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...
Main Authors: | , , |
---|---|
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 |