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SQM/COSMO Scoring Function: Reliable Quantum‐Mechanical Tool for Sampling and Ranking in Structure‐Based Drug Design

Adam Pecina, Saltuk M. Eyrilmez, Cemal Köprülüoğlu, Vijay Madhav Miriyala, Martin Lepšı́k, Jindřich Fanfrlík, Jan Řezáč, Pavel Hobza

2020ChemPlusChem28 citationsDOI

Abstract

Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.

Topics & Concepts

Virtual screeningComputer scienceRanking (information retrieval)GeneralityQuantum chemicalQuantumData miningMachine learningComputational chemistryChemistryMolecular dynamicsPhysicsPsychologyMoleculePsychotherapistQuantum mechanicsOrganic chemistryComputational Drug Discovery MethodsProtein Structure and DynamicsChemical Synthesis and Analysis
SQM/COSMO Scoring Function: Reliable Quantum‐Mechanical Tool for Sampling and Ranking in Structure‐Based Drug Design | Litcius