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Computational Modelling and Molecular Dynamics Simulations of Biological Systems
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Computational Modelling and Molecular Dynamics Simulations of Biological Systems

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (20 September 2024) | Viewed by 13483

Special Issue Editor

Dr. Tamara Bidone

E-Mail Website
Guest Editor
1. Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
2. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
Interests: molecular dynamics simulations; multiscale modeling; Brownian dynamics simulations; coarse-graining methods; elastic network modeling

Special Issue Information

Dear Colleagues, 

Computational modeling and simulations are playing an increasingly important role in the advancement of biological sciences, especially when used in combination with experimental and theoretical studies. The general goal of a computational model is to reproduce the behavior of the system it parallels, which it does based on known properties of the system components, in order to provide new insights and predict new properties. Models based on molecular mechanics principles have been successfully applied to the study of protein structures, biomolecular rearrangements, and biological pathways since the 1960s. In the following years, the use of supercomputers, combined with the development of coarse-graining methods and enhanced sampling methods, has allowed us to access longer length scales and longer time scales to understand complex systems such as biomembranes, the HIV capsid, the nuclear pore complex and nucleic acids. Concomitantly, the use of mesoscale computational methods, including kinetic models based on Brownian dynamics, agent-based methods and Monte Carlo approaches, have allowed us to carry out virtual experiments on systems that include a variety of molecular and macromolecular biological components and interactions to demonstrate whether a proposed mechanism is sufficient for producing an observed phenomenon. More recently, efforts to utilize machine learning for modeling biological systems have led to data-driven approaches, providing new opportunities to accelerate the advancement of fundamental and applied biological sciences through modeling and simulations.

For this Special Issue, "Computational Modelling and Molecular Dynamics Simulations of Biological Systems", we welcome your contributions in the form of original research and review articles on all applications of computational modeling and simulations, as well as articles proposing new approaches, applications of machine learning and multiscale methods for the study of biological systems.

Dr. Tamara Bidone
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • molecular dynamics simulations
  • coarse-graining approaches
  • computational biophysics
  • agent-based modeling
  • mechanistic modeling
  • multiscale modeling
  • machine learning
  • protein structure and function

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Published Papers (7 papers)

