The steadiness and proper folding of modular macromolecules like proteins; 3D model structure and the respective sequence analysis of protein design and evolution, and protein-protein interactions in several signaling pathways is studied from protein folding dynamics. Molecular dynamics (MD) is a highly efficient tool to investigate the folding and dynamics of a protein following in silico approaches. Even though just a only some years before the vibrant performance of a protein macromolecule could be conjured up, only in the environs of the experimentally deduced conformation (or unfolding of a protein could be simulated at elevated temperature), the initiation of allocated computing, new procedures, for instance, replica-exchange MD, new advances (based upon, e.g., the stochastic difference equation), and physics-based dimished and optimized models of protein macromolecules, presently provide it probable to analyse protein-folding phenomena from the newly built tertiary anf functional models.
Published in Chapter:
Adaptive Simulated Annealing Algorithm to Solve Bio-Molecular Optimization
Sujay Ray (University of Kalyani, India)
Copyright: © 2016
|Pages: 15
DOI: 10.4018/978-1-5225-0058-2.ch020
Abstract
Energy minimization is a paramount zone in the field of computational and structural biology for protein modeling. It helps in mending distorted geometries in the folded functional protein by moving its atoms to release internal constraints. It attempts to hold back to zero value for the net atomic force on every atom. But to overcome certain disadvantages in energy minimization, Simulated Annealing (SA) can be helpful. SA is a molecular dynamics technique, where temperature is gradually reduced during the simulation. It provides the best configuration of bio-molecules in shorter time. With the advancement in computational knowledge, one essential but less sensitive variant of SA: Adaptive Simulated Annealing (ASA) algorithm is beneficial, because it automatically adjusts the temperature scheme and abrupt opting of step. Therefore it benefits to prepare stable protein models and further to investigate protein-protein interactions. Thus, a residue-level study can be analyzed in details for the benefit of the entire biota.