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Llop-Peiró A, Macip G, Garcia-Vallvé S, Pujadas G. Are protein-ligand docking programs good enough to predict experimental poses of noncovalent ligands bound to the SARS-CoV-2 main protease? Drug Discov Today 2024; 29:104137. [PMID: 39151594 DOI: 10.1016/j.drudis.2024.104137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 08/10/2024] [Accepted: 08/12/2024] [Indexed: 08/19/2024]
Abstract
Hundreds of virtual screening (VS) studies have targeted the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) main protease (M-pro) to identify small molecules that inhibit its proteolytic action. Most studies use AutoDock Vina or Glide methodologies [high-throughput VS (HTVS), standard precision (SP), or extra precision (XP)], independently or in a VS workflow. Moreover, the Protein Data Bank (PDB) includes multiple complexes between M-pro and various noncovalent ligands, providing an excellent benchmark for assessing the predictive capabilities of docking programs. Here, we analyze the ability of the three Glide methodologies and AutoDock Vina by using various target structures/preparations to predict the experimental poses of these complexes. Our aims are to optimize target setup and docking methodologies, minimize false positives, and maximize the identification of various chemotypes in a SARS-CoV-2 M-pro noncovalent inhibitor VS campaign.
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Affiliation(s)
- Ariadna Llop-Peiró
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, 43007 Tarragona, Catalonia, Spain
| | - Guillem Macip
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, 43007 Tarragona, Catalonia, Spain; CELLEX Research Laboratories, CibeRes (Centro de Investigación Biomédica en Red de Enfermedades Respiratorias. 06/06/0028), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Catalonia, Spain; Pulmonology Department, Hospital Clínic, 08036 Barcelona, Catalonia, Spain
| | - Santiago Garcia-Vallvé
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, 43007 Tarragona, Catalonia, Spain.
| | - Gerard Pujadas
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, 43007 Tarragona, Catalonia, Spain.
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2
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Yarovaya OI, Filimonov AS, Baev DS, Borisevich SS, Zaykovskaya AV, Chirkova VY, Marenina MK, Meshkova YV, Belenkaya SV, Shcherbakov DN, Gureev MA, Luzina OA, Pyankov OV, Salakhutdinov NF, Khvostov MV. The Potential of Usnic-Acid-Based Thiazolo-Thiophenes as Inhibitors of the Main Protease of SARS-CoV-2 Viruses. Viruses 2024; 16:215. [PMID: 38399993 PMCID: PMC10893357 DOI: 10.3390/v16020215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/25/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
Although the COVID-19 pandemic caused by SARS-CoV-2 viruses is officially over, the search for new effective agents with activity against a wide range of coronaviruses is still an important task for medical chemists and virologists. We synthesized a series of thiazolo-thiophenes based on (+)- and (-)-usnic acid and studied their ability to inhibit the main protease of SARS-CoV-2. Substances containing unsubstituted thiophene groups or methyl- or bromo-substituted thiophene moieties showed moderate activity. Derivatives containing nitro substituents in the thiophene heterocycle-just as pure (+)- and (-)-usnic acids-showed no anti-3CLpro activity. Kinetic parameters of the most active compound, (+)-3e, were investigated, and molecular modeling of the possible interaction of the new thiazolo-thiophenes with the active site of the main protease was carried out. We evaluated the binding energies of the ligand and protein in a ligand-protein complex. Active compound (+)-3e was found to bind with minimum free energy; the binding of inactive compound (+)-3g is characterized by higher values of minimum free energy; the positioning of pure (+)-usnic acid proved to be unstable and is accompanied by the formation of intermolecular contacts with many amino acids of the catalytic binding site. Thus, the molecular dynamics results were consistent with the experimental data. In an in vitro antiviral assay against six strains (Wuhan, Delta, and four Omicron sublineages) of SARS-CoV-2, (+)-3e demonstrated pronounced antiviral activity against all the strains.
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Affiliation(s)
- Olga I. Yarovaya
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Aleksandr S. Filimonov
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Dmitriy S. Baev
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
- Synchrotron Radiation Facility SKIF, G.K. Boreskov Institute of Catalysis SB RAS, 630559 Koltsovo, Russia;
| | - Sophia S. Borisevich
- Synchrotron Radiation Facility SKIF, G.K. Boreskov Institute of Catalysis SB RAS, 630559 Koltsovo, Russia;
- Laboratory of Chemical Physics, Ufa Institute of Chemistry, Ufa Federal Research Centre, 450078 Ufa, Russia
| | - Anna V. Zaykovskaya
- State Research Center of Virology and Biotechnology VECTOR, Rospotrebnadzor, 630559 Koltsovo, Russia; (A.V.Z.); (O.V.P.)
| | - Varvara Yu. Chirkova
- Institute of Biology and Biotechnology, Altay State University, 656049 Barnaul, Russia;
| | - Mariya K. Marenina
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Yulia V. Meshkova
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Svetlana V. Belenkaya
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
- State Research Center of Virology and Biotechnology VECTOR, Rospotrebnadzor, 630559 Koltsovo, Russia; (A.V.Z.); (O.V.P.)
| | - Dmitriy N. Shcherbakov
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
- State Research Center of Virology and Biotechnology VECTOR, Rospotrebnadzor, 630559 Koltsovo, Russia; (A.V.Z.); (O.V.P.)
- Institute of Biology and Biotechnology, Altay State University, 656049 Barnaul, Russia;
| | - Maxim A. Gureev
- Laboratory of Bio- and Cheminformatics, St. Petersburg School of Physics, Mathematics and Computer Science, HSE University, 194100 St. Peterburg, Russia;
| | - Olga A. Luzina
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Oleg V. Pyankov
- State Research Center of Virology and Biotechnology VECTOR, Rospotrebnadzor, 630559 Koltsovo, Russia; (A.V.Z.); (O.V.P.)
| | - Nariman F. Salakhutdinov
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
| | - Mikhail V. Khvostov
- Department of Medicinal Chemistry, N.N. Vorozhtsov Novosibirsk Institute of Organic Chemistry SB RAS, 630090 Novosibirsk, Russia; (A.S.F.); (D.S.B.); (M.K.M.); (Y.V.M.); (S.V.B.); (D.N.S.); (O.A.L.); (N.F.S.); (M.V.K.)
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3
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Sokouti B. A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors. EXPLORATION OF TARGETED ANTI-TUMOR THERAPY 2023; 4:994-1026. [PMID: 38023988 PMCID: PMC10651357 DOI: 10.37349/etat.2023.00177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/22/2023] [Indexed: 12/01/2023] Open
Abstract
The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.
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Affiliation(s)
- Babak Sokouti
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz 5165665813, Iran
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4
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Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics. Int J Mol Sci 2023; 24:ijms24054401. [PMID: 36901832 PMCID: PMC10003049 DOI: 10.3390/ijms24054401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/19/2023] [Accepted: 02/21/2023] [Indexed: 02/25/2023] Open
Abstract
Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.
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5
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Vittorio S, Lunghini F, Pedretti A, Vistoli G, Beccari AR. Ensemble of structure and ligand-based classification models for hERG liability profiling. Front Pharmacol 2023; 14:1148670. [PMID: 37033661 PMCID: PMC10076575 DOI: 10.3389/fphar.2023.1148670] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.
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Affiliation(s)
- Serena Vittorio
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | | | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | - Andrea R. Beccari
- EXSCALATE, Dompé Farmaceutici SpA, Napoli, Italy
- *Correspondence: Andrea R. Beccari,
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6
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Blanes-Mira C, Fernández-Aguado P, de Andrés-López J, Fernández-Carvajal A, Ferrer-Montiel A, Fernández-Ballester G. Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening. Molecules 2022; 28:molecules28010175. [PMID: 36615367 PMCID: PMC9821981 DOI: 10.3390/molecules28010175] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022] Open
Abstract
The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.
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7
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Beccari AR, Vistoli G. Exscalate4CoV: Innovative High Performing Computing (HPC) Strategies to Tackle Pandemic Crisis. Int J Mol Sci 2022; 23:ijms231911576. [PMID: 36232873 PMCID: PMC9569893 DOI: 10.3390/ijms231911576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 09/28/2022] [Indexed: 11/07/2022] Open
Affiliation(s)
- Andrea R. Beccari
- EXSCALATE, Dompé Farmaceutici S.p.A., Via Tommaso De Amicis 95, I-80131 Napoli, Italy
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli 25, I-20133 Milano, Italy
- Correspondence:
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8
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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9
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Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel. Int J Mol Sci 2022; 23:ijms23147558. [PMID: 35886905 PMCID: PMC9317601 DOI: 10.3390/ijms23147558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/30/2022] [Accepted: 07/04/2022] [Indexed: 11/27/2022] Open
Abstract
(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations.
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10
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Iaconis D, Bordi L, Matusali G, Talarico C, Manelfi C, Cesta MC, Zippoli M, Caccuri F, Bugatti A, Zani A, Filippini F, Scorzolini L, Gobbi M, Beeg M, Piotti A, Montopoli M, Cocetta V, Bressan S, Bucci EM, Caruso A, Nicastri E, Allegretti M, Beccari AR. Characterization of raloxifene as a potential pharmacological agent against SARS-CoV-2 and its variants. Cell Death Dis 2022; 13:498. [PMID: 35614039 PMCID: PMC9130985 DOI: 10.1038/s41419-022-04961-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 05/12/2022] [Accepted: 05/17/2022] [Indexed: 12/14/2022]
Abstract
The new coronavirus SARS-CoV-2 is the causative agent of the COVID-19 pandemic, which so far has caused over 6 million deaths in 2 years, despite new vaccines and antiviral medications. Drug repurposing, an approach for the potential application of existing pharmaceutical products to new therapeutic indications, could be an effective strategy to obtain quick answers to medical emergencies. Following a virtual screening campaign on the most relevant viral proteins, we identified the drug raloxifene, a known Selective Estrogen Receptor Modulator (SERM), as a new potential agent to treat mild-to-moderate COVID-19 patients. In this paper we report a comprehensive pharmacological characterization of raloxifene in relevant in vitro models of COVID-19, specifically in Vero E6 and Calu-3 cell lines infected with SARS-CoV-2. A large panel of the most common SARS-CoV-2 variants isolated in Europe, United Kingdom, Brazil, South Africa and India was tested to demonstrate the drug's ability in contrasting the viral cytopathic effect (CPE). Literature data support a beneficial effect by raloxifene against the viral infection due to its ability to interact with viral proteins and activate protective estrogen receptor-mediated mechanisms in the host cells. Mechanistic studies here reported confirm the significant affinity of raloxifene for the Spike protein, as predicted by in silico studies, and show that the drug treatment does not directly affect Spike/ACE2 interaction or viral internalization in infected cell lines. Interestingly, raloxifene can counteract Spike-mediated ADAM17 activation in human pulmonary cells, thus providing new insights on its mechanism of action. A clinical study in mild to moderate COVID-19 patients (NCT05172050) has been recently completed. Our contribution to evaluate raloxifene results on SARS-CoV-2 variants, and the interpretation of the mechanisms of action will be key elements to better understand the trial results, and to design new clinical studies aiming to evaluate the potential development of raloxifene in this indication.
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Affiliation(s)
| | - Licia Bordi
- grid.419423.90000 0004 1760 4142National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy
| | - Giulia Matusali
- grid.419423.90000 0004 1760 4142National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy
| | | | | | | | | | - Francesca Caccuri
- grid.7637.50000000417571846Department of Molecular and Translational Medicine, Section of Microbiology and Virology, University of Brescia Medical School, Brescia, Italy
| | - Antonella Bugatti
- grid.7637.50000000417571846Department of Molecular and Translational Medicine, Section of Microbiology and Virology, University of Brescia Medical School, Brescia, Italy
| | - Alberto Zani
- grid.7637.50000000417571846Department of Molecular and Translational Medicine, Section of Microbiology and Virology, University of Brescia Medical School, Brescia, Italy
| | - Federica Filippini
- grid.7637.50000000417571846Department of Molecular and Translational Medicine, Section of Microbiology and Virology, University of Brescia Medical School, Brescia, Italy
| | - Laura Scorzolini
- grid.419423.90000 0004 1760 4142National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy
| | - Marco Gobbi
- grid.4527.40000000106678902Department of Biochemistry and Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Marten Beeg
- grid.4527.40000000106678902Department of Biochemistry and Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Arianna Piotti
- grid.4527.40000000106678902Department of Biochemistry and Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Monica Montopoli
- grid.5608.b0000 0004 1757 3470Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, VIMM Veneto Institute Molecular Medicine, Padua, Italy
| | - Veronica Cocetta
- grid.5608.b0000 0004 1757 3470Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, VIMM Veneto Institute Molecular Medicine, Padua, Italy
| | - Silvia Bressan
- grid.5608.b0000 0004 1757 3470Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, VIMM Veneto Institute Molecular Medicine, Padua, Italy
| | - Enrico M. Bucci