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Research

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16 pages, 2437 KiB  
Article
Polymer Physics Models Reveal Structural Folding Features of Single-Molecule Gene Chromatin Conformations
by Mattia Conte, Alex Abraham, Andrea Esposito, Liyan Yang, Johan H. Gibcus, Krishna M. Parsi, Francesca Vercellone, Andrea Fontana, Florinda Di Pierno, Job Dekker and Mario Nicodemi
Int. J. Mol. Sci. 2024, 25(18), 10215; https://doi.org/10.3390/ijms251810215 - 23 Sep 2024
Cited by 1 | Viewed by 1443
Abstract
Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2 Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in silico [...] Read more.
Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2 Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in silico the ensemble of single-molecule LTN1 3D structures, which we benchmark against recent in situ Hi-C 2.0 data. The model-derived single molecules are then used to predict structural folding features at the single-cell level, providing testable predictions for super-resolution microscopy experiments. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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20 pages, 2746 KiB  
Article
Identification of a Clade-Specific HLA-C*03:02 CTL Epitope GY9 Derived from the HIV-1 p17 Matrix Protein
by Samuel Kyobe, Savannah Mwesigwa, Gyaviira Nkurunungi, Gaone Retshabile, Moses Egesa, Eric Katagirya, Marion Amujal, Busisiwe C. Mlotshwa, Lesedi Williams, Hakim Sendagire, on behalf of the CAfGEN Consortium, Dithan Kiragga, Graeme Mardon, Mogomotsi Matshaba, Neil A. Hanchard, Jacqueline Kyosiimire-Lugemwa and David Robinson
Int. J. Mol. Sci. 2024, 25(17), 9683; https://doi.org/10.3390/ijms25179683 - 6 Sep 2024
Cited by 1 | Viewed by 1436
Abstract
Efforts towards an effective HIV-1 vaccine have remained mainly unsuccessful. There is increasing evidence for a potential role of HLA-C-restricted CD8+ T cell responses in HIV-1 control, including our recent report of HLA-C*03:02 among African children. However, there are no documented optimal [...] Read more.
Efforts towards an effective HIV-1 vaccine have remained mainly unsuccessful. There is increasing evidence for a potential role of HLA-C-restricted CD8+ T cell responses in HIV-1 control, including our recent report of HLA-C*03:02 among African children. However, there are no documented optimal HIV-1 CD8+ T cell epitopes restricted by HLA-C*03:02; additionally, the structural influence of HLA-C*03:02 on epitope binding is undetermined. Immunoinformatics approaches provide a fast and inexpensive method to discover HLA-restricted epitopes. Here, we employed immunopeptidomics to identify HLA-C*03:02 CD8+ T cell epitopes. We identified a clade-specific Gag-derived GY9 (GTEELRSLY) HIV-1 p17 matrix epitope potentially restricted to HLA-C*03:02. Residues E62, T142, and E151 in the HLA-C*03:02 binding groove and positions p3, p6, and p9 on the GY9 epitope are crucial in shaping and stabilizing the epitope binding. Our findings support the growing evidence of the contribution of HLA-C molecules to HIV-1 control and provide a prospect for vaccine strategies. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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20 pages, 2695 KiB  
Article
High-Throughput Molecular Modeling and Evaluation of the Anti-Inflammatory Potential of Açaí Constituents against NLRP3 Inflammasome
by Elaine Cristina Medeiros da Rocha, João Augusto Pereira da Rocha, Renato Araújo da Costa, Andreia do Socorro Silva da Costa, Edielson dos Santos Barbosa, Luiz Patrick Cordeiro Josino, Luciane do Socorro Nunes dos Santos Brasil, Laura Fernanda Osmari Vendrame, Alencar Kolinski Machado, Solange Binotto Fagan and Davi do Socorro Barros Brasil
Int. J. Mol. Sci. 2024, 25(15), 8112; https://doi.org/10.3390/ijms25158112 - 25 Jul 2024
Cited by 1 | Viewed by 1550
Abstract
The search for bioactive compounds in natural products holds promise for discovering new pharmacologically active molecules. This study explores the anti-inflammatory potential of açaí (Euterpe oleracea Mart.) constituents against the NLRP3 inflammasome using high-throughput molecular modeling techniques. Utilizing methods such as molecular [...] Read more.
The search for bioactive compounds in natural products holds promise for discovering new pharmacologically active molecules. This study explores the anti-inflammatory potential of açaí (Euterpe oleracea Mart.) constituents against the NLRP3 inflammasome using high-throughput molecular modeling techniques. Utilizing methods such as molecular docking, molecular dynamics simulation, binding free energy calculations (MM/GBSA), and in silico toxicology, we compared açaí compounds with known NLRP3 inhibitors, MCC950 and NP3-146 (RM5). The docking studies revealed significant interactions between açaí constituents and the NLRP3 protein, while molecular dynamics simulations indicated structural stabilization. MM/GBSA calculations demonstrated favorable binding energies for catechin, apigenin, and epicatechin, although slightly lower than those of MCC950 and RM5. Importantly, in silico toxicology predicted lower toxicity for açaí compounds compared to synthetic inhibitors. These findings suggest that açaí-derived compounds are promising candidates for developing new anti-inflammatory therapies targeting the NLRP3 inflammasome, combining efficacy with a superior safety profile. Future research should include in vitro and in vivo validation to confirm the therapeutic potential and safety of these natural products. This study underscores the value of computational approaches in accelerating natural product-based drug discovery and highlights the pharmacological promise of Amazonian biodiversity. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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16 pages, 6083 KiB  
Article
Application of Funnel Metadynamics to the Platelet Integrin αIIbβ3 in Complex with an RGD Peptide
by Robert E. Coffman and Tamara C. Bidone
Int. J. Mol. Sci. 2024, 25(12), 6580; https://doi.org/10.3390/ijms25126580 - 14 Jun 2024
Viewed by 1037
Abstract
Integrin αIIbβ3 mediates platelet aggregation by binding the Arginyl-Glycyl-Aspartic acid (RGD) sequence of fibrinogen. RGD binding occurs at a site topographically proximal to the αIIb and β3 subunits, promoting the conformational activation of the receptor from bent to [...] Read more.
