Abstract: A system and method that given one or more input molecules, produces a contextualized summary of characteristics of related target molecules, e.g., proteins. Using a knowledge graph which is populated with all known molecules, input molecules are analyzed according to various similarity indexes which relate the input molecules to target proteins or other biological entities. The knowledge graph may also comprise scientific literature, governmental data (FDA clinical phase data), private research endeavors (general assays, etc.), and other related biological data. The summary produced may comprise target proteins that satisfy certain biological properties, general assay results (ADMET characteristics), related diseases, off-target molecule interactions (non-targeted molecules involved in a specific pathway or cascade), market opportunities, patents, experiments, and new hypothesis.

Abstract: A system and method that given one or more input molecules, produces a contextualized summary of characteristics of related target molecules, e.g., proteins. Using a knowledge graph which is populated with all known molecules, input molecules are analyzed according to various similarity indexes which relate the input molecules to target proteins or other biological entities. The knowledge graph may also comprise scientific literature, governmental data (FDA clinical phase data), private research endeavors (general assays, etc.), and other related biological data. The summary produced may comprise target proteins that satisfy certain biological properties, general assay results (ADMET characteristics), related diseases, off-target molecule interactions (non-targeted molecules involved in a specific pathway or cascade), market opportunities, patents, experiments, and new hypothesis.

Abstract: A system and method that takes in a data set comprising molecular structure data and properties of interest, e.g., ADMET, EC50, IC50, etc., and determines the substructures that cause or do not cause the property of interest. The substructures may then be used to filter out potentially harmful new proposed/generated molecules or create a new data set of known active/inactive substructures of a property of interest that may fulfill other obligations. The system comprises a substructure extraction module which further comprises a scaffold extraction module and a comparison module. A scaffold extraction module clusters, searches, and extracts substructures in question while a comparison module compares the bioactivity of each molecule with and without each substructure in question to determine the substructures effect on the property of interest.

Abstract: A system and method that takes in a data set comprising molecular structure data and properties of interest, e.g., ADMET, EC50, IC50, etc., and determines the substructures that cause or do not cause the property of interest. The substructures may then be used to filter out potentially harmful new proposed/generated molecules or create a new data set of known active/inactive substructures of a property of interest that may fulfill other obligations. The system comprises a substructure extraction module which further comprises a scaffold extraction module and a comparison module. A scaffold extraction module clusters, searches, and extracts substructures in question while a comparison module compares the bioactivity of each molecule with and without each substructure in question to determine the substructures effect on the property of interest.

Abstract: A system and method that predicts whether a given protein-ligand pair is active or inactive, the ground-truth protein-ligand complex crystalline-structure similarity, and an associated bioactivity value. The system and method further produce 3-D visualizations of previously unknown protein-ligand pairs that show directly the importance assigned to protein-ligand interactions, the positive/negative-ness of the saliencies, and magnitude. Furthermore, the system and method make enhancements in the art by accurately predicting protein-ligand pair bioactivity from decoupled models, removing the need for docking simulations, as well as restricting attention of the machine learning between protein and ligand atoms only.

Abstract: A system and method for an automated pharmaceutical research data platform comprising a data curation platform which searches for and ingests a plurality of unstructured, heterogenous medical data sources, extracts relevant information from the ingested data sources, and creates a massive, custom-built and intricately related knowledge graph using the extracted data, and a data analysis engine which receives data queries from a user interface, conducts analyses in response to queries, and returns results based on the analyses. The system hosts a suite of modules and tools, integrated with the custom knowledge graph and accessible via the user interface, which may provide a plurality of functions such as statistical and graphical analysis, similarity based searching, and edge prediction among others.