NDLI: A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction.

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A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Liu, Tianyun Horst, Jeremy A. Samudrala, Ram
Description	Country affiliation: United States Author Affiliation: Liu T ( Department of Genetics, Stanford University, Stanford, California, USA.)
Abstract	The principal bottleneck in protein structure prediction is the refinement of models from lower accuracies to the resolution observed by experiment. We developed a novel constraints-based refinement method that identifies a high number of accurate input constraints from initial models and rebuilds them using restrained torsion angle dynamics (rTAD). We previously created a Bayesian statistics-based residue-specific all-atom probability discriminatory function (RAPDF) to discriminate native-like models by measuring the probability of accuracy for atom type distances within a given model. Here, we exploit RAPDF to score (i.e., filter) constraints from initial predictions that may or may not be close to a native-like state, obtain consensus of top scoring constraints amongst five initial models, and compile sets with no redundant residue pair constraints. We find that this method consistently produces a large and highly accurate set of distance constraints from which to build refinement models. We further optimize the balance between accuracy and coverage of constraints by producing multiple structure sets using different constraint distance cutoffs, and note that the cutoff governs spatially near versus distant effects in model generation. This complete procedure of deriving distance constraints for rTAD simulations improves the quality of initial predictions significantly in all cases evaluated by us. Our procedure represents a significant step in solving the protein structure prediction and refinement problem, by enabling the use of consensus constraints, RAPDF, and rTAD for protein structure modeling and refinement.
File Format	HTM / HTML
ISSN	08873585
e-ISSN	10970134
DOI	10.1002/prot.22434
Journal	Proteins: Structure, Function, and Bioinformatics
Issue Number	1
Volume Number	77
Language	English
Publisher	Wiley-Liss
Publisher Date	2009-10-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Proteins Chemistry Computational Biology Discipline Biochemistry Protein Conformation
Content Type	Text
Resource Type	Article
Subject	Structural Biology Biochemistry Molecular Biology

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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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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