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 .
Status of the Claims
Claims 1-20 are currently pending and under exam herein.
Claims 1-20 are rejected.
Priority
The instant application claims priority from provisional application 63/379,376 filed on 10/14/2022. Thus, the effective filing date of the instant application is 10/14/2022.
Drawings
The Drawings filed on 10/05/2023 were considered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/19/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
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 1-20 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 1-20 are directed to a system, method, and computer program for physics-based binding affinity estimation.
[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 or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generate a model for a ligand bound to a target molecule; (mathematical concept and/or mental process)
and estimate a binding affinity between said ligand and said target molecule by: (mathematical concept and/or mental process)
creating a unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables; exchanging data for said four variables between a subset of said replicas; (mathematical concept and/or mental process)
and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (mathematical concept and/or mental process)
Dependent claim 2 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said processor is configured to generate said model using at least one docking method. (mathematical concept)
Dependent claim 3 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said processor is configured to generate said model using x-ray crystallography. (Mathematical concept, examiner does not interpret this as a data gathering step but using Xray crystallography data in a mathematical model in order to generate a binding posed. Based on the mathematical relationship inherent in crystallography)
Dependent claim 4 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said processor is configured to generate said model by simulating said ligand and said target molecule in a box of water and ions. (mathematical concept)
Dependent claim 5 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said processor is configured to generate said model by simulating a harmonic restraint on said ligand and said target molecule (mathematical concept)
Dependent claim 6 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (S2), a root-mean- square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square- deviation of said target molecule with respect to said reference structure (rp). (mathematical concept)
Dependent claim 7 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said ligand is a drug, and wherein said target molecule is a protein. (mathematical concept – these just limits what the process is done on)
Independent claim 8 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
creating a unified simulation for a ligand and a target molecule, said unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables; (mathematical concept and/or mental process)
exchanging data for said four variables between a subset of said replicas; (mathematical concept and/or mental process)
and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (mathematical concept and/or mental process)
Dependent claim 9 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (S2), a root-mean- square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square- deviation of said target molecule with respect to said reference structure (rp). (mathematical concept)
Dependent claim 10 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (S2), a root-mean- square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square- deviation of said target molecule with respect to said reference structure (rp). (mathematical concept)
Dependent claim 11 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein step of simulating varying distances between said ligand and said target molecule further comprises performing all the simulations simultaneously (mathematical concept)
Dependent claim 12 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the step of exchanging data for said four variables further comprises the steps of: establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and using said replicas to move between said nodes. (mathematical concept)
Dependent claim 13 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
herein said replicas have different centers for said four restraints. (mathematical concept)
Dependent claim 14 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the step of performing said single non-parametric reweighting analysis further comprises: estimating a likelihood of finding said ligand in the bulk versus finding said ligand at a specific orientation and conformation within a binding pocket of the target molecule; (mathematical concept and/or mental process)
estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of movement; estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of fluctuations in root-mean-square deviation; and (mathematical concept and/or mental process)
estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of orientational changes. (mathematical concept and/or mental process)
Dependent claim 15 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the step of performing said single non-parametric reweighting analysis further comprises the step of estimating AG° according to the equation
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(mathematical concept)
Dependent claim 16 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
further comprising the step of recording said data exchanged between said subset of replicas. (mathematical concept and/or mental process)
Independent claim 17 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
generating a model for a ligand bound to a target molecule; (mathematical concept and/or mental process)
creating a unified simulation for said ligand and said target molecule, said unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables; (mathematical concept and/or mental process)
exchanging data for said four variables between a subset of said replicas; (mathematical concept and/or mental process)
recording said data; and (mathematical concept and/or mental process)
performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (mathematical concept and/or mental process)
Dependent claim 18 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (Q), a root-mean-square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square-deviation of said target molecule with respect to said reference structure (rp). (mathematical concept)
Dependent claim 19 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and (mathematical concept and/or mental process)
using said replicas to move between said nodes. (mathematical concept and/or mental process)
Dependent claim 20 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
estimating a likelihood of finding said ligand in the bulk versus finding said ligand at a specific orientation and conformation within a binding pocket of the target molecule; (mathematical concept and/or mental process)
estimating a difference between flexibility for said ligand in the bulk versus in said binding pocket in terms of movement; (mathematical concept and/or mental process)
estimating a difference between flexibility for said ligand in the bulk versus in said binding pocket in terms of fluctuations in root-mean-square deviation for said ligand; and (mathematical concept and/or mental process)
estimating a difference between flexibility for said ligand in the bulk versus in said binding pocket in terms of orientational changes. (mathematical concept and/or mental process)
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.
Therefore, claims 1-20 recite an abstract idea as the dependent claims will inherit the abstract ideas from the independent claims.
[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.
The additional element in independent claim 1 includes:
A system, comprising: a computer having a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to:
The additional element in independent claim 8 includes:
A method for physics-based binding affinity estimation, the method comprising the steps of
The additional element in independent claim 17 includes:
A method for physics-based binding affinity estimation, the method comprising the steps of:
The additional elements of a system, comprising: a computer having a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: (Claim 1), a method for physics-based binding affinity estimation, the method comprising the steps of (Claim 8) a method for physics-based binding affinity estimation, the method comprising the steps of (Claim 17) fail to integrate a judicial exception into a practical application 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).
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 1-20 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, and therefore claims 1-20 are directed to an abstract idea (MPEP 2106.04(d)).
[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.
The additional elements recited in claims 1-20 are identified above, and carried over from Step 2A: Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A: Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of a system, comprising: a computer having a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: (Claim 1), a method for physics-based binding affinity estimation, the method comprising the steps of (Claim 8) a method for physics-based binding affinity estimation, the method comprising the steps of (Claim 17) are conventional fail to integrate a judicial exception into a practical application 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).
Therefore, when taken alone, all additional elements in claims 1-20 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-20 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (Kumar et al, Binding Affinity Estimation From Restrained Umbrella Sampling Simulations, bioarxiv, October 28, 2021) in view of Heinzelmann et al. (Heinzelmann, G.; Gilson, M. K. Automation of Absolute Protein-Ligand Binding Free Energy Calculations for Docking Refinement and Compound Evaluation. Scientific Reports 2021, 11 (1)) in further view of Sugita et al. (Yuji Sugita, Akio Kitao, Yuko Okamoto; Multidimensional replica-exchange method for free-energy calculations. J. Chem. Phys. 15 October 2000; 113 (15): 6042–6051.) in further view of Woo et al. (Woo, H.-J.; Roux, B. Calculation of Absolute Protein–Ligand Binding Free Energy from Computer Simulations. Proceedings of the National Academy of Sciences 2005, 102 (19), 6825–6830). The italicized text corresponds to the instant claim limitations.
With respect to the limitations of Claims 1, 8, 10, 17, Kumar et al. teaches The introduction of a restraining potential based on the root-mean-square deviation (RMSD) of the ligand relative to its average bound conformation, reduces the flexibility of the ligand and the number of conformations that need to be sampled. the orientation angle of the ligand with respect to the protein as determined using the orientation quaternion formalism, provides a simple way of determining the absolute binding free energy with a feasible computational cost. Among the four different sets of restraints, the two involving orientation restraints predict binding free energies similar to that determined experimentally. (pg. 25, 1st paragraph, and estimate a binding affinity between said ligand and said target molecule by: creating a unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables (Claim 1) A method for physics-based binding affinity estimation, the method comprising the steps of: creating a unified simulation for a ligand and a target molecule, said unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables; (Claim 8); A method for physics-based binding affinity estimation, the method comprising the steps of: (Claim 17), creating a unified simulation for said ligand and said target molecule, said unified simulation comprising a plurality of replicas, wherein each replica is associated with four restraints along four variables; (Claim 17) Kumar et al. also teaches also teaches each sampled configuration will be assigned a weight, which can be used to construct the PMF in terms of a desired collective variable. Suppose that a system is biased (for instance, within a BEUS scheme) using N different biasing potentials 𝑈𝑖(𝒓), where 𝑖 = 1,…,𝑁, and 𝒓 represents all atomic coordinates. Typically, 𝑈𝑖(𝒓) is a harmonic potential defined in terms of a collective variable with varying centers for different 𝑖. Assuming an equal number of sampled configurations from each of the 𝑁 generated trajectories, we can combine them in a single set of samples {𝒓𝑘} (irrespective of which bias was used to generate each sample 𝒓𝑘) and determine the weight of each sample (Free energy calculations using non-parametric reweighting, and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule (Claim 1) performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (Claim 8) recording said data; and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (Claim 17), wherein the step of creating said unified simulation further comprises the step of simulating varying distances between said ligand and said target molecule, wherein the distance between said ligand and said target molecule in a first replica reflects said ligand and said target molecule when completely bound, wherein the distance between said ligand and said target molecule in a second replica reflects said ligand and said target molecule when completely unbound, and wherein the distances between said ligand and said target molecule in the remaining replicas falls between those of the first replica and the second replica. (Claim 10), wherein the step of performing said single non-parametric reweighting analysis further comprises: estimating a likelihood of finding said ligand in the bulk versus finding said ligand at a specific orientation and conformation within a binding pocket of the target molecule; estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of movement; estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of fluctuations in root-mean-square deviation; and estimating a difference between flexibility for said ligand in the bulk versus within said binding pocket in terms of orientational changes. (Claims 14, Claim 20)
With respect to the limitations of Claims 4, Kumar et al. teaches the models were solvated in a box of TIP3P waters and 0.15 M NaCl. (pg. 14, paragraph 2, wherein said processor is configured to generate said model by simulating said ligand and said target molecule in a box of water and ions (Claim 4)
With respect to the limitations of Claims 6, 9, 18, Kumar et al. teaches (1) distance between the heavy atom center of mass of heparin and that of the protein (𝑑) and (2) the orientation angle of heparin with respect to the protein (Ω). Two independent sets of simulations were performed. The distance-based SMD simulation was run for 9.5 ns, while the orientation based SMD simulation was run for 8 ns. (pg. 15) and Four independent sets of distance (𝑑) based BEUS simulations were performed, with no restraints, restraint on Ω, restraint on 𝑟𝐿 and 𝑃, and restraints on Ω, 𝑟𝐿, and 𝑟𝑃. Two sets of BEUS simulations were also performed using the Ω collective variable, one with and one without a restraint on 𝑟𝐿 and 𝑟𝑃. Selected SMD conformations were assigned to individual BEUS windows with equal spacing in each one of these BEUS simulations. The distance-based BEUS simulation ran for 10 ns with 31 replicas/windows and the orientation-based simulation ran for 10 ns with 30 replicas/windows. The force constant used for ligand-protein distance (𝑑) in distance-based BEUS was 2 kcal/(mol.Å2) while the orientation was restrained as in SMD simulations using a force constant of 0.5 kcal/(mol. 𝑑𝑒𝑔𝑟𝑒𝑒2 ). For orientation-based BEUS simulations, the force constant for the ligand orientation angle (as in SMD simulations) was set to 0.5 kcal/(mol. 𝑑𝑒𝑔𝑟𝑒𝑒2 ). The force constant used for 𝑟𝐿 and 𝑟𝑃 was 1 kcal/(mol.Å2). (pg. 16) (wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (Q), a root-mean-square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square-deviation of said target molecule with respect to said reference structure (rp). (Claim 6) wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (Q), a root-mean-square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square-deviation of said target molecule with respect to said reference structure (rp). (Claim 9), wherein said four variables comprise a distance between the mass centers of said ligand and said target molecule (d), an orientation of said ligand (Q), a root-mean-square-deviation of said ligand with respect to a reference structure (rL), and a root-mean-square-deviation of said target molecule with respect to said reference structure (rp). (Claim 18))
Kumar et al. does not explicitly teach
generate a model for a ligand bound to a target molecule and estimate a binding affinity between said ligand and said target molecule by (Claim 1, 8, 17),
exchanging data for said four variables between a subset of said replicas; (Claim 1, 8, 17)
wherein said processor is configured to generate said model using at least one docking method. (claim 2),
wherein said processor is configured to generate said model using x-ray crystallography. (Claim 3)
wherein said processor is configured to generate said model by simulating a harmonic restraint on said ligand and said target molecule (Claim 5)
wherein said ligand is a drug, and wherein said target molecule is a protein. (Claim 7)
wherein step of simulating varying distances between said ligand and said target molecule further comprises performing all the simulations simultaneously. (Claim 11)
wherein the step of exchanging data for said four variables further comprises the steps of: establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and using said replicas to move between said nodes (Claim 12)
further wherein said replicas have different centers for said four restraints. (Claim 13)
wherein the step of performing said single non-parametric reweighting analysis further comprises the step of estimating AG° according to the equation
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(Claim 15)
further comprising the step of recording said data exchanged between said subset of replicas (Claim 16)
wherein the step of exchanging data for said four variables further comprises the steps of: establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and using said replicas to move between said nodes (Claim 19)
With respect to the limitations of Claims 1-3, 7, 8, 15, 17, Heinzelmann et al. teaches Absolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies (abstract) The SDR method was applied to the crystal pose as well as five poses generated by docking with the AutoDock Vina script included in the BAT.py distribution and explained in the User Guide (Protein-ligand test systems, 2nd paragraph, generate a model for a ligand bound to a target molecule and estimate a binding affinity between said ligand and said target molecule by (Claim 1), creating a unified simulation for a ligand and a target molecule (Claim 8), generating a model for a ligand bound to a target molecule (Claim 17), wherein said processor is configured to generate said model using at least one docking method. (claim 2), wherein said processor is configured to generate said model using x-ray crystallography. (Claim 3), wherein said ligand is a drug, and wherein said target molecule is a protein. (Claim 7) wherein the step of performing said single non-parametric reweighting analysis further comprises the step of estimating AG° according to the equation
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(Claim 15, any skilled person in the art would understand to use the standard formula to calculate free energy)
With respect to the limitations of Claims 1, 8, 11, 16, 17, Sugita et al. developed a new simulation algorithm for free-energy calculations. The method is a multidimensional extension of the replica-exchange method. While pairs of replicas with different temperatures are exchanged during the simulation in the original replica-exchange method, pairs of replicas with different temperatures and/or different parameters of the potential energy are ex changed in the new algorithm. This greatly enhances the sampling of the conformational space and allows accurate calculations of free energy in a wide temperature range from a single simulation run, using the weighted histogram analysis method. (abstract) After every 10 fs of parallel MD simulations, eight pairs of replicas corresponding to neighboring temperatures were simultaneously exchanged, and the pairing was alternated between the two possible choices. The difference between REUS1 and US1 is whether replica exchange is performed or not during the parallel MD simulations. In REUS1 seven pairs of replicas corresponding to “neighboring” umbrella potentials, Vm and Vm+1, were simultaneously exchanged after every 200 fs of parallel MD simulations, and the pairing was alternated between the two possible choices. (pg. 7, paragraph 3, exchanging data for said four variables between a subset of said replicas; (Claim 1) creating a unified simulation comprising a plurality of replicas, (Claim 1) creating a unified simulation for a ligand and a target molecule, (Claim 8) exchanging data for said four variables between a subset of said replicas; and (Claim 8) creating a unified simulation for said ligand and said target molecule, (Claim 17), exchanging data for said four variables between a subset of said replicas (Claim 17) recording said data; and (Claim 17) Sugita et al. also teaches the random walk allows the simulation to go over any energy barrier and sample much wider configurational space than by conventional methods. Monitoring the energy in a single simulation run, one can obtain not only the global-minimum-energy state but also any thermodynamic quantities as a function of temperature for a wide temperature range. The latter is made possible by the single-histogram [2] or multiple-histogram [3] reweighting techniques (an extension of the multiple-histogram method is also referred to as the weighted histogram analysis method (WHAM) (Introduction, first paragraph). To cover the entire range of the coordinate, biasing potentials, which are called “umbrella potentials,” are imposed. Thus, the system is restrained to remain near the prechosen value of the reaction coordinate specified by each umbrella potential, and a series of simulations with different