Literature DB >> 27183985

Prospects of Applying Enhanced Semi-Empirical QM Methods for 2101 Virtual Drug Design.

Nusret Duygu Yilmazer, Martin Korth1.   

Abstract

The last five years have seen a renaissance of semiempirical quantum mechanical (SQM) methods in the field of virtual drug design, largely due to the increased accuracy of so-called enhanced SQM approaches. These methods make use of additional terms for treating dispersion (D) and hydrogen bond (H) interactions with an accuracy comparable to dispersion-corrected density functional theory (DFT-D). DFT-D in turn was shown to provide an accuracy comparable to the most sophisticated QM approaches when it comes to non-covalent intermolecular forces, which usually dominate the protein/ligand interactions that are central to virtual drug design. Enhanced SQM methods thus offer a very promising way to improve upon the current state of the art in the field of virtual drug design.

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Year:  2016        PMID: 27183985     DOI: 10.2174/0929867323666160517120005

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  3 in total

Review 1.  Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges.

Authors:  Isabella A Guedes; Felipe S S Pereira; Laurent E Dardenne
Journal:  Front Pharmacol       Date:  2018-09-24       Impact factor: 5.810

2.  Semiempirical Quantum-Chemical Methods with Orthogonalization and Dispersion Corrections.

Authors:  Pavlo O Dral; Xin Wu; Walter Thiel
Journal:  J Chem Theory Comput       Date:  2019-02-27       Impact factor: 6.006

Review 3.  Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization.

Authors:  Claudio N Cavasotto; Natalia S Adler; Maria G Aucar
Journal:  Front Chem       Date:  2018-05-29       Impact factor: 5.221

  3 in total

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