1
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Pant P. Flexible RNA aptamers as inhibitors of Bacillus anthracis ribosomal protein S8: Insights from molecular dynamics simulations. Biophys Chem 2024; 312:107273. [PMID: 38850843 DOI: 10.1016/j.bpc.2024.107273] [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: 03/08/2024] [Accepted: 06/02/2024] [Indexed: 06/10/2024]
Abstract
Bacillus anthracis, the causative agent of anthrax, poses a substantial threat to public health and national security, and is recognized as a potential bioweapon due to its capacity to form resilient spores with enduring viability. Inhalation or ingestion of even minute quantities of aerosolized spores can lead to widespread illness and fatalities, underscoring the formidable lethality of the bacterium. With an untreated mortality rate of 100%, Bacillus anthracis is a disconcerting candidate for bioterrorism. In response to this critical scenario, we employed state-of-the-art computational tools to conceive and characterize flexible RNA aptamer therapeutics tailored for anthrax. The foundational structure of the flexible RNA aptamers was designed by removing the C2'-C3' in each nucleotide unit. Leveraging the crystal structure of Bacillus anthracis ribosomal protein S8 complexed with an RNA aptamer, we explored the structural, dynamic, and energetic aspects of the modified RNA aptamer - S8 protein complexes through extensive all-atom explicit-solvent molecular dynamics simulations (400 ns, 3 replicas each), followed by drawing comparisons to the control system. Our findings demonstrate the enhanced binding competencies of the flexible RNA aptamers to the S8 protein via better shape complementarity and improved H-bond network compared to the control RNA aptamer. This research offers valuable insights into the development of RNA aptamer therapeutics targeting Bacillus anthracis, paving the way for innovative strategies to mitigate the impact of this formidable pathogen.
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Affiliation(s)
- Pradeep Pant
- Department of Biotechnology, School of Engineering and Applied Sciences, Bennett University, Greater Noida, U.P., India.
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2
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Hei B, Tardiff JC, Schwartz SD. Human cardiac β-myosin powerstroke energetics: Thin filament, Pi displacement, and mutation effects. Biophys J 2024:S0006-3495(24)00451-X. [PMID: 39001604 DOI: 10.1016/j.bpj.2024.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 07/01/2024] [Accepted: 07/09/2024] [Indexed: 07/25/2024] Open
Abstract
The powerstroke of human cardiac β-myosin is an important stage of the cross-bridge cycle that generates force for muscle contraction. However, the starting structure of this process has never been resolved, and the relative timing of the powerstroke and inorganic phosphate (Pi) release is still controversial. In this study, we generated an atomistic model of myosin on the thin filament and utilized metadynamics simulations to predict the absent starting structure of the powerstroke. We demonstrated that the displacement of Pi from the active site during the powerstroke is likely necessary, reducing the energy barrier of the conformation change. The effects of the presence of the thin filament, the hypertrophic cardiomyopathy mutation R712L, and the binding of mavacamten on the powerstroke process were also investigated.
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Affiliation(s)
- Bai Hei
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, Arizona
| | - Jil C Tardiff
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Steven D Schwartz
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, Arizona.
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3
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Bhat SS, Kulkarni SR, Uttarkar A, Niranjan V. Computational Insights into Papaveroline as an In Silico Drug Candidate for Alzheimer's Disease via Fyn Tyrosine Kinase Inhibition. Mol Biotechnol 2024:10.1007/s12033-024-01236-0. [PMID: 39004678 DOI: 10.1007/s12033-024-01236-0] [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: 12/06/2023] [Accepted: 06/25/2024] [Indexed: 07/16/2024]
Abstract
Alzheimer's disease (AD) poses a significant global health challenge, necessitating the exploration of novel therapeutic strategies. Fyn Tyrosine Kinase has emerged as a key player in AD pathogenesis, making it an attractive target for drug development. This study focuses on investigating the potential of Papaveroline as a drug candidate for AD by targeting Fyn Tyrosine Kinase. The research employed high-throughput virtual screening and QSAR analysis were conducted to identify compounds with optimal drug-like properties, emphasizing adherence to ADMET parameters for further evaluation. Molecular dynamics simulations to analyze the binding interactions between Papaveroline and Staurosporine with Fyn Tyrosine Kinase over a 200-ns period. The study revealed detailed insights into the binding mechanisms and stability of the Papaveroline-Fyn complex, showcasing the compound's potential as an inhibitor of Fyn Tyrosine Kinase. Comparative analysis with natural compounds and a reference compound highlighted Papaveroline's unique characteristics and promising therapeutic implications for AD treatment. Overall, the findings underscore Papaveroline's potential as a valuable drug candidate for targeting Fyn Tyrosine Kinase in AD therapy, offering new avenues for drug discovery in neurodegenerative diseases. This study contributes to advancing our understanding of molecular interactions in AD pathogenesis and paves the way for further research and development in this critical area.
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Affiliation(s)
- Shreya Satyanarayan Bhat
- Department of Biotechnology, R V College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi 590018), Bangalore, 560059, India
| | - Spoorthi R Kulkarni
- Department of Biotechnology, R V College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi 590018), Bangalore, 560059, India
| | - Akshay Uttarkar
- Department of Biotechnology, R V College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi 590018), Bangalore, 560059, India
| | - Vidya Niranjan
- Department of Biotechnology, R V College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi 590018), Bangalore, 560059, India.
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4
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Al Adawiah R, Zaenal Mustopa A, Budiarti S, Nur Umami R, Hertati A, Irawan H, Ikramullah MC, Arwansyah A, Mamangkey J, Kartikasari I, Salahudin Darusman H. Molecular dynamics simulation and purification of chimeric L1/L2 protein from human papillomavirus type 52 expressed in Escherichia coli BL21 (DE3). J Immunoassay Immunochem 2024:1-20. [PMID: 38965835 DOI: 10.1080/15321819.2024.2376034] [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: 07/06/2024]
Abstract
The available prophylactic vaccines for human papillomavirus (HPV) in the market are only effective against specific types of HPV, rendering them ineffective for other types of HPV infections. The objective of this research is to investigate the stability of the recombinant protein constructed, namely chimeric L1/L2 protein from HPV type 52, with improved cross-neutralization ability. The 3D model, predicted using Alphafold, Robetta, I-Tasser, and refined with Galaxy Refinement, is validated using Ramachandran plot analysis. The stability is verified through molecular dynamics simulations, considering parameters such as RMSD, RMSF, Rg, and SASA, where stable conditions are observed. The chimeric L1/L2 protein from HPV type 52 is purified using affinity chromatography, and the His-tag is cleaved using SUMO protease to obtain pure chimeric protein with the size of ~ 55 kDa. Western blot analysis confirms binding to anti-L1 HPV type 52 polyclonal antibody. The obtained vaccine candidate can be utilized as an effective prophylactic vaccine against HPV.
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Affiliation(s)
| | - Apon Zaenal Mustopa
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), KST Soekarno, Cibinong, Bogor, Indonesia
| | - Sri Budiarti
- Department of Biology, IPB University, Bogor, Indonesia
| | - Rifqiyah Nur Umami
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), KST Soekarno, Cibinong, Bogor, Indonesia
| | - Ai Hertati
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), KST Soekarno, Cibinong, Bogor, Indonesia
| | - Herman Irawan
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), KST Soekarno, Cibinong, Bogor, Indonesia
| | - Muh Chaeril Ikramullah
- Biotechnology Study Program, Postgraduate School of Universitas Gadjah Mada, Yogyakarta, Indonesia
| | | | - Jendri Mamangkey
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), KST Soekarno, Cibinong, Bogor, Indonesia
- Department of Biology Education, Faculty of Education and Teacher Training, Universitas Kristen Indonesia, Jakarta, Indonesia
| | | | - Huda Salahudin Darusman
- Department of Anatomy, Physiology and Pharmacology, School of Veterinary Medicine and Biomedical, IPB University Indonesia,Bogor
- Primate Animal Study Center, Research Institution and Community Service (LPPM), IPB University, Bogor, Indonesia
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5
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Garduño-Juárez R, Tovar-Anaya DO, Perez-Aguilar JM, Lozano-Aguirre Beltran LF, Zubillaga RA, Alvarez-Perez MA, Villarreal-Ramirez E. Molecular Dynamic Simulations for Biopolymers with Biomedical Applications. Polymers (Basel) 2024; 16:1864. [PMID: 39000719 PMCID: PMC11244511 DOI: 10.3390/polym16131864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/13/2024] [Accepted: 04/13/2024] [Indexed: 07/17/2024] Open
Abstract
Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its use in biomedical engineering for biopolymer materials has only recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: (A) Computer-aided design (CAD/CAM) utilizes specialized software to design and model biopolymers for various biomedical applications. This technology allows researchers to create precise three-dimensional models of biopolymers, taking into account their chemical, structural, and functional properties. These models can be used to enhance the structure of biopolymers and improve their effectiveness in specific medical applications. (B) Finite element analysis, a computational technique used to analyze and solve problems in engineering and physics. This approach divides the physical domain into small finite elements with simple geometric shapes. This computational technique enables the study and understanding of the mechanical and structural behavior of biopolymers in biomedical environments. (C) Molecular dynamics (MD) simulations involve using advanced computational techniques to study the behavior of biopolymers at the molecular and atomic levels. These simulations are fundamental for better understanding biological processes at the molecular level. Studying the wide-ranging uses of MD simulations in biopolymers involves examining the structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton's equations of motion for all-atom systems, producing spatial trajectories for each atom. This provides valuable insights into properties such as water absorption on biopolymer surfaces and interactions with solid surfaces, which are crucial for assessing biomaterials. This review provides a comprehensive overview of the various applications of MD simulations in biopolymers. Additionally, it highlights the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.
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Affiliation(s)
- Ramón Garduño-Juárez
- Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
| | - David O Tovar-Anaya
- Laboratorio de Bioingeniería de Tejidos, División de Estudios de Posgrado e Investigación, Coyoacán 04510, Mexico
| | - Jose Manuel Perez-Aguilar
- School of Chemical Sciences, Meritorious Autonomous University of Puebla (BUAP), University City, Puebla 72570, Mexico
| | | | - Rafael A Zubillaga
- Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Mexico City 09340, Mexico
| | - Marco Antonio Alvarez-Perez
- Laboratorio de Bioingeniería de Tejidos, División de Estudios de Posgrado e Investigación, Coyoacán 04510, Mexico
| | - Eduardo Villarreal-Ramirez
- Laboratorio de Bioingeniería de Tejidos, División de Estudios de Posgrado e Investigación, Coyoacán 04510, Mexico
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6
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Basciu A, Athar M, Kurt H, Neville C, Malloci G, Muredda FC, Bosin A, Ruggerone P, Bonvin AMJJ, Vargiu AV. Predicting binding events in very flexible, allosteric, multi-domain proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.02.597018. [PMID: 38895346 PMCID: PMC11185556 DOI: 10.1101/2024.06.02.597018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Knowledge of the structures formed by proteins and small ligands is of fundamental importance for understanding molecular principles of chemotherapy and for designing new and more effective drugs. Due to the still high costs and to the several limitations of experimental techniques, it is most often desirable to predict these ligand-protein complexes in silico, particularly when screening for new putative drugs from databases of millions of compounds. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology aimed at generating bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites. Validation was performed on the enzyme adenylate kinase (ADK), a paradigmatic example of proteins that undergo very large conformational changes upon ligand binding. By only exploiting the unbound structure and the putative binding sites of the protein, we generated a significant fraction of bound-like structures, which employed in ensemble-docking calculations allowed to find native-like poses of substrates, inhibitors, and catalytically incompetent binders. Our protocol provides a general framework for the generation of bound-like conformations of flexible proteins that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening for difficult targets, prediction of the impact of amino acid mutations on structure and dynamics, and protein engineering.
