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Uddin KM, Meem MH, Akter M, Rahman S, Al-Gawati MA, Alarifi N, Albrithen H, Alodhayb A, Poirier RA, Bhuiyan MH. Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration. MethodsX 2024; 12:102691. [PMID: 38660042 PMCID: PMC11041845 DOI: 10.1016/j.mex.2024.102691] [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: 11/06/2023] [Accepted: 04/02/2024] [Indexed: 04/26/2024] Open
Abstract
In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1-5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1-5). Molecular docking was used to assess the binding interactions of these derivatives (1-5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol-1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides. Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1-5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1-5.
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Affiliation(s)
- Kabir M. Uddin
- Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka 1217, Bangladesh
| | - Mehnaz Hossain Meem
- Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka 1217, Bangladesh
| | - Mokseda Akter
- Bioorganic and Medicinal Chemistry Laboratory, Department of Chemistry, University of Chittagong, Chattogram 4331, Bangladesh
| | - Shofiur Rahman
- Biological and Environmental Sensing Research Unit, King Abdullah Institute for Nanotechnology, King Saud University, Riyadh 11451, Saudi Arabia
| | - Mahmoud A. Al-Gawati
- Biological and Environmental Sensing Research Unit, King Abdullah Institute for Nanotechnology, King Saud University, Riyadh 11451, Saudi Arabia
| | - Nahed Alarifi
- Research Chair for Tribology, Surface, and Interface Sciences, Department of Physics and Astronomy, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
| | - Hamad Albrithen
- Biological and Environmental Sensing Research Unit, King Abdullah Institute for Nanotechnology, King Saud University, Riyadh 11451, Saudi Arabia
- Research Chair for Tribology, Surface, and Interface Sciences, Department of Physics and Astronomy, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
| | - Abdullah Alodhayb
- Biological and Environmental Sensing Research Unit, King Abdullah Institute for Nanotechnology, King Saud University, Riyadh 11451, Saudi Arabia
- Research Chair for Tribology, Surface, and Interface Sciences, Department of Physics and Astronomy, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
| | - Raymond A. Poirier
- Department of Chemistry, Memorial University, St. John's, Newfoundland A1B 3 × 7, Canada
| | - Md. Mosharef H. Bhuiyan
- Bioorganic and Medicinal Chemistry Laboratory, Department of Chemistry, University of Chittagong, Chattogram 4331, Bangladesh
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2
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Habib A, Liang Y, Xu X, Zhu N, Xie J. Immunoinformatic Identification of Multiple Epitopes of gp120 Protein of HIV-1 to Enhance the Immune Response against HIV-1 Infection. Int J Mol Sci 2024; 25:2432. [PMID: 38397105 PMCID: PMC10889372 DOI: 10.3390/ijms25042432] [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: 01/11/2024] [Revised: 02/10/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
Acquired Immunodeficiency Syndrome is caused by the Human Immunodeficiency Virus (HIV), and a significant number of fatalities occur annually. There is a dire need to develop an effective vaccine against HIV-1. Understanding the structural proteins of viruses helps in designing a vaccine based on immunogenic peptides. In the current experiment, we identified gp120 epitopes using bioinformatic epitope prediction tools, molecular docking, and MD simulations. The Gb-1 peptide was considered an adjuvant. Consecutive sequences of GTG, GSG, GGTGG, and GGGGS linkers were used to bind the B cell, Cytotoxic T Lymphocytes (CTL), and Helper T Lymphocytes (HTL) epitopes. The final vaccine construct consisted of 315 amino acids and is expected to be a recombinant protein of approximately 35.49 kDa. Based on docking experiments, molecular dynamics simulations, and tertiary structure validation, the analysis of the modeled protein indicates that it possesses a stable structure and can interact with Toll-like receptors. The analysis demonstrates that the proposed vaccine can provoke an immunological response by activating T and B cells, as well as stimulating the release of IgA and IgG antibodies. This vaccine shows potential for HIV-1 prophylaxis. The in-silico design suggests that multiple-epitope constructs can be used as potentially effective immunogens for HIV-1 vaccine development.
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Affiliation(s)
- Arslan Habib
- Laboratory of Molecular Immunology, State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China; (A.H.); (X.X.); (N.Z.)
| | - Yulai Liang
- Laboratory of Molecular Immunology, State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China; (A.H.); (X.X.); (N.Z.)
| | - Xinyi Xu
- Laboratory of Molecular Immunology, State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China; (A.H.); (X.X.); (N.Z.)
| | - Naishuo Zhu
- Laboratory of Molecular Immunology, State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China; (A.H.); (X.X.); (N.Z.)
- Institute of Biomedical Sciences, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Jun Xie
- Laboratory of Molecular Immunology, State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China; (A.H.); (X.X.); (N.Z.)
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3
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Tamanna T, Rahman MS. Leveraging immunoinformatics for developing a multi-epitope subunit vaccine against Helicobacter pylori and Fusobacterium nucleatum. J Biomol Struct Dyn 2023:1-14. [PMID: 38116749 DOI: 10.1080/07391102.2023.2292295] [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: 03/22/2023] [Accepted: 11/25/2023] [Indexed: 12/21/2023]
Abstract
Gastric ulcers caused by Helicobacter pylori and Fusobacterium nucleatum remain a significant global health concern without an established vaccine. In this study, we utilized immunoinformatics methods to design a multi-epitope vaccine targeting these pathogens. Outer membrane proteins from H. pylori and F. nucleatum were scrutinized to identify high antigenic T-cell and B-cell epitopes. The resulting vaccine comprised carefully analyzed and evaluated epitopes, including cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocytes epitopes. This vaccine exhibited notable antigenicity, suitable immunogenicity, and demonstrated non-allergenicity and non-toxicity. It displayed favorable physiochemical characteristics and high solubility. In interaction studies, the vaccine exhibited robust binding to toll-like receptor 4 (TLR4). Molecular dynamic simulations revealed cohesive structural integrity and stable attachment. Codon adaptation utilizing Escherichia coli K12 host yielded a vaccine with elevated Codon Adaptation Index (CAI) and optimal GC content. In silico cloning into the pET28+(a) vector demonstrated efficient expression. Immune simulations indicated the vaccine's ability to initiate immune responses in humans, mirroring real-life scenarios. Based on these comprehensive findings, we propose that our developed vaccine has the potential to confer robust immunity against H. pylori and F. nucleatum infections.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Tanjin Tamanna
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
- Bioinformatics and Microbial Biotechnology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md Shahedur Rahman
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
- Bioinformatics and Microbial Biotechnology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
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4
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Moin AT, Ullah MA, Patil RB, Faruqui NA, Araf Y, Das S, Uddin KMK, Hossain MS, Miah MF, Moni MA, Chowdhury DUS, Islam S. A computational approach to design a polyvalent vaccine against human respiratory syncytial virus. Sci Rep 2023; 13:9702. [PMID: 37322049 PMCID: PMC10272159 DOI: 10.1038/s41598-023-35309-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: 11/14/2022] [Accepted: 05/16/2023] [Indexed: 06/17/2023] Open
Abstract
Human Respiratory Syncytial Virus (RSV) is one of the leading causes of lower respiratory tract infections (LRTI), responsible for infecting people from all age groups-a majority of which comprises infants and children. Primarily, severe RSV infections are accountable for multitudes of deaths worldwide, predominantly of children, every year. Despite several efforts to develop a vaccine against RSV as a potential countermeasure, there has been no approved or licensed vaccine available yet, to control the RSV infection effectively. Therefore, through the utilization of immunoinformatics tools, a computational approach was taken in this study, to design a multi-epitope polyvalent vaccine against two major antigenic subtypes of RSV, RSV-A and RSV-B. Potential predictions of the T-cell and B-cell epitopes were followed by extensive tests of antigenicity, allergenicity, toxicity, conservancy, homology to human proteome, transmembrane topology, and cytokine-inducing ability. The peptide vaccine was modeled, refined, and validated. Molecular docking analysis with specific Toll-like receptors (TLRs) revealed excellent interactions with suitable global binding energies. Additionally, molecular dynamics (MD) simulation ensured the stability of the docking interactions between the vaccine and TLRs. Mechanistic approaches to imitate and predict the potential immune response generated by the administration of vaccines were determined through immune simulations. Subsequent mass production of the vaccine peptide was evaluated; however, there remains a necessity for further in vitro and in vivo experiments to validate its efficacy against RSV infections.
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Affiliation(s)
- Abu Tayab Moin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh.
| | - Md Asad Ullah
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Rajesh B Patil
- Department of Pharmaceutical Chemistry, Sinhgad Technical Education Society's, Sinhgad College of Pharmacy, Pune, Maharashtra, India
| | - Nairita Ahsan Faruqui
- Biotechnology Program, Department of Mathematics and Natural Sciences, School of Data and Sciences, BRAC University, Dhaka, Bangladesh
| | - Yusha Araf
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Sowmen Das
- Department of Computer Science and Engineering, School of Physical Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Khaza Md Kapil Uddin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | - Md Shakhawat Hossain
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | - Md Faruque Miah
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Mohammad Ali Moni
- Bone Biology Division, The Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- WHO Collaborating Centre on eHealth, UNSW Digital Health, School of Public Health and Community Medicine, Faculty of Medicine, UNSW Sydney, Sydney, Australia
- Artificial Intelligence and Data Science, Faculty of Health and Behavioural Sciences, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
| | - Dil Umme Salma Chowdhury
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh.
| | - Saiful Islam
- Bangladesh Council of Scientific and Industrial Research (BCSIR), Chattogram Laboratories, Chattogram, Bangladesh.
