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Boosting the analysis of protein interfaces with multiple interface string alignments: Illustration on the spikes of coronaviruses.
Béreux, Stéphane; Delmas, Bernard; Cazals, Frédéric.
  • Béreux S; Université Côte d'Azur, École polytechnique, Inria, France.
  • Delmas B; INRAe, France.
  • Cazals F; Université Côte d'Azur, Inria, France.
Proteins ; 90(3): 848-857, 2022 03.
Article in English | MEDLINE | ID: covidwho-1519517
ABSTRACT
We introduce multiple interface string alignment (MISA), a visualization tool to display coherently various sequence and structure based statistics at protein-protein interfaces (SSE elements, buried surface area, ΔASA , B factor values, etc). The amino acids supporting these annotations are obtained from Voronoi interface models. The benefit of MISA is to collate annotated sequences of (homologous) chains found in different biological contexts, that is, bound with different partners or unbound. The aggregated views MISA/SSE, MISA/BSA, MISA/ΔASA, and so forth, make it trivial to identify commonalities and differences between chains, to infer key interface residues, and to understand where conformational changes occur upon binding. As such, they should prove of key relevance for knowledge-based annotations of protein databases such as the Protein Data Bank. Illustrations are provided on the receptor binding domain of coronaviruses, in complex with their cognate partner or (neutralizing) antibodies. MISA computed with a minimal number of structures complement and enrich findings previously reported. The corresponding package is available from the Structural Bioinformatics Library (http//sbl.inria.frand https//sbl.inria.fr/doc/Multiple_interface_string_alignment-user-manual.html).
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Coronavirus / Spike Glycoprotein, Coronavirus Language: English Journal: Proteins Journal subject: Biochemistry Year: 2022 Document Type: Article Affiliation country: Prot.26279

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Coronavirus / Spike Glycoprotein, Coronavirus Language: English Journal: Proteins Journal subject: Biochemistry Year: 2022 Document Type: Article Affiliation country: Prot.26279