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Affiliation(s)
- Andrea Basciu
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Mohd Athar
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Han Kurt
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Christine Neville
- Institute for Computational Molecular Science, Temple University, Philadelphia, PA 19122, USA
- Department of Biology, Temple University, Philadelphia, PA 19122, USA
| | - Giuliano Malloci
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Fabrizio C. Muredda
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Andrea Bosin
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Paolo Ruggerone
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
| | - Alexandre M. J. J. Bonvin
- Bijvoet Centre for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Attilio V. Vargiu
- Physics Department, University of Cagliari, Cittadella Universitaria, I-09042 Monserrato (CA), Italy
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7
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Johan UUM, Rahman RNZRA, Kamarudin NHA, Ali MSM. Thermodynamics of a hyperthermostable carboxylesterase from Anoxybacillus geothermalis D9. Arch Biochem Biophys 2024; 756:109996. [PMID: 38621445 DOI: 10.1016/j.abb.2024.109996] [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: 12/04/2023] [Revised: 03/08/2024] [Accepted: 04/12/2024] [Indexed: 04/17/2024]
Abstract
Hyperthermostable enzymes are highly desirable biocatalysts due to their exceptional stability at extreme temperatures. Recently, a hyperthermostable carboxylesterase EstD9 from Anoxybacillus geothermalis D9 was biochemically characterized. The enzyme exhibited remarkable stability at high temperature. In this study, we attempted to probe the conformational adaptability of EstD9 under extreme conditions via in silico approaches. Circular dichroism revealed that EstD9 generated new β-sheets at 80 °C, making the core of the hydrolase fold more stable. Interestingly, the profiles of molecular dynamics simulation showed the lowest scores of radius of gyration and solvent accessible surface area (SASA) at 80 °C. Three loops were responsible for protecting the catalytic site, which resided at the interface between the large and cap domains. To further investigate the structural adaptation in extreme conditions, the intramolecular interactions of the native structure were investigated. EstD9 revealed 18 hydrogen bond networks, 7 salt bridges, and 9 hydrophobic clusters, which is higher than the previously reported thermostable Est30. Collectively, the analysis indicates that intramolecular interactions and structural dynamics play distinct roles in preserving the overall EstD9 structure at elevated temperatures. This work is relevant to both fundamental and applied research involving protein engineering of industrial thermostable enzymes.
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Affiliation(s)
- Ummie Umaiera Mohd Johan
- Enzyme and Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Raja Noor Zaliha Raja Abd Rahman
- Enzyme and Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Nor Hafizah Ahmad Kamarudin
- Enzyme and Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Centre of Foundation Studies for Agricultural Science, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Mohd Shukuri Mohamad Ali
- Enzyme and Microbial Technology Research Centre, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
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8
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Singh A, Varadarajan A, Pant P, Singh TP, Vikram NK, Sharma S, Sharma P. Identification of potential anti-mucor agents by targeting endothelial cell receptor glucose-regulated protein-78 using in silico approach. J Biomol Struct Dyn 2024; 42:4344-4355. [PMID: 37288794 DOI: 10.1080/07391102.2023.2220809] [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: 12/22/2022] [Accepted: 05/28/2023] [Indexed: 06/09/2023]
Abstract
Mucormycosis is a fungal infection of the sinuses, brain and lungs that is the cause of approximately 50% mortality rate despite the available first-line therapy. Glucose-Regulated Protein 78 (GRP78) is already reported to be a novel host receptor that mediates invasion and damage of human endothelial cells by Rhizopus oryzae and Rhizopus delemar, the most common etiologic species of Mucorales. The expression of GRP78 is also regulated by the levels of iron and glucose in the blood. There are several antifungal drugs in the market but they pose a serious side effect to the vital organs of the body. Therefore, there is an immediate need to discover effective drug molecules having increased efficacy with no side effects. With the help of various computational tools, the current study was attempted to determine potential antimucor agents against GRP78. The receptor molecule GRP78 was screened against 8820 known drugs deposited in DrugBank library using high-throughput virtual screening method. Total top 10 compounds were selected based on the binding energies greater than the reference co-crystal molecule. Furthermore, molecular dynamic (MD) simulations using AMBER were performed to calculate the stability of the top-ranked compounds in the active site of GRP78. After extensive computational studies, we propose that two compounds (CID439153 and CID5289104) have inhibitory potency against mucormycosis and can serve as potential drugs that can form the basis of treating mucormycosis disease.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Anamika Singh
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Ashwin Varadarajan
- Department of Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Pradeep Pant
- Department of Chemistry, Indian Institute of Technology, New Delhi, India
| | - Tej P Singh
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Naval K Vikram
- Department of Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Sujata Sharma
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Pradeep Sharma
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
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9
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Xu C, Zhang X, Zhao L, Verkhivker GM, Bai F. Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies. JACS AU 2024; 4:1632-1645. [PMID: 38665669 PMCID: PMC11040708 DOI: 10.1021/jacsau.4c00123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 04/28/2024]
Abstract
The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure-kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate constant (koff), enabling a direct assessment of the drug-target residence time. These models demonstrated good predictive performance, where hydrophobic and hydrogen bond interactions significantly influence the koff prediction. In subsequent applications, our models were used to assist in the discovery of new inhibitors for the N-terminal domain of HSP90α (N-HSP90α), demonstrating predictive capabilities on an experimental validation set with a new scaffold. In X-ray crystallography experiments, the loop-middle conformation of apo N-HSP90α was observed for the first time (previously, the loop-middle conformation had only been observed in holo-N-HSP90α structures). Interestingly, we observed different conformations of apo N-HSP90α simultaneously in an asymmetric unit, which was also observed in a holo-N-HSP90α structure, suggesting an equilibrium of conformations between different states in solution, which could be one of the determinants affecting the binding kinetics of the ligand. Different ligands can undergo conformational selection or alter the equilibrium of conformations, inducing conformational rearrangements and resulting in different effects on binding kinetics. We then used molecular dynamics simulations to describe conformational changes of apo N-HSP90α in different conformational states. In summary, the study of the binding kinetics and molecular mechanisms of N-HSP90α provides valuable information for the development of more targeted therapeutic approaches.
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Affiliation(s)
- Chao Xu
- Shanghai
Institute for Advanced Immunochemical Studies and School of Life Science
and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China
| | - Xianglei Zhang
- Shanghai
Institute for Advanced Immunochemical Studies and School of Life Science
and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China
| | - Lianghao Zhao
- Shanghai
Institute for Advanced Immunochemical Studies and School of Life Science
and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China
| | - Gennady M. Verkhivker
- Keck
Center for Science and Engineering, Graduate Program in Computational
and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
- Department
of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
| | - Fang Bai
- Shanghai
Institute for Advanced Immunochemical Studies and School of Life Science
and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China
- School
of Information Science and Technology, ShanghaiTech
University, 393 Middle Huaxia Road, Shanghai 201210, China
- Shanghai
Clinical Research and Trial Center, Shanghai 201210, China
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10
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Viegas RG, Martins IBS, Sanches MN, Oliveira Junior AB, Camargo JBD, Paulovich FV, Leite VBP. ELViM: Exploring Biomolecular Energy Landscapes through Multidimensional Visualization. J Chem Inf Model 2024; 64:3443-3450. [PMID: 38506664 DOI: 10.1021/acs.jcim.4c00034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.
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Affiliation(s)
- Rafael Giordano Viegas
- Federal Institute of Education, Science and Technology of São Paulo (IFSP), Catanduva, São Paulo 15.808-305, Brazil
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Ingrid B S Martins
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Murilo Nogueira Sanches
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | | | - Juliana B de Camargo
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Fernando V Paulovich
- Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, Eindhoven 5600 MB, The Netherlands
| | - Vitor B P Leite
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
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11
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Ferraz-Caetano J, Teixeira F, Cordeiro MNDS. Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy. J Chem Inf Model 2024; 64:2250-2262. [PMID: 37603608 PMCID: PMC11005042 DOI: 10.1021/acs.jcim.3c00544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Indexed: 08/23/2023]
Abstract
Many challenges persist in developing accurate computational models for predicting solvation free energy (ΔGsol). Despite recent developments in Machine Learning (ML) methodologies that outperformed traditional quantum mechanical models, several issues remain concerning explanatory insights for broad chemical predictions with an acceptable speed-accuracy trade-off. To overcome this, we present a novel supervised ML model to predict the ΔGsol for an array of solvent-solute pairs. Using two different ensemble regressor algorithms, we made fast and accurate property predictions using open-source chemical features, encoding complex electronic, structural, and surface area descriptors for every solvent and solute. By integrating molecular properties and chemical interaction features, we have analyzed individual descriptor importance and optimized our model though explanatory information form feature groups. On aqueous and organic solvent databases, ML models revealed the predictive relevance of solutes with increasing polar surface area and decreasing polarizability, yielding better results than state-of-the-art benchmark Neural Network methods (without complex quantum mechanical or molecular dynamic simulations). Both algorithms successfully outperformed previous ΔGsol predictions methods, with a maximum absolute error of 0.22 ± 0.02 kcal mol-1, further validated in an external benchmark database and with solvent hold-out tests. With these explanatory and statistical insights, they allow a thoughtful application of this method for predicting other thermodynamic properties, stressing the relevance of ML modeling for further complex computational chemistry problems.
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Affiliation(s)
- José Ferraz-Caetano
- Department
of Chemistry and Biochemistry − Faculty of Sciences, University of Porto - Rua do Campo Alegre, S/N, 4169-007 Porto, Portugal
| | - Filipe Teixeira
- Centre
of Chemistry, University of Minho, Campus
de Gualtar, 4710-057 Braga, Portugal
| | - M. Natália D. S. Cordeiro
- Department
of Chemistry and Biochemistry − Faculty of Sciences, University of Porto - Rua do Campo Alegre, S/N, 4169-007 Porto, Portugal
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12
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Wu X, Lin H, Bai R, Duan H. Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design. Eur J Med Chem 2024; 268:116262. [PMID: 38387334 DOI: 10.1016/j.ejmech.2024.116262] [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: 01/04/2024] [Revised: 02/06/2024] [Accepted: 02/17/2024] [Indexed: 02/24/2024]
Abstract
Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.
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Affiliation(s)
- Xinyi Wu
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, PR China
| | - Huitian Lin
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, PR China
| | - Renren Bai
- School of Pharmacy, Hangzhou Normal University, Hangzhou, 311121, PR China.
| | - Hongliang Duan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, PR China.
