Molecular dynamics simulations and novel drug discovery

Abstract

Molecular dynamics (MD) simulations can provide not only plentiful dynamical structural information on biomacromolecules but also a wealth of energetic information about protein and ligand interactions. Such information is very important to understanding the structure-function relationship of the target and the essence of protein-ligand interactions and to guiding the drug discovery and design process. Thus, MD simulations have been applied widely and successfully in each step of modern drug discovery. Areas covered: In this review, the authors review the applications of MD simulations in novel drug discovery, including the pathogenic mechanisms of amyloidosis diseases, virtual screening and the interaction mechanisms between drugs and targets. Expert opinion: MD simulations have been used widely in investigating the pathogenic mechanisms of diseases caused by protein misfolding, in virtual screening, and in investigating drug resistance mechanisms caused by mutations of the target. These issues are very difficult to solve by experimental methods alone. Thus, in the future, MD simulations will have wider application with the further improvement of computational capacity and the development of better sampling methods and more accurate force fields together with more efficient analysis methods.

Machine learning for multi-fidelity scale bridging and dynamical simulations of materials

“…Ever since the first successful demonstration of molecular dynamics (MD) to determine the diffusion coefficient of liquid argon more than 50 years ago [1], MD has become an indispensable tool to understand and predict materials properties for a broad range of applications, including drug discovery [2,3,4,5], materials design [6,7,8] and defect chemistry [9,10,11]. Its generality, i.e., being applicable to a diverse range of materials (metals, ceramics, amorphous glasses, polymers, or biomolecules), along with its versatility, i.e, the ability to capture thermodynamic, mechanical, electrical and chemical behavior of materials, make it a pervasive and vital theoretical tool, as highlighted in Figure 1a.…”

Gibbs Free Energy Calculation of Mutation in PncA and RpsA Associated With Pyrazinamide Resistance

“…To explore the dynamic properties behind mutations, molecular dynamic (MD) simulations have been widely performed, and have been especially useful in unveiling the mechanism of drug failure behind mutation (Carter Childers and Daggett, 2017;Dong et al, 2018;Hashemzadeh et al, 2019;Kaushik et al, 2019). MD simulation studies of ligand-protein interactions are a widely applied approach for explaining the mechanisms of drug resistance behind mutations (Aggarwal et al, 2017;Carter Childers and Daggett, 2017;Bera et al, 2018;Liu et al, 2018;Pandey et al, 2018;Ishima et al, 2019). During in vivo analysis, the crystal structure is analyzed for drug resistance.…”

Identifying novel sphingosine kinase 1 inhibitors as therapeutics against breast cancer

“…The main objective of present work is to identify a potent lead compound against breast cancer using several computational approaches such as the ligand-based virtual screening (LBVS) [24][25][26] , molecular docking [27][28][29] , molecular dynamics (MD) simulations [30][31][32][33] , and the molecular mechanics (MM) Poisson-Boltzmann surface area (MMPBSA) calculations 34 . The molecular interaction studies of predicted lead molecules with target protein SphK1 were also carried out in order to check the strength of drug binding.…”