DETAILED ACTION
Applicant's response, filed 25 February 2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Priority
The instant application claims benefit of priority to U.S. Provisional Application No. 63/151,377 filed on 02/29/2021. The claim to the benefit of priority is acknowledged. As such, the effective filing date of claims 1-20 is 02/29/2021.
Claim Status
Claims 1-2, 4-9, and 13-20 are pending.
Claims 3, 8, and 10-12 are cancelled.
Claims 1-2, 4-7, 9, and 13-20 are rejected.
Applicant used incorrect notation to show deleted claim limitations, specifically using single brackets instead of double brackets, however in furtherance of compact prosecution examiner is treating terms in single brackets as deleted.
Drawings
Response to Amendment
In view of applicant’s amendments to the drawings previous objections to the drawings over the inclusion of color drawings is withdrawn.
Claim Objections
Claim 1 is objected to because of the following informalities: “neural network” is misspelled in line 11. Appropriate correction is required.
Claims 14-15 and 20 are objected to because of the following informalities: “moleculular” should be “molecular”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections under 35 U.S.C. 112 of claims 8 and 10 have been withdrawn.
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 1-2, 4-7, and 9 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.
Claim 1 recites the limitation "the first molecule" in line 7. There is insufficient antecedent basis for this limitation in the claim as there is no previous recitation of a first molecule. It can be interpreted it to have meant the initial molecule and can be amended as such to overcome the rejection. Claims 2-12 do not rectify the indefiniteness of claim 1 and are therefore rejected under the same grounds.
Claim 9 recites the limitation "the molecule" in line 3. There is insufficient antecedent basis for this limitation in the claim as there is previously recited “an initial molecule”, “the first molecule”, and “a first modified molecule”.
Claim 9 recites the limitation "the first modified molecule“ in line 7. There is insufficient antecedent basis for this limitation in the claim as there is previously recited a “first modified molecule” in claim 8 and “a first modified molecule” in claim 1.
Claim Rejections - 35 USC § 101
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections under 35 U.S.C. 101 have been reviewed, updated, and provided below.
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 1-2, 4-9, and 13-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite a method and a CRM for generating a chemical and physical structure of a molecule that has a specified property. The judicial exception is not integrated into a practical application because while claims 1-20 attempt to integrate the exception into a practical application, said application is either generically recited computer elements that do not add a meaningful limitation to the abstract idea or it is insignificant extra solution activity and merely implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer elements only store and retrieve information in memory as well as perform basic calculations that are known to be well-understood, routine and conventional computer functions as recognized by the decisions listed in MPEP § 2106.05(d).
Framework with which to Analyze Subject Matter Eligibility:
Step 1: Are the claims directed to a category of statutory subject matter (a process, machine, manufacture, or composition of matter)? [see MPEP § 2106.03]
Claims are directed to statutory subject matter, specifically a method (claims 1-12), and a CRM (Claims 13-20).
Step 2A Prong One: Do the claims recite a judicially recognized exception, i.e., an abstract idea, a law of nature, or a natural phenomenon? [see MPEP § 2106.04(a)]
The claims herein recite abstract ideas, specifically mental processes and mathematical concepts.
With respect to the Step 2A Prong One evaluation, the instant claims are found herein to recite abstract ideas that fall into the grouping of mental processes and mathematical concepts.
Claim 1: Selecting a first attribute of the initial molecule, evaluating the performance of the first molecule, modifying a portion of the chemical and physical structures of the molecule, predicting the performance of the modified molecule, selecting at least one of the first through x modified molecules, further modifying the molecule based upon the predicted performance, are all processes of selecting, modifying and predicting information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 2: Modifying a portion of the chemical and physical structures to form a second through nth modified molecules, predicting the performance of the second through n-1 molecules, and further modifying each of the molecules based upon the predicted performance are all processes of modifying and predicting information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 3: Predicting the performances of the second through n-1 molecules before a next molecule is generated, is merely specifying the order of modifying and predicting information (which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes), and is therefore itself a mental process.
Claim 4: Prior to further modification, modifying at least a portion of the chemical structure and a physical structure of the molecules, at least to different changes to the chemical and physical structures are made to the same previously modified molecule, is a process of modifying existing information which can either be done with a pen and paper and/or within the human mind, and is therefore an abstract idea, specifically a mental process.
Claim 5: The molecule with the best predicted performance with respect to the specified property is further modified, is a process of ranking/ordering predicted performance which can either be done with a pen and paper and/or within the human mind, and is therefore an abstract idea, specifically a mental process.
Claim 6: The property being selected being binding energy is merely further limiting the type of data you are selecting, which is itself inherently abstract, thus it’s just further limiting the type of decision you are making and can either be done with a pen and paper and/or within the human mind, which is therefore an abstract idea, specifically a mental process.
Claim 7: The property being the location of a potential chemical binding site is merely further limiting the type of data you are selecting, which is itself inherently abstract, thus it’s just further limiting the type of decision you are making and can either be done with a pen and paper and/or within the human mind, which is therefore an abstract idea, specifically a mental process.
Claim 9: Selecting a third attribute of the initial molecule, evaluating the performance of the molecule, modifying a portion of the chemical and physical structures of the molecule, and predicting the performance of the modified molecule are all processes of selecting, modifying and predicting information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 13: Generating one or more modified version of the initial molecular structure, predicting a final metric or score, selecting one or more versions of the initial molecular structures based on the predicted metrics/scores, and generating one or more second molecular structures based upon the actions are processes of predicting information, choosing actions to take and modifying/creating diagrams based upon said actions, which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes. Representing user inputs in the form of a numeric matrix is merely a verbal articulation of a mathematical process and therefore is a mathematical concept.
Claim 14: Generating an initial numeric matrix representative of a molecule structure is merely a verbal articulation of a mathematical process and therefore is a mathematical concept.
Claim 15: Repeating the predicting of a final metric/score a number of n times based upon a specified number, is merely predicting information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 16: Selecting n based upon a user input is a process of choosing a number which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 19: Tabulating the properties of one or more molecules generated, is a process of generating a specifically formatted set of information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Claim 20: Selecting one or more actions based on the predicted metric or scores includes accessing relative importance weights to predict metrics or scores Is merely the process of retrieving predetermined information which can either be done with a pen and paper and/or within the human mind, and are therefore abstract ideas, specifically mental processes.
Step 2A Prong Two: If the claims recite a judicial exception under prong one, then is the judicial exception integrated into a practical application? [see MPEP § 2106.04(d) and MPEP §
2106.05(a)-(c) & (e)-(h)]
Because the claims do recite judicial exceptions, direction under Step 2A Prong Two provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application.
The following claims recite the following additional elements in the form of non-abstract elements:
Claim 1: Providing an initial molecule having chemical and physical structure is an insignificant extra solution activity, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. A neural network is a generic and nonspecific computer element that does not improve the functioning of any computer or technology described herein [See MPEP § 2106.04(d)(1) and MPEP § 2106.05(d)].
Claim 13: A non-transitory computer readable medium, instructions, processors, and computing system are generic and nonspecific computer elements that do not improve the functioning of any computer or technology described herein [See MPEP § 2106.04(d)(1) and MPEP § 2106.05(d)].
Claim 17: The one or more dimensions including an initial molecule represented in SMILE format is an insignificant extra solution activity, specifically specifying a particular data source (See Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) and Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937) [See MPEP § 2106.05(g)].
Claim 18: The one or more dimensions including an initial molecule represented in chemical file format is an insignificant extra solution activity, specifically specifying a particular data source (See Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) and Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937) [See MPEP § 2106.05(g)].
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept? [see MPEP § 2106.05]
Because the additional claim elements do not integrate the abstract idea into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept.
The claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that are generic, conventional or nonspecific. These additional elements include:
The additional elements of a non-tranistory computer readable medium, instructions, processors, neural network, and computing system, are generic and nonspecific elements of a computer that are well-understood, routine, and conventional within the art and therefore does not improve the functioning of any computer or technology described therein (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values), and Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)) [See § MPEP 2106.05(d)(II)]. Therefore, taken both individually and as a whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept. Therefore, taken both individually and as whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
The additional elements of providing an initial molecule having chemical and physical structure (Conventional Data Gathering: Specification [0057]), and providing a second through an mth initial molecule having both chemical and physical structure (Conventional Data Gathering: Specification [0057]), are insignificant extra solutional activities, specifically mere data gathering, that are recognized as well understood, routine and conventional by the courts (See Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), and Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)) [See MPEP § 2106.05(g)]. Therefore, taken both individually and as whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
The additional elements of the property being selected being binding energy (Conventional Property: Roche et al. 2015), the property being the location of a potential chemical binding site (Conventional Property: Roche et al. 2015), the one or more dimensions including an initial molecule represented in SMILE format (Conventional Format: Hirohara et al. 2018, Karwath et al. 2006, and Ozturk et al. 2016), and the one or more dimensions including an initial molecule represented in chemical file format (Conventional Format: Hirohara et al. 2018, Karwath et al. 2006, and Ozturk et al. 2016), are insignificant extra solution activities, specifically focusing on the data source and type, which is merely selecting a particular data source [see MPEP § 2106.5(g)]. Therefore, taken both individually and as whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
Therefore, claims 1-2, 4-9, and 13-20, when the limitations are considered individually and as a whole, are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed 2/25/2025 have been fully considered but they are not persuasive.
Applicant asserts on page 13 of the Remarks filed 2/25/2026 that the methodology and use of non-transitory computer readable media is a non-abstract element and that the judicial exception is integrated into a practical and useful application. However, examiner reminds applicant that according to MPEP 2106.04(d), in order to integrate the judicial exception into a practical application the limitations must direct the invention to An improvement in the functioning of a computer, or an improvement to other technology or technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a); Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2); Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b); Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e), and limitations that do not integrate a judicial exception were found to be Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). Conversely, as shown above the limitations of the instant application, specifically the additional elements, are well understood, routine and conventional additional elements that generally link the use of the judicial exception to a particular technology, computers in this case.
Claim Rejections - 35 USC § 102
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections of claims 1-5 under 35 U.S.C. 102 have been withdrawn.
Response to Arguments
Applicant’s arguments, see pages 10-11 of the Remarks, filed 2/25/2026, with respect to rejections under 35 U.S.C. 102 have been fully considered and are persuasive. The rejections of claims 1-5 has been withdrawn. Specifically, amendments to the claims no longer enable Fleishman et al. to anticipate claims 1-5.
Claim Rejections - 35 USC § 103
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections of claims under 35 U.S.C. 103 have been reviewed, updated, and provided below.
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 1-2, 4-5, 9, 13-16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fleishman et al. (US 20170032079 A1), Barbosa et al. (International Conference on Vector and Parallel Processing (1998) 508-521), and Stepniewska-Dziubinska et al. (Bioinformatics (2018) 3666-3674).
Claim 1 is directed to a method of generating a chemical and physical structure of a molecule with a specified property.