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13
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Molina GA, Mendes LFS, Fuzo CA, Costa-Filho AJ, Ward RJ. Mapping secondary substrate-binding sites on the GH11 xylanase from Bacillus subtilis. FEBS Lett 2024; 598:363-376. [PMID: 38253842 DOI: 10.1002/1873-3468.14799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/07/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024]
Abstract
Xylanases are of significant interest for biomass conversion technologies. Here, we investigated the allosteric regulation of xylan hydrolysis by the Bacillus subtilis GH11 endoxylanase. Molecular dynamics simulations (MDS) in the presence of xylobiose identified binding to the active site and two potential secondary binding sites (SBS) around surface residues Asn54 and Asn151. Arabinoxylan titration experiments with single cysteine mutants N54C and N151C labeled with the thiol-reactive fluorophore acrylodan or the ESR spin-label MTSSL validated the MDS results. Ligand binding at the SBS around Asn54 confirms previous reports, and analysis of the second SBS around N151C discovered in the present study includes residues Val98/Ala192/Ser155/His156. Understanding the regulation of xylanases contributes to efforts for industrial decarbonization and to establishing a sustainable energy matrix.
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Affiliation(s)
- Gustavo Avelar Molina
- Department of Chemistry, Faculty of Philosophy, Sciences and Literature at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Luis Felipe Santos Mendes
- Department of Physics, Faculty of Philosophy, Sciences and Literature at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Carlos Alessandro Fuzo
- Department of Chemistry, Faculty of Philosophy, Sciences and Literature at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
- Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Antonio José Costa-Filho
- Department of Physics, Faculty of Philosophy, Sciences and Literature at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Richard John Ward
- Department of Chemistry, Faculty of Philosophy, Sciences and Literature at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
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14
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Romero ME, McElhenney SJ, Yu J. Trapping a non-cognate nucleotide upon initial binding for replication fidelity control in SARS-CoV-2 RNA dependent RNA polymerase. Phys Chem Chem Phys 2024; 26:1792-1808. [PMID: 38168789 DOI: 10.1039/d3cp04410f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The RNA dependent RNA polymerase (RdRp) in SARS-CoV-2 is a highly conserved enzyme responsible for viral genome replication/transcription. To understand how the viral RdRp achieves fidelity control during such processes, here we computationally investigate the natural non-cognate vs. cognate nucleotide addition and selectivity during viral RdRp elongation. We focus on the nucleotide substrate initial binding (RdRp active site open) to the prechemical insertion (active site closed) of the RdRp. The current studies were first carried out using microsecond ensemble equilibrium all-atom molecular dynamics (MD) simulations. Due to the slow conformational changes (from open to closed) during nucleotide insertion and selection, enhanced or umbrella sampling methods have been further employed to calculate the free energy profiles of the nucleotide insertion. Our studies find notable stability of noncognate dATP and GTP upon initial binding in the active-site open state. The results indicate that while natural cognate ATP and Remdesivir drug analogue (RDV-TP) are biased toward stabilization in the closed state to facilitate insertion, the natural non-cognate dATP and GTP can be well trapped in off-path initial binding configurations and prevented from insertion so that to be further rejected. The current work thus presents the intrinsic nucleotide selectivity of SARS-CoV-2 RdRp for natural substrate fidelity control, which should be considered in antiviral drug design.
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Affiliation(s)
- Moises E Romero
- Department of Chemistry, University of California, Irvine, CA 92697, USA
| | | | - Jin Yu
- Department of Physics and Astronomy, Department of Chemistry, NSF-Simmons Center for Multi-scale Cell Fate Research, University of California, Irvine, CA 92697, USA.
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15
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Raubenolt B, Blankenberg D. Generalized open-source workflows for atomistic molecular dynamics simulations of viral helicases. Gigascience 2024; 13:giae026. [PMID: 38869150 PMCID: PMC11170216 DOI: 10.1093/gigascience/giae026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 03/04/2024] [Accepted: 05/06/2024] [Indexed: 06/14/2024] Open
Abstract
Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double-stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including the location of substrate binding sites, flexible domains, and the discovery of potential inhibitors. Here we present a series of new Galaxy tools and workflows for performing and analyzing molecular dynamics simulations of viral helicases. We first validate them by demonstrating recapitulation of data from previous simulations of Zika (NS3) and SARS-CoV-2 (NSP13) helicases in apo and complex with inhibitors. We further demonstrate the utility and generalizability of these Galaxy workflows by applying them to new cases, proving their usefulness as a widely accessible method for exploring antiviral activity.
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Affiliation(s)
- Bryan Raubenolt
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Daniel Blankenberg
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Center for Computational Life Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
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16
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Odunitan TT, Saibu OA, Apanisile BT, Omoboyowa DA, Balogun TA, Awe AV, Ajayi TM, Olagunju GV, Mahmoud FM, Akinboade M, Adeniji CB, Abdulazeez WO. Integrating biocomputational techniques for Breast cancer drug discovery via the HER-2, BCRA, VEGF and ER protein targets. Comput Biol Med 2024; 168:107737. [PMID: 38000249 DOI: 10.1016/j.compbiomed.2023.107737] [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: 10/05/2023] [Revised: 11/03/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023]
Abstract
Computational modelling remains an indispensable technique in drug discovery. With myriad of high computing resources, and improved modelling algorithms, there has been a high-speed in the drug development cycle with promising success rate compared to the traditional route. For example, lapatinib; a well-known anticancer drug with clinical applications was discovered with computational drug design techniques. Similarly, molecular modelling has been applied to various disease areas ranging from cancer to neurodegenerative diseases. The techniques ranges from high-throughput virtual screening, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) to molecular dynamics simulation. This review focuses on the application of computational modelling tools in the identification of drug candidates for Breast cancer. First, we begin with a succinct overview of molecular modelling in the drug discovery process. Next, we take note of special efforts on the developments and applications of combining these techniques with particular emphasis on possible breast cancer therapeutic targets such as estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), breast cancer gene 1 (BRCA1), and breast cancer gene 2 (BRCA2). Finally, we discussed the search for covalent inhibitors against these receptors using computational techniques, advances, pitfalls, possible solutions, and future perspectives.
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Affiliation(s)
- Tope T Odunitan
- Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria; Genomics Unit, Helix Biogen Institute, Ogbomoso, Oyo State, Nigeria
| | - Oluwatosin A Saibu
- Department of Chemistry and Biochemistry, New Mexico State University, Las Cruces, NM, USA.
| | - Boluwatife T Apanisile
- Department of Nutrition and Dietetics, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
| | - Damilola A Omoboyowa
- Department of Biochemistry, Adekunle Ajasin University, Akungba-Akoko, Oyo State, Nigeria
| | - Toheeb A Balogun
- Department of Biological Sciences, University of California, San Diego, CA, USA
| | - Adeyoola V Awe
- Department of Medical Laboratory Science, Lead City, University, Ibadan, Oyo State, Nigeria
| | - Temitope M Ajayi
- Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
| | - Grace V Olagunju
- Department of Molecular Biology, New Mexico State University, Las Cruces, NM, USA
| | - Fatimah M Mahmoud
- Department of Molecular Biology, New Mexico State University, Las Cruces, NM, USA
| | - Modinat Akinboade
- Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
| | - Catherine B Adeniji
- Department of Environmental Management and Toxicology, Lead City University, Ibadan, Oyo State, Nigeria
| | - Waliu O Abdulazeez
- Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
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17
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Zhao Q, Zhao Z, Zhang J, Ni Y, Ouyang S, Qi H, Yu Y, Miron RJ, Tang H, Zhang Y. Fn-HMGB1 Adsorption Behavior Initiates Early Immune Recognition and Subsequent Osteoinduction of Biomaterials. Adv Healthc Mater 2024; 13:e2301808. [PMID: 37602504 DOI: 10.1002/adhm.202301808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/11/2023] [Indexed: 08/22/2023]
Abstract
Implantable biomaterials are widely used in bone tissue engineering, but little is still known about how they initiate early immune recognition and the initial dynamics. Herein, the early immune recognition and subsequent osteoinduction of biphasic calcium phosphate (BCP) after implantation to the protein adsorption behavior is attributed. By liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis, the biomaterial-related molecular patterns (BAMPs) formed after BCP implantation are mapped, dominated by the highly expressed extracellular matrix protein fibronectin (Fn) and the high mobility group box 1 (HMGB1). Molecular dynamics simulations show that Fn has the ability to bind more readily to the BCP surface than HMGB1. The preferential binding of Fn provides a higher adsorption energy for HMGB1. Furthermore, multiple hydrogen bonding sites between HMGB1 and Fn are demonstrated using a molecular docking approach. Ultimately, the formation of BAMPs through HMGB1 antagonist glycyrrhizic acid (GA), resulting in impaired immune recognition of myeloid differentiation factor 88 (MYD88) mediated dendritic cells (DCs) and macrophages (Mφs), as well as failed osteoinduction processes is obstructed. This study introduces a mechanism for early immune recognition of implant materials based on protein adsorption, providing perspectives for future design and application of tissue engineering materials.
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Affiliation(s)
- Qin Zhao
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Zifan Zhao
- Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology; National Center of Stomatology; National Engineerœing Research Center of Oral Biomaterials and Digital Medical Devices; Beijing Key Laboratory of Digital Stomatology; Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health, National Clinical Research Center for Oral Diseases, Beijing, 100081, China
| | - Jing Zhang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Yueqi Ni
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Simin Ouyang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Haoning Qi
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Yiqian Yu
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
| | - Richard J Miron
- Department of Periodontology, University of Bern, Bern, 300392, Switzerland
| | - Hua Tang
- Department of Rheumatology and Autoimmunology, Shandong Provincial Key Laboratory for Rheumatic Disease and Translational Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, 250000, China
- Institute of Infection and Immunity, Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250000, China
| | - Yufeng Zhang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430079, China
- Medical Research Institute, School of Medicine, Wuhan University, Wuhan, 430071, China
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18
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Wu J, Lv J, Zhao L, Zhao R, Gao T, Xu Q, Liu D, Yu Q, Ma F. Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167028. [PMID: 37704131 DOI: 10.1016/j.scitotenv.2023.167028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 09/03/2023] [Accepted: 09/10/2023] [Indexed: 09/15/2023]
Abstract
Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.
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Affiliation(s)
- Jieting Wu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Jin Lv
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Lei Zhao
- State Key Laboratory of Urban Water Resources & Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Ruofan Zhao
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Tian Gao
- Key Laboratory of Integrated Regulation and Resource Development of Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Xikang Road #1, Nanjing 210098, China
| | - Qi Xu
- PetroChina Fushun Petrochemical Company, Fushun 113000, China
| | - Dongbo Liu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Qiqi Yu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Fang Ma
- State Key Laboratory of Urban Water Resources & Environment, Harbin Institute of Technology, Harbin 150090, China.
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19
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Castillo-García EL, Cossio-Ramírez AL, Córdoba-Méndez ÓA, Loza-Mejía MA, Salazar JR, Chávez-Gutiérrez E, Bautista-Poblet G, Castillo-Mendieta NT, Moreno DA, García-Viguera C, Pinto-Almazán R, Almanza-Pérez JC, Gallardo JM, Guerra-Araiza C. In Silico and In Vivo Evaluation of the Maqui Berry ( Aristotelia chilensis (Mol.) Stuntz) on Biochemical Parameters and Oxidative Stress Markers in a Metabolic Syndrome Model. Metabolites 2023; 13:1189. [PMID: 38132871 PMCID: PMC10744843 DOI: 10.3390/metabo13121189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 11/25/2023] [Accepted: 12/01/2023] [Indexed: 12/23/2023] Open
Abstract
Metabolic syndrome (MetS) is a complex disease that includes metabolic and physiological alterations in various organs such as the heart, pancreas, liver, and brain. Reports indicate that blackberry consumption, such as maqui berry, has a beneficial effect on chronic diseases such as cardiovascular disease, obesity, and diabetes. In the present study, in vivo and in silico studies have been performed to evaluate the molecular mechanisms implied to improve the metabolic parameters of MetS. Fourteen-day administration of maqui berry reduces weight gain, blood fasting glucose, total blood cholesterol, triacylglycerides, insulin resistance, and blood pressure impairment in the diet-induced MetS model in male and female rats. In addition, in the serum of male and female rats, the administration of maqui berry (MB) improved the concentration of MDA, the activity of SOD, and the formation of carbonyls in the group subjected to the diet-induced MetS model. In silico studies revealed that delphinidin and its glycosylated derivatives could be ligands of some metabolic targets such as α-glucosidase, PPAR-α, and PPAR-γ, which are related to MetS parameters. The experimental results obtained in the study suggest that even at low systemic concentrations, anthocyanin glycosides and aglycones could simultaneously act on different targets related to MetS. Therefore, these molecules could be used as coadjuvants in pharmacological interventions or as templates for designing new multitarget molecules to manage patients with MetS.
