PRECOG: PREdicting COupling probabilities of G-protein coupled receptors

被引：16

作者：

Singh, Gurdeep ^{[1
,2
]}

Inoue, Asuka ^{[3
]}

Gutkind, J. Silvio ^{[4
,5
]}

Russell, Robert B. ^{[1
,2
]}

Raimondi, Francesco ^{[1
,2
]}

机构：

[1] Heidelberg Univ, Bioquant, CellNetworks, Neuenheimer Feld 267, D-69120 Heidelberg, Germany

[2] Heidelberg Univ, BZH, Neuenheimer Feld 328, D-69120 Heidelberg, Germany

[3] Tohoku Univ, Grad Sch Pharmaceut Sci, Sendai, Miyagi 9808578, Japan

[4] Univ Calif San Diego, Dept Pharmacol, La Jolla, CA 92093 USA

[5] Univ Calif San Diego, Moores Canc Ctr, La Jolla, CA 92093 USA

来源：

NUCLEIC ACIDS RESEARCH | 2019年 / 47卷 / W1期

关键词：

STRUCTURAL COMMUNICATION; STRUCTURE NETWORK; GPCRS; SPECIFICITY; SUBTYPES; MACHINE; MODELS;

D O I：

10.1093/nar/gkz392

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

G-protein coupled receptors (GPCRs) control multiple physiological states by transducing a multitude of extracellular stimuli into the cell via coupling to intra-cellular heterotrimeric G-proteins. Deciphering which G-proteins couple to each of the hundreds of GPCRs present in a typical eukaryotic organism is therefore critical to understand signalling. Here, we present PRECOG (precog.russelllab.org): a web server for predicting GPCR coupling, which allows users to: (i) predict coupling probabilities for GPCRs to individual G-proteins instead of subfamilies; (ii) visually inspect the protein sequence and structural features that are responsible for a particular coupling; (iii) suggest mutations to rationally design artificial GPCRs with new coupling properties based on predetermined coupling features.

引用

页码：W395 / W401

页数：7

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