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Recent applications of computational methods to allosteric drug discovery.
Govindaraj, Rajiv Gandhi; Thangapandian, Sundar; Schauperl, Michael; Denny, Rajiah Aldrin; Diller, David J.
Afiliação
  • Govindaraj RG; Computational Chemistry, HotSpot Therapeutics Inc., Boston, MA, United States.
  • Thangapandian S; Computational Chemistry, HotSpot Therapeutics Inc., Boston, MA, United States.
  • Schauperl M; Computational Chemistry, HotSpot Therapeutics Inc., Boston, MA, United States.
  • Denny RA; Medizen Inc., Canton, MA, United States.
  • Diller DJ; Computational Chemistry, HotSpot Therapeutics Inc., Boston, MA, United States.
Front Mol Biosci ; 9: 1070328, 2022.
Article em En | MEDLINE | ID: mdl-36710877
ABSTRACT
Interest in exploiting allosteric sites for the development of new therapeutics has grown considerably over the last two decades. The chief driving force behind the interest in allostery for drug discovery stems from the fact that in comparison to orthosteric sites, allosteric sites are less conserved across a protein family, thereby offering greater opportunity for selectivity and ultimately tolerability. While there is significant overlap between structure-based drug design for orthosteric and allosteric sites, allosteric sites offer additional challenges mostly involving the need to better understand protein flexibility and its relationship to protein function. Here we examine the extent to which structure-based drug design is impacting allosteric drug design by highlighting several targets across a variety of target classes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article