Open AccessSIMULATING DRUG-TARGET INTERACTION USING LARGE SCALE MOLECULAR DYNAMICS AND FUZZY-ART
Author(s) -
Ankush Rai,
Jagadeesh Kannan
Publication year - 2017
Publication title -
asian journal of pharmaceutical and clinical research
Language(s) - English
Resource type - Journals
eISSN - 2455-3891
pISSN - 0974-2441
DOI - 10.22159/ajpcr.2017.v10s1.19973
Subject(s) - molecular dynamics , microsecond , computer science , biological system , drug target , drug discovery , molecular descriptor , coupling (piping) , process (computing) , fuzzy logic , scale (ratio) , chemistry , computational chemistry , computational biology , artificial intelligence , machine learning , materials science , physics , biology , quantitative structure–activity relationship , biochemistry , quantum mechanics , astronomy , metallurgy , operating system
The examination of bio-molecular associations between a complex drug compound and its target is of foremost significance for the improvement of new biomarkers or bioresponsive compounds. In this paper, we exhibited a combinatorial technique of simulation of molecular dynamics (MD) and fuzzy ART to focus on the coupling factors of in the molecular binding process and its intermediary transitioning state. Here, MD simulations divided into microsecond length enable us to watch a inter-molecular coupling events, taking after different dynamical pathways and accomplishing ordered binding assembly of molecules. Results form such simulations are used to evaluate parameters corresponding to its thermodynamic and molecular kinetic properties, getting a decent concurrence with accessible experimental information. Utilizing machine learning algorithms in conjunction with MD simulations could enhance the productive for identifying key parts of drug–target binding and localization.