Analysis of docking algorithms by HPC methods generated in bioinformatics studies

High-performance computing (HPC) is an important domain of the computer science field. For more than 30 years, it has allowed finding solutions to problems and enhanced progress in many scientific areas such as bioinformatics and drug design. The binding of small molecule ligands to large protein ta...

Full description

Bibliographic Details
Main Authors: Stoilov Anton, Yurukov Borislav, Milanov Peter
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20181602009
id doaj-7123e4fa1d53481089875ae346e5c3ad
record_format Article
spelling doaj-7123e4fa1d53481089875ae346e5c3ad2021-02-02T07:28:44ZengEDP SciencesITM Web of Conferences2271-20972018-01-01160200910.1051/itmconf/20181602009itmconf_amcse2018_02009Analysis of docking algorithms by HPC methods generated in bioinformatics studiesStoilov AntonYurukov BorislavMilanov PeterHigh-performance computing (HPC) is an important domain of the computer science field. For more than 30 years, it has allowed finding solutions to problems and enhanced progress in many scientific areas such as bioinformatics and drug design. The binding of small molecule ligands to large protein targets is central to numerous biological processes. The accurate prediction of the binding modes between the ligand and protein (the docking problem) is of fundamental importance in modern structure-based drug design. The interactions between the receptor and ligand are quantum mechanical in nature, but due to the complexity of biological systems, quantum theory cannot be applied directly. Consequently, most methods used in docking and computational drug discovery are more empirical in nature and usually lack generality.https://doi.org/10.1051/itmconf/20181602009
collection DOAJ
language English
format Article
sources DOAJ
author Stoilov Anton
Yurukov Borislav
Milanov Peter
spellingShingle Stoilov Anton
Yurukov Borislav
Milanov Peter
Analysis of docking algorithms by HPC methods generated in bioinformatics studies
ITM Web of Conferences
author_facet Stoilov Anton
Yurukov Borislav
Milanov Peter
author_sort Stoilov Anton
title Analysis of docking algorithms by HPC methods generated in bioinformatics studies
title_short Analysis of docking algorithms by HPC methods generated in bioinformatics studies
title_full Analysis of docking algorithms by HPC methods generated in bioinformatics studies
title_fullStr Analysis of docking algorithms by HPC methods generated in bioinformatics studies
title_full_unstemmed Analysis of docking algorithms by HPC methods generated in bioinformatics studies
title_sort analysis of docking algorithms by hpc methods generated in bioinformatics studies
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2018-01-01
description High-performance computing (HPC) is an important domain of the computer science field. For more than 30 years, it has allowed finding solutions to problems and enhanced progress in many scientific areas such as bioinformatics and drug design. The binding of small molecule ligands to large protein targets is central to numerous biological processes. The accurate prediction of the binding modes between the ligand and protein (the docking problem) is of fundamental importance in modern structure-based drug design. The interactions between the receptor and ligand are quantum mechanical in nature, but due to the complexity of biological systems, quantum theory cannot be applied directly. Consequently, most methods used in docking and computational drug discovery are more empirical in nature and usually lack generality.
url https://doi.org/10.1051/itmconf/20181602009
work_keys_str_mv AT stoilovanton analysisofdockingalgorithmsbyhpcmethodsgeneratedinbioinformaticsstudies
AT yurukovborislav analysisofdockingalgorithmsbyhpcmethodsgeneratedinbioinformaticsstudies
AT milanovpeter analysisofdockingalgorithmsbyhpcmethodsgeneratedinbioinformaticsstudies
_version_ 1724299331092086784