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Affiliation(s)
- Emily Leonela Castillo-García
- Unidad de Investigación Médica en Farmacología, Hospital de Especialidades Dr. Bernardo Sepúlveda, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico; (E.L.C.-G.); (G.B.-P.)
- Doctorado en Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Mexico City 52919, Mexico
| | - Ana Lizzet Cossio-Ramírez
- Maestría en Ciencias de la Salud, Sección de Estudios de Posgrado e Investigación, Escuela Superior de Medicina, Instituto Politécnico Nacional, Mexico City 11340, Mexico;
| | - Óscar Arturo Córdoba-Méndez
- Design, Isolation, and Synthesis of Bioactive Molecules Research Group, Chemical Sciences School, Universidad La Salle-México, Benjamín Franklin 45, Mexico City 06140, Mexico; (Ó.A.C.-M.); (M.A.L.-M.); (J.R.S.)
| | - Marco A. Loza-Mejía
- Design, Isolation, and Synthesis of Bioactive Molecules Research Group, Chemical Sciences School, Universidad La Salle-México, Benjamín Franklin 45, Mexico City 06140, Mexico; (Ó.A.C.-M.); (M.A.L.-M.); (J.R.S.)
| | - Juan Rodrigo Salazar
- Design, Isolation, and Synthesis of Bioactive Molecules Research Group, Chemical Sciences School, Universidad La Salle-México, Benjamín Franklin 45, Mexico City 06140, Mexico; (Ó.A.C.-M.); (M.A.L.-M.); (J.R.S.)
| | - Edwin Chávez-Gutiérrez
- Doctorado en Ciencias en Biomedicina y Biotecnología Molecular, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Prolongación Manuel Carpio y Plan de Ayala s/n, Mexico City 11340, Mexico;
| | - Guadalupe Bautista-Poblet
- Unidad de Investigación Médica en Farmacología, Hospital de Especialidades Dr. Bernardo Sepúlveda, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico; (E.L.C.-G.); (G.B.-P.)
- Doctorado en Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Mexico City 52919, Mexico
| | - Nadia Tzayaka Castillo-Mendieta
- Postdoctorate-Conacyt-Unidad de Investigación Médica en Enfermedades Neurologicas, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Av. Cuauhtémoc 330 Col. Doctores, Mexico City 06725, Mexico;
| | - Diego A. Moreno
- Laboratorio de Fitoquímica y Alimentos Saludables (LabFAS), CEBAS, CSIC. Campus Universitario de Espinardo-25, E-30100 Murcia, Spain; (D.A.M.); (C.G.-V.)
| | - Cristina García-Viguera
- Laboratorio de Fitoquímica y Alimentos Saludables (LabFAS), CEBAS, CSIC. Campus Universitario de Espinardo-25, E-30100 Murcia, Spain; (D.A.M.); (C.G.-V.)
| | - Rodolfo Pinto-Almazán
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Medicina, Instituto Politécnico Nacional, Plan de San Luis y Díaz Mirón, Mexico City 11340, Mexico
| | - Julio César Almanza-Pérez
- Laboratorio de Farmacologia, Departamento de Ciencias de la Salud, DCBS, UAM-I, Mexico City 09310, Mexico;
| | - Juan Manuel Gallardo
- Unidad de Investigación Médica en Enfermedades Nefrológicas, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico;
| | - Christian Guerra-Araiza
- Unidad de Investigación Médica en Farmacología, Hospital de Especialidades Dr. Bernardo Sepúlveda, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico; (E.L.C.-G.); (G.B.-P.)
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20
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Vassiliev P, Gusev E, Komelkova M, Kochetkov A, Dobrynina M, Sarapultsev A. Computational Analysis of CD46 Protein Interaction with SARS-CoV-2 Structural Proteins: Elucidating a Putative Viral Entry Mechanism into Human Cells. Viruses 2023; 15:2297. [PMID: 38140538 PMCID: PMC10747966 DOI: 10.3390/v15122297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
This study examines an unexplored aspect of SARS-CoV-2 entry into host cells, which is widely understood to occur via the viral spike (S) protein's interaction with human ACE2-associated proteins. While vaccines and inhibitors targeting this mechanism are in use, they may not offer complete protection against reinfection. Hence, we investigate putative receptors and their cofactors. Specifically, we propose CD46, a human membrane cofactor protein, as a potential putative receptor and explore its role in cellular invasion, acting possibly as a cofactor with other viral structural proteins. Employing computational techniques, we created full-size 3D models of human CD46 and four key SARS-CoV-2 structural proteins-EP, MP, NP, and SP. We further developed 3D models of CD46 complexes interacting with these proteins. The primary aim is to pinpoint the likely interaction domains between CD46 and these structural proteins to facilitate the identification of molecules that can block these interactions, thus offering a foundation for novel pharmacological treatments for SARS-CoV-2 infection.
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Affiliation(s)
- Pavel Vassiliev
- Laboratory for Information Technology in Pharmacology and Computer Modeling of Drugs, Research Center for Innovative Medicines, Volgograd State Medical University, 39 Novorossiyskaya Street, Volgograd 400087, Russia;
| | - Evgenii Gusev
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 106 Pervomaiskaya Street, Yekaterinburg 620049, Russia; (E.G.); (M.D.)
- Russian-Chinese Education and Research Center of System Pathology, South Ural State University, 76 Lenin Prospekt, Chelyabinsk 454080, Russia;
| | - Maria Komelkova
- Russian-Chinese Education and Research Center of System Pathology, South Ural State University, 76 Lenin Prospekt, Chelyabinsk 454080, Russia;
| | - Andrey Kochetkov
- Laboratory for Information Technology in Pharmacology and Computer Modeling of Drugs, Research Center for Innovative Medicines, Volgograd State Medical University, 39 Novorossiyskaya Street, Volgograd 400087, Russia;
| | - Maria Dobrynina
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 106 Pervomaiskaya Street, Yekaterinburg 620049, Russia; (E.G.); (M.D.)
| | - Alexey Sarapultsev
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 106 Pervomaiskaya Street, Yekaterinburg 620049, Russia; (E.G.); (M.D.)
- Russian-Chinese Education and Research Center of System Pathology, South Ural State University, 76 Lenin Prospekt, Chelyabinsk 454080, Russia;
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21
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Singh VK, Thakur DC, Rajak N, Mishra A, Kumar A, Giri R, Garg N. The multi-protein targeting potential of bioactive syringin in inflammatory diseases: using molecular modelling and in-silico analysis of regulatory elements. J Biomol Struct Dyn 2023:1-12. [PMID: 37882327 DOI: 10.1080/07391102.2023.2273440] [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: 08/02/2023] [Accepted: 10/14/2023] [Indexed: 10/27/2023]
Abstract
Inflammation plays a crucial role in the onset or progression of a variety of acute and chronic diseases. Non-steroidal anti-inflammatory drugs (NSAIDs) are the only available FDA-approved therapy. The therapeutic outcome of NSAIDs is still finite due to off-target effects and extreme side effects on other vital organs. Bioactive syringin has been manifested to hold anti-osteoporosis, cardiac hypertrophy, alter autophagy, anti-cancer, neuro-preventive effects, etc. However, its multi-protein targeting potential in inflammation mostly remains unexplored. In the present work, we have checked the multi-protein targeting potential of bioactive glycoside syringin in inflammatory diseases. Based on the binding score of protein-ligand complexes, glycoside syringin scored greater than -7 kcal/mol against 12 inflammatory proteins. Our molecular dynamic simulation study (200 ns) confirmed that bioactive syringin remained inside the binding cavity of inflammatory proteins (JAK1, TYK2, and COX1) in a stable conformation. Further, our co-expression analysis suggests that these genes play an essential role in multiple pathways and are regulated by multiple miRNAs. Our study demonstrates that bioactive glycoside syringin might be a multi-protein targeting potential against inflammatory diseases and could be further investigated utilizing different preclinical approaches.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Vipendra Kumar Singh
- School of Biosciences and Bioengineering, Indian Institute of Technology Mandi, Mandi, India
| | - D C Thakur
- School of Biosciences and Bioengineering, Indian Institute of Technology Mandi, Mandi, India
| | - Naina Rajak
- Faculty of Ayurveda, Department of Medicinal Chemistry, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Anand Mishra
- Molecular Plant Pathology Laboratory, CSIR-Institute of Himalayan Bioresource Technology, Palampur, India
| | - Ankur Kumar
- School of Biosciences and Bioengineering, Indian Institute of Technology Mandi, Mandi, India
| | - Rajanish Giri
- School of Biosciences and Bioengineering, Indian Institute of Technology Mandi, Mandi, India
| | - Neha Garg
- Faculty of Ayurveda, Department of Medicinal Chemistry, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
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22
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Pant P, Leese F. Probing the Nucleic Acid Flexibility to Disarm the Viral Counter-Defense Machinery: Design and Characterization of Potent p19 Inhibitors. J Phys Chem B 2023; 127:8842-8851. [PMID: 37797202 DOI: 10.1021/acs.jpcb.3c04788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Plant viruses are highly destructive and significant contributors to several global pandemics and epidemics in plants. A viral disease outbreak in plants can cause a scarcity of food supply and is a severe concern to humanity. The siRNA (small interfering RNA)-mediated RNA-induced silencing complex (RISC) formation is a primary defense mechanism in plants against viruses, where the RISC binds and degrades viral mRNAs. As a counter-defense, many viruses encode RNA-silencing suppressor proteins (e.g., the p19 protein from the Tombusviridae family) for viral proliferation in plants. The functional form of p19 (homodimer) binds to plant siRNA with high affinities, thereby interrupting the RISC formation and thus preventing the viral mRNA silencing in plants. By altering the RISC formation, the p19 protein helps the virus invasion in the plant and ultimately stunts host growth. In this study, we designed several modified siRNA-based molecules for p19 inhibition. The viral p19 protein is known to interact predominantly through H-bonds with 2'-OH and phosphates of the plant siRNA. We utilized this information and in silico-designed flexible substituents of siRNA, where we removed the C2'-C3' bond in each nucleotide unit. We performed all-atom explicit-solvent molecular dynamics simulations (400 ns, 3 replicates each) for control/modified siRNA─p19 complexes (8 in total) followed by energetic estimations. Strikingly, in a few modified complexes, the siRNA not only retained the double-helical structural integrity but also displayed remarkably enhanced p19 binding compared to the control siRNA; hence, we consider it important to perform biological and chemical in vitro and in vivo studies on proposed flexible nucleic acids as p19 inhibitors for crop protection.
