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Molecular Dynamics Simulations and Structural Analysis of Protein Domains

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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 (31 March 2024) | Viewed by 6442

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Special Issue Editor

Prof. Dr. Alexandre G. De Brevern

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Guest Editor

Department of Biological Research on the Red Blood Cells, INTS, INSERM UMR_S 1134, Université de Paris, Université de la Réunion, 75739 Paris, France
Interests: structural bioinformatics; bioinformatics; next-generation sequence; drug design; deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 3D structure of proteins is the basis for all their biological functions. For more than 50 years, obtaining this structure has been difficult, costly and sometimes impossible. Molecular modelling approaches are therefore making it possible to increase our knowledge by providing high-quality 3D structural models. In this context, the AlphaFold2 deep learning approach has enabled significant progress, with hundreds of millions of 3D structural models being made available to the scientific community.

However, the 3D structure gives only a small insight into biological function. The 3D structure or 3D model is static, whereas the different parts of proteins are rigid, flexible, highly flexible or even completely disordered. Similarly, biological function can be associated with major conformational changes that are not provided by knowledge of a single structure. It is therefore essential to understand the life of protein structures through their dynamics. Molecular dynamics simulations (DMs), both classical and advanced, provide access to much more detailed questions of critical biomedical interest. For example, a point mutation in a structural model does not explain the functional change at the atomic level. Molecular dynamics simulations are needed to generate hypotheses about the effects of these variants. In this way, DMs allow us to see allosteric changes that are sometimes impossible to characterise experimentally.

This Special Issue will therefore focus on issues ranging from the most fundamental to the most applied research on protein structures (or structural models), through the use and/or development of both classical and more innovative simulations. It can start with the construction of a model or the use of a 3D structure and then its analysis by DMs, the comparison between different variants, the question of the binding of ligands or proteins of interest, etc.

Prof. Dr. Alexandre G. De Brevern
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

protein structures
molecular dynamics
advanced molecular dynamics
variants
pathologies
drug design
allostery
protein domains
secondary structures
methodological development
protein design
ligands
normal mode analysis
machine learning

Published Papers (6 papers)

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Research

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19 pages, 2741 KiB

Open AccessArticle

Conformational Space of the Translocation Domain of Botulinum Toxin: Atomistic Modeling and Mesoscopic Description of the Coiled-Coil Helix Bundle

by Alexandre Delort, Grazia Cottone, Thérèse E. Malliavin and Martin Michael Müller

Int. J. Mol. Sci. 2024, 25(5), 2481; https://doi.org/10.3390/ijms25052481 - 20 Feb 2024

Viewed by 583

Abstract

The toxicity of botulinum multi-domain neurotoxins (BoNTs) arises from a sequence of molecular events, in which the translocation of the catalytic domain through the membrane of a neurotransmitter vesicle plays a key role. A recent structural study of the translocation domain of BoNTs [...] Read more.

α

helical switch towards a

β

hairpin. Atomistic simulations in conjunction with the mesoscopic Twister model are used to investigate the consequences of this proposition for the toxin–membrane interaction. The conformational mobilities of the domain, as well as the effect of the membrane, implicitly examined by comparing water and water–ethanol solvents, lead to the conclusion that the transition of the switch modifies the internal dynamics and the effect of membrane hydrophobicity on the whole protein. The central two

α

helices, helix 1 and helix 2, forming two coiled-coil motifs, are analyzed using the Twister model, in which the initial deformation of the membrane by the protein is caused by the presence of local torques arising from asymmetric positions of hydrophobic residues. Different torque distributions are observed depending on the switch conformations and permit an origin for the mechanism opening the membrane to be proposed. Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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26 pages, 7267 KiB

Open AccessArticle

Synergy of Mutation-Induced Effects in Human Vitamin K Epoxide Reductase: Perspectives and Challenges for Allo-Network Modulator Design

by Marina Botnari and Luba Tchertanov

Int. J. Mol. Sci. 2024, 25(4), 2043; https://doi.org/10.3390/ijms25042043 - 07 Feb 2024

Cited by 1 | Viewed by 602

Abstract

The human Vitamin K Epoxide Reductase Complex (hVKORC1), a key enzyme transforming vitamin K into the form necessary for blood clotting, requires for its activation the reducing equivalents delivered by its redox partner through thiol-disulfide exchange reactions. The luminal loop (L-loop) is the principal mediator of hVKORC1 activation, and it is a region frequently harbouring numerous missense mutations. Four L-loop hVKORC1 mutants, suggested in vitro as either resistant (A41S, H68Y) or completely inactive (S52W, W59R), were studied in the oxidised state by numerical approaches (in silico). The DYNASOME and POCKETOME of each mutant were characterised and compared to the native protein, recently described as a modular protein composed of the structurally stable transmembrane domain (TMD) and the intrinsically disordered L-loop, exhibiting quasi-independent dynamics. The DYNASOME of mutants revealed that L-loop missense point mutations impact not only its folding and dynamics, but also those of the TMD, highlighting a strong mutation-specific interdependence between these domains. Another consequence of the mutation-induced effects manifests in the global changes (geometric, topological, and probabilistic) of the newly detected cryptic pockets and the alternation of the recognition properties of the L-loop with its redox protein. Based on our results, we postulate that (i) intra-protein allosteric regulation and (ii) the inherent allosteric regulation and cryptic pockets of each mutant depend on its DYNASOME; and (iii) the recognition of the redox protein by hVKORC1 (INTERACTOME) depend on their DYNASOME. This multifaceted description of proteins produces “omics” data sets, crucial for understanding the physiological processes of proteins and the pathologies caused by alteration of the protein properties at various “omics” levels. Additionally, such characterisation opens novel perspectives for the development of “allo-network drugs” essential for the treatment of blood disorders. Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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14 pages, 8235 KiB

