lines 1-7). This teaches flexible bonds of a candidate ligand, which suggests that the ligand is in its unbound state and has more than one conformation. These potential ligand conformations are enumerated by performing a conformational search.
Anderson [B] does not disclose overlapping a respective pharmacophore model of the candidate ligand for each of the potential candidate ligand conformations with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule.
However, Bemis et al. discloses superimposing the scaffold of the query ligand onto the scaffold of the comparison ligand, where the scaffolds can be pharmacophores (pg. 19, col. 6, lines 37-48; pg. 23, col. 13, lines 14-16). Also, further discloses the comparison ligand can be docked into the target macromolecule of interest (pg. 19, col. 6, lines 47-48). This teaches overlapping pharmacophore models of the candidate ligand with the template ligand while the template ligand is bound to the target macromolecule.
With respect to claim 19:
Claim 19 recites a non-transitory computer readable storage medium.
Broadly claiming an automated means to replace a manual function to accomplish the same result does not distinguish over the prior art. See Leapfrog Enters., Inc. v. Fisher-Price, Inc., 485 F .3d 1157, 1161, 82 USPQ2d 1687, 1691 (Fed. Cir. 2007) (“Accommodating a prior art mechanical device that accomplishes [a desired] goal to modern electronics would have been reasonably obvious to one of ordinary skill in designing children’s learning devices. Applying modern electronics to older mechanical devices has been commonplace in recent years.”); In re Venner, 262 F. 2d 91, 95, 120 USPQ 193, 194 (CCPA 1958); see also MPEP § 2144.04. Furthermore, implementing a known function on a computer has been deemed obvious to one of ordinary skill in the art if the automation of the known function on a general purpose computer is nothing more than the predictable use of prior art elements according to their established functions. KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417, 82 USPQ2d 1385, 1396 (2007); see also MPEP § 2143, Exemplary Rationales D and F. Likewise, it has been found to be obvious to adapt an existing process to incorporate Internet and Web browser technologies for communicating and displaying information because these technologies had become commonplace for those functions. Muniauction, Inc. v. Thomson Corp., 532 F.3d 1318, 1326-27, 87 USPQ2d 1350, 1357 (Fed. Cir. 2008).
Bemis et al. does not disclose wherein the computer readable program when executed on a computer causes the computer to rank a plurality of candidate ligands for selection for synthesis and assaying in a rational drug design method, the ranking being based on predicting a docked position for each of the plurality of candidate ligands in a binding site of a biomolecule.
However, Anderson [B] discloses using software to identify binding modes of ligands in the structure of a target and scoring their docked positions, producing a ranked list of ligands (pg. 359-360, para. 2, lines 3-7; pg. 363-364, para. 7). Top-scoring molecules from this ranked list are synthesize, which are further evaluated in the laboratory using in vitro assays with a target (pg. 360, para. 1, lines 1-3; pg. 363-364, para. 7). This teaches using a computer to generate a ranked list of ligands based on predicted dock positions and selecting the top-scoring ligands from the ranked list for synthesis and assaying.
Anderson [B] does not disclose receiving information identifying a corresponding ligand of the plurality candidate ligands and a template ligand-biomolecule structure, using a preparation module stored in computer memory and coupled to at least one computer processor, the template ligand-biomolecule structure comprising a template ligand docked in the binding site of the biomolecule.
However, Bemis et al. discloses a computer comprising a memory that stores instructions for identifying a substructure of the query ligand and comparison ligands in a set of 3D structural models, where each 3D structural model comprises a comparison ligand and a comparison macromolecule (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of identifying candidate ligands and a template ligand-biomolecule structure comprising a template ligand docked in the binding site of a biomolecule.
Anderson [B] does not disclose identifying a pharmacophore match between the template ligand and the corresponding candidate ligand, using a pharmacophore matcher module stored in the computer memory and coupled to at the least one computer processor, wherein the identifying of the pharmacophore match further comprises comparing a pharmacophore model of the template ligand to a pharmacophore model of the corresponding candidate ligand.
