Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy
Probing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success...
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doaj-6b438ca0dbf14bc9a713eca2fb906d0a2021-02-26T00:04:01ZengMDPI AGMolecules1420-30492021-02-01261224122410.3390/molecules26051224Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing StrategyPaula Jofily0Pedro G. Pascutti1Pedro H. M. Torres2Laboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21941-902, BrazilLaboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21941-902, BrazilLaboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21941-902, BrazilProbing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success rates, it is less practical when a large number of molecules must be screened against many detected binding sites. On the other hand, blind docking allows for simultaneous search of the whole protein surface, which however entails the loss of accuracy and speed. To bridge this gap, in this study, we developed and tested BLinDPyPr, an automated pipeline which uses FTMap and DOCK6 to perform a hybrid blind docking strategy. Through our algorithm, FTMap docked probe clusters are converted into DOCK6 spheres for determining binding regions. Because these spheres are solely derived from FTMap probes, their locations are contained in and specific to multiple potential binding pockets, which become the regions that are simultaneously probed and chosen by the search algorithm based on the properties of each candidate ligand. This method yields pose prediction results (45.2–54.3% success rates) comparable to those of site-specific docking with the classic DOCK6 workflow (49.7–54.3%) and is half as time-consuming as the conventional blind docking method with DOCK6.https://www.mdpi.com/1420-3049/26/5/1224blind dockingftmapdock6pipeline |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Paula Jofily Pedro G. Pascutti Pedro H. M. Torres |
spellingShingle |
Paula Jofily Pedro G. Pascutti Pedro H. M. Torres Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy Molecules blind docking ftmap dock6 pipeline |
author_facet |
Paula Jofily Pedro G. Pascutti Pedro H. M. Torres |
author_sort |
Paula Jofily |
title |
Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy |
title_short |
Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy |
title_full |
Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy |
title_fullStr |
Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy |
title_full_unstemmed |
Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy |
title_sort |
improving blind docking in dock6 through an automated preliminary fragment probing strategy |
publisher |
MDPI AG |
series |
Molecules |
issn |
1420-3049 |
publishDate |
2021-02-01 |
description |
Probing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success rates, it is less practical when a large number of molecules must be screened against many detected binding sites. On the other hand, blind docking allows for simultaneous search of the whole protein surface, which however entails the loss of accuracy and speed. To bridge this gap, in this study, we developed and tested BLinDPyPr, an automated pipeline which uses FTMap and DOCK6 to perform a hybrid blind docking strategy. Through our algorithm, FTMap docked probe clusters are converted into DOCK6 spheres for determining binding regions. Because these spheres are solely derived from FTMap probes, their locations are contained in and specific to multiple potential binding pockets, which become the regions that are simultaneously probed and chosen by the search algorithm based on the properties of each candidate ligand. This method yields pose prediction results (45.2–54.3% success rates) comparable to those of site-specific docking with the classic DOCK6 workflow (49.7–54.3%) and is half as time-consuming as the conventional blind docking method with DOCK6. |
topic |
blind docking ftmap dock6 pipeline |
url |
https://www.mdpi.com/1420-3049/26/5/1224 |
work_keys_str_mv |
AT paulajofily improvingblinddockingindock6throughanautomatedpreliminaryfragmentprobingstrategy AT pedrogpascutti improvingblinddockingindock6throughanautomatedpreliminaryfragmentprobingstrategy AT pedrohmtorres improvingblinddockingindock6throughanautomatedpreliminaryfragmentprobingstrategy |
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