1. ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs
- Author
-
Jacob de Vlieg, Wilco W. M. Fleuren, Wynand Alkema, Stefan Verhoeven, Marijn P. A. Sanders, Jan P. G. Klomp, Sven van den Beld, and Data Sciences for Life Science & Health
- Subjects
Models, Molecular ,Chemical and physical biology [NCMLS 7] ,Subfamily ,g-protein-coupled/chemistry ,receptors ,Sequence alignment ,Computational biology ,Plasma protein binding ,protein binding ,Biology ,lcsh:Computer applications to medicine. Medical informatics ,sequence alignment/methods ,Biochemistry ,Receptors, G-Protein-Coupled ,Structural Biology ,receptors, g-protein-coupled/chemistry ,Site-directed mutagenesis ,humans ,lcsh:QH301-705.5 ,Molecular Biology ,G protein-coupled receptor ,Multiple sequence alignment ,ligands ,Applied Mathematics ,biochemie ,Molecular biology ,Small molecule ,Transmembrane protein ,Computer Science Applications ,animals ,lcsh:Biology (General) ,Research Programm of Institute for Molecules and Materials ,lcsh:R858-859.7 ,entropy ,Sequence Alignment ,Research Article - Abstract
Background G-protein coupled receptors (GPCRs) are involved in many different physiological processes and their function can be modulated by small molecules which bind in the transmembrane (TM) domain. Because of their structural and sequence conservation, the TM domains are often used in bioinformatics approaches to first create a multiple sequence alignment (MSA) and subsequently identify ligand binding positions. So far methods have been developed to predict the common ligand binding residue positions for class A GPCRs. Results Here we present 1) ss-TEA, a method to identify specific ligand binding residue positions for any receptor, predicated on high quality sequence information. 2) The largest MSA of class A non olfactory GPCRs in the public domain consisting of 13324 sequences covering most of the species homologues of the human set of GPCRs. A set of ligand binding residue positions extracted from literature of 10 different receptors shows that our method has the best ligand binding residue prediction for 9 of these 10 receptors compared to another state-of-the-art method. Conclusions The combination of the large multi species alignment and the newly introduced residue selection method ss-TEA can be used to rapidly identify subfamily specific ligand binding residues. This approach can aid the design of site directed mutagenesis experiments, explain receptor function and improve modelling. The method is also available online via GPCRDB at http://www.gpcr.org/7tm/.
- Full Text
- View/download PDF