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Yan L, Ke Y, Wang Y, Yang J, He Y, Wu L. Effect of Mini-PEGs Modification on the Enzymatic Digestion of D-Amino Acid-Containing Peptides under the Action of PROK. Chemistry 2023; 29:e202203524. [PMID: 36541269 DOI: 10.1002/chem.202203524] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
It was previously reported that D-amino acid-containing peptides exhibited the ability to resist enzymatic hydrolysis. This study investigated the influence of mini-PEGs modification on enzymatic hydrolysis ability of D-amino acid-containing peptides. The results showed that PEGylation promoted enzymatic hydrolysis of the D-amino acid-containing peptide, especially, the cleavage rate of the D-amino acid-containing peptide 6-w with PEG3 modification at the N-ends was up to 17 times higher in the presence of proteinase K (PROK) compared to those without PEG3 modification. Moreover, analysis of the enzymatic cleavage sites demonstrated a similar cleavage pattern of the PEGylated D-amino acid-containing peptide to that of the unmodified peptide. The computational simulations further showed that the enhanced enzymatic hydrolysis ability can be attributed to the strong interaction between PROK and the peptide after PEG3 modification and the resulting formation of a mature catalytic triad structure.
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Affiliation(s)
- Liang Yan
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Yongqi Ke
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Yu Wang
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Jingkui Yang
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Yujian He
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
- State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical Sciences, Peking University, Beijing, 100191, P. R. China
| | - Li Wu
- School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
- State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical Sciences, Peking University, Beijing, 100191, P. R. China
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2
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Seyedi SH, Alhagh MS, Ahmadizad M, Ardalan N, Hosseininezhadian Koushki E, Farshadfar C, Amjadi B. Structural screening into the recognition of a potent inhibitor against non-structural protein 16: a molecular simulation to inhibit SARS-CoV-2 infection. J Biomol Struct Dyn 2022; 40:14115-14130. [PMID: 34762019 DOI: 10.1080/07391102.2021.2001374] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
COVID-19 infection is caused by endemic crown infection (SARS-CoV-2) and is associated with lung damage and severe immune response. Non-Structural Proteins are the central components of coronaviral transcription and replication machinery in SARS-CoV-2 and also stimulate mRNA cap methylation to avoid the immune response. Non-Structural Protein 16 (NSP16) is one of the primary targets for the drug discovery of coronaviruses. Discovering an effective inhibitor against the NSP16 in comparison with Sinefungin was the main purpose of this investigation. Binding free-energy calculations, computational methods of molecular dynamics, docking, and virtual screening were utilized in this study. The ZINC and PubChem databases were applied to screen some chemical compounds regarding Sinefungin as a control inhibitor. Based on structural similarity to Sinefungin, 355 structures were obtained from the mentioned databases. Subsequently, this set of compounds were monitored by AutoDock Vina software, and ultimately the potent inhibitor (PUBCHEM512713) was chosen. At the next stage, molecular dynamics were carried out by GROMACS software to evaluate the potential elected compounds in a simulated environment and in a timescale of 100 nanoseconds. MM-PBSA investigation exhibited that the value of binding free energy for PUBCHEM512713 (-30.829 kJ.mol-1) is more potent than Sinefungin (-11.941 kJ.mol-1). Furthermore, the results of ADME analysis illustrated that the pharmacokinetics, drug-likeness, and lipophilicity parameters of PUBCHEM512713 are admissible for human utilization. Finally, our data suggested that PUBCHEM512713 is an effective drug candidate for inhibiting the NSP16 and is suitable for in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Seyed Hamid Seyedi
- Department of Biochemistry, Science and Research Branch, Islamic Azad University, Sanandaj, Iran
| | - Mohammad Shakib Alhagh
- Department of Microbiology, Faculty of Medicine, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Mehran Ahmadizad
- Department of Biochemistry, Science and Research Branch, Islamic Azad University, Sanandaj, Iran
| | - Noeman Ardalan
- Department of Microbiology, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | | | - Chiako Farshadfar
- Department of Biochemistry, Science and Research Branch, Islamic Azad University, Sanandaj, Iran
| | - Barzan Amjadi
- Department of Biochemistry, Science and Research Branch, Islamic Azad University, Sanandaj, Iran
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3
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Abdizadeh R, Hadizadeh F, Abdizadeh T. Evaluation of apigenin-based biflavonoid derivatives as potential therapeutic agents against viral protease (3CLpro) of SARS-CoV-2 via molecular docking, molecular dynamics and quantum mechanics studies. J Biomol Struct Dyn 2022:1-31. [PMID: 35848354 DOI: 10.1080/07391102.2022.2098821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent of the pandemic COVID-19 disease that affects human respiratory function. Despite the scientific progression made in the development of the vaccine, there is an urgent need for the discovery of antiviral drugs for better performance at different stages of SARS-CoV-2 reproduction. The main protease (Mpro or 3CLpro) plays a pivotal role in the life cycle of the virus, making it an attractive target for the development of antiviral agents effective against the new strains of coronaviruses (CoVs). In this study, a series of apigenin-based natural biflavonoid derivatives as potential inhibitors of coronaviruses 3CLpro was investigated by in silico approaches. For this purpose, the molecular docking was performed to analyze the interaction of the natural biflavonoids with SARS-Cov-2 main protease and for further investigation, docking to the 3CLpro of SARS-CoV and MERS-CoV. Based on docking scores and comparison with the reference inhibitors (ritonavir and lopinavir), more than half of the biflavonoids had strong interactions with the residues of the binding pocket of the coronaviruses 3CLpro and exhibited better binding affinities toward the main protease than ritonavir and lopinavir. The top biflavonoids were further explored through molecular dynamics simulation, binding free energy calculation and residual energy contributions estimated by the MM-PBSA. Also, drug likeness property investigation by Swiss ADME tools and density functional theory (DFT) calculations were performed. The results confirmed that the 3CLpro-amentoflavone, 3CLpro-bilobetin, 3CLpro-ginkgetin, and 3CLpro-sotetsuflavone complexes possess a large amount of dynamic properties such as high stability, significant binding energy and fewer conformation fluctuations. Also, the pharmacokinetics and drug-likeness studies and HOMO-LUMO and DFT descriptor values indicated a promising result of the selected natural biflavonoids. Overall findings indicate that the apigenin-based biflavonoids may inhibit COVID-19 by significant interactions in the binding pocket and those results can pave the way in drug discovery although the effectiveness of these bioactive compounds should be further validated by in-vitro and in-vivo investigations. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rahman Abdizadeh
- Department of Medical Parasitology and Mycology, Faculty of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | - Farzin Hadizadeh
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Tooba Abdizadeh
- Clinical Biochemistry Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran
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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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