Integrin αIIbβ3 mediates platelet aggregation by binding the Arginyl-Glycyl-Aspartic acid (RGD) sequence of fibrinogen. RGD binding occurs at a site topographically proximal to the αIIb and β3 subunits, promoting the conformational activation of the receptor from bent to extended states. While several experimental approaches have characterized RGD binding to αIIbβ3 integrin, applying computational methods has been significantly more challenging due to limited sampling and the need for a priori information regarding the interactions between the RGD peptide and integrin. In this study, we employed all-atom simulations using funnel metadynamics (FM) to evaluate the interactions of an RGD peptide with the αIIb and β3 subunits of integrin. FM incorporates an external history-dependent potential on selected degrees of freedom while applying a funnel-shaped restraint potential to limit RGD exploration of the unbound state. Furthermore, it does not require a priori information about the interactions, enhancing the sampling at a low computational cost. Our FM simulations reveal significant molecular changes in the β3 subunit of integrin upon RGD binding and provide a free-energy landscape with a low-energy binding mode surrounded by higher-energy prebinding states. The strong agreement between previous experimental and computational data and our results highlights the reliability of FM as a method for studying dynamic interactions of complex systems such as integrin. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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26 pages, 9062 KiB  
Article
Molecular Dynamics Simulations Combined with Markov Model to Explore the Effect of Allosteric Inhibitor Binding on Bromodomain-Containing Protein 4
by Xiaotang Yang, Yilin Gao, Fuyan Cao and Song Wang
Int. J. Mol. Sci. 2023, 24(13), 10831; https://doi.org/10.3390/ijms241310831 - 29 Jun 2023
Cited by 3 | Viewed by 2254
Abstract
Bromodomain-Containing Protein 4 (BRD4) can play an important role in gene transcriptional regulation of tumor development and survival by participating in histone modification epigenetic mechanism. Although it has been reported that novel allosteric inhibitors such as ZL0590 have a high affinity with target [...] Read more.
Bromodomain-Containing Protein 4 (BRD4) can play an important role in gene transcriptional regulation of tumor development and survival by participating in histone modification epigenetic mechanism. Although it has been reported that novel allosteric inhibitors such as ZL0590 have a high affinity with target protein BRD4 and good efficacy, their inhibitory mechanism has not been studied further. The aim of this study was to reveal the inhibition mechanism of allosteric inhibitor ZL0590 on Free-BRD4 and BRD4 binding MS436 (orthosteric inhibitor) by molecular dynamics simulation combined with a Markov model. Our results showed that BRD4-ZL0590 led to α-helices formation of 100–105 compared with Free-BRD4; the combination of MS436 caused residues 30–40 and 95–105 to form α-helices, while the combination of allosteric inhibitors untangled the α-helices formed by the MS436. The results of Markov flux analysis showed that the binding process of inhibitors mainly involved changes in the degree of α-helices at ZA loop. The binding of ZL0590 reduced the distance between ZA loop and BC loop, blocked the conformation at the active site, and inhibited the binding of MS436. After the allosteric inhibitor binding, the MS436 that could normally penetrate into the interior of the pocket was floating on the edge of the active pocket and did not continue to penetrate into the active pocket as expected. In summary, we provide a theoretical basis for the inhibition mechanism of ZL0590 against BRD4, which can be used as a reference for improving the development of drug targets for cancer therapy. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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31 pages, 22109 KiB  
Article
A Computational Biology Study on the Structure and Dynamics Determinants of Thermal Stability of the Chitosanase from Aspergillus fumigatus
by Qian Wang, Song Liu, Kecheng Li, Ronge Xing, Xiaolin Chen and Pengcheng Li
Int. J. Mol. Sci. 2023, 24(7), 6671; https://doi.org/10.3390/ijms24076671 - 3 Apr 2023
Cited by 1 | Viewed by 1981
Abstract
Environmentally friendly and efficient biodegradation with chitosanase for degrading chitosan to oligosaccharide has been gaining more importance. Here, we studied a chitosanase from Aspergillus fumigatus with potential for production, but does not have the ideal thermal stability. The structure predicted by the Alphafold2 [...] Read more.
Environmentally friendly and efficient biodegradation with chitosanase for degrading chitosan to oligosaccharide has been gaining more importance. Here, we studied a chitosanase from Aspergillus fumigatus with potential for production, but does not have the ideal thermal stability. The structure predicted by the Alphafold2 model, especially the binding site and two catalytic residues, has been found to have a high similarity with the experimental structure of the chitosanase V-CSN from the same family. The effects of temperature on structure and function were studied by dynamic simulation and the results showed that the binding site had high flexibility. After heating up from 300 K to 350 K, the RMSD and RMSF of the binding site increased significantly, in particular, the downward shift of loop6 closed the binding site, resulting in the spatial hindrance of binding. The time proportions of important hydrogen bonds at the binding site decreased sharply, indicating that serious disruption of hydrogen bonds should be the main interaction factor for conformational changes. The residues contributing energetically to binding were also revealed to be in the highly flexible region, which inevitably leads to the decrease in the activity stability at high temperature. These findings provide directions for the modification of thermal stability and perspectives on the research of proteins without experimental structures. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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Review

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22 pages, 1101 KiB  
Review
Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways
by Jinping Feng, Xinan Zhang and Tianhai Tian
Int. J. Mol. Sci. 2024, 25(18), 10204; https://doi.org/10.3390/ijms251810204 - 23 Sep 2024
Viewed by 1757
Abstract
The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in [...] Read more.
The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data. Full article
(This article belongs to the Special Issue Computational Modelling and Molecular Dynamics Simulations of Biological Systems)
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