umbrella potentials are performed. WHAM [4] is often employed to calculate the free-energy profiles from the histograms obtained by each simulation. And have also presented a multidimensional extension of the original replica-exchange method. One example of this approach is the combination of the replica-exchange method with the umbrella sampling, which we refer to as the replica-exchange umbrella sampling (REUS). While pairs of replicas with different temperatures are exchanged during the simulation in the original replica-exchange method, pairs of replicas with different temperatures and/or different biasing potentials for the umbrella sampling are exchanged in REUS. This greatly enhances the sampling of the conformational space and allows accurate calculations of free energy in a wide temperature range from a single simulation run, using the weighted histogram analysis method. The difference between REUS and the conventional umbrella sampling is just whether the replica-exchange process is performed or not. Only minor modifications to the conventional umbrella sampling method are necessary. However, the advantage of REUS over the umbrella sampling is significant, and the effectiveness was established with the system of an alanine trimer. (Conclusion) the probability distributions corresponding to neighboring parameters should have enough overlaps. Applicant claims connectivity across four restraint dimensions so that one analysis becomes possible. Sugita et al. also teaches that, the overlap precondition, demonstrates it works in two dimensions and suggests it can be applied to more. The simulations are run simultaneously. (and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule (Claim 1) performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (Claim 8), recording said data; and performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy for said ligand and said target molecule. (Claim 17) wherein step of simulating varying distances between said ligand and said target molecule further comprises performing all the simulations simultaneously. (Claim 11), further comprising the step of recording said data exchanged between said subset of replicas (Claim 16)
With respect to the limitations of Claims 12, 13 19, Sugita et al. teaches it is best to assign each replica to each node exchanging Tm, Eλm an dTn, Eλn among nodes is much faster than exchanging coordinates and momenta. This means that we keep track of the permutation function m (i;t) =f−1 (i;t) in Eq.(3) as a function of MD step t throughout the simulation. There are exchange rules that govern this. (pg. 4, wherein the step of exchanging data for said four variables further comprises the steps of: establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and using said replicas to move between said nodes (Claim 12), further wherein said replicas have different centers for said four restraints. (Claim 13), wherein the step of exchanging data for said four variables further comprises the steps of: establishing exchange rules to connect said plurality of replicas, wherein each replica is associated with one of a plurality of nodes in the unified simulation; and using said replicas to move between said nodes (Claim 19)
With respect to the limitations of Claims 1, 5, Woo et al. teaches running a simulation on a computer and harmonic biasing potentials used are the conformational restraint uc, the orientational restraint uo, and the axis restraint ua. (pg. 6828, col. 1, paragraph 1) a system, comprising: a computer having a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to (Claim 1), wherein said processor is configured to generate said model by simulating a harmonic restraint on said ligand and said target molecule (Claim 5)
A person of ordinary skill in the art would be motivated to combine Kumar et al. in view of Sugita et al. in view of Woo et al. in view of Heinzelmann et al. to create a method for estimating free energy in protein ligand binding. As Kumar et al. provides the creating a unified simulation comprising a plurality of replicas four restraints along four variables; Sugita et al. also teaches creating a unified simulation comprising a plurality of replicas as well as performing a single non-parametric reweighting analysis with said data to estimate an absolute binding free energy via connectivity across dimensions.
Woo et al. teaches the use of harmonic restraints in a simulation. Heinzelmann et al. teaches the calculation of free energies from protein ligand binding simulations as well as using crystal poses in their models as well as applying simulations to determine protein ligand free energy interactions. There is a reasonable expectation of success each part of the method works independently therefore they are expected to continue to work together.
Conclusion
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/C.H.B./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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