- grid.264727.20000 0001 2248 3398Sbarro Health Research Organization, Biology Department CFT, Temple University, Philadelphia, PA USA
| | - Arnaldo Caruso
- grid.7637.50000000417571846Department of Molecular and Translational Medicine, Section of Microbiology and Virology, University of Brescia Medical School, Brescia, Italy
| | - Emanuele Nicastri
- grid.419423.90000 0004 1760 4142National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, Rome, Italy
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11
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Corona A, Wycisk K, Talarico C, Manelfi C, Milia J, Cannalire R, Esposito F, Gribbon P, Zaliani A, Iaconis D, Beccari AR, Summa V, Nowotny M, Tramontano E. Natural Compounds Inhibit SARS-CoV-2 nsp13 Unwinding and ATPase Enzyme Activities. ACS Pharmacol Transl Sci 2022; 5:226-239. [PMID: 35434533 PMCID: PMC9003574 DOI: 10.1021/acsptsci.1c00253] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Indexed: 12/27/2022]
Abstract
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SARS-CoV-2 infection
is still spreading worldwide, and new antiviral
therapies are an urgent need to complement the approved vaccine preparations.
SARS-CoV-2 nps13 helicase is a validated drug target participating
in the viral replication complex and possessing two associated activities:
RNA unwinding and 5′-triphosphatase. In the search of SARS-CoV-2
direct antiviral agents, we established biochemical assays for both
SARS-CoV-2 nps13-associated enzyme activities and screened both in silico and in vitro a small in-house
library of natural compounds. Myricetin, quercetin, kaempferol, and
flavanone were found to inhibit the SARS-CoV-2 nps13 unwinding activity
at nanomolar concentrations, while licoflavone C was shown to block
both SARS-CoV-2 nps13 activities at micromolar concentrations. Mode
of action studies showed that all compounds are nsp13 noncompetitive
inhibitors versus ATP, while computational studies suggested that
they can bind both nucleotide and 5′-RNA nsp13 binding sites,
with licoflavone C showing a unique pattern of interaction with nsp13
amino acid residues. Overall, we report for the first time natural
flavonoids as selective inhibitors of SARS-CoV-2 nps13 helicase with
low micromolar activity.
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Affiliation(s)
- Angela Corona
- Dipartimento di Scienze della vita e dell'ambiente, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, SS-554, 09042 Monserrato, Cagliari, Italy
| | - Krzysztof Wycisk
- Laboratory of Protein Structure, International Institute of Molecular and Cell Biology, Ks. Trojdena 4, Warsaw 02-109, Poland
| | - Carmine Talarico
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Candida Manelfi
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Jessica Milia
- Dipartimento di Scienze della vita e dell'ambiente, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, SS-554, 09042 Monserrato, Cagliari, Italy
| | - Rolando Cannalire
- Department of Pharmacy, University of Napoli "Federico II", via D. Montesano 49, Napoli 80131, Italy
| | - Francesca Esposito
- Dipartimento di Scienze della vita e dell'ambiente, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, SS-554, 09042 Monserrato, Cagliari, Italy
| | - Philip Gribbon
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Andrea Zaliani
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Daniela Iaconis
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Andrea R Beccari
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Vincenzo Summa
- Department of Pharmacy, University of Napoli "Federico II", via D. Montesano 49, Napoli 80131, Italy
| | - Marcin Nowotny
- Laboratory of Protein Structure, International Institute of Molecular and Cell Biology, Ks. Trojdena 4, Warsaw 02-109, Poland
| | - Enzo Tramontano
- Dipartimento di Scienze della vita e dell'ambiente, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, SS-554, 09042 Monserrato, Cagliari, Italy
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12
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Wang J, Ge W, Peng X, Yuan L, He S, Fu X. Investigating the active compounds and mechanism of HuaShi XuanFei formula for prevention and treatment of COVID-19 based on network pharmacology and molecular docking analysis. Mol Divers 2022; 26:1175-1190. [PMID: 34105049 PMCID: PMC8187140 DOI: 10.1007/s11030-021-10244-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 06/03/2021] [Indexed: 01/13/2023]
Abstract
