NDLI: Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge

Content Provider	Springer Nature Link
Author	Ye, Zhaofeng Baumgartner, Matthew P. Wingert, Bentley M. Camacho, Carlos J.
Copyright Year	2016
Abstract	Induced fit or protein flexibility can make a given structure less useful for docking and/or scoring. The 2015 Drug Design Data Resource (D3R) Grand Challenge provided a unique opportunity to prospectively test optimal strategies for virtual screening in these type of targets: heat shock protein 90 (HSP90), a protein with multiple ligand-induced binding modes; and mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4), a kinase with a large flexible pocket. Using previously known co-crystal structures, we tested predictions from methods that keep the receptor structure fixed and used (a) multiple receptor/ligand co-crystals as binding templates for minimization or docking (“close”), (b) methods that align or dock to a single receptor (“cross”), and (c) a hybrid approach that chose from multiple bound ligands as initial templates for minimization to a single receptor (“min-cross”). Pose prediction using our “close” models resulted in average ligand RMSDs of 0.32 and 1.6 Å for HSP90 and MAP4K4, respectively, the most accurate models of the community-wide challenge. On the other hand, affinity ranking using our “cross” methods performed well overall despite the fact that a fixed receptor cannot model ligand-induced structural changes,. In addition, “close” methods that leverage the co-crystals of the different binding modes of HSP90 also predicted the best affinity ranking. Our studies suggest that analysis of changes on the receptor structure upon ligand binding can help select an optimal virtual screening strategy.
Starting Page	695
Ending Page	706
Page Count	12
File Format	PDF
ISSN	0920654X
Journal	Journal of Computer-Aided Molecular Design
Volume Number	30
Issue Number	9
e-ISSN	15734951
Language	English
Publisher	Springer International Publishing
Publisher Date	2016-08-29
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Drug discovery Virtual screening D3R Induced fit Affinity ranking Pose prediction Physical Chemistry Computer Applications in Chemistry Animal Anatomy / Morphology / Histology
Content Type	Text
Resource Type	Article
Subject	Drug Discovery Physical and Theoretical Chemistry Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015

D3R grand challenge 2015: Evaluation of protein–ligand pose and affinity predictions

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

Protein-ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3.

Docking-undocking combination applied to the D3R Grand Challenge 2015

Interaction with specific HSP90 residues as a scoring function: validation in the D3R Grand Challenge 2015

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

Blind prediction of HIV integrase binding from the SAMPL4 challenge

Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge

Similar Documents

Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015

D3R grand challenge 2015: Evaluation of protein–ligand pose and affinity predictions

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

Protein-ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3.

Docking-undocking combination applied to the D3R Grand Challenge 2015

Interaction with specific HSP90 residues as a scoring function: validation in the D3R Grand Challenge 2015

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

Blind prediction of HIV integrase binding from the SAMPL4 challenge

Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge