GRaSP: a graph-based residue neighborhood strategy to predict binding sites | Zendy

Charles Abreu Santana | Zendy; Sabrina de Azevedo Silveira | Zendy; João Pedro Moraes | Zendy; Sandro C. Izidoro | Zendy; Raquel C. de Melo-Minardi | Zendy; António J. M. Ribeiro | Zendy; Jonathan D. Tyzack | Zendy; Neera Borkakoti | Zendy; Janet M. Thornton | Zendy

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GRaSP: a graph-based residue neighborhood strategy to predict binding sites

Author(s) -

Charles Abreu Santana,

Sabrina de Azevedo Silveira,

João Pedro Moraes,

Sandro C. Izidoro,

Raquel C. de Melo-Minardi,

António J. M. Ribeiro,

Jonathan D. Tyzack,

Neera Borkakoti,

Janet M. Thornton

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa805

Subject(s) - grasp , computer science , graph , residue (chemistry) , artificial intelligence , theoretical computer science , chemistry , biochemistry , programming language

The discovery of protein-ligand-binding sites is a major step for elucidating protein function and for investigating new functional roles. Detecting protein-ligand-binding sites experimentally is time-consuming and expensive. Thus, a variety of in silico methods to detect and predict binding sites was proposed as they can be scalable, fast and present low cost.

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