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Affiliation(s)
- Pradeep Pant
- Faculty of Biology, University of Duisburg Essen, Essen 45141, Germany
| | - Florian Leese
- Faculty of Biology, University of Duisburg Essen, Essen 45141, Germany
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23
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Orlando C, Prejanò M, Russo N, Marino T. On the Role of Temperature in the Depolymerization of PET by FAST-PETase: An Atomistic Point of View on Possible Active Site Pre-Organization and Substrate-Destabilization Effects. Chembiochem 2023; 24:e202300412. [PMID: 37556192 DOI: 10.1002/cbic.202300412] [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: 06/21/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 08/10/2023]
Abstract
Enzyme FAST-PETase, recently obtained by a machine learning approach, can depolymerize poly(ethylene terephthalate) (PET), a synthetic resin employed in plastics and in clothing fibers. Therefore it represents a promising solution for the recycling of PET-based materials. In this study, a model of PET was adopted to describe the substrate, and all-atoms classical molecular dynamics (MD) simulations on apo- and substrate-bound FAST-PETase were carried out at 30 and 50 °C to provide atomistic details on the binding step of the catalytic cycle. Comparative analysis shed light on the interactions occurring between the FAST-PETase and 4PET at 50 °C, the optimal working conditions of the enzyme. Pre-organization of the enzyme active and binding sites has been highlighted, while MD simulations of FAST-PETase:4PET pointed out the occurrence of solvent-inaccessible conformations of the substrate promoted by the enzyme. Indeed, neither of these conformations was observed during MD simulations of the substrate alone in solution performed at 30, 50 and 150 °C. The analysis led us to propose that, at 50 °C, the FAST-PETase is pre-organized to bind the PET and that the interactions occurring in the binding site can promote a more reactive conformation of PET substrate, thus enhancing the catalytic activity of the enzyme.
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Affiliation(s)
- Carla Orlando
- Dipartimento di Chimica e Tecnologie Chimiche Laboratorio PROMOCS cubo 14C, Università della Calabria, 87036, Rende (CS), Italy
| | - Mario Prejanò
- Dipartimento di Chimica e Tecnologie Chimiche Laboratorio PROMOCS cubo 14C, Università della Calabria, 87036, Rende (CS), Italy
| | - Nino Russo
- Dipartimento di Chimica e Tecnologie Chimiche Laboratorio PROMOCS cubo 14C, Università della Calabria, 87036, Rende (CS), Italy
| | - Tiziana Marino
- Dipartimento di Chimica e Tecnologie Chimiche Laboratorio PROMOCS cubo 14C, Università della Calabria, 87036, Rende (CS), Italy
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24
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Akash S, Bayıl I, Hossain MS, Islam MR, Hosen ME, Mekonnen AB, Nafidi HA, Bin Jardan YA, Bourhia M, Bin Emran T. Novel computational and drug design strategies for inhibition of human papillomavirus-associated cervical cancer and DNA polymerase theta receptor by Apigenin derivatives. Sci Rep 2023; 13:16565. [PMID: 37783745 PMCID: PMC10545697 DOI: 10.1038/s41598-023-43175-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/20/2023] [Indexed: 10/04/2023] Open
Abstract
The present study deals with the advanced in-silico analyses of several Apigenin derivatives to explore human papillomavirus-associated cervical cancer and DNA polymerase theta inhibitor properties by molecular docking, molecular dynamics, QSAR, drug-likeness, PCA, a dynamic cross-correlation matrix and quantum calculation properties. The initial literature study revealed the potent antimicrobial and anticancer properties of Apigenin, prompting the selection of its potential derivatives to investigate their abilities as inhibitors of human papillomavirus-associated cervical cancer and DNA polymerase theta. In silico molecular docking was employed to streamline the findings, revealing promising energy-binding interactions between all Apigenin derivatives and the targeted proteins. Notably, Apigenin 4'-O-Rhamnoside and Apigenin-4'-Alpha-L-Rhamnoside demonstrated higher potency against the HPV45 oncoprotein E7 (PDB ID 2EWL), while Apigenin and Apigenin 5-O-Beta-D-Glucopyranoside exhibited significant binding energy against the L1 protein in humans. Similarly, a binding affinity range of - 7.5 kcal/mol to - 8.8 kcal/mol was achieved against DNA polymerase theta, indicating the potential of Apigenin derivatives to inhibit this enzyme (PDB ID 8E23). This finding was further validated through molecular dynamic simulation for 100 ns, analyzing parameters such as RMSD, RMSF, SASA, H-bond, and RoG profiles. The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADMET, pharmacokinetics, and drug-likeness properties, fulfilling all the necessary criteria. QSAR, PCA, dynamic cross-correlation matrix, and quantum calculations were conducted, yielding satisfactory outcomes. Since this study utilized in silico computational approaches and obtained outstanding results, further validation is crucial. Therefore, additional wet-lab experiments should be conducted under in vivo and in vitro conditions to confirm the findings.
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Affiliation(s)
- Shopnil Akash
- Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Birulia, Ashulia, Dhaka, 1216, Bangladesh.
| | - Imren Bayıl
- Department of Bioinformatics and Computational Biology, Gaziantep University, Gaziantep, Turkey
| | - Md Saddam Hossain
- Department of Biomedical Engineering, Faculty of Engineering & Technology, Islamic University, Kushtia, Bangladesh
| | - Md Rezaul Islam
- Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Birulia, Ashulia, Dhaka, 1216, Bangladesh
| | - Md Eram Hosen
- Professor Joarder DNA and Chromosome Research Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | | | - Hiba-Allah Nafidi
- Department of Food Science, Faculty of Agricultural and Food Sciences, Laval University, 2325, Quebec City, QC, G1V 0A6, Canada
| | - Yousef A Bin Jardan
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Mohammed Bourhia
- Department of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, 70000, Laayoune, Morocco
| | - Talha Bin Emran
- Department of Pathology and Laboratory Medicine, Warren Alpert Medical School & Legorreta Cancer Center, Brown University, Providence, RI 02912, United States.
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25
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Conflitti P, Raniolo S, Limongelli V. Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness. J Chem Theory Comput 2023; 19:6047-6061. [PMID: 37656199 PMCID: PMC10536999 DOI: 10.1021/acs.jctc.3c00641] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Indexed: 09/02/2023]
Abstract
Computational techniques applied to drug discovery have gained considerable popularity for their ability to filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus of these studies has historically been the search for compounds endowed with high affinity for a specific molecular target to ensure the formation of stable and long-lasting complexes. Recent evidence has also correlated the in vivo drug efficacy with its binding kinetics, thus opening new fascinating scenarios for ligand/protein binding kinetic simulations in drug discovery. The present article examines the state of the art in the field, providing a brief summary of the most popular and advanced ligand/protein binding kinetics techniques and evaluating their current limitations and the potential solutions to reach more accurate kinetic models. Particular emphasis is put on the need for a paradigm change in the present methodologies toward ligand and protein parametrization, the force field problem, characterization of the transition states, the sampling issue, and algorithms' performance, user-friendliness, and data openness.
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Affiliation(s)
- Paolo Conflitti
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
| | - Stefano Raniolo
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
| | - Vittorio Limongelli
- Faculty
of Biomedical Sciences, Euler Institute, Universitá della Svizzera italiana (USI), 6900 Lugano, Switzerland
- Department
of Pharmacy, University of Naples “Federico
II”, 80131 Naples, Italy
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26
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Wijker S, Palmans ARA. Protein-Inspired Control over Synthetic Polymer Folding for Structured Functional Nanoparticles in Water. Chempluschem 2023; 88:e202300260. [PMID: 37417828 DOI: 10.1002/cplu.202300260] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/06/2023] [Accepted: 07/06/2023] [Indexed: 07/08/2023]
Abstract
The folding of proteins into functional nanoparticles with defined 3D structures has inspired chemists to create simple synthetic systems mimicking protein properties. The folding of polymers into nanoparticles in water proceeds via different strategies, resulting in the global compaction of the polymer chain. Herein, we review the different methods available to control the conformation of synthetic polymers and collapse/fold them into structured, functional nanoparticles, such as hydrophobic collapse, supramolecular self-assembly, and covalent cross-linking. A comparison is made between the design principles of protein folding to synthetic polymer folding and the formation of structured nanocompartments in water, highlighting similarities and differences in design and function. We also focus on the importance of structure for functional stability and diverse applications in complex media and cellular environments.
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Affiliation(s)
- Stefan Wijker
- Institute for Complex Molecular Systems, Laboratory of Macromolecular and Organic Chemistry, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands
| | - Anja R A Palmans
- Institute for Complex Molecular Systems, Laboratory of Macromolecular and Organic Chemistry, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands
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27
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pour PM, Mahnam K, Taherzadeh M, Ahangarzadeh S, Alibakhshi A, Mohammadi E. The effect of mutation on neurotoxicity reduction of new chimeric reteplase, a computational study. Res Pharm Sci 2023; 18:404-412. [PMID: 37614611 PMCID: PMC10443662 DOI: 10.4103/1735-5362.378087] [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: 09/27/2022] [Revised: 11/23/2022] [Accepted: 05/27/2022] [Indexed: 08/25/2023] Open
Abstract
Background and purpose Excitotoxicity in nerve cells is a type of neurotoxicity in which excessive stimulation of receptors (such as N-methyl-d-aspartate glutamate receptors (NMDAR)) leads to the influx of high-level calcium ions into cells and finally cell damage or death. This complication can occur after taking some of the plasminogen activators like tissue plasminogen activator and reteplase. The interaction of the kringle2 domain in such plasminogen activator with the amino-terminal domain (ATD) of the NR1 subunit of NMDAR finally leads to excitotoxicity. In this study, we assessed the interaction of two new chimeric reteplase, mutated in the kringle2 domain, with ATD and compared the interaction of wild-type reteplase with ATD, computationally. Experimental approach Homology modeling, protein docking, molecular dynamic simulation, and molecular dynamics trajectory analysis were used for the assessment of this interaction. Findings/Results The results of the free energy analysis between reteplase and ATD (wild reteplase: -2127.516 ± 0.0, M1-chr: -1761.510 ± 0.0, M2-chr: -521.908 ± 0.0) showed lower interaction of this chimeric reteplase with ATD compared to the wild type. Conclusion and implications The decreased interaction between two chimeric reteplase and ATD of NR1 subunit in NMDAR which leads to lower neurotoxicity related to these drugs, can be the start of a way to conduct more tests and if the results confirm this feature, they can be considered potential drugs in acute ischemic stroke treatment.
