D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.
J Comput Aided Mol Des
; 34(2): 99-119, 2020 02.
Article
em En
| MEDLINE
| ID: mdl-31974851
ABSTRACT
The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Desenho de Fármacos
/
Ácido Aspártico Endopeptidases
/
Inibidores Enzimáticos
/
Secretases da Proteína Precursora do Amiloide
/
Bibliotecas de Moléculas Pequenas
Tipo de estudo:
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
J Comput Aided Mol Des
Assunto da revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos