Your browser doesn't support javascript.
loading
Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4.
Kotelnikov, Sergei; Alekseenko, Andrey; Liu, Cong; Ignatov, Mikhail; Padhorny, Dzmitry; Brini, Emiliano; Lukin, Mark; Coutsias, Evangelos; Dill, Ken A; Kozakov, Dima.
Afiliación
  • Kotelnikov S; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
  • Alekseenko A; Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
  • Liu C; Innopolis University, Innopolis, Russia.
  • Ignatov M; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
  • Padhorny D; Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
  • Brini E; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
  • Lukin M; Department of Chemistry, Stony Brook University, Stony Brook, NY, USA.
  • Coutsias E; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
  • Dill KA; Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
  • Kozakov D; Institute for Advanced Computational Sciences, Stony Brook University, Stony Brook, NY, USA.
J Comput Aided Mol Des ; 34(2): 179-189, 2020 02.
Article en En | MEDLINE | ID: mdl-31879831
We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design Data Resource blind Grand Challenge competition. This method was among the best performers in the competition, giving sub-angstrom prediction quality for the majority of the targets.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diseño de Fármacos / Ácido Aspártico Endopeptidasas / Compuestos Macrocíclicos / Secretasas de la Proteína Precursora del Amiloide / Simulación del Acoplamiento Molecular Tipo de estudio: Health_economic_evaluation / Prognostic_studies Límite: Humans Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diseño de Fármacos / Ácido Aspártico Endopeptidasas / Compuestos Macrocíclicos / Secretasas de la Proteína Precursora del Amiloide / Simulación del Acoplamiento Molecular Tipo de estudio: Health_economic_evaluation / Prognostic_studies Límite: Humans Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos