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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Main Authors: Paula Jofily, Pedro G. Pascutti, Pedro H. M. Torres
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Molecules
Subjects:
Online Access:https://www.mdpi.com/1420-3049/26/5/1224
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spelling 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
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