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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: 20 September 2024 | Viewed by 3550

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

Published Papers (2 papers)

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Research

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 1 | Viewed by 1451
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
Viewed by 1361
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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