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Advanced Research on Protein Structure and Protein Dynamics
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Advanced Research on Protein Structure and Protein Dynamics

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

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 1641

Special Issue Editor

Dr. Robert T. Youker

E-Mail Website
Guest Editor
Department of Biology, Western Carolina University, Cullowhee, NC, USA
Interests: cystic fibrosis; protein folding and quality control; protein trafficking; chaperones
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Proteins are critical “workhorses” in the cells of all living organisms and are essential for a variety of processes, such as signal transduction, cell division, and metabolic pathways. Biophysical and biochemical studies have revealed that proteins are not static entities but are subject to dramatic molecular movements that span from femtosecond vibrations of atoms to slow motions of domains that can last for micro-to-milliseconds. The field of protein dynamics endeavors to study these complex molecular motions. Advances in biophysical and computational techniques are providing new insights into these protein structural changes. For example, the use of cryogenic-electron microscopy (cryo-EM) has led to greater insight into the molecular motions of G-protein coupled receptors upon ligand binding and activation. Combining structural studies with molecular dynamic simulations has been instrumental in investigating the protein folding problem and led to new hypotheses and avenues of research. The latest generation of computing hardware combined with artificial intelligence (AI) promises to advance the field of protein dynamics.

Researchers that utilize biophysical (e.g., cryo-EM, X-ray crystallography, NMR), biochemical (e.g., Fluorescence Fluctuation Techniques), or computational techniques (e.g., molecular dynamic simulations) applied to any domain of cell and molecular biology are welcome to submit their work for consideration. This Special Issue aims to showcase original research articles, reviews, mini-reviews, and commentaries describing the current knowledge of protein dynamics and the protein structural changes that contribute to these molecular movements.

Dr. Robert T. Youker
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

  • allostery
  • receptor
  • kinase
  • protein folding
  • simulations
  • X-ray crystallography
  • NMR
  • super-resolution imaging
  • fluorescence fluctuation techniques
  • thermodynamic
  • enzyme
  • catalysis
  • artificial intelligence

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Published Papers (2 papers)

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Research

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14 pages, 1904 KiB  
Article
A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants
by Léopold Quitté, Mickael Leclercq, Julien Prunier, Marie-Pier Scott-Boyer, Gautier Moroy and Arnaud Droit
Int. J. Mol. Sci. 2024, 25(12), 6535; https://doi.org/10.3390/ijms25126535 - 13 Jun 2024
Viewed by 682
Abstract
Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the [...] Read more.
Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants—namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies. Full article
(This article belongs to the Special Issue Advanced Research on Protein Structure and Protein Dynamics)
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Review

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29 pages, 3830 KiB  
Review
Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics
by Ahrum Son, Woojin Kim, Jongham Park, Wonseok Lee, Yerim Lee, Seongyun Choi and Hyunsoo Kim
Int. J. Mol. Sci. 2024, 25(17), 9725; https://doi.org/10.3390/ijms25179725 - 8 Sep 2024
Viewed by 534
Abstract
Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, [...] Read more.
Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery. Full article
(This article belongs to the Special Issue Advanced Research on Protein Structure and Protein Dynamics)
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