Computational Drug Discovery Methods
Computational Drug Discovery Methods is a research topic within Computational Theory and Mathematics. Science Explorer counts 78k research works in it since 1950. 24.2% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on computational methods, virtual screening, and molecular docking techniques used in drug discovery. It covers topics such as drug target identification, pharmacokinetics, chemical properties, machine learning applications, polypharmacology, and network pharmacology.
- Molecular Docking
- Virtual Screening
- Drug Target Identification
- QSAR Modeling
- Pharmacokinetics
- Chemical Properties
- Machine Learning
- Polypharmacology
- Network Pharmacology
- Medicinal Chemistry
- Research works
- 78k fractional, since 1950
- In the world top 10%
- 19k per year above
- Top-10% rate
- 24.2% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +58% the tick is no change
Which countries lead Computational Drug Discovery Methods research?
By volume, China and India publish the most (3.6k and 3.4k works in 2022–2025).
By volume, 2022–2025
- 1 China 3.6k works
- 2 India 3.4k works
- 3 United States 3k works
- 4 Indonesia 634 works
- 5 United Kingdom 565 works
- 6 Germany 532 works
- 7 Saudi Arabia 477 works
- 8 Japan 409 works
- 9 Türkiye 407 works
- 10 Italy 397 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Computational Drug Discovery Methods research?
By volume in 2022–2025, King Saud University publishes the most Computational Drug Discovery Methods research, followed by Vellore Institute of Technology University and University of North Carolina at Chapel Hill.
By volume, 2022–2025
- 1 King Saud University Saudi Arabia 86 works
- 2 Vellore Institute of Technology University India 81 works
- 3 University of North Carolina at Chapel Hill United States 70 works
- 4 SRM Institute of Science and Technology India 56 works
- 5 Central South University China 52 works
- 6 Chinese Academy of Sciences China 51 works
- 7 Zhejiang University China 51 works
- 8 Jadavpur University India 50 works
- 9 Saveetha University India 49 works
- 10 China Pharmaceutical University China 41 works
Who are the leading researchers in Computational Drug Discovery Methods?
The most-cited researchers publishing on Computational Drug Discovery Methods include Peter A. Kollman, Minoru Kanehisa and Amirhossein Sahebkar.
- 1 Peter A. Kollman 6.3k citations
- 2 Minoru Kanehisa 5.7k citations
- 3 Amirhossein Sahebkar 5.6k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Computational Drug Discovery Methods research done?
The largest centres of Computational Drug Discovery Methods research in 2022–2025 are Beijing (China), Shanghai (China), Chennai (India) and New Delhi (India). Among places with at least 20 works in it, it is an unusually large share of all research in Rahway.
Largest cities, 2022–2025
Where it is the local speciality
- RahwayUS · 20.2 works12×
Location quotient: how much more of its research is in Computational Drug Discovery Methods than the world average.
Where is the best place to study Computational Drug Discovery Methods?
Among universities, judged by research, COMSATS University Islamabad, University of Sialkot and Jadavpur University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | COMSATS University Islamabad Pakistan | 74.1 | 41.4% | 7.8× | 35 | +1279.1% |
| 2 | University of Sialkot ?? | 64.8 | 61.4% | 30.4× | 10 | — |
| 3 | Jadavpur University India | 64.4 | 42.7% | 9.7× | 50 | -2.1% |
| 4 | Central University of Punjab India | 63.8 | 36.3% | 9.9× | 14 | +354.2% |
| 5 | Vellore Institute of Technology University India | 62.3 | 33.5% | 4.2× | 81 | +300.2% |
| 6 | JSS Academy of Higher Education and Research India | 60.5 | 16.0% | 13.5× | 30 | +257.8% |
| 7 | King Saud University Saudi Arabia | 60.3 | 31.1% | 4.9× | 86 | +51.0% |
| 8 | Shri Vile Parle Kelavani Mandal India | 60.1 | 30.8% | 24.2× | 30 | +88.6% |
| 9 | Dibrugarh University India | 60.0 | 28.2% | 13.8× | 16 | +264.6% |
| 10 | Macao Polytechnic University Macau | 58.5 | 35.0% | 9.7× | 16 | — |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Computational Drug Discovery Methods research growing?
Output in 2018–2022 was 58% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Computational Drug Discovery Methods.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.