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State-of-the-Art Molecular Biophysics in USA

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

Deadline for manuscript submissions: 15 April 2024 | Viewed by 6192

Special Issue Editors

Schmid College of Science and Technology, Computational and Data Science, School of Pharmacy, Chapman University, Orange, CA 92866, USA
Interests: computational biology; structural bioinformatics; computational virology; computational systems biology; theoretical and computational approaches for studies of protein dynamics; mechanisms of allosteric regulation; network modeling of biomolecular systems; machine learning; allosteric drug discovery and engineering of allosteric functions; AI and machine learning approaches for exploring allosteric landscapes and drug design
Special Issues, Collections and Topics in MDPI journals
Department of Molecular Medicine, USF Health Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd, MDC07, Tampa, FL 33612, USA
Interests: intrinsically disordered proteins; protein folding; protein misfolding; partially folded proteins; protein aggregation; protein structure; protein function; protein stability; protein biophysics; protein bioinformatics; conformational diseases; protein–ligand interactions; protein–protein interactions; liquid-liquid phase transitions
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Collection aims to publish significant contributions on all aspects of the physical principles governing biomolecular and biomimetic systems in USA. We welcome submissions that provide novel and mechanistic insights and papers that report significant advances in the fields. Topics include, but are not limited to:

  • molecular structure and dynamics
  • protein structure and dynamics;
  • ion channels
  • molecule biophysics;
  • drug discovery
  • structure–function relationships
  • energy balance

The only limitation is that the main part of the study has to have been carried out in USA or by American researchers.

The reliability of the results provided by novel tools for virtual screening and/or the discovery of new actives by virtual screening must be either validated in silico or in vitro before first submission of a manuscript to IJMS. Theoretical studies should offer new insights into understanding experimental results and/or suggest new experimentally testable hypotheses.

Dr. Ciria C. Hernandez
Prof. Dr. Gennady Verkhivker
Prof. Dr. Vladimir N. Uversky
Collection Editors

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

  • protein structure
  • protein dynamics
  • ion channels
  • molecule biophysics
  • drug delivery
  • energy

Published Papers (3 papers)

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Research

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14 pages, 1862 KiB  
Article
Assembly of Synaptic Protein–DNA Complexes: Critical Role of Non-Specific Interactions
by Sridhar Vemulapalli, Mohtadin Hashemi, Anatoly B. Kolomeisky and Yuri L. Lyubchenko
Int. J. Mol. Sci. 2023, 24(12), 9800; https://doi.org/10.3390/ijms24129800 - 06 Jun 2023
Viewed by 869
Abstract
The synaptic protein–DNA complexes, formed by specialized proteins that bridge two or more distant sites on DNA, are critically involved in various genetic processes. However, the molecular mechanism by which the protein searches for these sites and how it brings them together is [...] Read more.
The synaptic protein–DNA complexes, formed by specialized proteins that bridge two or more distant sites on DNA, are critically involved in various genetic processes. However, the molecular mechanism by which the protein searches for these sites and how it brings them together is not well understood. Our previous studies directly visualized search pathways used by SfiI, and we identified two pathways, DNA threading and site-bound transfer pathways, specific to the site-search process for synaptic DNA–protein systems. To investigate the molecular mechanism behind these site-search pathways, we assembled complexes of SfiI with various DNA substrates corresponding to different transient states and measured their stability using a single-molecule fluorescence approach. These assemblies corresponded to specific–specific (synaptic), non-specific–non-specific (non-specific), and specific–non-specific (pre-synaptic) SfiI–DNA states. Unexpectedly, an elevated stability in pre-synaptic complexes assembled with specific and non-specific DNA substrates was found. To explain these surprising observations, a theoretical approach that describes the assembly of these complexes and compares the predictions with the experiment was developed. The theory explains this effect by utilizing entropic arguments, according to which, after the partial dissociation, the non-specific DNA template has multiple possibilities of rebinding, effectively increasing the stability. Such difference in the stabilities of SfiI complexes with specific and non-specific DNA explains the utilization of threading and site-bound transfer pathways in the search process of synaptic protein–DNA complexes discovered in the time-lapse AFM experiments. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Biophysics in USA)
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36 pages, 7462 KiB  
Article
Probing Mechanisms of Binding and Allostery in the SARS-CoV-2 Spike Omicron Variant Complexes with the Host Receptor: Revealing Functional Roles of the Binding Hotspots in Mediating Epistatic Effects and Communication with Allosteric Pockets
by Gennady Verkhivker, Steve Agajanian, Ryan Kassab and Keerthi Krishnan
Int. J. Mol. Sci. 2022, 23(19), 11542; https://doi.org/10.3390/ijms231911542 - 29 Sep 2022
Cited by 9 | Viewed by 1797
Abstract
In this study, we performed all-atom MD simulations of RBD–ACE2 complexes for BA.1, BA.1.1, BA.2, and BA.3 Omicron subvariants, conducted a systematic mutational scanning of the RBD–ACE2 binding interfaces and analysis of electrostatic effects. The binding free energy computations of the Omicron RBD–ACE2 [...] Read more.
In this study, we performed all-atom MD simulations of RBD–ACE2 complexes for BA.1, BA.1.1, BA.2, and BA.3 Omicron subvariants, conducted a systematic mutational scanning of the RBD–ACE2 binding interfaces and analysis of electrostatic effects. The binding free energy computations of the Omicron RBD–ACE2 complexes and comprehensive examination of the electrostatic interactions quantify the driving forces of binding and provide new insights into energetic mechanisms underlying evolutionary differences between Omicron variants. A systematic mutational scanning of the RBD residues determines the protein stability centers and binding energy hotpots in the Omicron RBD–ACE2 complexes. By employing the ensemble-based global network analysis, we propose a community-based topological model of the Omicron RBD interactions that characterized functional roles of the Omicron mutational sites in mediating non-additive epistatic effects of mutations. Our findings suggest that non-additive contributions to the binding affinity may be mediated by R493, Y498, and Y501 sites and are greater for the Omicron BA.1.1 and BA.2 complexes that display the strongest ACE2 binding affinity among the Omicron subvariants. A network-centric adaptation model of the reversed allosteric communication is unveiled in this study, which established a robust connection between allosteric network hotspots and potential allosteric binding pockets. Using this approach, we demonstrated that mediating centers of long-range interactions could anchor the experimentally validated allosteric binding pockets. Through an array of complementary approaches and proposed models, this comprehensive and multi-faceted computational study revealed and quantified multiple functional roles of the key Omicron mutational site R493, R498, and Y501 acting as binding energy hotspots, drivers of electrostatic interactions as well as mediators of epistatic effects and long-range communications with the allosteric pockets. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Biophysics in USA)
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Review

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20 pages, 2960 KiB  
Review
From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on “Allosteric Intersection” of Biochemical and Big Data Approaches
by Gennady Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao and Peng Tao
Int. J. Mol. Sci. 2023, 24(9), 7747; https://doi.org/10.3390/ijms24097747 - 24 Apr 2023
Cited by 5 | Viewed by 2559
Abstract
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed [...] Read more.
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Biophysics in USA)
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