Leaderboards/Computational Drug Discovery Methods

Computational Drug Discovery Methods

Last updated July 15, 2026

Rising Stars

Fresh ink, massive impact

Researchers

1
Guo‐Li Xiong
King University
2
Danielle Maeser
University of Minnesota
3
Marine Bugnon
SIB Swiss Institute of Bioinformatics
4
Andrew T. McNutt
University of Pittsburgh
5
Dávid Péter Kovács
University of Cambridge
6
Aleksandr Ianevski
Institute for Molecular Medicine Finland
7
Philipp Schake
Technische Universität Dresden
8
Alexander Kroll
Steinbeis Foundation
9
Mehmet Akdel
Wageningen University & Research
10
Yuto Unoh
Futaba (Japan)

Papers

1
SwissDock 2024: major enhancements for small-molecule docking with Attracting Cavities and AutoDock Vina
Nucleic Acids Research|2024
480 cit.
2
Publication in Nucleic Acids Research (2025) [185 citations, W4410251219]
Nucleic Acids Research|2025
185 cit.
3
MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules
Journal of the American Chemical Society|2025
160 cit.
4
GNINA 1.3: the next increment in molecular docking with deep learning
Journal of Cheminformatics|2025
105 cit.
5
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
Nature Communications|2024
50 cit.
6
DLKcat cannot predict meaningful <i>k</i>cat values for mutants and unfamiliar enzymes
Biology Methods and Protocols|2024
30 cit.
7
A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships
PLoS Computational Biology|2024
29 cit.
8
The combination of pleconaril, rupintrivir, and remdesivir efficiently inhibits enterovirus infections in vitro, delaying the development of drug-resistant virus variants
Antiviral Research|2024
23 cit.
9
SPOT: A machine learning model that predicts specific substrates for transport proteins
PLoS Biology|2024
21 cit.
10
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies
Briefings in Bioinformatics|2024
20 cit.

Emerging Leaders

Drafting the new consensus

Researchers

1
Suzanna C. Ward
Cambridge Crystallographic Data Centre
2
Stefano Forli
Scripps Research Institute
3
Feixiong Cheng
Cleveland Clinic Lerner College of Medicine
4
Mengzhu Zheng
Shenyang Pharmaceutical University
5
Vasuk Gautam
University of Alberta
6
Connor W. Coley
Massachusetts Institute of Technology
7
Alex H. Wagner
European Bioinformatics Institute
8
Qinxue Chen
Beijing Museum of Natural History
9
Patrick Riley
Relay Therapeutics (United States)
10
Anil K. Giri
Sungkyunkwan University

Papers

1
Independent gradient model based on Hirshfeld partition: A new method for visual study of interactions in chemical systems
Journal of Computational Chemistry|2022
3.5k cit.
2
PHASTEST: faster than PHASTER, better than PHAST
Nucleic Acids Research|2023
589 cit.
3
Simple, Efficient, and Universal Energy Decomposition Analysis Method Based on Dispersion-Corrected Density Functional Theory
The Journal of Physical Chemistry A|2023
449 cit.
4
DGIdb 5.0: rebuilding the drug–gene interaction database for precision medicine and drug discovery platforms
Nucleic Acids Research|2023
445 cit.
5
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework
Nature Machine Intelligence|2022
268 cit.
6
Deep learning for drug repurposing: Methods, databases, and applications
Wiley Interdisciplinary Reviews Computational Molecular Science|2022
175 cit.
7
Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease
Alzheimer s Research & Therapy|2022
120 cit.
8
Machine learning modeling of family wide enzyme-substrate specificity screens
PLoS Computational Biology|2022
117 cit.
9
Evaluation of <scp>AlphaFold2</scp> structures as docking targets
Protein Science|2022
106 cit.
10
Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer’s disease
Cell Reports|2022
104 cit.

Current Senior Leaders

Wrote the book, still writing it

Researchers

1
Arthur J. Olson
Scripps Research Institute
2
W. Minor
University of Virginia
3
Olivier Michielin
SIB Swiss Institute of Bioinformatics
4
Vincent Zoete
SIB Swiss Institute of Bioinformatics
5
Brian K. Shoichet
University of California, San Francisco
6
Tingjun Hou
Pharmaceutical Biotechnology (Czechia)
7
Alexander Tropsha
University of North Carolina at Chapel Hill
8
Peer Bork
Max Delbrück Center
9
Jürgen Bajorath
University of Bonn
10
Robin Taylor
Cambridge Crystallographic Data Centre

Papers

1
AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
Journal of Computational Chemistry|2009
37.1k cit.
2
[20] Processing of X-ray diffraction data collected in oscillation mode
Methods in enzymology on CD-ROM/Methods in enzymology|1997
33.6k cit.
3
AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
Journal of Computational Chemistry|2009
25k cit.
4
SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules
Scientific Reports|2017
17.1k cit.
5
Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation
Nucleic Acids Research|2021
11.7k cit.
6
Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
Journal of Computational Chemistry|1998
10.8k cit.
7
Enterotypes of the human gut microbiome
Nature|2011
7.6k cit.
8
Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
Journal of Molecular Biology|1997
6.7k cit.
9
Interactive Tree Of Life (iTOL) v4: recent updates and new developments
Nucleic Acids Research|2019
6.5k cit.
10
Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees
Nucleic Acids Research|2016
5.4k cit.

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