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 1-9 are currently pending and under exam herein.
Claims 1-9 are rejected.
Priority
The instant application claims priority from foreign application CN202111570217.2 filed on 12/21/2021. Thus the effective filing date of the instant application is 12/21/2021
Drawings
The Drawings filed on 7/22/2022 are objected. Figure 4 is blurry and cannot be deciphered. Therefore, it is objected to by the examiner.
Claim Rejections - 35 USC § 112
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.
Claim 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “quasi-prediction” in claim 2 is a relative term which renders the claim indefinite. The term “quasi-prediction” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
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 1-9 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 1-9 are directed to a bioretrosynthetic method based on an AND-OR tree and single-step reaction template prediction and are eligible.
[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:
A bioretrosynthetic method based on an AND-OR tree and single-step reaction template prediction, comprising the following steps: Sl: selecting an OR node from a pre-constructed AND-OR tree, and using a molecule corresponding to the OR node as a product molecule to be predicted (mental process)
wherein the pre-constructed AND-OR tree comprises two types of nodes: AND node and OR node; the AND node represents a reaction template, and the OR node represents a molecule (mental process, this limits what the mental process is done on)
predicting k templates in a preset template set that are most likely to synthesize the product molecule using a pre-constructed single-step reaction template prediction model, forming a template set Top-k, and assigning a weight value ranged between 0 and 1 to each template (mental process, mathematics)
wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
expanding the pre-constructed AND-OR tree, specifically comprising: adding each template in the Top-k as a new AND node to the AND-OR tree to obtain newly-added k AND nodes, and using the OR node selected in step S 1 as a parent node of the newly-added k AND nodes (mental process, mathematics)
adding each reaction substrate molecule corresponding to each newly-added AND node to the AND-OR tree as an OR node to obtain newly-added OR nodes, with the newly-added AND node as a parent node of the newly-added OR nodes (mental process, mathematics)
determining whether there is an AND node in step S3, wherein a substrate molecule corresponding to a child node of the AND node belongs to a known metabolite set: Sink- Compounds set; if there is an AND node, finding a biosynthetic pathway, stopping an iterative retrosynthetic process, and generating the biosynthetic pathway (mental process, mathematics)
if there is no AND node, determining whether the maximum number of iterations has been reached; if the maximum number of iterations is reached, stopping the iterative retrosynthetic process (mental process, mathematics)
repeating steps S1 to S4 until a biosynthetic pathway is found or the maximum number of iterations is reached. (mental process, mathematics)
Dependent claim 2 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein in step Si: in the AND-OR tree, a root node and a leaf node each are an OR node, and an intermediate node is an AND node or an OR node; a child node of each AND node is an OR node, representing all substrate molecules in a reaction template (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
a child node of each non-leaf OR node in the AND-OR tree is an AND node (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
each AND node represents a reaction template capable of producing a molecule corresponding to a parent node of the AND node, and the root node of the AND-OR tree is a target molecule node for quasi-prediction of a biosynthetic pathway (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
an initially-constructed AND- OR tree comprises only one root node, corresponding to the target molecule of a biosynthetic pathway to be predicted. (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
Dependent claim 3 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein in step S1, each node of the AND-OR tree has a weight value; (mathematical process)
wherein in step S1, each node of the AND-OR tree has a weight value; a weight value of the AND node is a weight value of a corresponding reaction template, indicating a prediction probability of the corresponding reaction template (mathematical process)
OR nodes other than the root node each have a weight value of the parent node except for the OR nodes, and the root node has a weight value of 1 (mathematical process).
