Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein-Ligand Complexes in Cognate Docking

0487122 - ÚOCHB 2018 RIV US eng J - Journal Article
Ajani, Haresh - Pecina, Adam - Eyrilmez, Saltuk M. - Fanfrlík, Jindřich - Haldar, Susanta - Řezáč, Jan - Hobza, Pavel - Lepšík, Martin
Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein-Ligand Complexes in Cognate Docking.
ACS Omega. Roč. 2, č. 7 (2017), s. 4022-4029. ISSN 2470-1343. E-ISSN 2470-1343
R&D Projects: GA ČR(CZ) GBP208/12/G016; GA ČR(CZ) GJ16-11321Y
Institutional support: RVO:61388963
Keywords : aldose reductase inhibition * biological applications * mechanical calculations
OECD category: Physical chemistry
https://pubs.acs.org/doi/full/10.1021/acsomega.7b00503

General and reliable description of structures and energetics in proteinligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called ”SQM/COSMO” SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs.
Permanent Link: http://hdl.handle.net/11104/0281802