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Affiliation(s)
- Pardis Mohammadi pour
- Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Karim Mahnam
- Biology Department, Faculty of Science, Shahrekord University, Shahrekord, Iran
| | - Mahsa Taherzadeh
- Department of Anatomy and Cell Biology, McGill University, Montreal, H3A 0C7, QC, Canada
| | - Shahrzad Ahangarzadeh
- Infectious Diseases and Tropical Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Abbas Alibakhshi
- Molecular Medicine Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Elmira Mohammadi
- Core Research Facilities, Isfahan University of Medical Sciences, Isfahan, Iran
- Applied Physiology Research Center, Cardiovascular Research Institute, Department of Physiology, Isfahan University of Medical Sciences, Isfahan, Iran
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28
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Mu ZC, Tan YL, Liu J, Zhang BG, Shi YZ. Computational Modeling of DNA 3D Structures: From Dynamics and Mechanics to Folding. Molecules 2023; 28:4833. [PMID: 37375388 DOI: 10.3390/molecules28124833] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/11/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023] Open
Abstract
DNA carries the genetic information required for the synthesis of RNA and proteins and plays an important role in many processes of biological development. Understanding the three-dimensional (3D) structures and dynamics of DNA is crucial for understanding their biological functions and guiding the development of novel materials. In this review, we discuss the recent advancements in computer methods for studying DNA 3D structures. This includes molecular dynamics simulations to analyze DNA dynamics, flexibility, and ion binding. We also explore various coarse-grained models used for DNA structure prediction or folding, along with fragment assembly methods for constructing DNA 3D structures. Furthermore, we also discuss the advantages and disadvantages of these methods and highlight their differences.
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Affiliation(s)
- Zi-Chun Mu
- Research Center of Nonlinear Science, School of Mathematical & Physical Sciences, Wuhan Textile University, Wuhan 430073, China
- School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan 430073, China
| | - Ya-Lan Tan
- Research Center of Nonlinear Science, School of Mathematical & Physical Sciences, Wuhan Textile University, Wuhan 430073, China
| | - Jie Liu
- Research Center of Nonlinear Science, School of Mathematical & Physical Sciences, Wuhan Textile University, Wuhan 430073, China
| | - Ben-Gong Zhang
- Research Center of Nonlinear Science, School of Mathematical & Physical Sciences, Wuhan Textile University, Wuhan 430073, China
| | - Ya-Zhou Shi
- Research Center of Nonlinear Science, School of Mathematical & Physical Sciences, Wuhan Textile University, Wuhan 430073, China
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29
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Bassani D, Moro S. Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies. Molecules 2023; 28:molecules28093906. [PMID: 37175316 PMCID: PMC10180087 DOI: 10.3390/molecules28093906] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 04/28/2023] [Accepted: 05/02/2023] [Indexed: 05/15/2023] Open
Abstract
The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.
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Affiliation(s)
- Davide Bassani
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy
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30
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Chen Z, Wang X, Chen X, Huang J, Wang C, Wang J, Wang Z. Accelerating therapeutic protein design with computational approaches toward the clinical stage. Comput Struct Biotechnol J 2023; 21:2909-2926. [PMID: 38213894 PMCID: PMC10781723 DOI: 10.1016/j.csbj.2023.04.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 01/13/2024] Open
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
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Affiliation(s)
- Zhidong Chen
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Juyang Huang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen 518107, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
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31
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Fiorentini R, Tarenzi T, Potestio R. Fast, Accurate, and System-Specific Variable-Resolution Modeling of Proteins. J Chem Inf Model 2023; 63:1260-1275. [PMID: 36735551 PMCID: PMC9976289 DOI: 10.1021/acs.jcim.2c01311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Indexed: 02/04/2023]
Abstract
In recent years, a few multiple-resolution modeling strategies have been proposed, in which functionally relevant parts of a biomolecule are described with atomistic resolution, with the remainder of the system being concurrently treated using a coarse-grained model. In most cases, the parametrization of the latter requires lengthy reference all-atom simulations and/or the usage of off-shelf coarse-grained force fields, whose interactions have to be refined to fit the specific system under examination. Here, we overcome these limitations through a novel multiresolution modeling scheme for proteins, dubbed coarse-grained anisotropic network model for variable resolution simulations, or CANVAS. This scheme enables a user-defined modulation of the resolution level throughout the system structure; a fast parametrization of the potential without the necessity of reference simulations; and the straightforward usage of the model on the most commonly used molecular dynamics platforms. The method is presented and validated with two case studies, the enzyme adenylate kinase and the therapeutic antibody pembrolizumab, by comparing the results obtained with the CANVAS model against fully atomistic simulations. The modeling software, implemented in Python, is made freely available for the community on a collaborative github repository.
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Affiliation(s)
- Raffaele Fiorentini
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Thomas Tarenzi
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Raffaello Potestio
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
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32
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Das NC, Chakraborty P, Bayry J, Mukherjee S. Comparative Binding Ability of Human Monoclonal Antibodies against Omicron Variants of SARS-CoV-2: An In Silico Investigation. Antibodies (Basel) 2023; 12:antib12010017. [PMID: 36975364 PMCID: PMC10045060 DOI: 10.3390/antib12010017] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 02/26/2023] Open
Abstract
Mutation(s) in the spike protein is the major characteristic trait of newly emerged SARS-CoV-2 variants such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Delta-plus. Omicron (B.1.1.529) is the latest addition and it has been characterized by high transmissibility and the ability to escape host immunity. Recently developed vaccines and repurposed drugs exert limited action on Omicron strains and hence new therapeutics are immediately needed. Herein, we have explored the efficiency of twelve therapeutic monoclonal antibodies (mAbs) targeting the RBD region of the spike glycoprotein against all the Omicron variants bearing a mutation in spike protein through molecular docking and molecular dynamics simulation. Our in silico evidence reveals that adintivimab, beludivimab, and regadanivimab are the most potent mAbs to form strong biophysical interactions and neutralize most of the Omicron variants. Considering the efficacy of mAbs, we incorporated CDRH3 of beludavimab within the framework of adintrevimab, which displayed a more intense binding affinity towards all of the Omicron variants viz. BA.1, BA.2, BA.2.12.1, BA.4, and BA.5. Furthermore, the cDNA of chimeric mAb was cloned in silico within pET30ax for recombinant production. In conclusion, the present study represents the candidature of human mAbs (beludavimab and adintrevimab) and the therapeutic potential of designed chimeric mAb for treating Omicron-infected patients.
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Affiliation(s)
- Nabarun Chandra Das
- Integrative Biochemistry & Immunology Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol 713 340, India
| | - Pritha Chakraborty
- Integrative Biochemistry & Immunology Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol 713 340, India
| | - Jagadeesh Bayry
- Department of Biological Sciences & Engineering, Indian Institute of Technology Palakkad, Palakkad 678 623, India
- Correspondence: (J.B.); or (S.M.)
| | - Suprabhat Mukherjee
- Integrative Biochemistry & Immunology Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol 713 340, India
- Correspondence: (J.B.); or (S.M.)
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33
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Fan Y, Xia W, Ma C, Huang Y, Li S, Wang X, Qian C, Chen K, Liu D. Recent advances of computational studies on bioethanol to light olefin reactions using zeolite and metal oxide catalysts. Chem Eng Sci 2023. [DOI: 10.1016/j.ces.2023.118532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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34
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Kou X, Zhang Y, Su D, Wang H, Huang X, Niu Y, Ke Q, Xiao Z, Meng Q. Study on host-guest interaction of aroma compounds/γ-cyclodextrin inclusion complexes. Lebensm Wiss Technol 2023. [DOI: 10.1016/j.lwt.2023.114589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
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35
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Oliva F, Musiani F, Giorgetti A, De Rubeis S, Sorokina O, Armstrong DJ, Carloni P, Ruggerone P. Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases. Front Chem 2023; 10:1059593. [PMID: 36700074 PMCID: PMC9868658 DOI: 10.3389/fchem.2022.1059593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 12/06/2022] [Indexed: 01/11/2023] Open
Abstract
The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the isoforms onto which mutations should be mapped due to there being several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task needs to be automatized. Here we present the MoNvIso (Modelling eNvironment for Isoforms) code, which identifies the most useful isoform for computational modelling, balancing the coverage of mutations of interest and the availability of templates to build a structural model of both the wild-type isoform and the related variants.
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Affiliation(s)
- Francesco Oliva
- Department of Physics, University of Cagliari, Monserrato (CA), Italy,Institute of Neuroscience and Medicine INM-9, Institute for Advanced Simulations IAS-5, Forschungszentrum Jülich, Jülich, Germany
| | - Francesco Musiani
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Alejandro Giorgetti
- Institute of Neuroscience and Medicine INM-9, Institute for Advanced Simulations IAS-5, Forschungszentrum Jülich, Jülich, Germany,Department of Biotechnology, University of Verona, Verona, Italy
| | - Silvia De Rubeis
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, United States,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States,The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Oksana Sorokina
- The School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Douglas J. Armstrong
- Institute of Neuroscience and Medicine INM-9, Institute for Advanced Simulations IAS-5, Forschungszentrum Jülich, Jülich, Germany,The School of Informatics, University of Edinburgh, Edinburgh, United Kingdom,Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, United Kingdom
| | - Paolo Carloni
- Institute of Neuroscience and Medicine INM-9, Institute for Advanced Simulations IAS-5, Forschungszentrum Jülich, Jülich, Germany,Department of Physics, RWTH Aachen University, Aachen, Germany,JARA-Institute: Molecular Neuroscience and Neuroimaging, Institute for Neuroscience and Medicine INM-11/JARA-BRAIN Institute JBI-2, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Paolo Ruggerone
- Department of Physics, University of Cagliari, Monserrato (CA), Italy,*Correspondence: Paolo Ruggerone,
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36
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Schuhmann F, Ryvkin L, McLaren JD, Gerhards L, Solov'yov IA. Across atoms to crossing continents: Application of similarity measures to biological location data. PLoS One 2023; 18:e0284736. [PMID: 37186599 PMCID: PMC10184918 DOI: 10.1371/journal.pone.0284736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 04/06/2023] [Indexed: 05/17/2023] Open
Abstract
Biological processes involve movements across all measurable scales. Similarity measures can be applied to compare and analyze these movements but differ in how differences in movement are aggregated across space and time. The present study reviews frequently-used similarity measures, such as the Hausdorff distance, Fréchet distance, Dynamic Time Warping, and Longest Common Subsequence, jointly with several measures less used in biological applications (Wasserstein distance, weak Fréchet distance, and Kullback-Leibler divergence), and provides computational tools for each of them that may be used in computational biology. We illustrate the use of the selected similarity measures in diagnosing differences within two extremely contrasting sets of biological data, which, remarkably, may both be relevant for magnetic field perception by migratory birds. Specifically, we assess and discuss cryptochrome protein conformational dynamics and extreme migratory trajectories of songbirds between Alaska and Africa. We highlight how similarity measures contrast regarding computational complexity and discuss those which can be useful in noise elimination or, conversely, are sensitive to spatiotemporal scales.