Dependent claim 4 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein in step S1, the selected OR node is a leaf node in the AND-OR tree that does not belong to the known Sink-Compounds set and has a maximum weight value (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
if there are a plurality of the leaf nodes with the maximum weight value, one of the leaf nodes is selected randomly as the OR node. (mental process, mathematics, this limits what the mental process and or mathematical process is done on)
Dependent claim 5 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the pre-constructed single-step reaction template prediction model is a multi-classification model based on machine learning; and step S2 specifically comprises: S2.1: predicting a probability that all reaction templates in the preset template set are capable of producing an input product molecule using the constructed multi-classification model (mathematical process)
S2.2: selecting top k reaction templates with the highest probabilities to form the template set Top-k (mental process, mathematical process)
setting a weight value of each reaction template in the template set Top-k as a corresponding probability value. (mathematical process)
Dependent claim 7 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein in step S4, a process of generating the biosynthetic pathway comprises the following steps: (1) checking whether each leaf node in the AND-OR tree is in the Sink-Compounds set (mental process)
marking the leaf node in the Sink-Compounds as "true", and marking the leaf node not in the Sink- Compounds as "false" (mental process)
(2) for a non-leaf AND node in the AND-OR tree, marking the non-leaf AND node as "true" if and only if each child node of the non-leaf AND node is marked as "true", otherwise marking the non-leaf AND node as "false"; and for a non-leaf OR node in the AND-OR tree, marking the non-leaf OR node as "true" if and only if the non-leaf OR node comprises at least one child node marked as "true", otherwise marking the non-leaf OR node as "false" (mental process)
(3) if the root node is marked as "false", it indicates that no synthetic pathway has been found, outputting "No Solution"; otherwise, deleting all nodes marked as "false" in the AND-OR tree, and remaining a subtree representing a synthetic pathway of a target molecule. (mental process)
Dependent claim 8 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
a retrosynthesis planning module used for selecting an OR node from a pre-constructed AND- OR tree, and using a molecule corresponding to the OR node as a product molecule to be predicted; wherein the pre-constructed AND-OR tree comprises two types of nodes, an AND node and the OR node (mental process)
AND node represents a reaction template, and the OR node represents a molecule (mental process)
a reaction template prediction module used for predicting k templates in a preset template set that are most likely to synthesize the product molecule using a pre-constructed single-step reaction template prediction model, forming a template set Top-k, and assigning a weight value ranged between 0 and 1 to each template (mental process, mathematical process)
wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set; an AND-OR tree extension module used for expanding the pre-constructed AND-OR tree, specifically comprising: adding each template in the Top-k as a new AND node to the AND-OR tree to obtain newly-added k AND nodes, and using the OR node selected in the retrosynthesis planning module as a parent node of the newly-added k AND nodes (mental process, mathematical process)
adding each reaction substrate molecule corresponding to each newly-added AND node to the AND-OR tree as an OR node to obtain newly-added OR nodes, with the newly-added AND node as a parent node of the newly- added OR nodes (mental process)
biosynthetic pathway generation module used for determining whether there is an AND node in the AND-OR tree obtained by the AND-OR tree extension module, wherein a substrate molecule corresponding to a child node of the AND node belongs to a known metabolite set: Sink- Compounds set (mental process)
if there is an AND node, finding a biosynthetic pathway, stopping an iterative retrosynthetic process, and generating the biosynthetic pathway; if there is no AND node, determining whether the maximum number of iterations has been reached; if the maximum number of iterations is reached, stopping the iterative retrosynthetic process (mental process)
if the maximum number of iterations is not reached, repeating steps of the retrosynthesis planning module to the biosynthetic pathway generation module until a biosynthetic pathway is found or the maximum number of iterations is reached (mental process, mathematical 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 1-9 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 6 includes:
wherein in step S3, each reaction substrate molecule of the newly-added AND nodes is obtained by calling a function in an open source library RDChiral
in the function, an input parameter is a SMILES sequence of the reaction template and the product molecule, and an output is a list of the corresponding substrate molecules.
The additional element in independent claim 9 includes:
a biosynthetic pathway visualization module for visually displaying an obtained biosynthetic pathway of a target molecule.
The additional elements of wherein in step S3, each reaction substrate molecule of the newly-added AND nodes is obtained by calling a function in an open source library RDChiral (Claim 6), in the function, an input parameter is a SMILES sequence of the reaction template and the product molecule, and an output is a list of the corresponding substrate molecules (Claim 6), a biosynthetic pathway visualization module for visually displaying an obtained biosynthetic pathway of a target molecule (Claim 9) merely invoke a computer as a tool and does not improve the computer (see MPEP 2106.04(d) and 2106.05(a)).