Fleishman et al. teaches in paragraph [0109] “According to some embodiments of the invention, the structural information is a set of atomic coordinates of the original polypeptide chain”, reading on providing an initial molecule having at least one of a chemical structure and a physical structure. Fleishman et al. teaches in claim 6 “A method of computationally designing a modified polypeptide chain starting from an original polypeptide chain”, reading on a method of generating at least one of the chemical and physical structure of at least one molecule having a property. Fleishman et al. teaches in claim 1 “wherein said substitutions are modifying the designed protein relative to a corresponding wild type protein, as determined by at least one of: a thermal denaturation temperature of the designed protein being equal or higher than a thermal denaturation temperature of the wild type protein; a solubility of the designed protein being equal or higher than a solubility of the wild type protein; a degree of misfolding of the designed protein being equal or lower than a degree of misfolding of the wild type protein; a half-life of the designed protein being equal or longer than a half-life of the wild type protein; a specific activity of the designed protein being equal or higher than a specific activity of the wild type protein; and a recombinant expression level of the designed protein being equal or higher than a recombinant expression level of the wild type protein”, reading on selecting at least a first attribute of the initial molecule relating to a first property thereof and evaluating the performance of the first molecule with respect to the first property thereof. Fleishman et al. teaches in claim 6 “the method comprising: (i) determining unsubstitutable positions and substitutable positions in an amino acid sequence of the original polypeptide chain; (ii) determining at least one position-specific amino acid alternative for each of said substitutable positions, and determining a position-specific stability scoring for each of said amino acid alternative; (iii) combinatorially generating a plurality of designed sequences, each of said designed sequences corresponds to a modified polypeptide chain; (iv) sorting said plurality of designed structures according to a minimized energy scoring, said minimized energy scoring is determined by subjecting each of said designed structures to an energy minimization”, and in in paragraph [0084] “FIGS. 2A-D are simplified illustrations of the output of the single position scanning step and the input of the iterative combinatorial design”, reading on modifying at least a portion of the at least one of a chemical structure and a physical structure of the initial molecule to form a first modified molecule. Fleishman et al. teaches in paragraph [0084] “FIGS. 2A-D are simplified illustrations of the output of the single position scanning step and the input of the iterative combinatorial design”, which in view of previous citations reads on predicting the performance of the first modified molecule, upon further modification thereof, with respect to the performance of that first modified molecule with respect to the first property thereof; and based on the predicted performance, further modifying the first modified molecule.
Furthermore, it would be obvious to a person who is skilled in the art to run in parallel as it is both widely and commonly used to reduce computation time (See Barbosa et al. Vector and Parallel Processing-VECPAR'98: Third International Conference (1999) 508-521), which in light of Fleishman et al. teaching as previously described, thus renders obvious the following: first through x modified molecules and selecting at least one of the first through x modified molecules for further modification.
Stepniewska-Dziubinska et al. teaches in the abstract “We have developed a novel deep neural network estimating the binding affinity of ligand–receptor complexes”, reading on the use of a neural network.
It would have been obvious at the time of invention to a person skilled in the art to modify the teachings of Fleishman et al. for the method of claim 1 with the teachings of Stepniewska-Dziubinska et al. for the representation of structure as a 4D tensor, as the latter points out “Three-dimensional structures of protein–ligand complexes require specific transformations and encoding in order to be utilized by a neural network” and the teachings of Barbosa et al. for performing the method on multiple molecules at a time as previously described. One would have had a reasonable expectation of success given that Stepniewska-Dziubinska et al. was successfully able to construct a DNN that predicted binding affinity and Barbosa et al. provides instruction for a common practice within the field. Therefore, it would have been obvious to person of ordinary skill in the art to incorporate the teachings of each and to be successful.
Claim 2 is directed to the method of claim 1 but further specifies modifying the molecule to form a second through n number of molecules, predicting the performance of each, and based upon the performance modifying the final molecule.
Fleishman et al. teaches in claim 6 “the method comprising: (i) determining unsubstitutable positions and substitutable positions in an amino acid sequence of the original polypeptide chain; (ii) determining at least one position-specific amino acid alternative for each of said substitutable positions, and determining a position-specific stability scoring for each of said amino acid alternative; (iii) combinatorially generating a plurality of designed sequences, each of said designed sequences corresponds to a modified polypeptide chain and comprises at least one amino acid substitution being one of said at least one position-specific amino acid alternative, and threading each of said designed sequences on a template structure of the original polypeptide chain, to thereby generate a plurality of designed structures; (iv) sorting said plurality of designed structures according to a minimized energy scoring, said minimized energy scoring is determined by subjecting each of said designed structures to an energy minimization; and (v) selecting at least one of said plurality of designed structures, corresponding to the modified polypeptide chain, based on said minimized energy scoring”, and in paragraph [0084] “FIGS. 2A-D are simplified illustrations of the output of the single position scanning step and the input of the iterative combinatorial design”, which reads on modifying at least a portion of the at least one of a chemical structure and a physical structure of the initial molecule to form second through nth modified molecules, where n is a positive integer; and predicting the performance of the second through n-1 modified molecules, upon further modification thereof, with respect to the performance of that second through n-1 modified molecules with respect to the property thereof, and based on the predicted performance, further modify each of the first through n-1 modified molecules to generate the nth modified molecule.
