KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks-Reference-Cited by-同舟云学术

KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

Published:2018-01-29 Issue:2 Volume:58 Page:287-296
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Jiménez José¹^ORCID,Škalič Miha¹^ORCID,Martínez-Rosell Gerard¹^ORCID,De Fabritiis Gianni¹²

Affiliation:

1. Computational Biophysics Laboratory, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Carrer del Dr. Aiguader 88, Barcelona 08003, Spain

2. Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain

Funder

European Regional Development Fund

Ministerio de Econom?a y Competitividad

H2020 European Research Council

Acellera Ltd.

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.7b00650

Reference61 articles.

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2. Surflex: Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine

3. Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy

4. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

5. Prediction of Absolute Solvation Free Energies using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field

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