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5
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Moin AT, Singh G, Ahmed N, Saiara SA, Timofeev VI, Ahsan Faruqui N, Sharika Ahsan S, Tabassum A, Nebir SS, Andalib KMS, Araf Y, Ullah MA, Sarkar B, Islam NN, Zohora US. Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework. J Biomol Struct Dyn 2023; 41:833-855. [PMID: 36617426 DOI: 10.1080/07391102.2021.2014969] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Abu Tayab Moin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | - Gagandeep Singh
- Section of Microbiology, Central Ayurveda Research Institute, Jhansi, Uttar Pradesh, India.,Kusuma School of Biological Sciences, Indian Institute of Technology, Delhi, India
| | - Nafisa Ahmed
- Biotechnology Program, Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh
| | | | - Vladimir I Timofeev
- Shubnikov Institute of Crystallography of Federal Scientific Research Centre "Crystallography and Photonics" of Russian Academy of Sciences, Moscow, Russian Federation
| | - Nairita Ahsan Faruqui
- Biotechnology Program, Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh
| | | | - Afrida Tabassum
- Department of Genetic Engineering and Biotechnology, Jagannath University, Dhaka, Bangladesh
| | - Sadman Sakib Nebir
- Department of Microbiology and Immunology, Bangladesh University of Health Sciences, Dhaka, Bangladesh
| | | | - Yusha Araf
- Community of Biotechnology, Dhaka, Bangladesh.,Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Md Asad Ullah
- Community of Biotechnology, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Bishajit Sarkar
- Community of Biotechnology, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Nafisa Nawal Islam
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Umme Salma Zohora
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
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6
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Adiyaman R, McGuffin LJ. Using Local Protein Model Quality Estimates to Guide a Molecular Dynamics-Based Refinement Strategy. Methods Mol Biol 2023; 2627:119-140. [PMID: 36959445 DOI: 10.1007/978-1-0716-2974-1_7] [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: 03/25/2023]
Abstract
The refinement of predicted 3D models aims to bring them closer to the native structure by fixing errors including unusual bonds and torsion angles and irregular hydrogen bonding patterns. Refinement approaches based on molecular dynamics (MD) simulations using different types of restraints have performed well since CASP10. ReFOLD, developed by the McGuffin group, was one of the many MD-based refinement approaches, which were tested in CASP 12. When the performance of the ReFOLD method in CASP12 was evaluated, it was observed that ReFOLD suffered from the absence of a reliable guidance mechanism to reach consistent improvement for the quality of predicted 3D models, particularly in the case of template-based modelling (TBM) targets. Therefore, here we propose to utilize the local quality assessment score produced by ModFOLD6 to guide the MD-based refinement approach to further increase the accuracy of the predicted 3D models. The relative performance of the new local quality assessment guided MD-based refinement protocol and the original MD-based protocol ReFOLD are compared utilizing many different official scoring methods. By using the per-residue accuracy (or local quality) score to guide the refinement process, we are able to prevent the refined models from undesired structural deviations, thereby leading to more consistent improvements. This chapter will include a detailed analysis of the performance of the local quality assessment guided MD-based protocol versus that deployed in the original ReFOLD method.
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Affiliation(s)
- Recep Adiyaman
- School of Biological Sciences, University of Reading, Reading, UK
| | - Liam J McGuffin
- School of Biological Sciences, University of Reading, Reading, UK.
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7
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Sarkar B, Ullah MA, Araf Y, Islam NN, Zohora US. Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV). Expert Rev Vaccines 2022; 21:1851-1871. [PMID: 33435759 PMCID: PMC7989953 DOI: 10.1080/14760584.2021.1874925] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 01/08/2021] [Indexed: 01/12/2023]
Abstract
OBJECTIVES The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options. METHODS In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2. RESULTS The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine. CONCLUSION If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.
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Affiliation(s)
- Bishajit Sarkar
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Md. Asad Ullah
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Yusha Araf
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Nafisa Nawal Islam
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Umme Salma Zohora
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
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8
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Omoboyede V, Ibrahim O, Umar HI, Bello T, Adedeji AA, Khalid A, Fayojegbe ES, Ayomide AB, Chukwuemeka PO. Designing a vaccine-based therapy against Epstein-Barr virus-associated tumors using immunoinformatics approach. Comput Biol Med 2022; 150:106128. [PMID: 36179514 DOI: 10.1016/j.compbiomed.2022.106128] [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: 05/23/2022] [Revised: 08/05/2022] [Accepted: 09/18/2022] [Indexed: 11/26/2022]
Abstract
Epstein-Barr virus (EBV) is widely known due to its role in the etiology of infectious mononucleosis. However, it is the first oncovirus that was identified and has been implicated in the etiology of several types of cancers. Globally, EBV infection is associated with more than 200, 000 new cancer cases and 150, 000 deaths yearly. A prophylactic or therapeutic vaccine targeting tumors associated with EBV infection is currently lacking. Therefore, this study aimed to develop a multiepitope-based polyvalent vaccine against EBV-associated tumors using immunoinformatics approach. The latency-associated proteins (LAP) of three strains of the virus were used in this study. Potential epitopes predicted from the proteins were analyzed and selected based on several predicted properties. Thirty viable B-cell and T-cell epitopes were selected and conjugated using various linkers alongside beta-defensin 3 as an adjuvant and pan HLA DR-binding epitope (PADRE) sequence to improve the immunogenicity of the vaccine construct. Molecular docking studies of the vaccine construct against toll-like receptors (TLRs) showed it is capable of inducing immune response via recognition by TLRs while immune simulation studies showed it could induce both cellular and humoral immune responses. Furthermore, molecular dynamics study of the complex formed by the vaccine candidate and TLR-4 showed that the complex was stable. Ultimately, the designed vaccine showed desirable properties based on in silico evaluation; however, experimental studies are needed to validate the efficacy of the vaccine against EBV-associated tumors.
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Affiliation(s)
- Victor Omoboyede
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Computer Aided Therapeutics Laboratory (CATL) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Computer Aided Therapeutics and Drug Design (CATDD) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
| | - Ochapa Ibrahim
- Computer Aided Therapeutics and Drug Design (CATDD) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Faculty of Pharmaceutical Sciences, Ahmadu Bello University, Zaria, Kaduna State, Nigeria.
| | - Haruna Isiyaku Umar
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Computer Aided Therapeutics and Drug Design (CATDD) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
| | - Taye Bello
- Department of Medical Rehabilitation, College of Health Sciences, Obafemi Awolowo University, Nigeria.
| | - Ayodeji Adeola Adedeji
- Department of Biochemistry, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
| | - Aqsa Khalid
- Research Center for Modelling and Simulation (RCMS), National University of Science and Technology (NUST), Islamabad, Pakistan.
| | | | - Adunola Blessing Ayomide
- Computer Aided Therapeutics Laboratory (CATL) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
| | - Prosper Obed Chukwuemeka
- Computer Aided Therapeutics Laboratory (CATL) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Computer Aided Therapeutics and Drug Design (CATDD) Group, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria; Department of Biotechnology, School of Sciences (SOS), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
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9
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Abstract
Epstein-Barr virus (EBV) is a lymphotropic virus responsible for numerous epithelial and lymphoid cell malignancies, including gastric carcinoma, Hodgkin's lymphoma, nasopharyngeal carcinoma, and Burkitt lymphoma. Hundreds of thousands of people worldwide get infected with this virus, and in most cases, this viral infection leads to cancer. Although researchers are trying to develop potential vaccines and drug therapeutics, there is still no effective vaccine to combat this virus. In this study, the immunoinformatics approach was utilized to develop a potential multiepitope subunit vaccine against the two most common subtypes of EBV, targeting three of their virulent envelope glycoproteins. Eleven cytotoxic T lymphocyte (CTL) epitopes, 11 helper T lymphocyte (HTL) epitopes, and 10 B-cell lymphocyte (BCL) epitopes were predicted to be antigenic, nonallergenic, nontoxic, and fully conserved among the two subtypes, and nonhuman homologs were used for constructing the vaccine after much analysis. Later, further validation experiments, including molecular docking with different immune receptors (e.g., Toll-like receptors [TLRs]), molecular dynamics simulation analyses (including root means square deviation [RMSD], root mean square fluctuation [RMSF], radius of gyration [Rg], principal-component analysis [PCA], dynamic cross-correlation [DCC], definition of the secondary structure of proteins [DSSP], and Molecular Mechanics Poisson-Boltzmann Surface Area [MM-PBSA]), and immune simulation analyses generated promising results, ensuring the safe and stable response of the vaccine with specific immune receptors after potential administration within the human body. The vaccine's high binding affinity with TLRs was revealed in the docking study, and a very stable interaction throughout the simulation proved the potential high efficacy of the proposed vaccine. Further, in silico cloning was also conducted to design an efficient mass production strategy for future bulk industrial vaccine production. IMPORTANCE Epstein-Barr virus (EBV) vaccines have been developing for over 30 years, but polyphyletic and therapeutic vaccines have failed to get licensed. Our vaccine surpasses the limitations of many such vaccines and remains very promising, which is crucial because the infection rate is higher than most viral infections, affecting a whopping 90% of the adult population. One of the major identifications covers a holistic analysis of populations worldwide, giving us crucial information about its effectiveness for everyone's unique immunological system. We targeted three glycoproteins that enhance the virulence of the virus to design an epitope-based polyvalent vaccine against two different strains of EBV, type 1 and 2. Our methodology in this study is nonconventional yet swift to show effective results while designing vaccines.
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10
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Islam SI, Sanjida S, Ahmed SS, Almehmadi M, Allahyani M, Aljuaid A, Alsaiari AA, Halawi M. Core Proteomics and Immunoinformatic Approaches to Design a Multiepitope Reverse Vaccine Candidate against Chagas Disease. Vaccines (Basel) 2022; 10:vaccines10101669. [PMID: 36298534 PMCID: PMC9607777 DOI: 10.3390/vaccines10101669] [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: 09/06/2022] [Revised: 09/23/2022] [Accepted: 10/02/2022] [Indexed: 11/05/2022] Open
Abstract
Chagas disease is a tropical ailment indigenous to South America and caused by the protozoan parasite Trypanosoma cruzi, which has serious health consequences globally. Insect vectors transmit the parasite and, due to the lack of vaccine availability and limited treatment options, we implemented an integrated core proteomics analysis to design a reverse vaccine candidate based on immune epitopes for disease control. Firstly, T. cruzi core proteomics was used to identify immunodominant epitopes. Therefore, we designed the vaccine sequence to be non-allergic, antigenic, immunogenic, and to have better solubility. After predicting the tertiary structure, docking and molecular dynamics simulation (MDS) were performed with TLR4, MHC-I, and MHC-II receptors to discover the binding affinities. The final vaccine design demonstrated significant hydrogen bond interactions upon docking with TLR4, MHC-I, and MHC-II receptors. This indicated the efficacy of the vaccine candidate. A server-based immune simulation approach was generated to predict the efficacy. Significant structural compactness and binding stability were found based on MDS. Finally, by optimizing codons on Escherichia coli K12, a high GC content and CAI value were obtained, which were then incorporated into the cloning vector pET2+ (a). Thus, the developed vaccine sequence may be a viable therapy option for Chagas disease.