Claim 4 is directed to the method of claim 2 and thus claim 1, but further specifies that at least 2 changes to the chemical and physical structure be made and the subsequent performance of the two molecules with respect to the property of interest be predicted.
Fleishman et al. teaches in claim 7 “wherein the modified polypeptide chain comprises at least six amino acid substitutions relative to the original polypeptide chain”, reading on wherein the modifying at least a portion of the at least one of a chemical structure and a physical structure of the at least one of the selected first through x molecule includes at least two different changes to the at least one of a chemical structure and a physical structure to create two candidate molecules, before the performance of the at least two candidate molecules with respect to the property thereof upon further modification thereof, is predicted.
Claim 5 is directed to the method of claim 4 and thus claim 1, but further specifies that the molecule with the best performance be further modified.
Fleishman et al. teaches in claim 6 “(iv) sorting said plurality of designed structures according to a minimized energy scoring, said minimized energy scoring is determined by subjecting each of said designed structures to an energy minimization; and (v) selecting at least one of said plurality of designed structures, corresponding to the modified polypeptide chain, based on said minimized energy scoring”, reading on wherein, as among the at least two candidate molecules, the one with the best predicted performance with respect to the property thereof, is modified to form the next one of the second through n-1 molecules.
Claim 6 is directed to the method of claim 1 but further specifies the property as binding energy.
Stepniewska-Dziubinska et al. teaches in the abstract “We have developed a novel deep neural network estimating the binding affinity of ligand–receptor complexes”, reading on wherein the property thereof is binding energy.
Claim 8 is directed to the method of claim 1 but further specifies the selection of a second attribute of the molecule and the evaluation, modification and prediction of the performance of the modified molecule as previously described in claim 1.
Fleishman et al. teaches in paragraph [0012] “The invention, according to some embodiments thereof, is directed at designed proteins, having a non-naturally occurring, man-made amino acid sequence, at least to some extent and at least in one polypeptide chain thereof, that are more stable and exhibit several modified characteristics compared to their wild type counterpart”, which while nonspecific as to the amount of characteristics, notes several which is at least more than two, which in view of Fleishman et al. reading on the method of claim 1, now reads on selecting a second attribute of the initial molecule relating to a second property thereof; evaluating the performance of the molecule with respect to the first and the second property thereof; modifying at least a portion of the at least one of a chemical structure and a physical structure of the initial molecule to form a first modified molecule; predicting the performance of the first modified molecule, upon further modification thereof, with respect to the performance of that first modified molecule with respect to the first and the second property thereof. It is obvious therefore to use multiple attributes in evaluation as Fleishman et al. points out “…exhibit several modified characteristics…”, i.e. more than one, which would make using more than one obvious.
Claim 9 is directed to the method of claim 8 and thus claim 1, but further specifies the selection of a third attribute of the molecule and the evaluation, modification and prediction of the performance of the modified molecule as previously described in claim 1.
Fleishman et al. teaches in paragraph [0012] “The invention, according to some embodiments thereof, is directed at designed proteins, having a non-naturally occurring, man-made amino acid sequence, at least to some extent and at least in one polypeptide chain thereof, that are more stable and exhibit several modified characteristics compared to their wild type counterpart”, which while nonspecific as to the amount of characteristics, notes several which is at least more than two, which in view of Fleishman et al. reading on the method of claim 1, now reads on selecting a third attribute of the initial molecule relating to a third property thereof; evaluating the performance of the molecule with respect to the first, the second and the property thereof; modifying at least a portion of the at least one of a chemical structure and a physical structure of the initial molecule to form a first modified molecule; predicting the performance of the first modified molecule, upon further modification thereof, with respect to the performance of that first modified molecule with respect to the first, the second and the third property thereof. It is obvious therefore to use multiple attributes in evaluation as Fleishman et al. points out “…exhibit several modified characteristics…”, i.e. more than one, which would make using more than one obvious.