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Affiliation(s)
- Fabian Schuhmann
- Department of Physics, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Leonie Ryvkin
- Department of Mathematics & Computer Science, Technische Universiteit Eindhoven, Eindhoven, Netherlands
- Department of Computer Science, Ruhr-Universität Bochum, Bochum, Germany
| | - James D McLaren
- Institute of Chemistry and Marine Biology, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Luca Gerhards
- Department of Physics, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Ilia A Solov'yov
- Department of Physics, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
- Research Centre for Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
- Center for Nanoscale Dynamics (CENAD), Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
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37
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Dolezal R. Accuracy and precision of binding free energy prediction for a tacrine related lead inhibitor of acetylcholinesterase with an arsenal of supercomputerized molecular modelling methods: a comparative study. J Biomol Struct Dyn 2022; 40:11291-11319. [PMID: 34323654 DOI: 10.1080/07391102.2021.1957716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Nowadays, advanced computational chemistry methods offer various strategies for revealing prospective hit structures in drug development essentially through accurate binding free energy predictions. After the era of molecular docking and quantitative structure-activity relationships, much interest has been lately oriented to perturbed molecular dynamic approaches like replica exchange with solute tempering and free energy perturbation (REST/FEP) and the potential of the mean force with adaptive biasing and accelerated weight histograms (PMF/AWH). Both of these receptor-based techniques can exploit exascale CPU&GPU supercomputers to achieve high throughput performance. In this fundamental study, we have compared the predictive power of a panel of supercomputerized molecular modelling methods to distinguish the major binding modes and the corresponding binding free energies of a promising tacrine related potential antialzheimerics in human acetylcholinesterase. The binding free energies were estimated using flexible molecular docking, molecular mechanics/generalized Born surface area/Poisson-Boltzmann surface area (MM/GBSA/PBSA), transmutation REST/FEP with 12 x 5 ns/λ windows, annihilation FEP with 20 x 5 ns/λ steps, PMF with weight histogram analysis method (WHAM) and 40 x 5 ns samples, and PMF/AWH with 10 x 100 ns replicas. Confrontation of the classical approaches such as canonical molecular dynamics and molecular docking with alchemical calculations and steered molecular dynamics enabled us to show how large errors in ΔG predictions can be expected if these in silico methods are employed in the elucidation of a common case of enzyme inhibition.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rafael Dolezal
- Department of Chemistry, Faculty of Science, University of Hradec Kralove, Hradec Kralove, Czech Republic.,Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic
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38
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In Vitro, In Silico and Network Pharmacology Mechanistic Approach to Investigate the α-Glucosidase Inhibitors Identified by Q-ToF-LCMS from Phaleria macrocarpa Fruit Subcritical CO 2 Extract. Metabolites 2022; 12:metabo12121267. [PMID: 36557305 PMCID: PMC9783102 DOI: 10.3390/metabo12121267] [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: 11/10/2022] [Revised: 11/30/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
The fruit of Phaleria macrocarpa have been traditionally used as an antidiabetic remedy in Malaysia and neighbouring countries. Despite its potential for diabetes treatment, no scientific study has ever been conducted to predict the inhibitor interaction of the protein α-glucosidase identified in an extract prepared with a non-conventional extraction technique. Hence, the major aim of this research was to evaluate the in vitro antioxidant, the α-glucosidase inhibitors, and the molecular dynamic simulations of the α-glucosidase inhibitors identified by Quadrupole Time-of-Flight Liquid Chromatography Mass Spectrometry (Q-ToF-LCMS) analysis. Initially, dry fruit were processed using non-conventional and conventional extraction methods to obtain subcritical carbon dioxide extracts (SCE-1 and SCE-2) and heating under reflux extract (HRE), respectively. Subsequently, all extracts were evaluated for their in vitro antioxidative and α-glucosidase inhibitory potentials. Subsequently, the most bioactive extract (SCE-2) was subjected to Q-ToF-LCMS analysis to confirm the presence of α-glucosidase inhibitors, which were then analysed through molecular dynamic simulations and network pharmacology approaches to confirm their possible mechanism of action. The highest inhibitory effects of the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and α-glucosidase on SCE-2 was found as 75.36 ± 0.82% and 81.79 ± 0.82%, respectively, compared to the SCE-1 and HRE samples. The Q-ToF-LCMS analysis tentatively identified 14 potent α-glucosidase inhibitors. Finally, five identified compounds, viz., lupenone, swertianolin, m-coumaric acid, pantothenic acid, and 8-C-glucopyranosyleriodictylol displayed significant stability, compactness, stronger protein-ligand interaction up to 100 ns further confirming their potential as α-glucosidase inhibitors. Consequently, it was concluded that the SCE-2 possesses a strong α-glucosidase inhibitory effect due to the presence of these compounds. The findings of this study might prove useful to develop these compounds as alternative safe α-glucosidase inhibitors to manage diabetes more effectively.
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39
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Gong S, He X, Meng Q, Ma Z, Shao B, Wang T, Liu TY. Stochastic Lag Time Parameterization for Markov State Models of Protein Dynamics. J Phys Chem B 2022; 126:9465-9475. [PMID: 36345778 DOI: 10.1021/acs.jpcb.2c03711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Markov state models (MSMs) play a key role in studying protein conformational dynamics. A sliding count window with a fixed lag time is widely used to sample sub-trajectories for transition counting and MSM construction. However, sub-trajectories sampled with a fixed lag time may not perform well under different selections of lag time, which requires strong prior practice and leads to less robust estimation. To alleviate it, we propose a novel stochastic method from a Poisson process to generate perturbative lag time for sub-trajectory sampling and utilize it to construct a Markov chain. Comprehensive evaluations on the double-well system, WW domain, BPTI, and RBD-ACE2 complex of SARS-CoV-2 reveal that our algorithm significantly increases the robustness and power of a constructed MSM without disturbing the Markovian properties. Furthermore, the superiority of our algorithm is amplified for slow dynamic modes in complex biological processes.
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Affiliation(s)
- Shiqi Gong
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhongguancun East Road, Beijing100190, China.,University of Chinese Academy of Sciences, No. 19 Yuquan Road, Beijing100049, China.,Microsoft Research AI4Science, Beijing100080, China
| | - Xinheng He
- University of Chinese Academy of Sciences, No. 19 Yuquan Road, Beijing100049, China.,Microsoft Research AI4Science, Beijing100080, China.,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai201203, China
| | - Qi Meng
- Microsoft Research AI4Science, Beijing100080, China
| | - Zhiming Ma
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhongguancun East Road, Beijing100190, China.,University of Chinese Academy of Sciences, No. 19 Yuquan Road, Beijing100049, China
| | - Bin Shao
- Microsoft Research AI4Science, Beijing100080, China
| | - Tong Wang
- Microsoft Research AI4Science, Beijing100080, China
| | - Tie-Yan Liu
- Microsoft Research AI4Science, Beijing100080, China
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40
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Zhou Y, Wu J, Xue G, Li J, Jiang L, Huang M. Structural study of the uPA-nafamostat complex reveals a covalent inhibitory mechanism of nafamostat. Biophys J 2022; 121:3940-3949. [PMID: 36039386 PMCID: PMC9674978 DOI: 10.1016/j.bpj.2022.08.034] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/02/2022] [Accepted: 08/24/2022] [Indexed: 11/23/2022] Open
Abstract
Nafamostat mesylate (NM) is a synthetic compound that inhibits various serine proteases produced during the coagulation cascade and inflammation. Previous studies showed that NM was a highly safe drug for the treatment of different cancers, but the precise functions and mechanisms of NM are not clear. In this study, we determined a series of crystal structures of NM and its hydrolysates in complex with a serine protease (urokinase-type plasminogen activator [uPA]). These structures reveal that NM was cleaved by uPA and that a hydrolyzed product (4-guanidinobenzoic acid [GBA]) remained covalently linked to Ser195 of uPA, and the other hydrolyzed product (6-amidino-2-naphthol [6A2N]) released from uPA. Strikingly, in the inactive uPA (uPA-S195A):NM structure, the 6A2N side of intact NM binds to the specific pocket of uPA. Molecular dynamics simulations and end-point binding free-energy calculations show that the conf1 of NM (6A2N as P1 group) in the uPA-S195A:NM complex may be more stable than conf2 of NM (GBA as P1 group). Moreover, in the structure of uPA:NM complex, the imidazole group of His57 flips further away from Ser195 and disrupts the stable canonical catalytic triad conformation. These results not only reveal the inhibitory mechanism of NM as an efficient serine protease inhibitor but also might provide the structural basis for the further development of serine protease inhibitors.
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Affiliation(s)
- Yang Zhou
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China
| | - Juhong Wu
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China
| | - Guangpu Xue
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China
| | - Jinyu Li
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China
| | - Longguang Jiang
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China; Fujian Key Laboratory of Marine Enzyme Engineering, Fuzhou University, Fuzhou, Fujian, P.R. China.
| | - Mingdong Huang
- College of Chemistry, Fuzhou University, Fuzhou, Fujian, P.R. China.
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41
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Conformational Stability and Denaturation Processes of Proteins Investigated by Electrophoresis under Extreme Conditions. Molecules 2022; 27:molecules27206861. [PMID: 36296453 PMCID: PMC9610776 DOI: 10.3390/molecules27206861] [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: 09/09/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/17/2022] Open
Abstract
The functional structure of proteins results from marginally stable folded conformations. Reversible unfolding, irreversible denaturation, and deterioration can be caused by chemical and physical agents due to changes in the physicochemical conditions of pH, ionic strength, temperature, pressure, and electric field or due to the presence of a cosolvent that perturbs the delicate balance between stabilizing and destabilizing interactions and eventually induces chemical modifications. For most proteins, denaturation is a complex process involving transient intermediates in several reversible and eventually irreversible steps. Knowledge of protein stability and denaturation processes is mandatory for the development of enzymes as industrial catalysts, biopharmaceuticals, analytical and medical bioreagents, and safe industrial food. Electrophoresis techniques operating under extreme conditions are convenient tools for analyzing unfolding transitions, trapping transient intermediates, and gaining insight into the mechanisms of denaturation processes. Moreover, quantitative analysis of electrophoretic mobility transition curves allows the estimation of the conformational stability of proteins. These approaches include polyacrylamide gel electrophoresis and capillary zone electrophoresis under cold, heat, and hydrostatic pressure and in the presence of non-ionic denaturing agents or stabilizers such as polyols and heavy water. Lastly, after exposure to extremes of physical conditions, electrophoresis under standard conditions provides information on irreversible processes, slow conformational drifts, and slow renaturation processes. The impressive developments of enzyme technology with multiple applications in fine chemistry, biopharmaceutics, and nanomedicine prompted us to revisit the potentialities of these electrophoretic approaches. This feature review is illustrated with published and unpublished results obtained by the authors on cholinesterases and paraoxonase, two physiologically and toxicologically important enzymes.
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42
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Berselli A, Benfenati F, Maragliano L, Alberini G. Multiscale modelling of claudin-based assemblies: a magnifying glass for novel structures of biological interfaces. Comput Struct Biotechnol J 2022; 20:5984-6010. [DOI: 10.1016/j.csbj.2022.10.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/24/2022] [Accepted: 10/24/2022] [Indexed: 11/03/2022] Open
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43
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Lenard AJ, Mulder FAA, Madl T. Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:113-139. [PMID: 36496256 DOI: 10.1016/j.pnmrs.2022.09.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 06/17/2023]
Abstract
Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.
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Affiliation(s)
- Aneta J Lenard
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Ageing, Molecular Biology and Biochemistry, Research Unit Integrative Structural Biology, Medical University of Graz, 8010 Graz, Austria.
| | - Frans A A Mulder
- Interdisciplinary Nanoscience Center and Department of Chemistry, University of Aarhus, DK-8000 Aarhus, Denmark; Institute of Biochemistry, Johannes Kepler Universität Linz, 4040 Linz, Austria.
| | - Tobias Madl
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Ageing, Molecular Biology and Biochemistry, Research Unit Integrative Structural Biology, Medical University of Graz, 8010 Graz, Austria; BioTechMed-Graz, 8010 Graz, Austria.
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44
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Qing R, Hao S, Smorodina E, Jin D, Zalevsky A, Zhang S. Protein Design: From the Aspect of Water Solubility and Stability. Chem Rev 2022; 122:14085-14179. [PMID: 35921495 PMCID: PMC9523718 DOI: 10.1021/acs.chemrev.1c00757] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Indexed: 12/13/2022]
Abstract
Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.