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Affiliation(s)
- Sk Injamamul Islam
- The International Graduate Program of Veterinary Science and Technology (VST), Department of Veterinary Microbiology, Faculty of Veterinary Science and Technology, Chulalongkorn University, Bangkok 10330, Thailand
- Correspondence: or
| | - Saloa Sanjida
- Department of Environmental Science and Technology, Faculty of Applied Science and Technology, Jashore University of Science and Technology, Jashore 7408, Bangladesh
| | - Sheikh Sunzid Ahmed
- Department of Botany, Faculty of Biological Sciences, University of Dhaka, Dhaka 1000, Bangladesh
| | - Mazen Almehmadi
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif 21944, Saudi Arabia
| | - Mamdouh Allahyani
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif 21944, Saudi Arabia
| | - Abdulelah Aljuaid
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif 21944, Saudi Arabia
| | - Ahad Amer Alsaiari
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif 21944, Saudi Arabia
| | - Mustafa Halawi
- Department of Medical Laboratory Technology, College of Applied Medical Sciences, Jazan University, Jazan 54943, Saudi Arabia
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11
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Islam SI, Mou MJ, Sanjida S. Application of reverse vaccinology to design a multi-epitope subunit vaccine against a new strain of Aeromonas veronii. J Genet Eng Biotechnol 2022; 20:118. [PMID: 35939149 PMCID: PMC9358925 DOI: 10.1186/s43141-022-00391-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/04/2022] [Indexed: 11/18/2022]
Abstract
Background Aeromonas veronii is one of the most common pathogens of freshwater fishes that cause sepsis and ulcers. There are increasing numbers of cases showing that it is a significant zoonotic and aquatic agent. Epidemiological studies have shown that A. veronii virulence and drug tolerance have both increased over the last few years as a result of epidemiological investigations. Cadaverine reverse transporter (CadB) and maltoporin (LamB protein) contribute to the virulence of A. veronii TH0426. TH0426 strain is currently showing severe cases on fish species, and its resistance against therapeutic has been increasing. Despite these devastating complications, there is still no effective cure or vaccine for this strain of A.veronii. Results In this regard, an immunoinformatic method was used to generate an epitope-based vaccine against this pathogen. The immunodominant epitopes were identified using the CadB and LamB protein of A. veronii. The final constructed vaccine sequence was developed to be immunogenic, non-allergenic as well as have better solubility. Molecular dynamic simulation revealed significant binding stability and structural compactness. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher CAI value, which was then included in the cloning vector pET2+ (a). Conclusion Altogether, our outcomes imply that the proposed peptide vaccine might be a good option for A. veronii TH0426 prophylaxis.
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Affiliation(s)
- Sk Injamamul Islam
- Department of Fisheries and Marine Bioscience, Faculty of Biological Science, Jashore University of Science and Technology, Jashore, 7408, Bangladesh. .,Center of Excellence in Fish Infectious Diseases (CE FID), Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand. .,The International Graduate Program of Veterinary Science and Technology (VST), Department of Veterinary Microbiology, Faculty of Veterinary Science and Technology, Chulalongkorn University, Bangkok, 10330, Thailand.
| | - Moslema Jahan Mou
- Department of Genetic Engineering and Biotechnology, Faculty of Life and Earth Science, University of Rajshahi, Rajshahi, Bangladesh
| | - Saloa Sanjida
- Department of Environmental Science and Technology, Faculty of Applied Science and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh
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12
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Araf Y, Moin AT, Timofeev VI, Faruqui NA, Saiara SA, Ahmed N, Parvez MSA, Rahaman TI, Sarkar B, Ullah MA, Hosen MJ, Zheng C. Immunoinformatic Design of a Multivalent Peptide Vaccine Against Mucormycosis: Targeting FTR1 Protein of Major Causative Fungi. Front Immunol 2022; 13:863234. [PMID: 35720422 PMCID: PMC9204303 DOI: 10.3389/fimmu.2022.863234] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 04/12/2022] [Indexed: 12/14/2022] Open
Abstract
Mucormycosis is a potentially fatal illness that arises in immunocompromised people due to diabetic ketoacidosis, neutropenia, organ transplantation, and elevated serum levels of accessible iron. The sudden spread of mucormycosis in COVID-19 patients engendered massive concern worldwide. Comorbidities including diabetes, cancer, steroid-based medications, long-term ventilation, and increased ferritin serum concentration in COVID-19 patients trigger favorable fungi growth that in turn effectuate mucormycosis. The necessity of FTR1 gene-encoded ferrous permease for host iron acquisition by fungi has been found in different studies recently. Thus, targeting the transit component could be a potential solution. Unfortunately, no appropriate antifungal vaccine has been constructed as of yet. To date, mucormycosis has been treated with antiviral therapy and surgical treatment only. Thus, in this study, the FTR1 protein has been targeted to design a convenient and novel epitope-based vaccine with the help of immunoinformatics against four different virulent fungal species. Furthermore, the vaccine was constructed using 8 CTL, 2 HTL, and 1 LBL epitopes that were found to be highly antigenic, non-allergenic, non-toxic, and fully conserved among the fungi under consideration. The vaccine has very reassuring stability due to its high pI value of 9.97, conclusive of a basic range. The vaccine was then subjected to molecular docking, molecular dynamics, and immune simulation studies to confirm the biological environment’s safety, efficacy, and stability. The vaccine constructs were found to be safe in addition to being effective. Finally, we used in-silico cloning to develop an effective strategy for vaccine mass production. The designed vaccine will be a potential therapeutic not only to control mucormycosis in COVID-19 patients but also be effective in general mucormycosis events. However, further in vitro, and in vivo testing is needed to confirm the vaccine’s safety and efficacy in controlling fungal infections. If successful, this vaccine could provide a low-cost and effective method of preventing the spread of mucormycosis worldwide.
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Affiliation(s)
- Yusha Araf
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh.,Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.,Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh
| | - Abu Tayab Moin
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | - Vladimir I Timofeev
- Shubnikov Institute of Crystallography, Federal Scientific Research Centre, Crystallography and Photonics, Russian Academy of Sciences, Moscow, Russia
| | - Nairita Ahsan Faruqui
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Biotechnology Program, Department of Mathematics and Natural Sciences, School of Data and Sciences, Brac University, Dhaka, Bangladesh
| | - Syeda Afra Saiara
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh
| | - Nafisa Ahmed
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Biotechnology Program, Department of Mathematics and Natural Sciences, School of Data and Sciences, Brac University, Dhaka, Bangladesh
| | - Md Sorwer Alam Parvez
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh.,Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Tanjim Ishraq Rahaman
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Faculty of Life Sciences, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Bishajit Sarkar
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Md Asad Ullah
- Department of Research and Development, Community of Biotechnology, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Mohammad Jakir Hosen
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Chunfu Zheng
- Department of Immunology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.,Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, AB, Canada
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13
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Use of Integrated Core Proteomics, Immuno-Informatics, and In Silico Approaches to Design a Multiepitope Vaccine against Zoonotic Pathogen Edwardsiella tarda. Appl Microbiol 2022. [DOI: 10.3390/applmicrobiol2020031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Multidrug-resistant Edwardsiella tarda has been reported as the main causative agent for massive fish mortality. The pathogen is well-known for causing hemorrhagic septicemia in fish and has been linked to gastrointestinal infections in humans. Formalin-inactivated Edwardsiella vaccination has previously been found to be ineffective in aquaculture species. Therefore, based on E. tarda’s integrated core complete sequenced genomes, the study aimed to design a subunit vaccine based on T and B cell epitopes employing immunoinformatics approach. Initially, the top immunodominant and antigenic epitopes were predicted from the core complete sequenced genomes of the E. tarda genome and designed the vaccine by using linkers and adjuvant. In addition, vaccine 3D structure was predicted followed by refinement, and molecular docking was performed for the analysis of interacting residues between vaccines with TLR5, MHC-I, and MHC-II, respectively. The final vaccine constructs demonstrated strong hydrogen bond interactions. Molecular dynamic simulation of vaccine-TLR5 receptor complex showed a stable structural binding and compactness. Furthermore, E. coli used as a model organism for codon optimization proved optimal GC content and CAI value, which were subsequently cloned in vector pET2+ (a). Overall, the findings of the study imply that the designed epitope vaccine might be a good option for prophylaxis for E. tarda.
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14
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Islam SI, Mou MJ, Sanjida S, Tariq M, Nasir S, Mahfuj S. Designing a novel mRNA vaccine against Vibrio harveyi infection in fish: an immunoinformatics approach. Genomics Inform 2022; 20:e11. [PMID: 35399010 PMCID: PMC9002004 DOI: 10.5808/gi.21065] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 01/07/2022] [Indexed: 11/20/2022] Open
Abstract
Vibrio harveyi belongs to the family Vibrionaceae of class Gammaproteobacteria. Around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness) in humans. A large number of bacterial particles can be found in the infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the bacteria. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against the most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as have a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computers revealed that the vaccination might elicit immune reactions Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.
