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Abstract
Citations are an essential aspect of research communication and have become the basis of many evaluation metrics in the academic world. Some see citation counts as a mark of scientific impact or even quality, but in reality the reasons for citing other work are manifold which makes the interpretation more complicated than a single citation count can reflect. Two years ago, the Journal of Cheminformatics proposed the CiTO Pilot for the adoption of a practice of annotating citations with their citation intentions. Basically, when you cite a journal article or dataset (or any other source), you also explain why specifically you cite that source. Particularly, the agreement and disagreement and reuse of methods and data are of interest. This article explores what happened after the launch of the pilot. We summarize how authors in the Journal of Cheminformatics used the pilot, shows citation annotations are distributed with Wikidata, visualized with Scholia, discusses adoption outside BMC, and finally present some thoughts on what needs to happen next.
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Macip G, Garcia-Segura P, Mestres-Truyol J, Saldivar-Espinoza B, Ojeda-Montes MJ, Gimeno A, Cereto-Massagué A, Garcia-Vallvé S, Pujadas G. Haste makes waste: A critical review of docking-based virtual screening in drug repurposing for SARS-CoV-2 main protease (M-pro) inhibition. Med Res Rev 2021; 42:744-769. [PMID: 34697818 PMCID: PMC8662214 DOI: 10.1002/med.21862] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/30/2021] [Accepted: 10/11/2021] [Indexed: 12/23/2022]
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.
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Affiliation(s)
- Guillem Macip
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain
| | - Pol Garcia-Segura
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain
| | - Júlia Mestres-Truyol
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain
| | - Bryan Saldivar-Espinoza
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain
| | | | - Aleix Gimeno
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Adrià Cereto-Massagué
- 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
| | - Santiago Garcia-Vallvé
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.,EURECAT, TECNIO, CEICS, Avinguda Universitat 1, Reus, Spain
| | - Gerard Pujadas
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.,EURECAT, TECNIO, CEICS, Avinguda Universitat 1, Reus, Spain
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Oselusi SO, Christoffels A, Egieyeh SA. Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds. Molecules 2021; 26:molecules26133970. [PMID: 34209681 PMCID: PMC8271829 DOI: 10.3390/molecules26133970] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 05/29/2021] [Accepted: 06/02/2021] [Indexed: 12/26/2022] Open
Abstract
The growing antimicrobial resistance (AMR) of pathogenic organisms to currently prescribed drugs has resulted in the failure to treat various infections caused by these superbugs. Therefore, to keep pace with the increasing drug resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have been shown to display promising in vitro activities against multidrug-resistant pathogens. Still, only a few of these compounds have been studied as prospective drug candidates. This may be due to the expensive and time-consuming process of conducting important studies on these compounds. The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens. Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.
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Affiliation(s)
- Samson Olaitan Oselusi
- School of Pharmacy, University of the Western Cape, Bellville, Cape Town 7535, South Africa;
- Correspondence:
| | - Alan Christoffels
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town 7535, South Africa;
| | - Samuel Ayodele Egieyeh
- School of Pharmacy, University of the Western Cape, Bellville, Cape Town 7535, South Africa;
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