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Otazu K, Olivos-Ramirez GE, Fernández-Silva PD, Vilca-Quispe J, Vega-Chozo K, Jimenez-Avalos GM, Chenet-Zuta ME, Sosa-Amay FE, Cárdenas Cárdenas RG, Ropón-Palacios G, Dattani N, Camps I. The Malaria Box molecules: a source for targeting the RBD and NTD cryptic pocket of the spike glycoprotein in SARS-CoV-2. J Mol Model 2024; 30:217. [PMID: 38888748 DOI: 10.1007/s00894-024-06006-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 06/05/2024] [Indexed: 06/20/2024]
Abstract
CONTEXT SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus's spike protein. METHOD We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.
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Affiliation(s)
- Kewin Otazu
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil
| | - Gustavo E Olivos-Ramirez
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil
- HPQC Labs, Waterloo, Canada
| | - Pablo D Fernández-Silva
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil
| | - Julissa Vilca-Quispe
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil
| | - Karolyn Vega-Chozo
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil
| | | | | | - Frida E Sosa-Amay
- Laboratorio de Farmacología y Toxicología, Facultad de Farmacia y Bioquímica, Universidad Nacional de la Amazonía Peruana, Iquitos, Perú
| | | | - Georcki Ropón-Palacios
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil.
- HPQC Labs, Waterloo, Canada.
| | - Nike Dattani
- HPQC College, Waterloo, Canada.
- HPQC Labs, Waterloo, Canada.
| | - Ihosvany Camps
- Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas-UNIFAL-MG, Alfenas, Minas Gerais, Brazil.
- HPQC Labs, Waterloo, Canada.
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Gupta G, Verkhivker G. Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking. Int J Mol Sci 2024; 25:4955. [PMID: 38732174 PMCID: PMC11084335 DOI: 10.3390/ijms25094955] [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: 03/19/2024] [Revised: 04/24/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.
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Affiliation(s)
- Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA;
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA;
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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Sulimov AV, Ilin IS, Tashchilova AS, Kondakova OA, Kutov DC, Sulimov VB. Docking and other computing tools in drug design against SARS-CoV-2. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2024; 35:91-136. [PMID: 38353209 DOI: 10.1080/1062936x.2024.2306336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/10/2024] [Indexed: 02/16/2024]
Abstract
The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.
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Affiliation(s)
- A V Sulimov
- Dimonta Ltd., Moscow, Russia
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
| | - I S Ilin
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
| | - A S Tashchilova
- Dimonta Ltd., Moscow, Russia
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
| | - O A Kondakova
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
| | - D C Kutov
- Dimonta Ltd., Moscow, Russia
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
| | - V B Sulimov
- Dimonta Ltd., Moscow, Russia
- Research Computing Center, Lomonosov Moscow State University, Moscow, Russia
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Lima Neto JX, Bezerra KS, Barbosa ED, Araujo RL, Galvão DS, Lyra ML, Oliveira JIN, Akash S, Jardan YAB, Nafidi HA, Bourhia M, Fulco UL. Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2. Front Mol Biosci 2024; 10:1325588. [PMID: 38304231 PMCID: PMC10830813 DOI: 10.3389/fmolb.2023.1325588] [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: 10/21/2023] [Accepted: 12/22/2023] [Indexed: 02/03/2024] Open
Abstract
Background: The RNA-dependent RNA polymerase (RdRp) complex, essential in viral transcription and replication, is a key target for antiviral therapeutics. The core unit of RdRp comprises the nonstructural protein NSP12, with NSP7 and two copies of NSP8 (NSP81 and NSP82) binding to NSP12 to enhance its affinity for viral RNA and polymerase activity. Notably, the interfaces between these subunits are highly conserved, simplifying the design of molecules that can disrupt their interaction. Methods: We conducted a detailed quantum biochemical analysis to characterize the interactions within the NSP12-NSP7, NSP12-NSP81, and NSP12-NSP82 dimers. Our objective was to ascertain the contribution of individual amino acids to these protein-protein interactions, pinpointing hotspot regions crucial for complex stability. Results: The analysis revealed that the NSP12-NSP81 complex possessed the highest total interaction energy (TIE), with 14 pairs of residues demonstrating significant energetic contributions. In contrast, the NSP12-NSP7 complex exhibited substantial interactions in 8 residue pairs, while the NSP12-NSP82 complex had only one pair showing notable interaction. The study highlighted the importance of hydrogen bonds and π-alkyl interactions in maintaining these complexes. Intriguingly, introducing the RNA sequence with Remdesivir into the complex resulted in negligible alterations in both interaction energy and geometric configuration. Conclusion: Our comprehensive analysis of the RdRp complex at the protein-protein interface provides invaluable insights into interaction dynamics and energetics. These findings can guide the design of small molecules or peptide/peptidomimetic ligands to disrupt these critical interactions, offering a strategic pathway for developing effective antiviral drugs.
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Affiliation(s)
- José Xavier Lima Neto
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Katyanna Sales Bezerra
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Emmanuel Duarte Barbosa
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Roniel Lima Araujo
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | | | - Jonas Ivan Nobre Oliveira
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Shopnil Akash
- Department of Pharmacy, Daffodil International University, Dhaka, Bangladesh
| | - Yousef A. Bin Jardan
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Hiba-Allah Nafidi
- Department of Food Science, Faculty of Agricultural and Food Sciences, Laval University, Quebec City, QC, Canada
| | - Mohammed Bourhia
- Department of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, Laayoune, Morocco
| | - Umberto Laino Fulco
- Department of Biophysics and Pharmacology, Bioscience Center, Federal University of Rio Grande do Norte, Natal, Brazil
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Wang P, Yan F, Dong J, Wang S, Shi Y, Zhu M, Zuo Y, Ma H, Xue R, Zhai D, Song X. A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression. Phys Chem Chem Phys 2023; 25:8341-8354. [PMID: 36880666 DOI: 10.1039/d2cp05676c] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Depression severely impairs the health of people all over the world. Cognitive dysfunction due to depression has resulted in a severe economic burden to family and society induced by the reduction of social functioning of patients. Norepinephrine-dopamine reuptake inhibitors (NDRIs) targeted with the human norepinephrine transporter (hNET) and distributed with the human dopamine transporter (hDAT) simultaneously treat depression and improve cognitive function, and they effectively prevent sexual dysfunction and other side effects. Because many patients continue to poorly respond to NDRIs, it is urgent to discover novel NDRI antidepressants that do not interfere with cognitive function. The aim of this work was to selectively identify novel NDRI candidates acting against hNET and hDAT from large compound libraries by a comprehensive strategy integrating support vector machine (SVM) models, ADMET, molecular docking, in vitro binding assays, molecular dynamics simulation, and binding energy calculation. First, 6522 compounds that do not inhibit the human serotonin transporter (hSERT) were obtained by SVM models of hNET, hDAT, and non-target hSERT with similarity analyses from compound libraries. ADMET and molecular docking were then used to identify compounds that could potently bind to the hNET and hDAT with satisfactory ADMET, and 4 compounds were successfully identified. According to their docking scores and ADMET information, 3719810 was advanced for profiling by in vitro assays as a novel NDRI lead compound due to its strongest druggability and balancing activities. Encouragingly, 3719810 performed comparative activities on two targets, with Ki values of 7.32 μM for hNET and 5.23 μM for hDAT. To obtain candidates with additional activities and balance the activities of 2 targets, 5 analogs were optimized, and 2 novel scaffold compounds were successively designed. By assessment of molecular docking, molecular dynamics simulations, and binding energy calculations, 5 compounds were validated as NDRI candidates with high activities, and 4 of them performed acceptable balancing activities acting on hNET and hDAT. This work supplied promising novel NDRIs for treatment of depression with cognitive dysfunction or other related neurodegenerative disorders, and also provided a strategy for highly efficient and cost-effective identification of inhibitors for dual targets with homologous non-targets.
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Affiliation(s)
- Panpan Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Fengmei Yan
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Jianghong Dong
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Shengqiang Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Yu Shi
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Mengdan Zhu
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Yuting Zuo
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Hui Ma
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Ruirui Xue
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Dingjie Zhai
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Xiaoyu Song
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
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Shanmugam A, Venkattappan A, Gromiha MM. Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design. Curr Top Med Chem 2023; 22:2396-2409. [PMID: 36330617 DOI: 10.2174/1568026623666221103091658] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/14/2022] [Accepted: 10/06/2022] [Indexed: 11/06/2022]
Abstract
The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.
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Affiliation(s)
- Anusuya Shanmugam
- Department of Pharmaceutical Engineering, Vinayaka Mission's Kirupananda Variyar Engineering College, Vinayaka Mission's Research Foundation (Deemed to be University), Salem, 636308, Tamil Nadu, India.,Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology ,Madras, Chennai, 600036, Tamil Nadu, India
| | - Anbazhagan Venkattappan
- Department of Chemistry, Vinayaka Mission's Kirupananda Variyar Arts and Science College, Vinayaka Mission's Research Foundation (Deemed to be University), Salem, 636308, Tamil Nadu, India
| | - M Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology ,Madras, Chennai, 600036, Tamil Nadu, India
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