However, Bemis et al. discloses comparing the scaffolds of query ligands to scaffolds of known ligands, where the scaffolds can be pharmacophores (pg. 19, col. 6, lines 37-42; pg. 25, col. 17, lines 32-39). Also, further discloses that this comparison leads to matching pharmacophores between a query ligand and a comparison ligand using a computer (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of identifying a pharmacophore match by comparing pharmacophore models between a template ligand and a candidate ligand.
Anderson [B] does not disclose predicting a docked ligand position of the target ligand, using a docking module stored in the computer memory and coupled to the at least one computer processor, wherein the docking module predicts the docked position of the corresponding candidate ligand in the binding site of the biomolecule based on a position of the pharmacophore model of the corresponding candidate ligand when overlapped with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule.
However, Bemis et al. discloses assigning atomic coordinates from the mapped scaffolds between the query ligand and the comparison ligand to the corresponding atoms of the query ligand, which are then used to position the query ligand in the target protein kinase (pg. 19, col. 6, lines 37-48; pg. 23, col. 13, lines 14-16; pg. 25, col. 17, lines 50-56). Also, further discloses the comparison ligand can be docked into the target macromolecule of interest (pg. 19, col. 6, lines 47-48). Bemis et al. discloses this assignation of atomic coordinates is performed using a computer (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of predicting the docked position of a candidate ligand based on the overlapped pharmacophore models between the candidate ligand and the template ligand.
With respect to claim 20:
Anderson [B] does not disclose wherein the plurality of candidate ligands are selected from a candidate ligand database, each of the plurality of candidate ligands being different from the template ligand, and wherein selecting the plurality of candidate ligands comprises comparing the pharmacophore model of the template ligand to a pharmacophore model of each respective one of the plurality of candidate ligands.
However, Bemis et al. discloses comparing pharmacophores of query ligands to pharmacophores of known ligands and identifying query ligands that share pharmacophores with comparison ligands (pg. 19, col. 6, lines 37-42). Also, further discloses query ligands being selected from a ligand database (pg. 20, col. 8, lines 50-56). This teaches selecting candidate ligands from a database by comparing pharmacophore models between a template ligand and a candidate ligand.
Claims 3 and 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Bemis et al. [US7826979B2] and Anderson [B] (Methods in Molecular Biology, 2013, 823, 359-366) as applied to claims 2, 4, and 19-20 above, in view of Wolber et al. (Journal of Chemical Information and Modeling, 2004, 45(1), 160-169).
Bemis et al. and Anderson [B] are applied to claims 2, 4, and 19-20 above.
With respect to claim 3:
Anderson [B] does not disclose receiving a plurality of template ligand-biomolecule structures, each template ligand-biomolecule structure having a different template ligand docked in the binding site of the biomolecule.
However, Bemis et al. discloses a set of 3D structural models, each comprising a comparison ligand and a comparison macromolecule (pg. 17, col. 2, lines 60-65). Ligand frameworks extracted from protein-ligand complexes structurally related to the target complex are employed as ligand templates for model building (pg. 19, col. 6, lines 14-17 and lines 31-33). This teaches comparison ligand-biomolecule structures comprising comparison ligands docked in their respective biomolecular targets.
Bemis et al. and Anderson [B] do not disclose generating the pharmacophore model of the template ligand by combining information from each of the template ligands from the plurality of template ligand-biomolecule structures.
However, Wolber et al. discloses deriving a common pharmacophore model of a ligand by merging the pharmacophore models of 1ncr, 1nd3, and 1c8m all containing Pleconaril bound to Rhinovirus subtype 16, which makes them human rhinovirus serotype 16 inhibitors (pg. 166, col. 2, para. 3; pg. 166, Figure 4). This teaches generating a pharmacophore model of a ligand by combining information of different ligands from a plurality of ligand-biomolecule structures.
