volume 27 issue 1 pages 151-164

Machine-learning methods for ligand–protein molecular docking

Kevin Crampon 1, 2, 3
Alexis Giorkallos 3
Myrtille Deldossi 3
Stéphanie Baud 4
Luiz Angelo Steffenel 2
Publication typeJournal Article
Publication date2022-01-01
scimago Q1
wos Q1
SJR1.742
CiteScore16.0
Impact factor7.5
ISSN13596446, 18785832
Drug Discovery
Pharmacology
Abstract
Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains use AI, including molecular simulation for drug discovery. In this review, we provide an overview of ligand-protein molecular docking and how machine learning (ML), especially deep learning (DL), a subset of ML, is transforming the field by tackling the associated challenges.
Found 
Found 

Top-30

Journals

1
2
3
4
5
6
7
8
Journal of Ethnopharmacology
8 publications, 3.02%
Molecules
7 publications, 2.64%
Scientific Reports
5 publications, 1.89%
Phytomedicine
5 publications, 1.89%
Medicine (United States)
5 publications, 1.89%
Letters in Drug Design and Discovery
5 publications, 1.89%
International Journal of Molecular Sciences
4 publications, 1.51%
Drug Design, Development and Therapy
4 publications, 1.51%
Food Bioscience
3 publications, 1.13%
Food Chemistry
3 publications, 1.13%
Briefings in Bioinformatics
3 publications, 1.13%
Journal of Chemical Information and Modeling
3 publications, 1.13%
Biomedicine and Pharmacotherapy
3 publications, 1.13%
International Journal of Biological Macromolecules
3 publications, 1.13%
Pharmaceuticals
3 publications, 1.13%
Current Medicinal Chemistry
3 publications, 1.13%
Computers in Biology and Medicine
3 publications, 1.13%
Antioxidants
2 publications, 0.75%
Marine Drugs
2 publications, 0.75%
Frontiers in Pharmacology
2 publications, 0.75%
Computational and Structural Biotechnology Journal
2 publications, 0.75%
European Journal of Pharmacology
2 publications, 0.75%
Journal of Computer-Aided Molecular Design
2 publications, 0.75%
Biomedical Chromatography
2 publications, 0.75%
Journal of Agricultural and Food Chemistry
2 publications, 0.75%
Comprehensive Reviews in Food Science and Food Safety
2 publications, 0.75%
Artificial Intelligence Chemistry
2 publications, 0.75%
Physical Chemistry Chemical Physics
2 publications, 0.75%
Expert Opinion on Drug Discovery
2 publications, 0.75%
1
2
3
4
5
6
7
8

Publishers

10
20
30
40
50
60
70
80
90
Elsevier
85 publications, 32.08%
Springer Nature
41 publications, 15.47%
MDPI
33 publications, 12.45%
Wiley
25 publications, 9.43%
Taylor & Francis
12 publications, 4.53%
American Chemical Society (ACS)
10 publications, 3.77%
Frontiers Media S.A.
7 publications, 2.64%
Ovid Technologies (Wolters Kluwer Health)
6 publications, 2.26%
Bentham Science Publishers Ltd.
6 publications, 2.26%
Institute of Electrical and Electronics Engineers (IEEE)
5 publications, 1.89%
Royal Society of Chemistry (RSC)
5 publications, 1.89%
Oxford University Press
4 publications, 1.51%
Cold Spring Harbor Laboratory
4 publications, 1.51%
Research Square Platform LLC
4 publications, 1.51%
Hindawi Limited
2 publications, 0.75%
IntechOpen
2 publications, 0.75%
Walter de Gruyter
2 publications, 0.75%
Annual Reviews
1 publication, 0.38%
Public Library of Science (PLoS)
1 publication, 0.38%
Pirogov Russian National Research Medical University
1 publication, 0.38%
IOP Publishing
1 publication, 0.38%
Pharmaceutical Society of Japan
1 publication, 0.38%
Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii
1 publication, 0.38%
Baishideng Publishing Group
1 publication, 0.38%
IGI Global
1 publication, 0.38%
PeerJ
1 publication, 0.38%
10
20
30
40
50
60
70
80
90
  • We do not take into account publications without a DOI.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
265
Share
Cite this
GOST |
Cite this
GOST Copy
Crampon K. et al. Machine-learning methods for ligand–protein molecular docking // Drug Discovery Today. 2022. Vol. 27. No. 1. pp. 151-164.
GOST all authors (up to 50) Copy
Crampon K., Giorkallos A., Deldossi M., Baud S., Steffenel L. A. Machine-learning methods for ligand–protein molecular docking // Drug Discovery Today. 2022. Vol. 27. No. 1. pp. 151-164.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.drudis.2021.09.007
UR - https://doi.org/10.1016/j.drudis.2021.09.007
TI - Machine-learning methods for ligand–protein molecular docking
T2 - Drug Discovery Today
AU - Crampon, Kevin
AU - Giorkallos, Alexis
AU - Deldossi, Myrtille
AU - Baud, Stéphanie
AU - Steffenel, Luiz Angelo
PY - 2022
DA - 2022/01/01
PB - Elsevier
SP - 151-164
IS - 1
VL - 27
PMID - 34560276
SN - 1359-6446
SN - 1878-5832
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2022_Crampon,
author = {Kevin Crampon and Alexis Giorkallos and Myrtille Deldossi and Stéphanie Baud and Luiz Angelo Steffenel},
title = {Machine-learning methods for ligand–protein molecular docking},
journal = {Drug Discovery Today},
year = {2022},
volume = {27},
publisher = {Elsevier},
month = {jan},
url = {https://doi.org/10.1016/j.drudis.2021.09.007},
number = {1},
pages = {151--164},
doi = {10.1016/j.drudis.2021.09.007}
}
MLA
Cite this
MLA Copy
Crampon, Kevin, et al. “Machine-learning methods for ligand–protein molecular docking.” Drug Discovery Today, vol. 27, no. 1, Jan. 2022, pp. 151-164. https://doi.org/10.1016/j.drudis.2021.09.007.