{"title":"Ab-initio binding of barnase–barstar with DelPhiForce steered Molecular Dynamics (DFMD) approach","authors":"Mahesh Koirala, E. Alexov","doi":"10.1142/s0219633620500169","DOIUrl":null,"url":null,"abstract":"Receptor–ligand interactions are involved in various biological processes, therefore understanding the binding mechanism and ability to predict the binding mode are essential for many biological investigations. While many computational methods exist to predict the 3D structure of the corresponding complex provided the knowledge of the monomers, here we use the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase to demonstrate that first-principles methods are also capable of modeling the binding. Essential component of DFMD approach is enhancing the role of long-range electrostatic interactions to provide guiding force of the monomers toward their correct binding orientation and position. Thus, it is demonstrated that the DFMD can successfully dock barstar to barnase even if the initial positions and orientations of both are completely different from the correct ones. Thus, the electrostatics provides orientational guidance along with pulling force to deliver the ligand in close proximity to the receptor.","PeriodicalId":49976,"journal":{"name":"Journal of Theoretical & Computational Chemistry","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1142/s0219633620500169","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Theoretical & Computational Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219633620500169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 2
Abstract
Receptor–ligand interactions are involved in various biological processes, therefore understanding the binding mechanism and ability to predict the binding mode are essential for many biological investigations. While many computational methods exist to predict the 3D structure of the corresponding complex provided the knowledge of the monomers, here we use the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase to demonstrate that first-principles methods are also capable of modeling the binding. Essential component of DFMD approach is enhancing the role of long-range electrostatic interactions to provide guiding force of the monomers toward their correct binding orientation and position. Thus, it is demonstrated that the DFMD can successfully dock barstar to barnase even if the initial positions and orientations of both are completely different from the correct ones. Thus, the electrostatics provides orientational guidance along with pulling force to deliver the ligand in close proximity to the receptor.
期刊介绍:
The Journal of Theoretical and Computational Chemistry (JTCC) is an international interdisciplinary journal aimed at providing comprehensive coverage on the latest developments and applications of research in the ever-expanding field of theoretical and computational chemistry.
JTCC publishes regular articles and reviews on new methodology, software, web server and database developments. The applications of existing theoretical and computational methods which produce significant new insights into important problems are also welcomed. Papers reporting joint computational and experimental investigations are encouraged. The journal will not consider manuscripts reporting straightforward calculations of the properties of molecules with existing software packages without addressing a significant scientific problem.
Areas covered by the journal include molecular dynamics, computer-aided molecular design, modeling effects of mutation on stability and dynamics of macromolecules, quantum mechanics, statistical mechanics and other related topics.