Traditional Chinese medicine (TCM) has exerted positive effects in controlling the COVID-19 pandemic. HuaShi XuanFei Formula (HSXFF) was developed to treat patients with mild and general COVID-19 in Zhejiang Province, China. The present study seeks to explore its potentially active compounds and pharmacological mechanisms against COVID-19 based on network pharmacology, molecular docking, and molecular dynamics (MD) simulation. All components of HSXFF were harvested from the pharmacology database of the TCMSP system. COVID-19-related targets were retrieved from using OMIM and GeneCards databases. The herb-compound-targets network was constructed by Cytoscape. The target protein-protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to discover the potential key target genes and mechanism. The main active compounds of HSXFF were docked with 3C-like (3CL) protease hydrolase and angiotensin-converting enzyme 2 (ACE2). The MD simulation confirmed the binding stability of docking results. The herbs-targets network mainly contained 52 compounds and 70 corresponding targets, including key targets such as RELA, TNF, TP53, IL6, MAPK1, CXCL8, IL-1β, and MAPK14. The GO and KEGG indicated that HSXFF may be mainly acting on the IL-17 signaling pathway, TNF signaling pathway, NF-κB signaling pathway, etc. The molecular docking results indicated that isovitexin and procyanidin B1 showed the highest affinity with 3CL and ACE2, respectively, which were confirmed by MD simulation. These findings suggested HSXFF exerted therapeutic effects involving "multi-compounds and multi-targets." It might be working through directly inhibiting the virus, improving immune function, and reducing the inflammatory in response to anti-COVID-19. In summary, the present study would provide a valuable direction for further research of HSXFF.
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Affiliation(s)
- Juan Wang
- Zhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China
| | - Wen Ge
- Zhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China
| | - Xin Peng
- Ningbo Research Institute of Zhejiang University, Zhejiang Province, Ningbo, 315100, People's Republic of China.
| | - Lixia Yuan
- Zhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China
| | - Shuaibing He
- Key Laboratory of Vector Biology and Pathogen Control of Zhejiang Province, School of Medicine, Huzhou University, Huzhou Central Hospital, Huzhou, People's Republic of China
| | - Xuyan Fu
- Key Laboratory of Vector Biology and Pathogen Control of Zhejiang Province, School of Medicine, Huzhou University, Huzhou Central Hospital, Huzhou, People's Republic of China
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13
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Tutone M, Almerico AM. Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics. Molecules 2021; 26:molecules26247500. [PMID: 34946582 PMCID: PMC8707150 DOI: 10.3390/molecules26247500] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 12/08/2021] [Indexed: 11/16/2022] Open
Abstract
To date, computational approaches have been recognized as a key component in drug design and discovery workflows [...].
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14
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Plavec Z, Pöhner I, Poso A, Butcher SJ. Virus structure and structure-based antivirals. Curr Opin Virol 2021; 51:16-24. [PMID: 34564030 PMCID: PMC8460353 DOI: 10.1016/j.coviro.2021.09.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/13/2021] [Accepted: 09/12/2021] [Indexed: 01/18/2023]
Abstract
Structure-based antiviral developments in the past two years have been dominated by the structure determination and inhibition of SARS-CoV-2 proteins and new lead molecules for picornaviruses. The SARS-CoV-2 spike protein has been targeted successfully with antibodies, nanobodies, and receptor protein mimics effectively blocking receptor binding or fusion. The two most promising non-structural proteins sharing strong structural and functional conservation across virus families are the main protease and the RNA-dependent RNA polymerase, for which design and reuse of broad range inhibitors already approved for use has been an attractive avenue. For picornaviruses, the increasing recognition of the transient expansion of the capsid as a critical transition towards RNA release has been targeted through a newly identified, apparently widely conserved, druggable, interprotomer pocket preventing viral entry. We summarize some of the key papers in these areas and ponder the practical uses and contributions of molecular modeling alongside empirical structure determination.
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Affiliation(s)
- Zlatka Plavec
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland; Helsinki Institute of Life Sciences-Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
| | - Ina Pöhner
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Antti Poso
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland; University Hospital Tübingen, Department of Internal Medicine VII, Tübingen, Germany
| | - Sarah J Butcher
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland; Helsinki Institute of Life Sciences-Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
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