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Affiliation(s)
- Sk Injamamul Islam
- Department of Fisheries and Marine Bioscience, Faculty of Biological Science, Jashore University of Science and Technology, Jashore 7408, Bangladesh.,Chulalongkorn University, Department of Veterinary Microbiology, Faculty of Veterinary Science and Technology, Bangkok 10330, Thailand
| | - Moslema Jahan Mou
- Department of Genetic Engineering & Biotechnology, Faculty of Earth and Life Science, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Saloa Sanjida
- Department of Environmental Science and Technology, Faculty of Applied Science and Technology, Jashore University of Science and Technology, Jashore 7408, Bangladesh
| | - Muhammad Tariq
- Department of Biotechnology, Faculty of Biological Sciences, University of Malakand, Chakdara 18800, Pakistan
| | - Saad Nasir
- Department of Clinical Medicine and Surgery, Faculty of Veterinary Medicine, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan
| | - Sarower Mahfuj
- Department of Fisheries and Marine Bioscience, Faculty of Biological Science, Jashore University of Science and Technology, Jashore 7408, Bangladesh
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15
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Holland J, Grigoryan G. Structure‐conditioned amino‐acid couplings: how contact geometry affects pairwise sequence preferences. Protein Sci 2022; 31:900-917. [PMID: 35060221 PMCID: PMC8927866 DOI: 10.1002/pro.4280] [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: 11/04/2021] [Revised: 01/06/2022] [Accepted: 01/12/2022] [Indexed: 11/11/2022]
Abstract
Relating a protein's sequence to its conformation is a central challenge for both structure prediction and sequence design. Statistical contact potentials, as well as their more descriptive versions that account for side‐chain orientation and other geometric descriptors, have served as simplistic but useful means of representing second‐order contributions in sequence–structure relationships. Here we ask what happens when a pairwise potential is conditioned on the fully defined geometry of interacting backbones fragments. We show that the resulting structure‐conditioned coupling energies more accurately reflect pair preferences as a function of structural contexts. These structure‐conditioned energies more reliably encode native sequence information and more highly correlate with experimentally determined coupling energies. Clustering a database of interaction motifs by structure results in ensembles of similar energies and clustering them by energy results in ensembles of similar structures. By comparing many pairs of interaction motifs and showing that structural similarity and energetic similarity go hand‐in‐hand, we provide a tangible link between modular sequence and structure elements. This link is applicable to structural modeling, and we show that scoring CASP models with structured‐conditioned energies results in substantially higher correlation with structural quality than scoring the same models with a contact potential. We conclude that structure‐conditioned coupling energies are a good way to model the impact of interaction geometry on second‐order sequence preferences.
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Affiliation(s)
- Jack Holland
- Department of Computer Science Dartmouth College Hanover New Hampshire USA
| | - Gevorg Grigoryan
- Department of Computer Science Dartmouth College Hanover New Hampshire USA
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16
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Application of reverse vaccinology for designing of an mRNA vaccine against re-emerging marine birnavirus affecting fish species. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100948] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
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17
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Heo L, Janson G, Feig M. Physics-based protein structure refinement in the era of artificial intelligence. Proteins 2021; 89:1870-1887. [PMID: 34156124 PMCID: PMC8616793 DOI: 10.1002/prot.26161] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 05/31/2021] [Accepted: 06/08/2021] [Indexed: 12/21/2022]
Abstract
Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement protocol based on an improved sampling strategy via MD simulations. MD simulations were carried out at an elevated temperature (360 K). An optimized use of biasing restraints and the use of multiple starting models led to enhanced sampling. The new protocol generally improved the model quality. In comparison with our previous protocols, the CASP14 protocol showed clear improvements. Our approach was successful with most initial models, many based on deep learning methods. However, we found that our approach was not able to refine machine-learning models from the AlphaFold2 group, often decreasing already high initial qualities. To better understand the role of refinement given new types of models based on machine-learning, a detailed analysis via MD simulations and Markov state modeling is presented here. We continue to find that MD-based refinement has the potential to improve AI predictions. We also identified several practical issues that make it difficult to realize that potential. Increasingly important is the consideration of inter-domain and oligomeric contacts in simulations; the presence of large kinetic barriers in refinement pathways also continues to present challenges. Finally, we provide a perspective on how physics-based refinement could continue to play a role in the future for improving initial predictions based on machine learning-based methods.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Giacomo Janson
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
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18
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Millán C, Keegan RM, Pereira J, Sammito MD, Simpkin AJ, McCoy AJ, Lupas AN, Hartmann MD, Rigden DJ, Read RJ. Assessing the utility of CASP14 models for molecular replacement. Proteins 2021; 89:1752-1769. [PMID: 34387010 PMCID: PMC8881082 DOI: 10.1002/prot.26214] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/20/2021] [Accepted: 07/27/2021] [Indexed: 11/21/2022]
Abstract
The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real‐world application. In CASP7, the metric for molecular replacement assessment involved full likelihood‐based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood‐based rigid‐body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log‐likelihood‐gain (LLG) score. This enabled multi‐copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative‐expected‐LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X‐ray, NMR or cryo‐EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.
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Affiliation(s)
- Claudia Millán
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, United Kingdom
| | - Ronan M Keegan
- Scientific Computing Dept., Science and Technologies Facilities Council, UK Research and Innovation, Didcot, Oxfordshire, United Kingdom
| | - Joana Pereira
- Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, Tübingen, Germany
| | - Massimo D Sammito
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, United Kingdom
| | - Adam J Simpkin
- Institute of Systems, Molecular and Integrative Biology, Biosciences Building, Crown Street, Liverpool L69 7BE, United Kingdom
| | - Airlie J McCoy
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, United Kingdom
| | - Andrei N Lupas
- Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, Tübingen, Germany
| | - Marcus D Hartmann
- Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, Tübingen, Germany
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, Biosciences Building, Crown Street, Liverpool L69 7BE, United Kingdom
| | - Randy J Read
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, United Kingdom
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19
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Foroutan B, Abbasian Najafabadi AR. Capabilities of bioinformatics tools for optimizing physicochemical features of proteins used in Nano biosensors: A short overview of the tools related to bioinformatics. Biochem Biophys Rep 2021; 27:101094. [PMID: 34401530 PMCID: PMC8350186 DOI: 10.1016/j.bbrep.2021.101094] [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: 06/13/2021] [Revised: 07/29/2021] [Accepted: 07/30/2021] [Indexed: 12/27/2022] Open
Abstract
Protein-protein ligand is one of the most detection methods used in Nano biosensors. Based on the advantage of specific docking between two special 3D structures, they have become a potent candidate in bioanalysis and Nanodiagnostic tools. These tools lease users to do a simple, fast, cost-effective, sensitive, and specific detection of molecular biomarkers in real samples. Recent advantages of using protein-protein ligand Nano-biosensors application is remarkable due to its special docking that refers to each protein unique 3D conformation. However, it challenges different problems such as low rate of docking and hard process for fixation on the basic layer. These challenges make developers to optimize the structure and functions of proteins. The process has different Nano scale calculation that could be done with algorithms and solutions are available as bioinformatics tools. This article aimed to have a short overview of the abilities of bioinformatics tools for modeling and optimization of physiochemical features of proteins in Nano scale. Nano biosensors use different strategies which based on docking between two molecules to detect and identify different proteins. Molecular docking between transducer in Nano biosensors and proteins rely on physicochemical features of transducer, protein and docking strategy. Nano bioinformatics use bioinformatics tools and algorithms as a collective solution for developing functional structure in Nano scale. Nano bioinformatics use different bioinformatics tools to optimize physicochemical features of proteins as a new approach in Nano biosensors and drug discovery.
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Affiliation(s)
- Behzad Foroutan
- Tropical and Communicable Diseases Research Center, Iranshahr University of Medical Sciences, Iranshahr, Iran
- Department of Pharmacology, School of Medicine, Iranshahr University of Medical Sciences, Iranshahr, Iran
- Corresponding author. Tropical and Communicable Diseases Research Center, Iranshahr University of Medical Sciences, Iranshahr, Iran.
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20
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Shuvo MH, Gulfam M, Bhattacharya D. DeepRefiner: high-accuracy protein structure refinement by deep network calibration. Nucleic Acids Res 2021; 49:W147-W152. [PMID: 33999209 PMCID: PMC8262753 DOI: 10.1093/nar/gkab361] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/18/2021] [Accepted: 04/23/2021] [Indexed: 12/20/2022] Open
Abstract
The DeepRefiner webserver, freely available at http://watson.cse.eng.auburn.edu/DeepRefiner/, is an interactive and fully configurable online system for high-accuracy protein structure refinement. Fuelled by deep learning, DeepRefiner offers the ability to leverage cutting-edge deep neural network architectures which can be calibrated for on-demand selection of adventurous or conservative refinement modes targeted at degree or consistency of refinement. The method has been extensively tested in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiments under the group name 'Bhattacharya-Server' and was officially ranked as the No. 2 refinement server in CASP13 (second only to 'Seok-server' and outperforming all other refinement servers) and No. 2 refinement server in CASP14 (second only to 'FEIG-S' and outperforming all other refinement servers including 'Seok-server'). The DeepRefiner web interface offers a number of convenient features, including (i) fully customizable refinement job submission and validation; (ii) automated job status update, tracking, and notifications; (ii) interactive and interpretable web-based results retrieval with quantitative and visual analysis and (iv) extensive help information on job submission and results interpretation via web-based tutorial and help tooltips.