Claim 13 is directed to a non-transitory CRM with instructions that perform the method of claim 1, utilizing a numeric matrix to generate one or more molecules.
Fleishman et al., Barbosa et al., and Stepniewska-Dziubinska et al. teach the method of claim 1 as previously described.
Fleishman et al. teaches in claim 6 “determining at least one position-specific amino acid alternative for each of said substitutable positions, and determining a position-specific stability scoring for each of said amino acid alternative… sorting said plurality of designed structures according to a minimized energy scoring, said minimized energy scoring is determined by subjecting each of said designed structures to an energy minimization; and (v) selecting at least one of said plurality of designed structures, corresponding to the modified polypeptide chain, based on said minimized energy scoring; thereby obtaining the modified polypeptide chain”, reading on predicting, using a model, a final metric or score assigned to a generated molecule upon completion for one or more actions, if that action were to be used as the next design action taken in the generation of one or more molecules; selecting one or more actions based on the predicted metric or scores; and generating one or more molecules based upon the selected actions.
Stepniewska-Dziubinska et al. teaches on page 3667, column 2, paragraph 5 “In our approach, we cropped the complex to a defined size of 20-A˚ cubic box focused at the geometric center of a ligand. We then discretized the positions of heavy atoms using a 3D grid with 1-A˚ resolution. This approach allowed for the representation of the input as a 4D tensor in which each point is defined by Cartesian coordinates and a vector of features”, reading on representing user inputs in the form of a numeric matrix of one or more dimensions.
Claim 14 is directed to the CRM of claim 13 but further specifies generating an initial numeric matrix that represents the structure of the molecule.
Stepniewska-Dziubinska et al. teaches on page 3667, column 2, paragraph 5 “In our approach, we cropped the complex to a defined size of 20-A˚ cubic box focused at the geometric center of a ligand. We then discretized the positions of heavy atoms using a 3D grid with 1-A˚ resolution. This approach allowed for the representation of the input as a 4D tensor in which each point is defined by Cartesian coordinates and a vector of features”, reading on generating an initial numeric matrix representative of a molecule structure received from a user input.
Claim 15 is directed to the CRM of claim 14 and thus claim 13, but further specifies that after predicting a final score or metric, that the process be repeated for an additional n number of times.
Fleishman et al. teaches in paragraph [0084] “FIGS. 2A-D are simplified illustrations of the output of the single position scanning step and the input of the iterative combinatorial design”, reading on after predicting a final metric or score assigned to a generated molecule upon completion for one or more actions repeating predicting a final metric or score assigned to a generated molecule upon completion for one or more actions and generating a molecule based on the selected actions n additional times, where n is a positive, whole number integer.
Claim 16 is directed to the CRM of claim 15 and thus claim 13, but further specifies selecting n based upon a user input.
Fleishman et al. teaches the method of claim 13 as previously described.
Fleishman et al. does not teach selecting n based upon a user input.
Stepniewska-Dziubinska et al. teaches on page 3673 “we are working on a more flexible implementation of the model, that will allow the user to easily manipulate network parameters and molecular complex representation, with minimal programming knowledge”, reading on selecting n based on a user input to the non-transitory computer readable medium.
Claim 20 is directed to the CRM of claim 13 but further specifies accessing relative importance weights for different molecular properties to use in predicting metrics/scores and generate molecules.
Fleishman et al. teaches in paragraph [0168] “According to some embodiments of the present invention, the rules by which a substitution of amino acids is dictated during a sequence design procedure include position-specific scoring matrix values” and in paragraph [0169] “A “position-specific scoring matrix” (PSSM), also known in the art as position weight matrix (PWM), or a position-specific weight matrix (PSWM), is a commonly used representation of recurring patterns in biological sequences”, reading on accessing relative importance weights for different molecular properties and using the relative importance weights to predict metric or scores and generate a molecule based on the selected actions.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Fleishman et al. (US 20170032079 A1), Barbosa et al. (International Conference on Vector and Parallel Processing (1998) 508-521), and Stepniewska-Dziubinska et al. (Bioinformatics (2018) 3666-3674) as applied to claims 1-2, 4-5, 8-9, 13-16, and 20 above, and further in view of Hirohara et al. (BMC bioinformatics (2018) 83-94).
Claim 19 is directed to the CRM of claim 13 but further specifies that the properties of each molecule be tabularized.
Fleishman et al., Barbosa et al., and Stepniewska-Dziubinska et al. teach the method of claim 13 as previously described.
Fleishman et al., Barbosa et al., and Stepniewska-Dziubinska et al. do not specifically teach that the properties of each molecule be tabularized.
Hirohara et al. teaches on page 93, column 1, paragraph 2 “In this study, we designed a feature matrix based on SMILES linear notation of compounds”, reading on further comprising a table generator to tabulate the properties of one or more molecules generated by the computer readable media.
It would have been obvious at the time of invention to a person skilled in the art to modify the teachings of Fleishman et al. for the method of claim 1 with the teachings of Stepniewska-Dziubinska et al. for the representation of structure as a 4D tensor, and the teachings on Hirohara et al. for the use of a feature matrix based on SMILEs notation as the matrix/table representation of the SMILE data would for similar classification models using a lower dimensional representation of said matrix/table. One would have had a reasonable expectation of success given that Hirohara et al. explicitly teaches the use of such a method using the same data format as the applicant for a similar process, chemical motif prediction/classification. Therefore, it would have been obvious to person of ordinary skill in the art to incorporate the teachings of each and to be successful.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Fleishman et al. (US 20170032079 A1), Barbosa et al. (International Conference on Vector and Parallel Processing (1998) 508-521), and Stepniewska-Dziubinska et al. (Bioinformatics (2018) 3666-3674) as applied to claims 1-2, 4-5, 8-9, 13-16, and 20 above, and further in view of Feldmeier et al. (Current Opinion in Chemical Biology (2013) 929-933).
Claim 7 is directed to the method of claim 1 but further specifies that the property being examined is the location of a potential chemical binding site.
Fleishman et al., Barbosa et al., and Stepniewska-Dziubinska et al. teach the method of claim 1 as previously described.
Fleishman et al., Barbosa et al., and Stepniewska-Dziubinska et al. do not teach that the property being examined is the location of a potential chemical binding site.
Feldmeier et al. teaches on page 930, column 1, paragraph 2 “The binding pocket was optimized with Rosetta, 55 designs based on four different theozymes were tested…”, reading on wherein the property thereof is the location of a potential chemical binding site with respect to the topography of the nth molecule.
It would have been obvious at the time of invention to a person skilled in the art to combine the teachings of Fleishman et al. for the method of claim 1, with the teachings of Feldmeier et al. for the focus on optimizing binding sites as Feldmeier et al. points out “Custom-made protein design has been a long-standing goal for biochemists”. One would have had a reasonable expectation of success given that Feldmeier et al. is a review paper of potential methods within the field, providing an overview of current and prior research and the trends over time. Therefore, it would have been obvious to person of ordinary skill in the art to incorporate the teachings of each and to be successful.
Claims 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Fleishman et al. (US 20170032079 A1), Barbosa et al. (International Conference on Vector and Parallel Processing (1998) 508-521), and Stepniewska-Dziubinska et al. (Bioinformatics (2018) 3666-3674) as applied to claims 6, 13-16, and 19-20 above, and further in view of Winter et al. (Chemical Science (2019) 1692-1701).