Claims 1-5, 7-8 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
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 6, 9 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 1-9 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 6, 9 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 wherein in step S3, each reaction substrate molecule of the newly-added AND nodes is obtained by calling a function in an open source library RDChiral (Claim 6), in the function, an input parameter is a SMILES sequence of the reaction template and the product molecule, and an output is a list of the corresponding substrate molecules (Claim 6), a biosynthetic pathway visualization module for visually displaying an obtained biosynthetic pathway of a target molecule (Claim 9) are conventional and merely invoke a computer as a tool used in the recited judicial exceptions (see MPEP 2106.05(a)). Evidence for conventionality is shown by González-Medina et al. (González-Medina et al. Open Chemoinformatic Resources to Explore the Structure, Properties and Chemical Space of Molecules. RSC Advances 2017, 7 (85), 54153–54163) which is a review for different chemoinformatic tools including RDKIT and various visualization modules (pg. 54160, col. 2 paragraph 2)
Claims 1-5, 7-8 do not recite any elements in addition to the judicial exception. Therefore, when taken alone, all additional elements in claims 6, 9 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 1-9 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 1-9 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (Chen et al. Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search, arxiv, 6/29/2020) in further view of Koch et al. (Koch et al. Reinforcement Learning for Bioretrosynthesis. ACS Synthetic Biology 2019, 9 (1), 157–168). The italicized text corresponds to the instant claim limitations.
With respect to the limitations of Claims 1, Chen et al. teaches that based on the AND-OR tree representation, we propose an A*-like planning algorithm which is guided by a neural network learned from past retrosynthesis planning experiences. (pg. 2, col. 1, paragraph 5, bioretrosynthetic method based on an AND-OR tree and single-step reaction template prediction (Claim 1)) Chen et al. also teaches the search tree of PNS is an AND-OR tree T, where each AND node needs all its children to be proved, while OR node requires at least one to be satisfied. Each node u ∈ T is associated with a proof number pn(u) that defines the minimum number of leaf nodes to be proved in order to prove u. Similarly, the disproof number dn(u) finds the minimum number of leaf nodes needed to disprove u. With such definition, we can recursively define these numbers for internal nodes. The application of one-step retrosynthesis model B on molecule m can be represented using one block of AND-OR tree (denoted as AND-OR stump), with molecule node as ‘OR’ node and reaction node as ‘AND’ node. This is because a molecule m can be synthesized using any one of its children reactions (or-relation), and each reaction node requires all of its children molecules (and-relation) to be ready (pg. 3, col. 2, par. 2-3) and S(l: selecting an OR node from a pre-constructed AND-OR tree, and using a molecule corresponding to the OR node as a product molecule to be predicted; wherein the pre-constructed AND-OR tree comprises two types of nodes: AND node and OR node; the AND node represents a reaction template, and the OR node represents a molecule (Claim 1)) Chen et al. also teaches the use of probability scores in order to rank top-k predictions and a template-based MLP model for one-step retrosynthesis. Following literature, they formulate the one-step retrosynthesis as a multi-class classification problem, where given a molecule as product, the goal is to predict possible reaction templates. Reactants are obtained by applying the predicted templates to product molecule. There are in total ∼ 380K distinct templates. Throughout all experiments, we take the top-50 templates predicted by MLP model and apply them on each product to get corresponding reactant lists (pg. 7, col. 1, paragraph 2, S2: predicting k templates in a preset template set that are most likely to synthesize the product molecule using a pre-constructed single-step reaction template prediction model, forming a template set Top-k, and assigning a weight value ranged between 0 and 1 to each template (Claim 1)) After picking the node m with minimum cost estimation, they will expand the search tree with k one-step