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Affiliation(s)
- Md Hossain Shuvo
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL 36849, USA
| | - Muhammad Gulfam
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL 36849, USA
| | - Debswapna Bhattacharya
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL 36849, USA
- Department of Biological Sciences, Auburn University, Auburn, AL 36849, USA
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21
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Obaidullah AJ, Alanazi MM, Alsaif NA, Albassam H, Almehizia AA, Alqahtani AM, Mahmud S, Sami SA, Emran TB. Immunoinformatics-guided design of a multi-epitope vaccine based on the structural proteins of severe acute respiratory syndrome coronavirus 2. RSC Adv 2021; 11:18103-18121. [PMID: 35480208 PMCID: PMC9033181 DOI: 10.1039/d1ra02885e] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 05/12/2021] [Indexed: 12/14/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in a contagious respiratory tract infection that has become a global burden since the end of 2019. Notably, fewer patients infected with SARS-CoV-2 progress from acute disease onset to death compared with the progression rate associated with two other coronaviruses, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Several research organizations and pharmaceutical industries have attempted to develop successful vaccine candidates for the prevention of COVID-19. However, increasing evidence indicates that the SARS-CoV-2 genome undergoes frequent mutation; thus, an adequate analysis of the viral strain remains necessary to construct effective vaccines. The current study attempted to design a multi-epitope vaccine by utilizing an approach based on the SARS-CoV-2 structural proteins. We predicted the antigenic T- and B-lymphocyte responses to four structural proteins after screening all structural proteins according to specific characteristics. The predicted epitopes were combined using suitable adjuvants and linkers, and a secondary structure profile indicated that the vaccine shared similar properties with the native protein. Importantly, the molecular docking analysis and molecular dynamics simulations revealed that the constructed vaccine possessed a high affinity for toll-like receptor 4 (TLR4). In addition, multiple descriptors were obtained from the simulation trajectories, including the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (R g), demonstrating the rigid nature and inflexibility of the vaccine and receptor molecules. In addition, codon optimization, based on Escherichia coli K12, was used to determine the GC content and the codon adaptation index (CAI) value, which further followed for the incorporation into the cloning vector pET28+(a). Collectively, these findings suggested that the constructed vaccine could be used to modulate the immune reaction against SARS-CoV-2.
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Affiliation(s)
- Ahmad J Obaidullah
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University P.O. Box 2457 Riyadh 11451 Saudi Arabia
| | - Mohammed M Alanazi
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University P.O. Box 2457 Riyadh 11451 Saudi Arabia
| | - Nawaf A Alsaif
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University P.O. Box 2457 Riyadh 11451 Saudi Arabia
| | - Hussam Albassam
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University P.O. Box 2457 Riyadh 11451 Saudi Arabia
| | - Abdulrahman A Almehizia
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University P.O. Box 2457 Riyadh 11451 Saudi Arabia
| | - Ali M Alqahtani
- Department of Pharmacology, College of Pharmacy, King Khalid University Abha 62529 Saudi Arabia
| | - Shafi Mahmud
- Microbiology Laboratory, Bioinformatics Division, Department of Genetic Engineering and Biotechnology, University of Rajshahi Rajshahi 6205 Bangladesh
| | - Saad Ahmed Sami
- Department of Pharmacy, Faculty of Biological Sciences, University of Chittagong Chittagong 4331 Bangladesh
| | - Talha Bin Emran
- Department of Pharmacy, BGC Trust University Bangladesh Chittagong 4381 Bangladesh
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22
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Cao X, Tian P. Molecular free energy optimization on a computational graph. RSC Adv 2021; 11:12929-12937. [PMID: 35423805 PMCID: PMC8697515 DOI: 10.1039/d1ra01455b] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 03/26/2021] [Indexed: 11/21/2022] Open
Abstract
Free energy is arguably the most important property of molecular systems. Despite great progress in both its efficient estimation by scoring functions/potentials and more rigorous computation based on extensive sampling, we remain far from accurately predicting and manipulating biomolecular structures and their interactions. There are fundamental limitations, including accuracy of interaction description and difficulty of sampling in high dimensional space, to be tackled. Computational graph underlies major artificial intelligence platforms and is proven to facilitate training, optimization and learning. Combining autodifferentiation, coordinates transformation and generalized solvation free energy theory, we construct a computational graph infrastructure to realize seamless integration of fully trainable local free energy landscape with end to end differentiable iterative free energy optimization. This new framework drastically improves efficiency by replacing local sampling with differentiation. Its specific implementation in protein structure refinement achieves superb efficiency and competitive accuracy when compared with state of the art all-atom mainstream methods.
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Affiliation(s)
- Xiaoyong Cao
- School of Life Sciences, Jilin University Changchun 130012 China +86 431 85155287
| | - Pu Tian
- School of Life Sciences, Jilin University Changchun 130012 China +86 431 85155287
- School of Artificial Intelligence, Jilin University Changchun 130012 China
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23
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Heo L, Arbour CF, Janson G, Feig M. Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation. J Chem Theory Comput 2021; 17:1931-1943. [PMID: 33562962 DOI: 10.1021/acs.jctc.0c01238] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. These methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore the conformational space more broadly. Based on the insights of this analysis, we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Collin F Arbour
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Giacomo Janson
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
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24
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Alom MW, Shehab MN, Sujon KM, Akter F. Exploring E, NS3, and NS5 proteins to design a novel multi-epitope vaccine candidate against West Nile Virus: An in-silico approach. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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25
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Islam E. Development of chemokine CXCL12-dependent immunotoxin against small cell lung cancer using in silico approaches. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100676] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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26
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Sarkar B, Ullah MA, Araf Y, Rahman MS. Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach. INFORMATICS IN MEDICINE UNLOCKED 2020; 21:100478. [PMID: 33200088 PMCID: PMC7656168 DOI: 10.1016/j.imu.2020.100478] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 10/30/2020] [Accepted: 11/05/2020] [Indexed: 02/08/2023] Open
Abstract
As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible countermeasures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for developing potential vaccines; however, most of them are proved to possess negative consequences. Therefore, in this study, immunoinformatics methods were exploited to design a novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog, and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vitro and in vivo studies are required on the predicted vaccine to finally validate its safety and efficacy.
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Affiliation(s)
- Bishajit Sarkar
- COVID Research Cell (CRC), Wazed Miah Science Research Centre (WMSRC), Jahangirnagar University, Savar, Dhaka, Bangladesh
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Md Asad Ullah
- COVID Research Cell (CRC), Wazed Miah Science Research Centre (WMSRC), Jahangirnagar University, Savar, Dhaka, Bangladesh
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Yusha Araf
- COVID Research Cell (CRC), Wazed Miah Science Research Centre (WMSRC), Jahangirnagar University, Savar, Dhaka, Bangladesh
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Mohammad Shahedur Rahman
- COVID Research Cell (CRC), Wazed Miah Science Research Centre (WMSRC), Jahangirnagar University, Savar, Dhaka, Bangladesh
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Savar, Dhaka, Bangladesh
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Toxoplasma gondii ROP38 protein: Bioinformatics analysis for vaccine design improvement against toxoplasmosis. Microb Pathog 2020; 149:104488. [PMID: 32916240 DOI: 10.1016/j.micpath.2020.104488] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 08/29/2020] [Accepted: 09/03/2020] [Indexed: 12/11/2022]
Abstract
Rhoptry proteins (ROPs) play a significant role in various stages of Toxoplasma gondii (T. gondii) life cycle, being critical for both invasion and intracellular survival. ROP38 is a key manipulator of host gene expression and has a function in tachyzoite to bradyzoite conversion. In this study, we've employed various bioinformatics online tools for immunogenicity prediction of ROP38 protein, comprising physico-chemical, antigenic and allergenic profiles, transmembrane domain, subcellular localization, post-translational modification (PTM) sites, secondary and 3D structure, B-cell, MHC-binding and cytotoxic T-lymphocyte (CTL) epitopes. The findings showed 54 PTM sites without a transmembrane domain. Also, ROP38 was proved a non-allergenic and antigenic protein. The protein had Sec signal peptide (Sec/SPI) with 0.8762 likelihood. The secondary structure included 52.68% random coil, 29.57% alpha helix and 17.74% extended strand. Based on Ramachandran plot output for refined model, 95.3%, 3.4%, and 1.4% of amino acid residues were incorporated in the favored, allowed, and outlier regions, respectively. B-cell epitopes TFPGDDIQTSS (67-72) and KAKNKWGRTRYTLQG (207-221) as well as T-cell epitope LSPVGFFTAL (6-15) possessed the highest antigenic index in the protein sequence. This paper is a premise for further researches, and provides insights for the development of a suitable vaccine against toxoplasmosis. More empirical studies are required using the ROP38 alone or in combination with other antigens/epitopes in the future.
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Sarkar B, Ullah MA, Araf Y, Das S, Rahman MH, Moin AT. Designing novel epitope-based polyvalent vaccines against herpes simplex virus-1 and 2 exploiting the immunoinformatics approach. J Biomol Struct Dyn 2020; 39:6585-6605. [DOI: 10.1080/07391102.2020.1803969] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Bishajit Sarkar
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Md. Asad Ullah
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Yusha Araf
- Department of Genetic Engineering and Biotechnology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Sowmen Das
- Department of Computer Science and Engineering, School of Physical Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh
| | - Md. Hasanur Rahman
- Department of Biotechnology and Genetic Engineering, Faculty of Life Sciences, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Abu Tayab Moin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
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29
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Majidiani H, Soltani S, Ghaffari AD, Sabaghan M, Taghipour A, Foroutan M. In-depth computational analysis of calcium-dependent protein kinase 3 of Toxoplasma gondii provides promising targets for vaccination. Clin Exp Vaccine Res 2020; 9:146-158. [PMID: 32864371 PMCID: PMC7445322 DOI: 10.7774/cevr.2020.9.2.146] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 06/23/2020] [Accepted: 07/28/2020] [Indexed: 01/26/2023] Open
Abstract
Purpose The Toxoplasma gondii calcium-dependent protein kinase-3 (CDPK3) is a key enzyme for parasite egress, control of calcium-dependent permeabilization in parasitophorous vacuole membrane and tissue cyst formation. In this study, we comprehensively explored the bioinformatics features of this protein to improve vaccine design against T. gondii. Materials and Methods Various web servers were employed for the analysis of physico-chemical properties, post-translational modifications, localization in the subcellular milieu, secondary and tertiary structures, as well as B-cell, major histocompatibility complex (MHC)-binding and cytotoxic T-lymphocyte (CTL) epitopes. Results This protein was a 537 amino acid antigenic and non-allergenic molecule with a molecular weight of 60.42 kDa, a grand average of hydropathicity score of −0.508, and aliphatic index of 79.50. There exists 46.74% alpha helix, 12.48% extended strand, and 40.78% random coil in the secondary structure. Ramachandran plot of the refined model demonstrated 99.3%, 0.7%, and 0.0% of residues in the favored, allowed and outlier areas, respectively. Besides, various potential B-cell (continuous and conformational), MHC-binding and CTL epitopes were predicted for Toxoplasma CDPK3 protein. Conclusion This article provides a foundation for further investigations, and laid a theoretical basis for the development of an appropriate vaccine against T. gondii infection.
