Abstract
Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Continuous modernization of simulation tools enables accurate prediction and characterization of the aforementioned mechanisms and these qualities are highly beneficial for the expedition of drug development when effectively applied to structure-based drug design (SBDD). In this review, current all-atom MD simulation methods, with focus on enhanced sampling techniques, utilized to examine protein structure, dynamics, and functions are discussed. This review will pivot around computer calculations of protein-ligand and protein-protein systems with applications to SBDD. In addition, we will also be highlighting limitations faced by current simulation tools as well as the improvements that have been made to ameliorate their efficiency.
Highlights
Proteins are vital constituents of living organisms, responsible for myriads of life-sustaining cellular processes such as molecular recognition, signal transduction, protein localization, and enzyme catalysis
While the history of molecular dynamics (MD) simulation of macromolecules began with a simple structural investigation of a small protein, namely bovine pancreatic trypsin inhibitor, the field has matured to a stage that calls for the development of new technology to facilitate the study of larger proteins and protein complexes with more intricate dynamics [2,3,4]
Replica-exchange molecular dynamics (REMD) method has been suggested by Sugita and Replica-exchange molecular dynamics (REMD) method has been suggested by Okamoto [9]
Summary
Proteins are vital constituents of living organisms, responsible for myriads of life-sustaining cellular processes such as molecular recognition, signal transduction, protein localization, and enzyme catalysis. MD simulation as a main tool the computational of proteins as well proteins as welluse as of a complementary machinery in in experimental studiesstudies has propelled actions to as a complementary machinery in experimental studiesbetter has propelled improve various improve various aspects of MD simulations, warranting predictiveactions power to and more reliable in aspects of MD simulations, warrantingdynamics better predictive power and morereview, reliablewe in silico analysis an of silico analysis of protein structures, and functions. In this will provide protein structures, dynamics and functions.
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