Recent progress in generating large virtual chemical libraries has added billions of diverse chemical structures that significantly extend opportunities for the discovery of new pharmaceutical agents. Despite the achievements of highly active antiretroviral therapy treatment of HIV infection and its comorbidities, discovery of safer and more efficacious medicines is still required. Agonists of toll-like receptors (TLR) and stimulators of IFN genes (STING) enhance innate and adaptive immunity, including inducing antitumor immune responses. We have thus tried to identify such novel molecules with the desirable biological activities among about one billion structures included in the SAVI library. To identify the potential hits, we applied in silico screening based on the modified version of computer program PASS (Prediction of Activity Spectra for Substances) jointly with the similarity estimates based on MNA (Multilevel Neighborhoods of Atoms) and QNA (Quantitative Neighborhoods of Atoms) descriptors. After the application of this combined procedure to the analysis of the whole SAVI library, about four thousand molecules were selected for further analysis by molecular docking using the ICM-Pro program. The application of the docking procedure for cleaning of the PASS training sets led to a significant increase in the accuracy of structure-activity relationships, which improves the results of prediction. Different strategies of virtual screening in large databases will be discussed, and the results of the analysis of the SAVI library will be presented.

Detection of novel TLR and STING ligands among one billion structures from the Synthetically Accessible Virtual Inventory (SAVI)

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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