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Affiliation(s)
- Hamidreza Majidiani
- Zoonotic Diseases Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | | | - Ali Dalir Ghaffari
- Department of Parasitology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | | | - Ali Taghipour
- Department of Parasitology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
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30
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Samad A, Ahammad F, Nain Z, Alam R, Imon RR, Hasan M, Rahman MS. Designing a multi-epitope vaccine against SARS-CoV-2: an immunoinformatics approach. J Biomol Struct Dyn 2020; 40:14-30. [PMID: 32677533 PMCID: PMC7441805 DOI: 10.1080/07391102.2020.1792347] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Ongoing COVID-19 outbreak has raised a drastic challenge to global public health
security. Most of the patients with COVID-19 suffer from mild flu-like illnesses such as
cold and fever; however, few percentages of the patients progress from severe illness to
death, mostly in an immunocompromised individual. The causative agent of COVID-19 is an
RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite
these debilitating conditions, no medication to stop the disease progression or
vaccination is available till now. Therefore, we aimed to formulate a multi-epitope
vaccine against SARS-CoV-2 by utilizing an immunoinformatics approach. For this purpose,
we used the SARS-CoV-2 spike glycoprotein to determine the immunodominant T- and B-cell
epitopes. After rigorous assessment, we designed a vaccine construct using four potential
epitopes from each of the three epitope classes such as cytotoxic T-lymphocytes, helper
T-lymphocyte, and linear B-lymphocyte epitopes. The designed vaccine was antigenic,
immunogenic, and non-allergenic with suitable physicochemical properties and has higher
solubility. More importantly, the predicted vaccine structure was similar to the native
protein. Further investigations indicated a strong and stable binding interaction between
the vaccine and the toll-like receptor (TLR4). Strong binding stability and structural
compactness were also evident in molecular dynamics simulation. Furthermore, the
computer-generated immune simulation showed that the vaccine could trigger real-life-like
immune responses upon administration into humans. Finally, codon optimization based on
Escherichia coli K12 resulted in optimal GC content and
higher CAI value followed by incorporating it into the cloning vector pET28+(a). Overall,
these results suggest that the designed peptide vaccine can serve as an excellent
prophylactic candidate against SARS-CoV-2. Communicated by Ramaswamy H. Sarma
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Affiliation(s)
- Abdus Samad
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Foysal Ahammad
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh.,Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Zulkar Nain
- Department of Genetic Engineering and Biotechnology, East West University, Dhaka, Bangladesh.,Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh
| | - Rahat Alam
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Raihan Rahman Imon
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Mahadi Hasan
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md Shahedur Rahman
- Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh
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31
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Bhattacharya D. refineD: improved protein structure refinement using machine learning based restrained relaxation. Bioinformatics 2020; 35:3320-3328. [PMID: 30759180 DOI: 10.1093/bioinformatics/btz101] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 01/22/2019] [Accepted: 02/11/2019] [Indexed: 12/20/2022] Open
Abstract
MOTIVATION Protein structure refinement aims to bring moderately accurate template-based protein models closer to the native state through conformational sampling. However, guiding the sampling towards the native state by effectively using restraints remains a major issue in structure refinement. RESULTS Here, we develop a machine learning based restrained relaxation protocol that uses deep discriminative learning based binary classifiers to predict multi-resolution probabilistic restraints from the starting structure and subsequently converts these restraints to be integrated into Rosetta all-atom energy function as additional scoring terms during structure refinement. We use four restraint resolutions as adopted in GDT-HA (0.5, 1, 2 and 4 Å), centered on the Cα atom of each residue that are predicted by ensemble of four deep discriminative classifiers trained using combinations of sequence and structure-derived features as well as several energy terms from Rosetta centroid scoring function. The proposed method, refineD, has been found to produce consistent and substantial structural refinement through the use of cumulative and non-cumulative restraints on 150 benchmarking targets. refineD outperforms unrestrained relaxation strategy or relaxation that is restrained to starting structures using the FastRelax application of Rosetta or atomic-level energy minimization based ModRefiner method as well as molecular dynamics (MD) simulation based FG-MD protocol. Furthermore, by adjusting restraint resolutions, the method addresses the tradeoff that exists between degree and consistency of refinement. These results demonstrate a promising new avenue for improving accuracy of template-based protein models by effectively guiding conformational sampling during structure refinement through the use of machine learning based restraints. AVAILABILITY AND IMPLEMENTATION http://watson.cse.eng.auburn.edu/refineD/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Debswapna Bhattacharya
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
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32
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Structural basis and designing of peptide vaccine using PE-PGRS family protein of Mycobacterium ulcerans—An integrated vaccinomics approach. Mol Immunol 2020; 120:146-163. [DOI: 10.1016/j.molimm.2020.02.009] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 01/16/2020] [Accepted: 02/12/2020] [Indexed: 12/29/2022]
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Nain Z, Abdulla F, Rahman MM, Karim MM, Khan MSA, Sayed SB, Mahmud S, Rahman SMR, Sheam MM, Haque Z, Adhikari UK. Proteome-wide screening for designing a multi-epitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches. J Biomol Struct Dyn 2019; 38:4850-4867. [PMID: 31709929 DOI: 10.1080/07391102.2019.1692072] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Elizabethkingia anophelis is an emerging human pathogen causing neonatal meningitis, catheter-associated infections and nosocomial outbreaks with high mortality rates. Besides, they are resistant to most antibiotics used in empirical therapy. In this study, therefore, we used immunoinformatic approaches to design a prophylactic peptide vaccine against E. anophelis as an alternative preventive measure. Initially, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were predicted from the highest antigenic protein. The CTL and HTL epitopes together had a population coverage of 99.97% around the world. Eventually, six CTL, seven HTL, and two LBL epitopes were selected and used to construct a multi-epitope vaccine. The vaccine protein was found to be highly immunogenic, non-allergenic, and non-toxic. Codon adaptation and in silico cloning were performed to ensure better expression within E. coli K12 host system. The stability of the vaccine structure was also improved by disulphide bridging. In addition, molecular docking and dynamics simulation revealed strong and stable binding affinity between the vaccine and toll-like receptor 4 (TLR4) molecule. The immune simulation showed higher levels of T-cell and B-cell activities which was in coherence with actual immune response. Repeated exposure simulation resulted in higher clonal selection and faster antigen clearance. Nevertheless, experimental validation is required to ensure the immunogenic potency and safety of this vaccine to control E. anophelis infection in the future.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Zulkar Nain
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Faruq Abdulla
- Department of Statistics, Faculty of Sciences, Islamic University, Kushtia, Bangladesh
| | - M Mizanur Rahman
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Mohammad Minnatul Karim
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Md Shakil Ahmed Khan
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Sifat Bin Sayed
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Shafi Mahmud
- Department of Biotechnology and Genetic Engineering, Faculty of Life and Earth Science, Rajshahi University, Rajshahi, Bangladesh
| | - S M Raihan Rahman
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Md Moinuddin Sheam
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
| | - Zahurul Haque
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia, Bangladesh
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Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J. Critical assessment of methods of protein structure prediction (CASP)-Round XIII. Proteins 2019; 87:1011-1020. [PMID: 31589781 DOI: 10.1002/prot.25823] [Citation(s) in RCA: 281] [Impact Index Per Article: 56.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 09/25/2019] [Accepted: 09/27/2019] [Indexed: 12/24/2022]
Abstract
CASP (critical assessment of structure prediction) assesses the state of the art in modeling protein structure from amino acid sequence. The most recent experiment (CASP13 held in 2018) saw dramatic progress in structure modeling without use of structural templates (historically "ab initio" modeling). Progress was driven by the successful application of deep learning techniques to predict inter-residue distances. In turn, these results drove dramatic improvements in three-dimensional structure accuracy: With the proviso that there are an adequate number of sequences known for the protein family, the new methods essentially solve the long-standing problem of predicting the fold topology of monomeric proteins. Further, the number of sequences required in the alignment has fallen substantially. There is also substantial improvement in the accuracy of template-based models. Other areas-model refinement, accuracy estimation, and the structure of protein assemblies-have again yielded interesting results. CASP13 placed increased emphasis on the use of sparse data together with modeling and chemical crosslinking, SAXS, and NMR all yielded more mature results. This paper summarizes the key outcomes of CASP13. The special issue of PROTEINS contains papers describing the CASP13 assessments in each modeling category and contributions from the participants.
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Affiliation(s)
| | - Torsten Schwede
- Biozentrum & SIB Swiss Institute of Bioinformatics, University of Basel, Basel, Switzerland
| | - Maya Topf
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, UK
| | | | - John Moult
- Institute for Bioscience and Biotechnology Research, Rockville, Maryland.,Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
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35
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Read RJ, Sammito MD, Kryshtafovych A, Croll TI. Evaluation of model refinement in CASP13. Proteins 2019; 87:1249-1262. [PMID: 31365160 PMCID: PMC6851427 DOI: 10.1002/prot.25794] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 07/03/2019] [Accepted: 07/27/2019] [Indexed: 12/25/2022]
Abstract
Performance in the model refinement category of the 13th round of Critical Assessment of Structure Prediction (CASP13) is assessed, showing that some groups consistently improve most starting models whereas the majority of participants continue to degrade the starting model on average. Using the ranking formula developed for CASP12, it is shown that only 7 of 32 groups perform better than a “naïve predictor” who just submits the starting model. Common features in their approaches include a dependence on physics‐based force fields to judge alternative conformations and the use of molecular dynamics to relax models to local minima, usually with some restraints to prevent excessively large movements. In addition to the traditional CASP metrics that focus largely on the quality of the overall fold, alternative metrics are evaluated, including comparisons of the main‐chain and side‐chain torsion angles, and the utility of the models for solving crystal structures by the molecular replacement method. It is proposed that the introduction of these metrics, as well as consideration of the accuracy of coordinate error estimates, would improve the discrimination between good and very good models.
