Chemical condition recommendation and pathway evaluation have been transformed from a complex problem to a regular process of structural simplification with the help of computer-assisted technologies. Condition recommendation and pathway evaluation helps to understand which chemical condition and pathways may be involved in response to a disease phenotype, or drug treatment. Alfa Chemistry has established various methodologies to carry out reliable condition recommendation and pathway evaluation with high reliability and reproducibility.
Figure 1. Reaction rules play the intermediate role in two-step models for condition recommendation and pathway evaluation (Fan, F.; et al. 2018)
At Alfa Chemistry, we utilize professional knowledge of computation chemistry to carry out reliable condition recommendation and pathway evaluation.
We have designed semi-empirical reaction modes in computers in which the rule-based and network-searching methods are applied to expand the databases, and build new approaches to recommend chemical conditions and evaluate the pathway.
1. Network searching
Modern computers are able to store and search for chemical databases as large as the entire set of known molecules and reactions. We support both breadth-first-search (BFS) and synthesis optimization with constrains (SOCS) scheme to generate many possible pathways. Moreover, our scientists can estimate chemical conditions and evaluate the pathway using different searching algorithms.
2. Rule matching
Rule-based synthetic design refers to use reaction rules to predict retrosynthesis reactions, and developing logic-based and knowledge-based searching strategies for designing reaction routes. Alfa Chemistry supports rule-based de novo synthesis prediction to explore new revolutionary ways to predict and evaluate synthetic pathways. We apply various types of methods ranging from bond disconnections in LHASA to minimize the combined scoring function in Syntaurus for ranking or scoring of pathways. Moreover, our methods can meet the requirements of basic coverage of reaction space to provide the recommendation of optimal chemical conditions services.
Over-representation analysis is one of the commonly applied pathway analysis approaches used for the functional interpretation of metabolomics datasets. We use ORA to obtain the interpretation of high-dimensional molecular data and perform the in-silico simulations based on datasets. A collection of pathways are used to be analyzed, and the results of best chemical condition and pathway are able to be delivered.
We use SYNCHEM to cluster similar reactions, and learn when reactions could be applied based on the presence of key functional groups. Our experts use computer algorithms with descriptors such as the fingerprint of molecules or reactions to do classification or similarity calculation, and predict the outcome of organic reactions to judge which condition and pathway to choose, assisting in the reaction prediction or pathway design.
Our experts use SMARTS transformation to describe the transformation between product molecules and reactants, and predict the outcome of reactions based on reactant fingerprints. Based on the results of prediction, we give the best chemical condition and pathway.
Our condition recommendation and pathway evaluation services remarkably reduce the cost, promote further experiments, and accelerate the process of drug design for customers worldwide. Our personalized and all-around services will satisfy your innovative study demands. If you are interested in our services, please don't hesitate to contact us. We are glad to cooperate with you and witness your success!