retrosynthesis proposals. Specifically, for each proposed retrosynthesis they create a reaction node, and for each molecule, they create a molecule node under the reaction node. This will create an AND-OR stump under node m. (pg. 4, col. 2 paragraph 5, S3: expanding the pre-constructed AND-OR tree, specifically comprising: adding each template in the Top-k as a new AND node to the AND-OR tree to obtain newly-added k AND nodes, and using the OR node selected in step S 1 as a parent node of the newly-added k AND nodes; adding each reaction substrate molecule corresponding to each newly-added AND node to the AND-OR tree as an OR node to obtain newly-added OR nodes, with the newly-added AND node as a parent node of the newly-added OR nodes (Claim 1)) Chen et al. also teaches that given a single target molecule t ∈ M and an initial set of molecules I ⊂ M, we are interested in synthesizing t via a sequence of chemical reactions using reactants that are from or can be synthesized by I. In this case, I corresponds to a set of molecules that are commercially available. (pg. 2, col. 2, Retrosynthesis planning, paragraph 1, S4: determining whether there is an AND node in step S3, wherein a substrate molecule corresponding to a child node of the AND node belongs to a known metabolite set: Sink- Compounds set; if there is an AND node, finding a biosynthetic pathway, stopping an iterative retrosynthetic process, and generating the biosynthetic pathway; and if there is no AND node, determining whether the maximum number of iterations has been reached; if the maximum number of iterations is reached, stopping the iterative retrosynthetic process; and if the maximum number of iterations is not reached, repeating steps S1 to S4 until a biosynthetic pathway is found or the maximum number of iterations is reached (Claim 1)).
With respect to the limitations of Claim 2, Chen et al. teaches the application of one-step retrosynthesis model B on molecule m can be represented using one block of AND-OR tree (denoted as AND-OR stump), with molecule node as ‘OR’ node and reaction node as ‘AND’ node. This is because a molecule m can be synthesized using any one of its children reactions (or-relation), and each reaction node requires all of its children molecules (and-relation) to be ready (pg. 3, col. 2, Represent retrosynthesis planning using AND-OR tree, paragraph 1, wherein in step Si: in the AND-OR tree, a root node and a leaf node each are an OR node, and an intermediate node is an AND node or an OR node; a child node of each AND node is an OR node, representing all substrate molecules in a reaction template; a child node of each non-leaf OR node in the AND-OR tree is an AND node; each AND node represents a reaction template capable of producing a molecule corresponding to a parent node of the AND node, and the root node of the AND-OR tree is a target molecule node for quasi-prediction of a biosynthetic pathway; and an initially-constructed AND- OR tree comprises only one root node, corresponding to the target molecule of a biosynthetic pathway to be predicted (Claim 2)).
With respect to the limitations of Claim 3, Chen et al. assigns a value function to each node for reactions and molecules as well as probabilities of each reaction and gives a cost needed to synthesize each molecule. (pg. 5, col. 1, paragraph 3, wherein in step S1, each node of the AND-OR tree has a weight value; a weight value of the AND node is a weight value of a corresponding reaction template, indicating a prediction probability of the corresponding reaction template; and OR nodes other than the root node each have a weight value of the parent node except for the OR nodes, and the root node has a weight value of 1. (Claim 3))
With respect to the limitations of Claim 4, Chen et al. explains the frontier contains all the molecule nodes in T that haven’t been expanded before. Since they want to minimize the total cost of the final solution, an ideal option to expand next would be the molecule node which is part of the best synthesis plan. The selection of the frontier nodes is the cost equivalent of selecting the maximum probability, as minimizing cost is equivalent to maximizing probability (pg. 4, col. 2, paragraph 2, wherein in step S1, the selected OR node is a leaf node in the AND-OR tree that does not belong to the known Sink-Compounds set and has a maximum weight value; and if there are a plurality of the leaf nodes with the maximum weight value, one of the leaf nodes is selected randomly as the OR node (Claim 4)).