It would have been prima facie obvious to one of ordinary skill in the art to modify the drug design method disclosed by Bemis et al. and Anderson [B] to incorporate generating a pharmacophore model of a template ligand disclosed by Wolber et al. One would be motivated to modify the drug design method to incorporate generation of a pharmacophore model because Wolber et al. discloses that by merging several selective pharmacophore models, the user can transparently enhance and adapt models, which were generated in a fully automated way (pg. 168, col. 2, para. 3, lines 11-14). This means that the pharmacophore models generated can be easily enhanced and are adaptable in the drug design method. There is a likelihood of success, since all teachings are of molecular docking or design, which are well known techniques in the field of computational chemistry.
With respect to claim 11:
Bemis et al. and Wolber et al. do not disclose selecting, based on the ranked list, one or more of the plurality candidate ligands for synthesis and assaying.
However, Anderson [B] discloses providing a ranked list of ligands and synthesizing the top-scoring ligands from the ranked list, which are further evaluated in the laboratory using in vitro assays with a target (pg. 363-364, para. 7). This teaches selecting ligands from a ranked list for synthesis and assaying.
With respect to claim 12:
Bemis et al. and Wolber et al. do not disclose synthesizing the one or more selected candidate ligands to provide one or more synthesized candidate ligands.
However, Anderson [B] discloses synthesizing the top-scoring ligands from a ranked list of ligands, which produces synthesized ligands further evaluated in the laboratory using in vitro assays with a target (pg. 363-364, para. 7). This teaches synthesizing ligands to provide synthesized ligands.
With respect to claim 13:
Bemis et al. and Wolber et al. do not disclose performing at least one assay of the one or more synthesized candidate ligands.
However, Anderson [B] discloses synthesizing top-scoring ligands from a ranked list of ligands, which are further evaluated in the laboratory using in vitro assays with a target (pg. 363-364, para. 7). This teaches performing assays on synthesized ligands.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Bemis et al. [US7826979B2], Anderson [B] (Methods in Molecular Biology, 2013, 823, 359-366), and Wolber et al. (Journal of Chemical Information and Modeling, 2004, 45(1), 160-169) as applied to claims 2-4, 11-13, and 19-20 above, in view of Hefti (BMC Neuroscience, 2008, 9(S7), 1-7).
Bemis et al., Anderson [B], and Wolber et al. are applied to claims 2-4, 11-13, and 19-20 above.
With respect to claim 14:
Bemis et al. and Wolber et al. do not disclose identifying a clinical candidate from the ranked list of candidate ligands based on the at least one assay.
However, Anderson [B] discloses compounds that succeed as hits in the laboratory assays are then subjected to further rounds of in silico screening (pg. 364, para. 2). These hits can be optimized, producing lead compounds that can be developed for drug-like properties, such as bioavailability, stability, and efficacy (pg. 360, para. 1, lines 3-10). This teaches identifying lead compounds from a ranked list of ligands based on assays.
Anderson [B] does not disclose identifying a clinical candidate.
However, Hefti discloses a drug discovery pathway for advancing an optimized lead compound to becoming a drug candidate suitable for clinical trials (pg. 6, Figure 1). This teaches determining clinical candidates from lead compounds.
It would have been prima facie obvious to one of ordinary skill in the art to combine identifying lead compounds disclosed by Bemis et al., Anderson [B], and Wolber et al. with determining clinical candidates from lead compounds disclosed by Hefti. One would have been motivated to combine identifying lead compounds with determining clinical candidates from lead compounds because Hefti discloses that mature drug discovery programs have a well-established critical path of in vitro and in vivo biologic assays by which chemicals are selected, and an optimized critical path allows the drug discovery researcher to select the best compound at each step without redundancies (pg. 3, col. 2, para. 3, lines 1-10). This means that the procedure for determining clinical candidates from lead compounds can be optimized for efficient selection of the clinical candidates. There is a likelihood of success, since all teachings are of molecular design or discovery, which are well known techniques in the field of computational chemistry.
