Expert Opinion on Drug Discovery
Published by Taylor & Francis
ISSN : 1746-0441 eISSN : 1746-045X
Abbreviation : Expert Opin. Drug Discov.
Aims & Scope
Expert Opinion on Drug Discovery (ISSN 1746-0441 [print], 1746-045X [electronic]) is a MEDLINE-indexed, peer-reviewed, international journal publishing review articles on novel technologies involved in the drug discovery process, leading to new leads and reduced attrition rates.
Each article is structured to incorporate the author’s own expert opinion on the scope for future development.
The Editors welcome: Reviews covering chemoinformatics; bioinformatics; assay development; novel screening technologies; in vitro/in vivo models; structure-based drug design; systems biology Drug Case Histories examining the steps involved in the preclinical and clinical development of a particular drug The audience consists of scientists and managers in the healthcare and pharmaceutical industry, academic pharmaceutical scientists and other closely related professionals looking to enhance the success of their drug candidates through optimisation at the preclinical level.
View Aims & ScopeMetrics & Ranking
Impact Factor
Year | Value |
---|---|
2025 | 4.9 |
2024 | 6.00 |
SJR (SCImago Journal Rank)
Year | Value |
---|---|
2024 | 1.195 |
Quartile
Year | Value |
---|---|
2024 | Q1 |
h-index
Year | Value |
---|---|
2024 | 90 |
Journal Rank
Year | Value |
---|---|
2024 | 3574 |
Journal Citation Indicator
Year | Value |
---|---|
2024 | 1843 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Pharmacology, Toxicology and Pharmaceutics, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
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The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities
Citation: 4066
Authors: Samuel, Ulf
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The influence of lipophilicity in drug discovery and design
Citation: 679
Authors: John A, Sonia Lobo
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Virtual screening with AutoDock: theory and practice
Citation: 538
Authors: Sandro, Stefano, Alex L, Rodney, David S, Arthur J
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Molecular dynamics simulations and novel drug discovery
Citation: 427
Authors: Xuewei, Danfeng, Shuangyan, Hongli, Huanxiang, Xiaojun
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Advances in structure-based drug discovery of carbonic anhydrase inhibitors
Citation: 350
Authors: Claudiu T.
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Artificial intelligence in drug discovery: recent advances and future perspectives
Citation: 310
Authors: José, Francesca, Nils, Gisbert