With respect to the limitations of Claim 5, Chen et al. formulates the one-step retrosynthesis as a multi-class classification problem, where given a molecule as product, the goal is to predict possible reaction templates. Reactants are obtained by applying the predicted templates to product molecule. There are in total ∼ 380K distinct templates. Throughout all experiments, we take the top-50 templates predicted by MLP model and apply them on each product to get corresponding reactant lists. (pg. 7, col. 1, paragraph 2, wherein the pre-constructed single-step reaction template prediction model is a multi-classification model based on machine learning; and step S2 specifically comprises: S2.1: predicting a probability that all reaction templates in the preset template set are capable of producing an input product molecule using the constructed multi-classification model; and S2.2: selecting top k reaction templates with the highest probabilities to form the template set Top-k, and setting a weight value of each reaction template in the template set Top-k as a corresponding probability value (Claim 5))
With respect to the limitations of Claim 6, Chen et al. further extracts reaction templates with RDChiral for all reactions and discard those whose reactants cannot be obtained by applying reaction templates to their products (pg. 7, col. 1, paragraph 1, step S3, each reaction substrate molecule of the newly-added AND nodes is obtained by calling a function in an open source library RDChiral; and in the function, an input parameter is a SMILES sequence of the reaction template and the product molecule, and an output is a list of the corresponding substrate molecules (Claim 6)).
With respect to the limitations of Claim 6, Chen et al. teaches the search tree of PNS is an AND-OR tree T, where each AND node needs all its children to be proved, while OR node requires at least one to be satisfied. Each node u ∈ T is associated with a proof number pn(u) that defines the minimum number of leaf nodes to be proved in order to prove u. Similarly, the disproof number dn(u) finds the minimum number of leaf nodes needed to disprove u. This corresponds to true and false depending if the node is proved or unproved (pg. 3, col. 2, paragraph 2, wherein in step S4, a process of generating the biosynthetic pathway comprises the following steps: (1) checking whether each leaf node in the AND-OR tree is in the Sink-Compounds set; marking the leaf node in the Sink-Compounds as "true", and marking the leaf node not in the Sink- Compounds as "false";(2) for a non-leaf AND node in the AND-OR tree, marking the non-leaf AND node as "true" if and only if each child node of the non-leaf AND node is marked as "true", otherwise marking the non-leaf AND node as "false"; and for a non-leaf OR node in the AND-OR tree, marking the non-leaf OR node as "true" if and only if the non-leaf OR node comprises at least one child node marked as "true", otherwise marking the non-leaf OR node as "false"; and (3) if the root node is marked as "false", it indicates that no synthetic pathway has been found, outputting "No Solution"; otherwise, deleting all nodes marked as "false" in the AND-OR tree, and remaining a subtree representing a synthetic pathway of a target molecule (Claim 7)).
With respect to the limitations of Claims 8, Chen et al. teaches that based on the AND-OR tree representation, we propose an A*-like planning algorithm which is guided by a neural network learned from past retrosynthesis planning experiences. (pg. 2, col. 1, paragraph 5) and the search tree of PNS is an AND-OR tree T, where each AND node needs all its children to be proved, while OR node requires at least one to be satisfied. Each node u ∈ T is associated with a proof number pn(u) that defines the minimum number of leaf nodes to be proved in order to prove u. Similarly, the disproof number dn(u) finds the minimum number of leaf nodes needed to disprove u. With such definition, we can recursively define these numbers for internal nodes. The application of one-step retrosynthesis model B on molecule m can be represented using one block of AND-OR tree (denoted as AND-OR stump), with molecule node as ‘OR’ node and reaction node as ‘AND’ node. This is because a molecule m can be synthesized using any one of its children reactions (or-relation), and each reaction node requires all of its children molecules (and-relation) to be ready (pg. 3, col. 2, par. 2-3 ,a retrosynthesis planning module used for selecting an OR node from a pre-constructed AND- OR tree, and using a molecule corresponding to the OR node as a product molecule to be predicted; wherein the pre-constructed AND-OR tree comprises two types of nodes, an AND node and the OR node; the AND node represents a reaction template, and the OR node represents a molecule) Chen et al. also teaches the use of probability scores in order to rank top-k predictions and a template-based MLP model for one-step retrosynthesis. Following literature, they formulate the one-step retrosynthesis as a multi-class classification problem, where given a molecule as product, the goal is to predict possible reaction templates. Reactants are obtained by applying the