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Affiliation(s)
- Rui Qing
- State
Key Laboratory of Microbial Metabolism, School of Life Sciences and
Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- The
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Shilei Hao
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- Key
Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Eva Smorodina
- Department
of Immunology, University of Oslo and Oslo
University Hospital, Oslo 0424, Norway
| | - David Jin
- Avalon GloboCare
Corp., Freehold, New Jersey 07728, United States
| | - Arthur Zalevsky
- Laboratory
of Bioinformatics Approaches in Combinatorial Chemistry and Biology, Shemyakin−Ovchinnikov Institute of Bioorganic
Chemistry RAS, Moscow 117997, Russia
| | - Shuguang Zhang
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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45
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Vymětal J, Vondrášek J. Iterative Landmark-Based Umbrella Sampling (ILBUS) Protocol for Sampling of Conformational Space of Biomolecules. J Chem Inf Model 2022; 62:4783-4798. [PMID: 36122323 DOI: 10.1021/acs.jcim.2c00370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Computer simulations of biomolecules such as molecular dynamics often suffer from insufficient sampling. Due to limited computational resources, insufficient sampling prevents obtaining proper equilibrium distributions of observed properties. To deal with this problem, we proposed a simulation protocol for efficient resampling of collected off-equilibrium trajectories. These trajectories are utilized for the initial mapping of the conformational space, which is later properly resampled by the introduced Iterative Landmark-Based Umbrella Sampling (ILBUS) method. Reconstruction of static equilibrium properties is achieved by the multistate Bennett acceptance ratio (MBAR) method, which enables efficient use of simulated data. The ILBUS protocol is geometry-based and does not demand any additional collective variable or a dimensional-reduction technique. The only requirement is a set of suitably spaced reference conformations, which serve as landmarks in the mapped conformational space. Additionally, the ILBUS protocol encompasses an iterative process that optimizes the force constant used in the umbrella sampling simulation. Such tuning is an inherent feature of the protocol and does not need to be performed by the user in advance. Furthermore, even the simulations with suboptimal force constants can be used in estimates by MBAR. We demonstrate the feasibility and the performance of this approach in the study of the conformational landscape of the alanine dipeptide, met-enkephalin, and adenylate kinase.
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Affiliation(s)
- Jiří Vymětal
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo náměstí 542/2, 160 00 Praha 6, Czech Republic
| | - Jiří Vondrášek
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo náměstí 542/2, 160 00 Praha 6, Czech Republic
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46
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Sun Y, Jiao Y, Shi C, Zhang Y. Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2. Comput Struct Biotechnol J 2022; 20:5014-5027. [PMID: 36091720 PMCID: PMC9448712 DOI: 10.1016/j.csbj.2022.09.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 08/03/2022] [Accepted: 09/03/2022] [Indexed: 11/26/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has led to a global pandemic. Deep learning (DL) technology and molecular dynamics (MD) simulation are two mainstream computational approaches to investigate the geometric, chemical and structural features of protein and guide the relevant drug design. Despite a large amount of research papers focusing on drug design for SARS-COV-2 using DL architectures, it remains unclear how the binding energy of the protein-protein/ligand complex dynamically evolves which is also vital for drug development. In addition, traditional deep neural networks usually have obvious deficiencies in predicting the interaction sites as protein conformation changes. In this review, we introduce the latest progresses of the DL and DL-based MD simulation approaches in structure-based drug design (SBDD) for SARS-CoV-2 which could address the problems of protein structure and binding prediction, drug virtual screening, molecular docking and complex evolution. Furthermore, the current challenges and future directions of DL-based MD simulation for SBDD are also discussed.
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Affiliation(s)
- Yao Sun
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518055, China
| | - Yanqi Jiao
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518055, China
| | - Chengcheng Shi
- State Key Lab of Urban Water Resource and Environment, School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518055, China
| | - Yang Zhang
- School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518055, China
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47
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Schulig L, Geist N, Delcea M, Link A, Kulke M. Fundamental Redesign of the TIGER2hs Kernel to Address Severe Parameter Sensitivity. J Chem Inf Model 2022; 62:4200-4209. [PMID: 36004729 DOI: 10.1021/acs.jcim.2c00476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Replica exchange molecular dynamics simulations are one of the most popular approaches to enhance conformational sampling of molecular systems. Applications range from protein folding to protein-protein or other host-guest interactions, as well as binding free energy calculations. While these methods are computationally expensive, highly accurate results can be obtained. We recently developed TIGER2hs, an improved version of the temperature intervals with global exchange of replicas (TIGER2) algorithm. This method combines the replica-based enhanced sampling in an explicit solvent with a hybrid solvent energy evaluation. During the exchange attempts, bulk water is replaced by an implicit solvent model, allowing sampling with significantly less replicas than parallel tempering (REMD). This enables accurate enhanced sampling calculations with only a fraction of computational resources compared to REMD. Our latest results highlight several issues with sampling imbalance and parameter sensitivity within the original TIGER2 exchange algorithms that affect the overall state populations. A high sensitivity on replica number and maximum temperature is eliminated by changing to a pairwise exchange kernel (PE) without additional sorting. Simulations are controlled by adjusting the average temperature change per exchange ⟨ΔT/χ⟩ to below 30 K to mimic a controlled temperature mixing of replicas similar to REMD. Thus, this parameter provides an applicable property for selecting combinations of replica number and maximum temperature to adjust simulations for best accuracy, with flexible resource investment. This increases the robustness of the method and ensures results in excellent agreement with REMD, as demonstrated for three different peptides.
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Affiliation(s)
- Lukas Schulig
- Department of Medicinal and Pharmaceutical Chemistry, University of Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany
| | - Norman Geist
- Department of Biophysical Chemistry, University of Greifswald, Felix-Hausdorff-Straße 4, 17489 Greifswald, Germany
| | - Mihaela Delcea
- Department of Biophysical Chemistry, University of Greifswald, Felix-Hausdorff-Straße 4, 17489 Greifswald, Germany
| | - Andreas Link
- Department of Medicinal and Pharmaceutical Chemistry, University of Greifswald, Friedrich-Ludwig-Jahn-Straße 17, 17489 Greifswald, Germany
| | - Martin Kulke
- MSU-DOE Plant Research Laboratory, Michigan State University, 612 Wilson Road, East Lansing, Michigan 48824, United States of America
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Polymorphisms in common antihypertensive targets: Pharmacogenomic implications for the treatment of cardiovascular disease. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2022; 94:141-182. [PMID: 35659371 DOI: 10.1016/bs.apha.2022.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The idea of personalized medicine came to fruition with sequencing the human genome; however, aside from a few cases, the genetic revolution has yet to materialize. Cardiovascular diseases are the leading cause of death globally, and hypertension is a common prelude to nearly all cardiovascular diseases. Thus, hypertension is an ideal candidate disease to apply tenants of personalized medicine to lessen cardiovascular disease. Herein is a survey that visually depicts the polymorphisms in the top eight antihypertensive targets. Although there are numerous genome-wide association studies regarding cardiovascular disease, few studies look at the effects of receptor polymorphisms on drug treatment. With 17,000+ polymorphisms in the combined target proteins examined, it is expected that some of the clinical variability in the treatment of hypertension is due to polymorphisms in the drug targets. Recent advances in techniques and technology, such as high throughput examination of single mutations, structure prediction, computational power for modeling, and CRISPR models of point mutations, allow for a relatively rapid and comprehensive examination of the effects of known and future polymorphisms on drug affinity and effects. As hypertension is easy to measure and has a plethora of clinically viable ligands, hypertension makes an excellent disease to study pharmacogenomics in the lab and the clinic. If the promises of personalized medicine are to materialize, a concerted effort to examine the effects polymorphisms have on drugs is required. A clinician with the knowledge of a patient's genotype can then prescribe drugs that are optimal for treating that specific patient.
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Santa-Coloma TA. Overlapping synthetic peptides as a tool to map protein-protein interactions ̶ FSH as a model system of nonadditive interactions. Biochim Biophys Acta Gen Subj 2022; 1866:130153. [DOI: 10.1016/j.bbagen.2022.130153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/06/2022] [Accepted: 04/12/2022] [Indexed: 10/18/2022]
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Nagel F, Palm GJ, Geist N, McDonnell TCR, Susemihl A, Girbardt B, Mayerle J, Lerch MM, Lammers M, Delcea M. Structural and Biophysical Insights into SPINK1 Bound to Human Cationic Trypsin. Int J Mol Sci 2022; 23:ijms23073468. [PMID: 35408828 PMCID: PMC8998336 DOI: 10.3390/ijms23073468] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 03/18/2022] [Accepted: 03/21/2022] [Indexed: 02/01/2023] Open
Abstract
(1) The serine protease inhibitor Kazal type 1 (SPINK1) inhibits trypsin activity in zymogen granules of pancreatic acinar cells. Several mutations in the SPINK1 gene are associated with acute recurrent pancreatitis (ARP) and chronic pancreatitis (CP). The most common variant is SPINK1 p.N34S. Although this mutation was identified two decades ago, the mechanism of action has remained elusive. (2) SPINK1 and human cationic trypsin (TRY1) were expressed in E. coli, and inhibitory activities were determined. Crystals of SPINK1-TRY1 complexes were grown by using the hanging-drop method, and phases were solved by molecular replacement. (3) Both SPINK1 variants show similar inhibitory behavior toward TRY1. The crystal structures are almost identical, with minor differences in the mutated loop. Both complexes show an unexpected rotamer conformation of the His63 residue in TRY1, which is a member of the catalytic triad. (4) The SPINK1 p.N34S mutation does not affect the inhibitory behavior or the overall structure of the protein. Therefore, the pathophysiological mechanism of action of the p.N34S variant cannot be explained mechanistically or structurally at the protein level. The observed histidine conformation is part of a mechanism for SPINK1 that can explain the exceptional proteolytic stability of this inhibitor.
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Affiliation(s)
- Felix Nagel
- Biophysical Chemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (F.N.); (N.G.); (A.S.)
| | - Gottfried J. Palm
- Synthetic and Structural Biochemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (G.J.P.); (B.G.); (M.L.)
| | - Norman Geist
- Biophysical Chemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (F.N.); (N.G.); (A.S.)
| | - Thomas C. R. McDonnell
- Biochemical Engineering Department, University College London, Bernard Katz, London WC1E 6BT, UK;
| | - Anne Susemihl
- Biophysical Chemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (F.N.); (N.G.); (A.S.)
- Department of Hematology and Oncology, Internal Medicine C, University of Greifswald, 17489 Greifswald, Germany
| | - Britta Girbardt
- Synthetic and Structural Biochemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (G.J.P.); (B.G.); (M.L.)
| | - Julia Mayerle
- Department of Medicine II, University Hospital Munich, Ludwig-Maximillian University Munich, 81377 Munich, Germany;
| | - Markus M. Lerch
- Department of Medicine A, University Medicine Greifswald, 17489 Greifswald, Germany;
| | - Michael Lammers
- Synthetic and Structural Biochemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (G.J.P.); (B.G.); (M.L.)
| | - Mihaela Delcea
- Biophysical Chemistry, Institute of Biochemistry, University of Greifswald, 17489 Greifswald, Germany; (F.N.); (N.G.); (A.S.)
- Correspondence:
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