Open AccessArticle

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

by Benjamin Tam, Zixin Qin, Bojin Zhao, Siddharth Sinha, Chon Lok Lei and San Ming Wang

Int. J. Mol. Sci. 2024, 25(2), 850; https://doi.org/10.3390/ijms25020850 - 10 Jan 2024

Viewed by 1088

Abstract

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named “Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)” to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure. Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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19 pages, 10102 KiB

Open AccessArticle

A Proposal for a Consolidated Structural Model of the CagY Protein of Helicobacter pylori

by Mario Angel López-Luis, Eva Elda Soriano-Pérez, José Carlos Parada-Fabián, Javier Torres, Rogelio Maldonado-Rodríguez and Alfonso Méndez-Tenorio

Int. J. Mol. Sci. 2023, 24(23), 16781; https://doi.org/10.3390/ijms242316781 - 26 Nov 2023

Viewed by 1115

Abstract

CagY is the largest and most complex protein from Helicobacter pylori’s (Hp) type IV secretion system (T4SS), playing a critical role in the modulation of gastric inflammation and risk for gastric cancer. CagY spans from the inner to the outer membrane, forming a channel through which Hp molecules are injected into human gastric cells. Yet, a tridimensional structure has been reported for only short segments of the protein. This intricate protein was modeled using different approaches, including homology modeling, ab initio, and deep learning techniques. The challengingly long middle repeat region (MRR) was modeled using deep learning and optimized using equilibrium molecular dynamics. The previously modeled segments were assembled into a 1595 aa chain and a 14-chain CagY multimer structure was assembled by structural alignment. The final structure correlated with published structures and allowed to show how the multimer may form the T4SS channel through which CagA and other molecules are translocated to gastric cells. The model confirmed that MRR, the most polymorphic and complex region of CagY, presents numerous cysteine residues forming disulfide bonds that stabilize the protein and suggest this domain may function as a contractile region playing an essential role in the modulating activity of CagY on tissue inflammation. Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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Review

Jump to: Research

43 pages, 3284 KiB

Open AccessReview

An Update on Protein Kinases as Therapeutic Targets—Part I: Protein Kinase C Activation and Its Role in Cancer and Cardiovascular Diseases

by Shmuel Silnitsky, Samuel J. S. Rubin, Mulate Zerihun and Nir Qvit

Int. J. Mol. Sci. 2023, 24(24), 17600; https://doi.org/10.3390/ijms242417600 - 18 Dec 2023

Cited by 2 | Viewed by 1762

Abstract

Protein kinases are one of the most significant drug targets in the human proteome, historically harnessed for the treatment of cancer, cardiovascular disease, and a growing number of other conditions, including autoimmune and inflammatory processes. Since the approval of the first kinase inhibitors in the late 1990s and early 2000s, the field has grown exponentially, comprising 98 approved therapeutics to date, 37 of which were approved between 2016 and 2021. While many of these small-molecule protein kinase inhibitors that interact orthosterically with the protein kinase ATP binding pocket have been massively successful for oncological indications, their poor selectively for protein kinase isozymes have limited them due to toxicities in their application to other disease spaces. Thus, recent attention has turned to the use of alternative allosteric binding mechanisms and improved drug platforms such as modified peptides to design protein kinase modulators with enhanced selectivity and other pharmacological properties. Herein we review the role of different protein kinase C (PKC) isoforms in cancer and cardiovascular disease, with particular attention to PKC-family inhibitors. We discuss translational examples and carefully consider the advantages and limitations of each compound (Part I). We also discuss the recent advances in the field of protein kinase modulators, leverage molecular docking to model inhibitor–kinase interactions, and propose mechanisms of action that will aid in the design of next-generation protein kinase modulators (Part II). Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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26 pages, 3214 KiB

Open AccessReview

An Update on Protein Kinases as Therapeutic Targets—Part II: Peptides as Allosteric Protein Kinase C Modulators Targeting Protein–Protein Interactions

by Mulate Zerihun, Samuel J. S. Rubin, Shmuel Silnitsky and Nir Qvit

Int. J. Mol. Sci. 2023, 24(24), 17504; https://doi.org/10.3390/ijms242417504 - 15 Dec 2023

Viewed by 861

Abstract

Human protein kinases are highly-sought-after drug targets, historically harnessed for treating cancer, cardiovascular disease, and an increasing number of autoimmune and inflammatory conditions. Most current treatments involve small molecule protein kinase inhibitors that interact orthosterically with the protein kinase ATP-binding pocket. As a result, these compounds are often poorly selective and highly toxic. Part I of this series reviews the role of PKC isoforms in various human diseases, featuring cancer and cardiovascular disease, as well as translational examples of PKC modulation applied to human health and disease. In the present Part II, we discuss alternative allosteric binding mechanisms for targeting PKC, as well as novel drug platforms, such as modified peptides. A major goal is to design protein kinase modulators with enhanced selectivity and improved pharmacological properties. To this end, we use molecular docking analysis to predict the mechanisms of action for inhibitor–kinase interactions that can facilitate the development of next-generation PKC modulators. Full article

(This article belongs to the Special Issue Molecular Dynamics Simulations and Structural Analysis of Protein Domains)

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