HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques

摘要

Molecular-similarity searches based on two-dimensional (2D) fingerprint and three-dimensional (3D) shape represent two widely used ligand-based virtual screening (VS) methods in computer-aided drug design. 2D fingerprint-based VS utilizes the binary fragment information on a known ligand, whereas 3D shape-based VS takes advantage of geometric information for predefined features from a 3D conformation. Given their different advantages, it would be desirable to hybridize 2D fingerprint and 3D shape molecular-similarity approaches in drug discovery. Here, we presented a general hybrid molecular-similarity protocol, referred to as HybridSim, obtained by combining the 2D fingerprint-and 3D shape-based similarity search methods and evaluated its performance on 595,036 actives and decoys for 40 pharmaceutically relevant targets available in the Directory of Useful Decoys Enhanced (DUD-E). Our results showed that HybridSim significantly improved the overall performance in 40 VS projects as compared with using only 2D fingerprint and 3D shape methods. Furthermore, HybridSim-VS, the first online platform using the proposed HybridSim method coupled with 17,839,945 screenable and purchasable compounds, was developed to provide large-scale and proficient VS capabilities to experts and nonexperts in the field.