Your browser doesn't support javascript.
loading
RosettaSurf-A surface-centric computational design approach.
Scheck, Andreas; Rosset, Stéphane; Defferrard, Michaël; Loukas, Andreas; Bonet, Jaume; Vandergheynst, Pierre; Correia, Bruno E.
Afiliación
  • Scheck A; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Rosset S; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
  • Defferrard M; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Loukas A; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
  • Bonet J; Signal Processing Laboratory (LTS2), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Vandergheynst P; Signal Processing Laboratory (LTS2), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
  • Correia BE; Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
PLoS Comput Biol ; 18(3): e1009178, 2022 03.
Article en En | MEDLINE | ID: mdl-35294435
ABSTRACT
Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ingeniería de Proteínas / Proteínas Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ingeniería de Proteínas / Proteínas Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza