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Bouback TA, Aljohani AM, Albeshri A, Al-Talhi H, Moatasim Y, GabAllah M, Badierah R, Albiheyri R, Al-Sarraj F, Ali MA. Antiviral activity of Humulus lupulus (HOP) aqueous extract against MERS-CoV and SARS-CoV-2: in-vitro and in-silico study. BIOTECHNOL BIOTEC EQ 2023. [DOI: 10.1080/13102818.2022.2158133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Affiliation(s)
- Thamer Ahmed Bouback
- Biological Department, Faculty of Science, King Abdul Aziz University, Jeddah, Saudi Arabia
- Princess Dr. Najla Bint Saud Al-Saud Center for Excellence Research in Biotechnology, King Abdul-Aziz University, Jeddah, Saudi Arabia
| | - Amal Mohammed Aljohani
- Biological Department, Faculty of Science, King Abdul Aziz University, Jeddah, Saudi Arabia
| | - Abdulaziz Albeshri
- Biological Department, Faculty of Science, King Abdul Aziz University, Jeddah, Saudi Arabia
| | - Hasan Al-Talhi
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Yassmin Moatasim
- Center of Scientific Excellence for Influenza Viruses, Environmental Research Division, National Research Centre (NRC), Cairo, Egypt
| | - Mohamed GabAllah
- Center of Scientific Excellence for Influenza Viruses, Environmental Research Division, National Research Centre (NRC), Cairo, Egypt
| | - Raied Badierah
- Center of Scientific Excellence for Influenza Viruses, Environmental Research Division, National Research Centre (NRC), Cairo, Egypt
| | - Raed Albiheyri
- Center of Scientific Excellence for Influenza Viruses, Environmental Research Division, National Research Centre (NRC), Cairo, Egypt
- Centre of Excellence in Bionanoscience Research, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Faisal Al-Sarraj
- Medical Laboratory, King Abdulaziz University Hospital, King Abdul-Aziz University, Jeddah, Saudi Arabia
| | - Mohamed Ahmed Ali
- Center of Scientific Excellence for Influenza Viruses, Environmental Research Division, National Research Centre (NRC), Cairo, Egypt
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2
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Sitthiyotha T, Treewattanawong W, Chunsrivirot S. Designing peptides predicted to bind to the omicron variant better than ACE2 via computational protein design and molecular dynamics. PLoS One 2023; 18:e0292589. [PMID: 37816037 PMCID: PMC10564162 DOI: 10.1371/journal.pone.0292589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 09/25/2023] [Indexed: 10/12/2023] Open
Abstract
Brought about by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease (COVID-19) pandemic has resulted in large numbers of worldwide deaths and cases. Several SARS-CoV-2 variants have evolved, and Omicron (B.1.1.529) was one of the important variants of concern. It gets inside human cells by using its S1 subunit's receptor-binding domain (SARS-CoV-2-RBD) to bind to Angiotensin-converting enzyme 2 receptor's peptidase domain (ACE2-PD). Using peptides to inhibit binding interactions (BIs) between ACE2-PD and SARS-CoV-2-RBD is one of promising COVID-19 therapies. Employing computational protein design (CPD) as well as molecular dynamics (MD), this study used ACE2-PD's α1 helix to generate novel 25-mer peptide binders (SPB25) of Omicron RBD that have predicted binding affinities (ΔGbind (MM‑GBSA)) better than ACE2 by increasing favorable BIs between SPB25 and the conserved residues of RBD. Results from MD and the MM-GBSA method identified two best designed peptides (SPB25T7L/K11A and SPB25T7L/K11L with ΔGbind (MM‑GBSA) of -92.4 ± 0.4 and -95.7 ± 0.5 kcal/mol, respectively) that have better ΔGbind (MM‑GBSA) to Omicron RBD than ACE2 (-87.9 ± 0.5 kcal/mol) and SPB25 (-71.6 ± 0.5 kcal/mol). Additionally, they were predicted to have slightly higher stabilities, based on their percent helicities in water, than SBP1 (the experimentally proven inhibitor of SARS-CoV-2-RBD). Our two best designed SPB25s are promising candidates as omicron variant inhibitors.
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Affiliation(s)
- Thassanai Sitthiyotha
- Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Pathumwan, Bangkok, Thailand
| | - Wantanee Treewattanawong
- Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Pathumwan, Bangkok, Thailand
| | - Surasak Chunsrivirot
- Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Pathumwan, Bangkok, Thailand
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3
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Kaur A, Goyal B. In silico design and identification of new peptides for mitigating hIAPP aggregation in type 2 diabetes. J Biomol Struct Dyn 2023:1-16. [PMID: 37691445 DOI: 10.1080/07391102.2023.2254411] [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: 05/10/2023] [Accepted: 08/27/2023] [Indexed: 09/12/2023]
Abstract
The aberrant misfolding and self-aggregation of human islet amyloid polypeptide (hIAPP or amylin) into cytotoxic aggregates are implicated in the pathogenesis of type 2 diabetes (T2D). Among various inhibitors, short peptides derived from the amyloidogenic regions of hIAPP have been employed as hIAPP aggregation inhibitors due to their low immunogenicity, biocompatibility, and high chemical diversity. Recently, hIAPP fragment HSSNN18-22 was identified as an amyloidogenic sequence and displayed higher antiproliferative activity to RIN-5F cells. Various hIAPP aggregation inhibitors have been designed by chemical modifications of the highly amyloidogenic sequence (NFGAIL) of hIAPP. In this work, a library of pentapeptides based on fragment HSSNN18-22 was designed and assessed for their efficacy in blocking hIAPP aggregation using an integrated computational screening approach. The binding free energy calculations by molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method identified HSSQN and HSSNQ that bind to hIAPP monomer with a binding affinity of -21.25 ± 4.90 and -19.73 ± 3.10 kcal/mol, respectively, which is notably higher as compared to HSSNN (-11.90 ± 4.12 kcal/mol). The sampling of the non aggregation-prone helical conformation was notably increased from 23.5 ± 3.0 in the hIAPP monomer to 38.1 ± 3.6, and 33.8 ± 3.0% on the incorporation of HSSQN, and HSSNQ, respectively, which indicate reduced aggregation propensity of hIAPP monomer. The pentapeptides, HSSQN and HSSNQ, identified as hIAPP aggregation inhibitors in this work can be further conjugated with various metal chelating peptides to yield more efficacious and clinically relevant multifunctional modulators for targeting various pathological hallmarks of T2D.
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Affiliation(s)
- Apneet Kaur
- School of Chemistry & Biochemistry, Thapar Institute of Engineering & Technology, Patiala, India
| | - Bhupesh Goyal
- School of Chemistry & Biochemistry, Thapar Institute of Engineering & Technology, Patiala, India
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4
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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: 13] [Impact Index Per Article: 6.5] [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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5
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Mastouri M, Baachaoui S, Mosbah A, Raouafi N. In silico screening for oligopeptides useful as capture and reporting probes for interleukin-6 biosensing. RSC Adv 2022; 12:13003-13013. [PMID: 35497015 PMCID: PMC9049833 DOI: 10.1039/d2ra01496c] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/24/2022] [Indexed: 11/21/2022] Open
Abstract
IL-6 is an important interleukin associated with inflammation and several diseases such as cancer. Evaluation of its levels in human blood sera is a critical step for an accurate diagnosis of the diseases. Our goal is to design peptides that can selectively bind in different poses with good affinities to IL-6. For this purpose, we started from the crystal structures of different IL-6/protein complexes available in the Protein Data Bank (PDB) to select short peptides in the interaction zones, in which we intentionally introduced point mutations to increase their stability and affinity. To examine their usefulness as capture and reporting probes for the IL-6 biosensing, the five peptides and their interaction with IL-6 were studied in saline aqueous solution. Molecular docking, MD, and MM-PBSA were used to investigate the affinity and stability of these complexes. The conformational changes, the distance between the mass centers, the gyration radii, and the numbers of hydrogen bonds were analyzed to select the most suitable candidates. Three peptides, namely CTE17, CAY15 and CSE25, have the highest affinities presenting significant numbers of residues that have contact frequencies greater than 50% of simulation run time and are the most promising candidates. CTE17 and CSE25 showed they can form a stable sandwich with the target protein. For sake of comparison, we examined the previously known peptides (FND20, INL19 and CEK17) having affinity to IL-6 and the affinity of the lead i.e. CSE25 to two other interleukin family members (IL-4 and to IL-10). In silico design by docking and molecular dynamics of short peptides that can selectively recognize IL-6 for biosensing purposes.![]()
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Affiliation(s)
- Mohamed Mastouri
- Sensors and Biosensors Group, Laboratory of Analytical Chemistry & Electrochemistry (LR99ES15), Faculty of Science, University of Tunis El Manar 2092 Tunis El Manar Tunisia
| | - Sabrine Baachaoui
- Sensors and Biosensors Group, Laboratory of Analytical Chemistry & Electrochemistry (LR99ES15), Faculty of Science, University of Tunis El Manar 2092 Tunis El Manar Tunisia
| | - Amor Mosbah
- BVBGR Laboratory (LR11ES31), ISBST, Biotechnopole Sidi Thabet, University of Manouba Ariana 2020 Tunisia
| | - Noureddine Raouafi
- Sensors and Biosensors Group, Laboratory of Analytical Chemistry & Electrochemistry (LR99ES15), Faculty of Science, University of Tunis El Manar 2092 Tunis El Manar Tunisia
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6
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Biswas S, Mahmud S, Mita MA, Afrose S, Hasan MR, Sultana Shimu MS, Saleh MA, Mostafa-Hedeab G, Alqarni M, Obaidullah AJ, Batiha GES. Molecular Docking and Dynamics Studies to Explore Effective Inhibitory Peptides Against the Spike Receptor Binding Domain of SARS-CoV-2. Front Mol Biosci 2022; 8:791642. [PMID: 35187069 PMCID: PMC8851422 DOI: 10.3389/fmolb.2021.791642] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 11/24/2021] [Indexed: 01/15/2023] Open
Abstract
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic due to the high transmission and mortality rate of this virus. The world health and economic sectors have been severely affected by this deadly virus, exacerbated by the lack of sufficient efficient vaccines. The design of effective drug candidates and their rapid development is necessary to combat this virus. In this study, we selected 23 antimicrobial peptides from the literature and predicted their structure using PEP-FOLD 3.5. In addition, we docked them to the SARS-CoV-2 spike protein receptor-binding domain (RBD) to study their capability to inhibit the RBD, which plays a significant role in virus binding, fusion and entry into the host cell. We used several docking programs including HDOCK, HPEPDOCK, ClusPro, and HawkDock to calculate the binding energy of the protein-peptide complexes. We identified four peptides with high binding free energy and docking scores. The docking results were further verified by molecular dynamics (MD) simulations to characterize the protein-peptide complexes in terms of their root-mean-square fluctuation (RMSF), root-mean-square deviation (RMSD), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen bond formation. Allergenicity and toxicity predictions suggested that the peptides we identified were non-allergenic and non-toxic. This study suggests that these four antimicrobial peptides could inhibit the RBD of SARS-CoV-2. Future in vitro and in vivo studies are necessary to confirm this.
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Affiliation(s)
- Suvro Biswas
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Shafi Mahmud
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
- *Correspondence: Shafi Mahmud, ; Md. Abu Saleh,
| | - Mohasana Akter Mita
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Shamima Afrose
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Robiul Hasan
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | | | - Md. Abu Saleh
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
- *Correspondence: Shafi Mahmud, ; Md. Abu Saleh,
| | - Gomaa Mostafa-Hedeab
- Pharmacology Department and Health Research Unit-medical College, Jouf University, Jouf, Saudi Arabia
- Pharmacology Department, Faculty of Medicine, Beni-Suef University, Beni Suef, Egypt
| | - Mohammed Alqarni
- Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Taif, Saudi Arabia
| | - Ahmad J. Obaidullah
- Drug Exploration and Development Chair (DEDC), Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Gaber El-Saber Batiha
- Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, Egypt
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7
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A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD-ACE2 Interaction. Int J Mol Sci 2021; 22:ijms222111627. [PMID: 34769056 PMCID: PMC8584250 DOI: 10.3390/ijms222111627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 01/18/2023] Open
Abstract
The angiotensin-converting enzyme 2 (ACE2) is the receptor used by SARS-CoV and SARS-CoV-2 coronaviruses to attach to cells via the receptor-binding domain (RBD) of their viral spike protein. Since the start of the COVID-19 pandemic, several structures of protein complexes involving ACE2 and RBD as well as monoclonal antibodies and nanobodies have become available. We have leveraged the structural data to design peptides to target the interaction between the RBD of SARS-CoV-2 and ACE2 and SARS-CoV and ACE2, as contrasting exemplar, as well as the dimerization surface of ACE2 monomers. The peptides were modelled using our original method: PiPreD that uses native elements of the interaction between the targeted protein and cognate partner(s) that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations surrogating key interactions at the interface. To facilitate the access to this information we have created a freely available and dedicated web-based repository, PepI-Covid19 database, providing convenient access to this wealth of information to the scientific community with the view of maximizing its potential impact in the development of novel therapeutic and diagnostic agents.
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8
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Kleandrova VV, Scotti MT, Speck-Planche A. Indirect-Acting Pan-Antivirals vs. Respiratory Viruses: A Fresh Perspective on Computational Multi-Target Drug Discovery. Curr Top Med Chem 2021; 21:2687-2693. [PMID: 34636311 DOI: 10.2174/1568026621666211012110819] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 09/23/2021] [Accepted: 09/23/2021] [Indexed: 12/22/2022]
Abstract
Respiratory viruses continue to afflict mankind. Among them, pathogens such as coronaviruses [including the current pandemic agent known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] and the one causing influenza A (IAV) are highly contagious and deadly. These can evade the immune system defenses while causing a hyperinflammatory response that can damage different tissues/organs. Simultaneously targeting immunomodulatory proteins is a plausible antiviral strategy since it could lead to the discovery of indirect-acting pan-antiviral (IAPA) agents for the treatment of diseases caused by respiratory viruses. In this context, computational approaches, which are an essential part of the modern drug discovery campaigns, could accelerate the identification of multi-target immunomodulators. This perspective discusses the usefulness of computational multi-target drug discovery for the virtual screening (drug repurposing) of IAPA agents capable of boosting the immune system through the activation of the toll-like receptor 7 (TLR7) and/or the stimulator of interferon genes (STING) while inhibiting key pro-inflammatory proteins, such as caspase-1 and tumor necrosis factor-alpha (TNF-α).
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Affiliation(s)
- Valeria V Kleandrova
- Laboratory of Fundamental and Applied Research of Quality and Technology of Food Production, Moscow State University of Food Production, Volokolamskoe shosse 11, 125080, Moscow. Russian Federation
| | - Marcus T Scotti
- Postgraduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, 58051-900, João Pessoa. Brazil
| | - Alejandro Speck-Planche
- Postgraduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, 58051-900, João Pessoa. Brazil
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