Claims 5-8, 15-18, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Bemis et al. [US7826979B2] and Anderson [B] (Methods in Molecular Biology, 2013, 823, 359-366) as applied to claims 2, 4, and 19-20 above, in view of Sherman et al. (J Med. Chem., 2006, 49(2), 534-553), as provided in the IDS filed 10/24/2023.
Bemis et al. and Anderson [B] are applied to claims 2, 4, and 19-20 above.
With respect to claim 5:
Bemis et al. and Anderson [B] do not disclose wherein predicting the docked position of the corresponding candidate ligand in the binding site of the biomolecule comprises ignoring at least one clash between the corresponding candidate ligand conformations' atomic coordinates and the biomolecule's atomic coordinates.
However, Sherman et al. discloses docking ligands into a rigid receptor using a softened energy function so that steric clashes do not prevent at least one ligand pose, and increasing the Glide Coulomb-vdW energy cutoff filter to enable tolerance of more steric clashes (pg. 535, col. 1, para. 3, lines 9-12; pg. 538, para. 1, col. 1, line 10-12). This teaches using a softened energy function and increasing the energy cutoff filter so steric clashes have little to no effect on the binding between the ligand and the biomolecule, therefore ignoring the steric clashes.
It would have been prima facie obvious to one of ordinary skill in the art to modify the drug design method disclosed by Bemis et al. and Anderson [B] to incorporate ignoring clashes between ligands and biomolecules disclosed by Sherman et al. One would be motivated to incorporate ignoring clashes into the drug design method because the induced fit algorithm disclosed by Sherman et al. is robust across a wide range of targets, can be applied in an automated fashion, and completes using an acceptable amount of computation time (pg. 551, col. 2, para. 2, lines 7-12). This means that a drug design method incorporating ignoring clashes between a ligand and a biomolecule will be robust and fast. There is a likelihood of success, since all teachings are of molecular docking and design, which are well known techniques in the field of computational chemistry.
With respect to claim 6:
Bemis et al. and Anderson [B] do not disclose for each candidate ligand conformation, modifying atomic coordinates of the biomolecule to reduce clashes between the docked candidate ligand conformations' atomic coordinates and the biomolecule's atomic coordinates, thereby creating an altered ligand-biomolecule structure comprising the docked candidate ligand and an altered biomolecule.
However, Sherman et al. discloses performing relaxation on protein structures as part of protein refinement, which is a two-part procedure that consists of optimizing hydroxyl and thiol torsions in the first stage followed by an all-atom constrained minimization in the second stage to relieve clashes (pg. 537, col. 2, para. 1, lines 3-8; pg. 538, col. 1, para. 3, lines 1-3; pg. 538, col. 2, para. 1, lines 10-12). This teaches modifying the biomolecule’s atomic coordinates to reduce clashes between the docked candidate ligand and the biomolecule.
With respect to claim 7:
Bemis et al. and Anderson [B] do not disclose predicting a re-docked position of each candidate ligand conformation by predicting each candidate ligand conformation's position in the binding site of the altered biomolecule.
However, Sherman et al. discloses performing a second round of ligand docking on refined protein structures (pg. 535, col. 1, para. 3, lines 16-20; pg. 535, col. 2, para. 4, lines 1-6). Also, further discloses Glide predicting the binding mode of this protein-ligand complex during this ligand resampling stage (pg. 536, col. 2, para. 3, lines 11-16). This teaches predicting a re-docked position of ligands by predicting the ligands’ positions in the binding site of the altered biomolecule.
Bemis et al. and Anderson [B] do not disclose for each candidate ligand conformation, modifying atomic coordinates of the altered biomolecule to reduce clashes between the atomic coordinates of the candidate ligand conformation's re-docked position and the atomic coordinates of the altered biomolecule, thereby creating a re-altered ligand-biomolecule structure comprising a re-docked candidate ligand and a re-altered biomolecule.
