RNA-dependent RNA polymerase (RdRP, RDR or RNA replicase) is an enzyme that catalyzes the replication of RNA from an RNA template. RdRPs play a vital role in the growth of RNA viruses and are important targets for antiviral drug development.

We offer Viral RNA-dependent RNA Polymerases (RdRPs) Targeted Library, which contains 1118 compounds with predicted activity against viral RdRPs. It has been carefully designed using machine learning (artificial neural networks and Bayesian statistics).

For machine learning 1706 compounds with known activity toward RdRPs of viruses (different strains of Hepatitis C virus, Hepatitis GB virus B, Influenza A virus, Influenza B virus and Human poliovirus 1) were randomly divided into two equal groups. Each group had the same amounts of active and inactive compounds (activity cutoff was 400 nM) and was used as training and test set. The training sets were used for development of Bayesian and artificial neural networks models. Both methods were based on a number of different molecular descriptors - fingerprints, topological descriptors, molecular weight, number of hydrogen donors and acceptors, number of rings, number of rotatable bonds, LogP, PSA and other. The test sets were used for validation of all models.

Virtual screening of Drug-like Green Collection toward best artificial neural networks and Bayesian models was performed. Top-scored compounds, selected by machine learning methods, were visually analyzed. The application of different artificial neural networks and models (14 in total) should allow increasing the number of active compounds identified during screenings.

Example of some compounds from training set for machine learning and
compounds selected by this approach

The designed Viral RdRPs Targeted Library comprises only drug-like compounds (PAINS compounds are filtered off). The library is intended for screening projects to find new antiviral compounds.

The summary of the Viral RdRPs Targeted Library characteristics:

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