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May 3, 2024
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Haste makes waste: A critical review of docking-based virtual screening in drug repurposing for SARS-CoV-2 main protease (M-pro) inhibition.

Publicated to:Medicinal Research Reviews. 42 (2): 744-769 - 2022-03-01 42(2), DOI: 10.1002/med.21862

Authors: Macip, Guillem; Garcia-Segura, Pol; Mestres-Truyol, Julia; Saldivar-Espinoza, Bryan; Ojeda-Montes, Maria Jose; Gimeno, Aleix; Cereto-Massague, Adria; Garcia-Vallve, Santiago; Pujadas, Gerard

Affiliations

Avinguda Univ 1, EURECAT, TECNIO, CEICS, Reus, Spain - Author
Barcelona Inst Sci & Technol, Inst Res Biomed, Joint IRB BSC CRG Program Computat Biol, IRB Barcelona, Barcelona, Spain - Author
Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain. - Author
EURECAT Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain. - Author
Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain. - Author
Joint Unit Univ Rovira & Virgili EURECAT, Unique Sci & Tech Infrastruct ICTS, EURECAT Ctr Tecnol Catalunya, Ctr Omic SciCOS, Reus, Spain - Author
Molecular Modeling Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. - Author
SIB Swiss Inst Bioinformat, Mol Modeling Grp, Lausanne, Switzerland - Author
Univ Rovira & Virgili, Res Grp Cheminformat & Nutr, Dept Bioquim & Biotecnol, C Marcel Li Domingo 1, Tarragona 43007, Spain - Author
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Abstract

This review makes a critical evaluation of 61 peer-reviewed manuscripts that use a docking step in a virtual screening (VS) protocol to predict SARS-CoV-2 M-pro (M-pro) inhibitors in approved or investigational drugs. Various manuscripts predict different compounds, even when they use a similar initial dataset and methodology, and most of them do not validate their methodology or results. In addition, a set of known 150 SARS-CoV-2 M-pro inhibitors extracted from the literature and a second set of 81 M-pro inhibitors and 113 inactive compounds obtained from the COVID Moonshot project were used to evaluate the reliability of using docking scores as feasible predictors of the potency of a SARS-CoV-2 M-pro inhibitor. Using two SARS-CoV-2 M-pro structures and five protein-ligand docking programs, we proved that the correlation between the pIC50 and docking scores is not good. Neither was any correlation found between the pIC50 and the ∆G calculated with an MM-GBSA method. When a group of experimentally known inactive compounds was added, neither the docking scores or the ∆G were able to distinguish between compounds with or without M-pro experimental inhibitory activity. Performances improved when covalent and noncovalent inhibitors were treated separately, but were not good enough to fully support using a docking score as a cutoff value for selecting new putative M-pro inhibitors or predicting the relative bioactivity of a compound by comparison with a reference compound. The two sets of known SARS-CoV-2 M-pro inhibitors presented here could be used for validating future VS protocols which aim to predict M-pro inhibitors.

Keywords

3c-like proteinase, sars-cov-2Antiviral agentsCoronavirus 3c proteasesCovid-19Drug repositioningDrug repurposingHumansM-pro inhibitorsMolecular dockingMolecular docking simulationMolecular dynamics simulationReproducibility of resultsSars-cov-2Sars-cov-2 3c proteaseVirtual screening

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Medicinal Research Reviews due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2022, it was in position 1/60, thus managing to position itself as a Q1 (Primer Cuartil), in the category Chemistry, Medicinal. Notably, the journal is positioned above the 90th percentile.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 4.73. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Field Citation Ratio (FCR) from Dimensions: 9.04 (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-22, the following number of citations:

  • WoS: 47
  • Europe PMC: 34

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-22:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 106.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 111 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 5.85.
  • The number of mentions on the social network X (formerly Twitter): 3 (Altmetric).
  • The number of mentions on Wikipedia: 1 (Altmetric).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Switzerland.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Macip Sancho, Guillem) .