However, Sherman et al. discloses repeating the induced fit docking (IFD) protocol if the top ranked re-docked protein-ligand structures have nearly identical scores (pg. 535-536, col. 2, para. 4-5, lines 18-27; pg. 537, col. 1, para. 3). The only difference between the first and second round of IFD is that the initial docking step of the second round does not use a softened potential, which means atomic coordinates of the altered protein structures are modified to relieve clashes is based only on performing relaxation on the protein structures in the protein refinement process (pg. 537, col. 2, para. 1, lines 3-8; pg. 538, col. 1, para. 3, lines 1-3; pg. 538, col. 2, para. 1, lines 10-12).
With respect to claim 8:
Bemis et al. and Anderson [B] do not disclose wherein providing the ranked list comprises ranking each altered and re-altered ligand-biomolecule structure using a scoring function.
However, Sherman et al. discloses a composite scoring function used for final ranking of altered protein-ligand structures (pg. 537, col. 1, para. 2, lines 1-2). If the IFD protocol is repeated, this means the composite scoring function will have provided lists ranking each altered and re-altered protein-ligand structure (pg. 537, col. 1, para. 3).
With respect to claim 15:
Claim 15 recites a computer system comprising a computer processor and a computer memory coupled to the processor.
Broadly claiming an automated means to replace a manual function to accomplish the same result does not distinguish over the prior art. See Leapfrog Enters., Inc. v. Fisher-Price, Inc., 485 F .3d 1157, 1161, 82 USPQ2d 1687, 1691 (Fed. Cir. 2007) (“Accommodating a prior art mechanical device that accomplishes [a desired] goal to modern electronics would have been reasonably obvious to one of ordinary skill in designing children’s learning devices. Applying modern electronics to older mechanical devices has been commonplace in recent years.”); In re Venner, 262 F. 2d 91, 95, 120 USPQ 193, 194 (CCPA 1958); see also MPEP § 2144.04. Furthermore, implementing a known function on a computer has been deemed obvious to one of ordinary skill in the art if the automation of the known function on a general purpose computer is nothing more than the predictable use of prior art elements according to their established functions. KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417, 82 USPQ2d 1385, 1396 (2007); see also MPEP § 2143, Exemplary Rationales D and F. Likewise, it has been found to be obvious to adapt an existing process to incorporate Internet and Web browser technologies for communicating and displaying information because these technologies had become commonplace for those functions. Muniauction, Inc. v. Thomson Corp., 532 F.3d 1318, 1326-27, 87 USPQ2d 1350, 1357 (Fed. Cir. 2008).
Anderson [B] and Sherman et al. do not disclose a preparation module, stored in the computer memory, wherein the preparation module is programmed to receive information identifying a plurality of candidate ligands and a template ligand-biomolecule structure comprising a template ligand and a biomolecule.
However, Bemis et al. discloses a computer comprising a memory that stores instructions for identifying a substructure of the query ligand and comparison ligands in a set of 3D structural models, where each 3D structural model comprises a comparison ligand and a comparison macromolecule (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of identifying candidate ligands and a template ligand-biomolecule structure comprising a template ligand and a biomolecule.
Anderson [B] and Sherman et al. do not disclose a pharmacophore matcher module, stored in the computer memory, wherein the pharmacophore matcher module is programmed to identify a pharmacophore match between the template ligand and each of the plurality of candidate ligands by comparing the pharmacophore model of the template ligand to the pharmacophore model of a corresponding candidate ligand of the plurality of candidate ligands.
However, Bemis et al. discloses comparing the scaffolds of query ligands to scaffolds of known ligands, where the scaffolds can be pharmacophores (pg. 19, col. 6, lines 37-42; pg. 25, col. 17, lines 32-39). Also, further discloses that this comparison leads to matching pharmacophores between a query ligand and a comparison ligand using a computer (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of identifying a pharmacophore match by comparing pharmacophore models between a template ligand and a candidate ligand.
