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Mini-Reviews in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1389-5575
ISSN (Online): 1875-5607

Mini-Review Article

Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) Simulation: A Tool for Structure-Based Drug Design and Discovery

Author(s): Prajakta U. Kulkarni, Harshil Shah and Vivek K. Vyas*

Volume 22, Issue 8, 2022

Published on: 11 January, 2022

Page: [1096 - 1107] Pages: 12

DOI: 10.2174/1389557521666211007115250

Price: $65

Abstract

Quantum Mechanics (QM) is the physics-based theory that explains the physical properties of nature at the level of atoms and sub-atoms. Molecular mechanics (MM) construct molecular systems through the use of classical mechanics. So, when combined, hybrid quantum mechanics and molecular mechanics (QM/MM) can act as computer-based methods that can be used to calculate the structure and property data of molecular structures. Hybrid QM/MM combines the strengths of QM with accuracy and MM with speed. QM/MM simulation can also be applied for the study of chemical processes in solutions, as well as in the proteins, and has a great scope in structure-based drug design (SBDD) and discovery. Hybrid QM/MM can also be applied to HTS to derive QSAR models. Due to the availability of many protein crystal structures, it has a great role in computational chemistry, especially in structure- and fragment-based drug design. Fused QM/MM simulations have been developed as a widespread method to explore chemical reactions in condensed phases. In QM/MM simulations, the quantum chemistry theory is used to treat the space in which the chemical reactions occur; however, the rest is defined through the molecular mechanics force field (MMFF). In this review, we have extensively reviewed recent literature pertaining to the use and applications of hybrid QM/MM simulations for ligand and structure-based computational methods for the design and discovery of therapeutic agents.

Keywords: Quantum mechanics (QM), molecular mechanics (MM), hybrid QM/MM, structure-based drug design, MD simulations, CADD.

Graphical Abstract

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