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Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches.
Gorgulla, Christoph; Jayaraj, Abhilash; Fackeldey, Konstantin; Arthanari, Haribabu.
Afiliação
  • Gorgulla C; Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Physics, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA; Department of Cancer Biology, Dana-Farber Cancer Institute (DFCI), Boston, M
  • Jayaraj A; Wesleyan University, Chemistry Department, Middletown, CT, USA.
  • Fackeldey K; Institute of Mathematics, Technical University Berlin, Berlin, Germany; Zuse Institute Berlin, Berlin, Germany.
  • Arthanari H; Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Cancer Biology, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA. Electronic address: hari_arthanari@hms.harvard.edu.
Curr Opin Chem Biol ; 69: 102156, 2022 08.
Article em En | MEDLINE | ID: mdl-35576813
ABSTRACT
Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein-protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Revista: Curr Opin Chem Biol Assunto da revista: BIOQUIMICA Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Revista: Curr Opin Chem Biol Assunto da revista: BIOQUIMICA Ano de publicação: 2022 Tipo de documento: Article