Anderson [B] and Sherman et al. do not disclose a docking module, stored in computer memory, wherein the docking module is programmed to predict, for the corresponding candidate ligand, a docked ligand position of the corresponding candidate ligand in the template ligand-biomolecule structure by overlapping the pharmacophore model of the corresponding candidate ligand with the pharmacophore model of the template ligand while the template ligand is in the binding site of the biomolecule.
However, Bemis et al. discloses assigning atomic coordinates from the mapped scaffolds between the query ligand and the comparison ligand to the corresponding atoms of the query ligand, which are then used to position the query ligand in the target protein kinase (pg. 19, col. 6, lines 37-48; pg. 23, col. 13, lines 14-16; pg. 25, col. 17, lines 50-56). Also, further discloses the comparison ligand can be docked into the target macromolecule of interest (pg. 19, col. 6, lines 47-48). Bemis et al. discloses this assignation of atomic coordinates is performed using a computer (pg. 39-40, col. 46-47, lines 55-70; pg. 23, col. 13, lines 58-61). This teaches a computer-implemented step of predicting the docked position of a candidate ligand based on the overlapped pharmacophore models between the candidate ligand and the template ligand.
Bemis et al. and Anderson [B] do not disclose a ranking module, stored in the computer memory, wherein the ranking module is programmed to rank each altered ligand-biomolecule structure using a scoring function and output the ranked list.
However, Sherman et al. discloses a composite scoring function used for final ranking of altered protein-ligand structures (pg. 537, col. 1, para. 2, lines 1-2). Also, further discloses that the induced fit docking (IFD) protocol can be run from a graphical user interface accessible from within the program Maestro (pg. 537, col. 1, para. 4). This teaches a computer-implemented step of ranking altered ligand-biomolecule structures using a scoring function and outputting the ranked list.
With respect to claim 16:
Bemis et al. and Anderson [B] do not disclose wherein the docking module is programmed to ignore at least one clash between the corresponding candidate ligand's atomic coordinates and the biomolecule's atomic coordinates when predicting the docked ligand position.
However, Sherman et al. discloses docking ligands into a rigid receptor using a softened energy function so that steric clashes do not prevent at least one ligand pose, and increasing the Glide Coulomb-vdW energy cutoff filter to enable tolerance of more steric clashes (pg. 535, col. 1, para. 3, lines 9-12; pg. 538, para. 1, col. 1, line 10-12). Also, further discloses that the induced fit docking (IFD) protocol can be run from a graphical user interface accessible from within the program Maestro (pg. 537, col. 1, para. 4). This teaches using a softened energy function and increasing the energy cutoff filter so steric clashes have little to no effect on the binding between the ligand and the biomolecule, therefore ignoring the steric clashes. This aspect is part of the IFD protocol, which is run on a computer.
With respect to claim 17:
Bemis et al. and Anderson [B] do not disclose a biomolecule modification module, stored in the computer memory, wherein the biomolecule modification module is programmed to modify atomic coordinates of the biomolecule to reduce clashes between the docked ligand position's atomic coordinates and the biomolecule's atomic coordinates, thereby creating an altered ligand-biomolecule structure having an altered biomolecule and a docked candidate ligand.
However, Sherman et al. discloses performing relaxation on protein structures as part of protein refinement, which is a two-part procedure that consists of optimizing hydroxyl and thiol torsions in the first stage followed by an all-atom constrained minimization in the second stage to relieve clashes (pg. 537, col. 2, para. 1, lines 3-8; pg. 538, col. 1, para. 3, lines 1-3; pg. 538, col. 2, para. 1, lines 10-12). Also, further discloses that the induced fit docking (IFD) protocol can be run from a graphical user interface accessible from within the program Maestro (pg. 537, col. 1, para. 4). This teaches a computer-implemented step of modifying the biomolecule’s atomic coordinates to reduce clashes between the docked candidate ligand and the biomolecule.
With respect to claim 18:
Anderson [B] and Sherman et al. do not disclose wherein at least one of the candidate ligands have more than one structural conformation, and wherein the preparation module is programmed to enumerate a plurality of potential candidate ligand structural conformations for the at least one candidate ligand, and each of the enumerated potential candidate ligand structural conformations is processed by the docking module and the biomolecule modification module.
