Combining structural and coevolution information to unveil allosteric sites

Author:

La Sala Giuseppina1ORCID,Pfleger Christopher2,Käck Helena3,Wissler Lisa3,Nevin Philip4,Böhm Kerstin4,Janet Jon Paul1,Schimpl Marianne5,Stubbs Christopher J.5,De Vivo Marco6,Tyrchan Christian7,Hogner Anders1,Gohlke Holger28ORCID,Frolov Andrey I.1ORCID

Affiliation:

1. Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

2. Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf, 40225 Düsseldorf, Germany

3. Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

4. Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

5. Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK

6. Laboratory of Molecular Modeling and Drug Design, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genoa, Italy

7. Medicinal Chemistry, Research and Early Development, Respiratory & Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

8. John von Neumann Institute for Computing (NIC), Jülich Supercomputing Centre (JSC), Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Institute of Bio- and Geosciences (IBG-4: Bioinformatics), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany

Abstract

Structure-based three-parameter model that integrates local binding site information, coevolutionary information, and information on dynamic allostery to identify potentially hidden allosteric sites in ensembles of protein structures.

Funder

Bundesministerium für Bildung und Forschung

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

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