Claim 17 is directed to the CRM of claim 13 but further specifies the input be represented in SMILE format.
Fleishman et al. and Stepniewska-Dziubinska et al. teach the method of claim 13 as previously described.
Fleishman et al. and Stepniewska-Dziubinska et al. do not teach that the input be represented in SMILE format.
Winter et al. teaches on page 1692, column 2, paragraph 3 “…work was also done to apply DNNs directly on supposedly more complete and lower-level representations of a molecule such as the molecular graph or the sequential SMILES representation”, and in column 1, paragraph 1, of the same page “Molecular descriptors play a crucial role in cheminformatics, since they allow representing chemical information of actual molecules in a computer-interpretable vector of numbers… A widely used concept to generate such theoretical molecular descriptors is molecular fingerprints”, and in the abstract “we propose to exploit the powerful ability of deep neural networks to learn a feature representation from low-level encodings of a huge corpus of chemical structures… Once the model is trained, this representation can be extracted for any new molecule and utilized as a descriptor… our method shows competitive performance in modelling quantitative structure–activity relationships in all analysed datasets. Additionally, we show that our descriptor significantly outperforms all baseline molecular fingerprints in two ligand-based virtual screening tasks”, reading on wherein the one or more dimensions include an initial molecule represented in SMILE format.
It would have been obvious at the time of invention to a person skilled in the art to combine the teachings of Fleishman et al. and Stepniewska-Dziubinska et al. for the CRM of claim 13 with the use of SMILE format data from Winter et al. as the latter outlines in the abstract “our method shows competitive performance in modelling quantitative structure–activity relationships in all analyzed datasets. Additionally, we show that our descriptor significantly outperforms all baseline molecular fingerprints in two ligand-based virtual screening tasks. Overall, our descriptors show the most consistent performances in all experiments”. One would have had a reasonable expectation of success given that Winter et al. is performing only the training portion of the model while simultaneously expressing that their training can be used for multiple cheminformatics tasks, of which the method of Fleishman et al. and Stepniewska-Dziubinska et al. is one. Therefore, it would have been obvious to person of ordinary skill in the art to incorporate the teachings of each and to be successful.
Claim 18 is directed to the CRM of claim 13 but further specifies the input be represented in chemical file format.
Fleishman et al. and Stepniewska-Dziubinska et al. teach the method of claim 13 as previously described.
Fleishman et al. and Stepniewska-Dziubinska et al. do not teach that the input be represented in SMILE format.
Winter et al. teaches on page 1692, column 2, paragraph 3 “…work was also done to apply DNNs directly on supposedly more complete and lower-level representations of a molecule such as the molecular graph or the sequential SMILES representation”, and in column 1, paragraph 1, of the same page “Molecular descriptors play a crucial role in cheminformatics, since they allow representing chemical information of actual molecules in a computer-interpretable vector of numbers… A widely used concept to generate such theoretical molecular descriptors is molecular fingerprints”, and in the abstract “we propose to exploit the powerful ability of deep neural networks to learn a feature representation from low-level encodings of a huge corpus of chemical structures… Once the model is trained, this representation can be extracted for any new molecule and utilized as a descriptor… our method shows competitive performance in modelling quantitative structure–activity relationships in all analysed datasets. Additionally, we show that our descriptor significantly outperforms all baseline molecular fingerprints in two ligand-based virtual screening tasks”, reading on wherein the one or more dimensions include an initial molecule represented in chemical file format, as SMILES is a type of chemical file format.
Response to Arguments
Applicant's arguments filed 2/25/2026 have been fully considered but they are not persuasive.
Applicant asserts on pages 11-13 of the Remarks filed 2/25/2026 that each of the specified claim groupings are allowable over amendments to claim 1 which are no longer anticipated by Fleishman et al. or covered by specified art. Examiner agrees and has modified the references cited to cure deficiencies of Fleishman et al. using previously cited art that was not applied to claims 1-5.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/K.N.A./Examiner, Art Unit 1687
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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