predicted templates to product molecule. There are in total ∼ 380K distinct templates. Throughout all experiments, we take the top-50 templates predicted by MLP model and apply them on each product to get corresponding reactant lists (pg. 7, col. 1, paragraph 2, a reaction template prediction module used for predicting k templates in a preset template set that are most likely to synthesize the product molecule using a pre-constructed single-step reaction template prediction model, forming a template set Top-k, and assigning a weight value ranged between 0 and 1 to each template (Claim 8)). Chen et al. also teaches that after picking the node m with minimum cost estimation, they will expand the search tree with k one-step retrosynthesis proposals. Specifically, for each proposed retrosynthesis they create a reaction node, and for each molecule, they create a molecule node under the reaction node. This will create an AND-OR stump under node m. (pg. 4, col. 2 paragraph 5, an AND-OR tree extension module used for expanding the pre-constructed AND-OR tree, specifically comprising: adding each template in the Top-k as a new AND node to the AND-OR tree to obtain newly-added k AND nodes, and using the OR node selected in the retrosynthesis planning module as a parent node of the newly-added k AND nodes; adding each reaction substrate molecule corresponding to each newly-added AND node to the AND-OR tree as an OR node to obtain newly-added OR nodes, with the newly-added AND node as a parent node of the newly- added OR nodes (Claim 8)). Chen et al. also teaches that given a single target molecule t ∈ M and an initial set of molecules I ⊂ M, we are interested in synthesizing t via a sequence of chemical reactions using reactants that are from or can be synthesized by I. In this case, I corresponds to a set of molecules that are commercially available. (pg. 2, col. 2, Retrosynthesis planning, paragraph 1, a biosynthetic pathway generation module used for determining whether there is an AND node in the AND-OR tree obtained by the AND-OR tree extension module, wherein a substrate molecule corresponding to a child node of the AND node belongs to a known metabolite set: Sink- Compounds set; if there is an AND node, finding a biosynthetic pathway, stopping an iterative retrosynthetic process, and generating the biosynthetic pathway; if there is no AND node, determining whether the maximum number of iterations has been reached; if the maximum number of iterations is reached, stopping the iterative retrosynthetic process; if the maximum number of iterations is not reached, repeating steps of the retrosynthesis planning module to the biosynthetic pathway generation module until a biosynthetic pathway is found or the maximum number of iterations is reached (Claim 8)).
With respect to the limitations of Claims 9, Chen et al. teaches a retrosynthetic tree diagram which includes visualization of a synthesis pathway (pg. 14, Figure 7, a biosynthetic pathway visualization module for visually displaying an obtained biosynthetic pathway of a target molecule (Claim 9)).
Chen et al. does not explicitly teach
wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set; (Claim 1)
wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set (Claim 8)
However these limitations were known at the time as taught by Koch et al.
With respect to the limitations of Claims 1 and 8, Koch et al. teaches that chemical similarity between query (applied on a new substrate) and the native chemical transformation has been used in various studies. They adapted the strategy that proceeds in a 2-step evaluation of the reaction. In a first step, before rule application, similarity between query and native substrates is calculated. After rule application, similarity between native and query products is also calculated. This allows accounting of similarity in a manner straightforward to use with mono component reaction rules. Using this metric allows us to select chemical reactions similar to the ones present in metabolic databases, increasing our chances that this predicted reaction can be catalyzed. (pg. 158, col. 1, paragraph 6) and that after validating biological relevance of predictions for metabolic engineering, we tested RetroPath RL on a larger data set. Their previous tool was tested on the LASER database that compiles successful metabolic engineering projects, completed with compounds taken from the Metabolic Engineering journal (pg. 160, col. 2, paragraph 2, wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set; (Claim 1) wherein the preset template set is constructed based on a metabolic reaction structure in a known metabolic reaction data set (Claim 8)).
It would be obvious to a person having ordinary skill in the art to combine the retrosynthesis methods of Chen et al. with Koch et al. because both are in the same field of endeavor and are attempting to solve the same problem. There is a reasonable expectation of success because the method does not change and Kock et al. just suggests to use a different dataset with the method of Chen et al.
Conclusion
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/C.H.B./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687