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Affiliation(s)
- Randy J Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - Massimo D Sammito
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | | | - Tristan I Croll
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
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36
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Geng H, Chen F, Ye J, Jiang F. Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins. Comput Struct Biotechnol J 2019; 17:1162-1170. [PMID: 31462972 PMCID: PMC6709365 DOI: 10.1016/j.csbj.2019.07.010] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 07/07/2019] [Accepted: 07/23/2019] [Indexed: 12/21/2022] Open
Abstract
Compared with rapid accumulation of protein sequences from high-throughput DNA sequencing, obtaining experimental 3D structures of proteins is still much more difficult, making protein structure prediction (PSP) potentially very useful. Currently, a vast majority of PSP efforts are based on data mining of known sequences, structures and their relationships (informatics-based). However, if closely related template is not available, these methods are usually much less reliable than experiments. They may also be problematic in predicting the structures of naturally occurring or designed peptides. On the other hand, physics-based methods including molecular dynamics (MD) can utilize our understanding of detailed atomic interactions determining biomolecular structures. In this mini-review, we show that all-atom MD can predict structures of cyclic peptides and other peptide foldamers with accuracy similar to experiments. Then, some notable successes in reproducing experimental 3D structures of small proteins through MD simulations (some with replica-exchange) of the folding were summarized. We also describe advancements of MD-based refinement of structure models, and the integration of limited experimental or bioinformatics data into MD-based structure modeling.
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Affiliation(s)
- Hao Geng
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Fangfang Chen
- Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics, Peking University Shenzhen Hospital, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, China
| | - Jing Ye
- Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics, Peking University Shenzhen Hospital, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, China
| | - Fan Jiang
- Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- NanoAI Biotech Co.,Ltd., Silicon Valley Compound, Longhua District, Shenzhen 518109, China
- Corresponding author at: Lab of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
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37
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Heo L, Arbour CF, Feig M. Driven to near-experimental accuracy by refinement via molecular dynamics simulations. Proteins 2019; 87:1263-1275. [PMID: 31197841 DOI: 10.1002/prot.25759] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 06/01/2019] [Accepted: 06/07/2019] [Indexed: 12/17/2022]
Abstract
Protein model refinement has been an essential part of successful protein structure prediction. Molecular dynamics simulation-based refinement methods have shown consistent improvement of protein models. There had been progress in the extent of refinement for a few years since the idea of ensemble averaging of sampled conformations emerged. There was little progress in CASP12 because conformational sampling was not sufficiently diverse due to harmonic restraints. During CASP13, a new refinement method was tested that achieved significant improvements over CASP12. The new method intended to address previous bottlenecks in the refinement problem by introducing new features. Flat-bottom harmonic restraints replaced harmonic restraints, sampling was performed iteratively, and a new scoring function and selection criteria were used. The new protocol expanded conformational sampling at reduced computational costs. In addition to overall improvements, some models were refined significantly to near-experimental accuracy.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan
| | - Collin F Arbour
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan
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38
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Shuid AN, Kempster R, McGuffin LJ. ReFOLD: a server for the refinement of 3D protein models guided by accurate quality estimates. Nucleic Acids Res 2019; 45:W422-W428. [PMID: 28402475 PMCID: PMC5570150 DOI: 10.1093/nar/gkx249] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Accepted: 04/03/2017] [Indexed: 12/29/2022] Open
Abstract
ReFOLD is a novel hybrid refinement server with integrated high performance global and local Accuracy Self Estimates (ASEs). The server attempts to identify and to fix likely errors in user supplied 3D models of proteins via successive rounds of refinement. The server is unique in providing output for multiple alternative refined models in a way that allows users to quickly visualize the key residue locations, which are likely to have been improved. This is important, as global refinement of a full chain model may not always be possible, whereas local regions, or individual domains, can often be much improved. Thus, users may easily compare the specific regions of the alternative refined models in which they are most interested e.g. key interaction sites or domains. ReFOLD was used to generate hundreds of alternative refined models for the CASP12 experiment, boosting our group's performance in the main tertiary structure prediction category. Our successful refinement of initial server models combined with our built-in ASEs were instrumental to our second place ranking on Template Based Modeling (TBM) and Free Modeling (FM)/TBM targets. The ReFOLD server is freely available at: http://www.reading.ac.uk/bioinf/ReFOLD/.
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Affiliation(s)
- Ahmad N. Shuid
- School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
- These authors contributed equally to this work as first authors
| | - Robert Kempster
- School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
- Lancaster Environment Centre, Lancaster University, LA1 1YQ, UK
- These authors contributed equally to this work as first authors
| | - Liam J. McGuffin
- School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
- To whom correspondence should be addressed. Tel: +44 118 378 6332; Fax: +44 118 378 8106;
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39
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Methods for the Refinement of Protein Structure 3D Models. Int J Mol Sci 2019; 20:ijms20092301. [PMID: 31075942 PMCID: PMC6539982 DOI: 10.3390/ijms20092301] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 04/24/2019] [Accepted: 05/07/2019] [Indexed: 12/25/2022] Open
Abstract
The refinement of predicted 3D protein models is crucial in bringing them closer towards experimental accuracy for further computational studies. Refinement approaches can be divided into two main stages: The sampling and scoring stages. Sampling strategies, such as the popular Molecular Dynamics (MD)-based protocols, aim to generate improved 3D models. However, generating 3D models that are closer to the native structure than the initial model remains challenging, as structural deviations from the native basin can be encountered due to force-field inaccuracies. Therefore, different restraint strategies have been applied in order to avoid deviations away from the native structure. For example, the accurate prediction of local errors and/or contacts in the initial models can be used to guide restraints. MD-based protocols, using physics-based force fields and smart restraints, have made significant progress towards a more consistent refinement of 3D models. The scoring stage, including energy functions and Model Quality Assessment Programs (MQAPs) are also used to discriminate near-native conformations from non-native conformations. Nevertheless, there are often very small differences among generated 3D models in refinement pipelines, which makes model discrimination and selection problematic. For this reason, the identification of the most native-like conformations remains a major challenge.
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40
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Jiang F, Wu HN, Kang W, Wu YD. Developments and Applications of Coil-Library-Based Residue-Specific Force Fields for Molecular Dynamics Simulations of Peptides and Proteins. J Chem Theory Comput 2019; 15:2761-2773. [DOI: 10.1021/acs.jctc.8b00794] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Fan Jiang
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Hao-Nan Wu
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Wei Kang
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Yun-Dong Wu
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
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41
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Wang A, Zhang Z, Li G. Higher Accuracy Achieved in the Simulations of Protein Structure Refinement, Protein Folding, and Intrinsically Disordered Proteins Using Polarizable Force Fields. J Phys Chem Lett 2018; 9:7110-7116. [PMID: 30514082 DOI: 10.1021/acs.jpclett.8b03471] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The accuracy of molecular mechanics force fields is of vital importance in biomolecular simulations. However, the admittedly more accurate polarizable force fields were recently reported to be less able to reproduce the experimental properties in comparison to additive force fields in some cases. Here, we perform long-time-scale molecular dynamics simulations to systematically evaluate the effect of explicit electronic polarization in polarizable force fields. The results show that the inclusion of electrostatic polarization effect in polarizable force fields can improve their accuracies in protein structure refinement and generate conformational ensembles more approximate to experiments for intrinsically disordered proteins. In contrast, it is difficult for polarizable force fields to approach the native structure, let alone to predict the native state when it is unknown a priori in the real protein structure predictions. We speculate that these effects might be attributed to the preference of protein-water interactions in polarizable force fields.
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Affiliation(s)
- Anhui Wang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
- State Key Laboratory of Fine Chemicals, School of Chemistry , Dalian University of Technology , Dalian 116024 , China
| | - Zhichao Zhang
- State Key Laboratory of Fine Chemicals, School of Chemistry , Dalian University of Technology , Dalian 116024 , China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
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42
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Experimental accuracy in protein structure refinement via molecular dynamics simulations. Proc Natl Acad Sci U S A 2018; 115:13276-13281. [PMID: 30530696 DOI: 10.1073/pnas.1811364115] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Refinement is the last step in protein structure prediction pipelines to convert approximate homology models to experimental accuracy. Protocols based on molecular dynamics (MD) simulations have shown promise, but current methods are limited to moderate levels of consistent refinement. To explore the energy landscape between homology models and native structures and analyze the challenges of MD-based refinement, eight test cases were studied via extensive simulations followed by Markov state modeling. In all cases, native states were found very close to the experimental structures and at the lowest free energies, but refinement was hindered by a rough energy landscape. Transitions from the homology model to the native states require the crossing of significant kinetic barriers on at least microsecond time scales. A significant energetic driving force toward the native state was lacking until its immediate vicinity, and there was significant sampling of off-pathway states competing for productive refinement. The role of recent force field improvements is discussed and transition paths are analyzed in detail to inform which key transitions have to be overcome to achieve successful refinement.
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43
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Ma T, Zang T, Wang Q, Ma J. Refining protein structures using enhanced sampling techniques with restraints derived from an ensemble-based model. Protein Sci 2018; 27:1842-1849. [PMID: 30098055 DOI: 10.1002/pro.3486] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 07/05/2018] [Accepted: 07/18/2018] [Indexed: 12/12/2022]
Abstract
This paper reports a method for high-accuracy protein structural refinement, which is a direct extension of the method in our recent publication (Zang, J Chem Phys 2018; 149:072319). It combines a parallel continuous simulated tempering (PCST) method with a temperature-dependent restraint and a blind model selection scheme. In this work, a single-reference-based restraint in previous work was changed to an ensemble-based model (EBM), in which the non-bonded Lennard-Jones term for each contacting atomic pair in previous restraining potential was replaced by a multi-Gaussian function whose parameters are derived from an ensemble of structures such as the ones from various CASP participating groups. The purpose of EBM is to take advantage of partial "correctness" distributed among members of the structural ensemble. Totally 18 targets were refined from the refinement category of CASP10, CASP11 and CASP12. In Top-1 group, 11 out of 18 targets had better models (greater GDT_TS scores) than the CASPR participants. In Top-5 group, nine out of 18 were better. Our results show that PCST-EBM method can considerably improve the low-accuracy structures.
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Affiliation(s)
- Tianqi Ma
- Applied Physics Program and Department of Bioengineering, Rice University, Houston, Texas, 77005
| | - Tianwu Zang
- Applied Physics Program and Department of Bioengineering, Rice University, Houston, Texas, 77005
| | - Qinghua Wang
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, 77030
| | - Jianpeng Ma
- Applied Physics Program and Department of Bioengineering, Rice University, Houston, Texas, 77005.,Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, 77030
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44
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Pfeiffenberger E, Bates PA. Predicting improved protein conformations with a temporal deep recurrent neural network. PLoS One 2018; 13:e0202652. [PMID: 30180164 PMCID: PMC6122789 DOI: 10.1371/journal.pone.0202652] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 08/07/2018] [Indexed: 02/03/2023] Open
Abstract
Accurate protein structure prediction from amino acid sequence is still an unsolved problem. The most reliable methods centre on template based modelling. However, the accuracy of these models entirely depends on the availability of experimentally resolved homologous template structures. In order to generate more accurate models, extensive physics based molecular dynamics (MD) refinement simulations are performed to sample many different conformations to find improved conformational states. In this study, we propose a deep recurrent network model, called DeepTrajectory, that is able to identify these improved conformational states, with high precision, from a variety of different MD based sampling protocols. The proposed model learns the temporal patterns of features computed from MD trajectory data in order to classify whether each recorded simulation snapshot is an improved quality conformational state, decreased quality conformational state or whether there is no perceivable change in state with respect to the starting conformation. The model was trained and tested on 904 trajectories from 42 different protein systems with a cumulative number of more than 1.7 million snapshots. We show that our model outperforms other state of the art machine-learning algorithms that do not consider temporal dependencies. To our knowledge, DeepTrajectory is the first implementation of a time-dependent deep-learning protocol that is re-trainable and able to adapt to any new MD based sampling procedure, thereby demonstrating how a neural network can be used to learn the latter part of the protein folding funnel.
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Affiliation(s)
- Erik Pfeiffenberger
- Biomolecular Modelling Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, United Kingdom
| | - Paul A. Bates
- Biomolecular Modelling Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, United Kingdom
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45
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Zang T, Ma T, Wang Q, Ma J. Improving low-accuracy protein structures using enhanced sampling techniques. J Chem Phys 2018; 149:072319. [PMID: 30134714 PMCID: PMC5995690 DOI: 10.1063/1.5027243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 05/23/2018] [Indexed: 11/14/2022] Open
Abstract
In this paper, we report results of using enhanced sampling and blind selection techniques for high-accuracy protein structural refinement. By combining a parallel continuous simulated tempering (PCST) method, previously developed by Zang et al. [J. Chem. Phys. 141, 044113 (2014)], and the structure based model (SBM) as restraints, we refined 23 targets (18 from the refinement category of the CASP10 and 5 from that of CASP12). We also designed a novel model selection method to blindly select high-quality models from very long simulation trajectories. The combined use of PCST-SBM with the blind selection method yielded final models that are better than initial models. For Top-1 group, 7 out of 23 targets had better models (greater global distance test total scores) than the critical assessment of structure prediction participants. For Top-5 group, 10 out of 23 were better. Our results justify the crucial position of enhanced sampling in protein structure prediction and refinement and demonstrate that a considerable improvement of low-accuracy structures is achievable with current force fields.
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Affiliation(s)
- Tianwu Zang
- Applied Physics Program and Department of Bioengineering, Rice University, Houston, Texas 77005, USA
| | - Tianqi Ma
- Applied Physics Program and Department of Bioengineering, Rice University, Houston, Texas 77005, USA
| | - Qinghua Wang
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, One Baylor Plaza, BCM-125, Houston, Texas 77030, USA
| | - Jianpeng Ma
- Author to whom correspondence should be addressed: . Telephone: 713-798-8187. Fax: 713-796-9438
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46
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Deng H, Jia Y, Zhang Y. Protein structure prediction. INTERNATIONAL JOURNAL OF MODERN PHYSICS. B 2018; 32:1840009. [PMID: 30853739 PMCID: PMC6407873 DOI: 10.1142/s021797921840009x] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Predicting 3D structure of protein from its amino acid sequence is one of the most important unsolved problems in biophysics and computational biology. This paper attempts to give a comprehensive introduction of the most recent effort and progress on protein structure prediction. Following the general flowchart of structure prediction, related concepts and methods are presented and discussed. Moreover, brief introductions are made to several widely-used prediction methods and the community-wide critical assessment of protein structure prediction (CASP) experiments.
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Affiliation(s)
- Haiyou Deng
- College of Science, Huazhong Agricultural University, Wuhan 4R0070, P. R. China
| | - Ya Jia
- College of Physical Science and Technology, Central China Normal University, Wuhan 430079, P. R. China
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 45108, USA
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47
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Heo L, Feig M. PREFMD: a web server for protein structure refinement via molecular dynamics simulations. Bioinformatics 2018; 34:1063-1065. [PMID: 29126101 PMCID: PMC5860225 DOI: 10.1093/bioinformatics/btx726] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 10/04/2017] [Accepted: 11/07/2017] [Indexed: 11/13/2022] Open
Abstract
Summary Refinement of protein structure models is a long-standing problem in structural bioinformatics. Molecular dynamics-based methods have emerged as an avenue to achieve consistent refinement. The PREFMD web server implements an optimized protocol based on the method successfully tested in CASP11. Validation with recent CASP refinement targets shows consistent and more significant improvement in global structure accuracy over other state-of-the-art servers. Availability and implementation PREFMD is freely available as a web server at http://feiglab.org/prefmd. Scripts for running PREFMD as a stand-alone package are available at https://github.com/feiglab/prefmd.git. Contact feig@msu.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Lim Heo
- Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - Michael Feig
- Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
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48
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Heo L, Feig M. What makes it difficult to refine protein models further via molecular dynamics simulations? Proteins 2018; 86 Suppl 1:177-188. [PMID: 28975670 PMCID: PMC5820117 DOI: 10.1002/prot.25393] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 09/11/2017] [Accepted: 09/29/2017] [Indexed: 01/20/2023]
Abstract
Protein structure refinement remains a challenging yet important problem as it has the potential to bring already accurate template-based models to near-native resolution. Refinement based on molecular dynamics simulations has been a highly promising approach and the performance of MD-based refinement in the Feig group during CASP12 is described here. During CASP12, sampling was extended well into the microsecond scale, an improved force field was applied, and new protocol variations were tested. Progress over previous rounds of CASP was found to be limited which is analyzed in terms of the quality of the initial models and dependency on the amount of sampling and refinement protocol variations. As current MD-based refinement protocols appear to be reaching a plateau, detailed analysis is presented to provide new insight into the major challenges towards more extensive structure refinement, focusing in particular on sampling with and without restraints.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
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49
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Hovan L, Oleinikovas V, Yalinca H, Kryshtafovych A, Saladino G, Gervasio FL. Assessment of the model refinement category in CASP12. Proteins 2017; 86 Suppl 1:152-167. [PMID: 29071750 DOI: 10.1002/prot.25409] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 10/03/2017] [Accepted: 10/24/2017] [Indexed: 01/07/2023]
Abstract
We here report on the assessment of the model refinement predictions submitted to the 12th Experiment on the Critical Assessment of Protein Structure Prediction (CASP12). This is the fifth refinement experiment since CASP8 (2008) and, as with the previous experiments, the predictors were invited to refine selected server models received in the regular (nonrefinement) stage of the CASP experiment. We assessed the submitted models using a combination of standard CASP measures. The coefficients for the linear combination of Z-scores (the CASP12 score) have been obtained by a machine learning algorithm trained on the results of visual inspection. We identified eight groups that improve both the backbone conformation and the side chain positioning for the majority of targets. Albeit the top methods adopted distinctively different approaches, their overall performance was almost indistinguishable, with each of them excelling in different scores or target subsets. What is more, there were a few novel approaches that, while doing worse than average in most cases, provided the best refinements for a few targets, showing significant latitude for further innovation in the field.
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Affiliation(s)
- Ladislav Hovan
- Department of Chemistry, University College London, WC1E 6BT, United Kingdom
| | | | - Havva Yalinca
- Department of Chemistry, University College London, WC1E 6BT, United Kingdom
| | | | - Giorgio Saladino
- Department of Chemistry, University College London, WC1E 6BT, United Kingdom
| | - Francesco Luigi Gervasio
- Department of Chemistry, University College London, WC1E 6BT, United Kingdom.,Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, United Kingdom
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50
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Lee GR, Heo L, Seok C. Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment. Proteins 2017; 86 Suppl 1:168-176. [PMID: 29044810 DOI: 10.1002/prot.25404] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 10/09/2017] [Accepted: 10/11/2017] [Indexed: 12/15/2022]
Abstract
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted residue contacts. Given semi-reliable or incomplete structural information, structure quality of a protein model has to be improved by ab initio methods such as energy-based simulation. In this study, we describe a new automatic refinement server method designed to improve locally inaccurate regions and overall structure simultaneously. Locally inaccurate regions may occur in protein structures due to non-convergent or missing information in template structures used in homology modeling or due to intrinsic structural flexibilities not resolved by experimental techniques. However, such variable or dynamic regions often play important functional roles by participating in interactions with other biomolecules or in transitions between different functional states. The new refinement method introduced here utilizes diverse types of geometric operators which drive both local and global changes, and the effect of structure changes and relaxations are accumulated. This resulted in consistent refinement of both local and global structural features. Performance of this method in CASP12 is discussed.
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Affiliation(s)
- Gyu Rie Lee
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Lim Heo
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
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