However, Bemis et al. discloses defining a set of fixed and flexible bonds of a query ligand and performing a conformational search to model various 3D conformations of the query ligand (pg. 22, col. 12, lines 1-7). Also, further discloses that the modeling methods of the invention can be implemented using a computer (pg. 23, col. 13, lines 51-54). This teaches flexible bonds of a candidate ligand, which suggests that the ligand has more than one conformation. These potential ligand conformations are enumerated by performing a conformational search using a computer.
With respect to claim 21:
Bemis et al. and Anderson [B] do not disclose wherein the step of predicting an initial docked position comprises ignoring at least one clash between the corresponding candidate ligand's atomic coordinates and the biomolecule's atomic coordinates.
However, Sherman et al. discloses docking ligands into a rigid receptor using a softened energy function so that steric clashes do not prevent at least one ligand pose, and increasing the Glide Coulomb-vdW energy cutoff filter to enable tolerance of more steric clashes (pg. 535, col. 1, para. 3, lines 9-12; pg. 538, para. 1, col. 1, line 10-12). This teaches using a softened energy function and increasing the energy cutoff filter so steric clashes have little to no effect on the binding between the ligand and the biomolecule, therefore ignoring the steric clashes.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Bemis et al. [US7826979B2], Anderson [B] (Methods in Molecular Biology, 2013, 823, 359-366), and Sherman et al. (J Med. Chem., 2006, 49(2), 534-553) as applied to claims 2, 4-8, and 15-21 above, in view of Zhu et al. (Journal of Medicinal Chemistry, 2013, 56(17), 6560-6572).
Bemis et al., Anderson [B], and Sherman et al. are applied to claims 2, 4-8, and 15-21 above.
With respect to claim 9:
Bemis et al., Anderson [B], and Sherman et al. do not disclose wherein the providing the ranked list comprises identifying, using the computer system, a subset of high-ranking candidate ligands corresponding to candidate ligands having a threshold value for an empirical activity.
However, Zhu et al. discloses that hit selection methods such as virtual screening in drug discovery typically include a manually set threshold such as a percentage inhibition at a given screening concentration (pg. 6561, col. 1-2, para. 2, lines 5-8). Only a small percentage of the top-ranked compounds using the threshold are tested (pg. 6567, col. 1, para. 2, lines 4-5). This teaches identifying a subset of high-ranking ligands that have a threshold value for an empirical activity.
It would have been prima facie obvious to one of ordinary skill in the art to modify the drug design method disclosed by Bemis et al., Anderson [B], and Sherman et al. to incorporate identifying high-ranking ligands having a threshold value for an empirical activity disclosed by Zhu et al. One would be motivated to incorporate a threshold value for an empirical activity when identifying high-ranking ligands in the drug design method because Zhu et al. discloses that low activity cutoffs improve the structural diversity of the hit compounds (pg. 6562, col. 1, para. 1, lines 15-21). This means that incorporating an empirical activity cutoff for identifying high-ranking ligands in the drug design method will improve diversity of the ligands. There is a likelihood of success, since all teachings are of molecular design or discovery, which are well known techniques in the field of computational chemistry.
With respect to claim 10:
Bemis et al., Sherman et al., and Zhu et al. do not disclose wherein the ranked list of target ligands that includes the target ligand based on the predicted dock position and synthesizing one or more target ligands from the ranked list.
However, Anderson [B] discloses identifying binding modes of ligands in the structure of a target and scoring their docked positions, producing a ranked list of ligands (pg. 359-360, para. 2, lines 3-7; pg. 363-364, para. 7). Top-scoring molecules from this ranked list are synthesized (pg. 360, para. 1, lines 1-3; pg. 363-364, para. 7). This teaches a ranked list of ligands based on predicted dock positions and synthesizing the top-scoring ligands from the ranked list.
Conclusion
No claims are allowed.
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/J.N.L./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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