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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: closed (30 September 2023) | Viewed by 18179

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Prof. Dr. II Soo Moon

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Guest Editor

Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Republic of Korea
Interests: protein structure and dynamics; protein conformational disorders; drug design; protein–protein interaction; neurodegenerative diseases; molecular modeling
Special Issues, Collections and Topics in MDPI journals

Dr. Raju Dash

E-Mail Website
Guest Editor

Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Republic of Korea
Interests: computational biology; molecular modeling; drug design; protein structure and dynamics; protein conformational disorders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Molecular dynamics (MD) simulation has emerged as a fundamental research methodology in biology, material sciences, and chemical physics to understand the physical basis of any molecular motion at the atomic level. This science of simulating motion allows the visualization and dynamic characterization of any system of particles that are expensive or empirically challenging. Of course, many advanced tools, including cryo-electron microscopy, X-ray crystallography, solid-state nuclear magnetic resonance, and fiber diffraction, have been developed to determine molecular structure and function. Still, these tools only provide a static picture, while dynamic properties are essential for a complete understanding of molecular functionality.

Recent advances in the computational platform, algorithms, analysis tools, software, and high-performance computing have made molecular simulations useful for investigating more complicated and large systems. In hypotheses and experiments, MD data may often be complementary to experimental studies since they can assist in analyzing and interpreting both in vivo and in vitro findings.

We warmly welcome your contributions to this Special Issue on “Research on Molecular Dynamics.” This Special Issue will cover any aspect of MD simulation, including the theory, techniques, and computational or methodological developments for the result analysis. Original research papers and review articles addressing MD simulation applications to diverse biomolecular systems, interactions, and functions are welcome. Submission of combined simulation and experimental studies is also encouraged.

Prof. Dr. II Soo Moon
Dr. Raju Dash
Guest Editors

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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.

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Keywords

molecular dynamics
quantum mechanics/molecular mechanics approaches
conformational change
dynamic changes of intermolecular interactions
protein–ligand interactions
nucleic acid ligand interactions
computational modeling of molecular systems
drug design and delivery
structure–function relationships in proteins
simulation of drug-like molecule and lipid membrane

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Published Papers (9 papers)

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Research

14 pages, 4364 KiB

Open AccessArticle

SAFoldNet: A Novel Tool for Discovering and Aligning Three-Dimensional Protein Structures Based on a Neural Network

by Denis V. Petrovskiy, Kirill S. Nikolsky, Vladimir R. Rudnev, Liudmila I. Kulikova, Tatiana V. Butkova, Kristina A. Malsagova, Arthur T. Kopylov and Anna L. Kaysheva

Int. J. Mol. Sci. 2023, 24(19), 14439; https://doi.org/10.3390/ijms241914439 - 22 Sep 2023

Cited by 1 | Viewed by 974

Abstract

The development and improvement of methods for comparing and searching for three-dimensional protein structures remain urgent tasks in modern structural biology. To solve this problem, we developed a new tool, SAFoldNet, which allows for searching, aligning, superimposing, and determining the exact coordinates of fragments of protein structures. The proposed search and alignment tool was built using neural networking. Specifically, we implemented the integrative synergy of neural network predictions and the well-known BLAST algorithm for searching and aligning sequences. The proposed method involves multistage processing, comprising a stage for converting the geometry of protein structures into sequences of a structural alphabet using a neural network, a search stage for forming a set of candidate structures, and a refinement stage for calculating the structural alignment and overlap and evaluating the similarity with the starting structure of the search. The effectiveness and practical applicability of the proposed tool were compared with those of several widely used services for searching and aligning protein structures. The results of the comparisons confirmed that the proposed method is effective and competitive relative to the available modern services. Furthermore, using the proposed approach, a service with a user-friendly web interface was developed, which allows for searching, aligning, and superimposing protein structures; determining the location of protein fragments; mapping onto a protein molecule chain; and providing structural similarity metrices (expected value and root mean square deviation). Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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15 pages, 3826 KiB

Open AccessArticle

Modeling Side Chains in the Three-Dimensional Structure of Proteins for Post-Translational Modifications

by Denis V. Petrovskiy, Kirill S. Nikolsky, Vladimir R. Rudnev, Liudmila I. Kulikova, Tatiana V. Butkova, Kristina A. Malsagova, Arthur T. Kopylov and Anna L. Kaysheva

Int. J. Mol. Sci. 2023, 24(17), 13431; https://doi.org/10.3390/ijms241713431 - 30 Aug 2023

Cited by 3 | Viewed by 1442

Abstract

Amino acid substitutions and post-translational modifications (PTMs) play a crucial role in many cellular processes by directly affecting the structural and dynamic features of protein interaction. Despite their importance, the understanding of protein PTMs at the structural level is still largely incomplete. The Protein Data Bank contains a relatively small number of 3D structures having post-translational modifications. Although recent years have witnessed significant progress in three-dimensional modeling (3D) of proteins using neural networks, the problem related to predicting accurate PTMs in proteins has been largely ignored. Predicting accurate 3D PTM models in proteins is closely related to another fundamental problem: predicting the correct side-chain conformations of amino acid residues in proteins. An analysis of publications as well as the paid and free software packages for modeling three-dimensional structures showed that most of them focus on working with unmodified proteins and canonical amino acid residues; the number of articles and software packages placing emphasis on modeling three-dimensional PTM structures is an order of magnitude smaller. This paper focuses on modeling the side-chain conformations of proteins containing PTMs (nonstandard amino acid residues). We collected our own libraries comprising the most frequently observed PTMs from the PDB and implemented a number of algorithms for predicting the side-chain conformation at modification points and in the immediate environment of the protein. A comprehensive analysis of both the algorithms per se and compared to the common Rosetta and FoldX structure modeling packages was also carried out. The proposed algorithmic solutions are comparable in their characteristics to the well-known Rosetta and FoldX packages for the modeling of three-dimensional structures and have great potential for further development and optimization. The source code of algorithmic solutions has been deposited to and is available at the GitHub source. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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15 pages, 1888 KiB

Open AccessArticle

Application of Molecular Dynamics Simulations to Determine Interactions between Canary Seed (Phalaris canariensis L.) Bioactive Peptides and Skin-Aging Enzymes

by José E. Aguilar-Toalá, Abraham Vidal-Limon, Andrea M. Liceaga, Maria L. Zambrano-Zaragoza and David Quintanar-Guerrero

Int. J. Mol. Sci. 2023, 24(17), 13420; https://doi.org/10.3390/ijms241713420 - 30 Aug 2023

Cited by 4 | Viewed by 1724

Abstract

Food bioactive peptides are well recognized for their health benefits such as antimicrobial, antioxidant, and antihypertensive benefits, among others. Their drug-like behavior has led to their potential use in targeting skin-related aging factors like the inhibition of enzymes related with the skin-aging process. In this study, canary seed peptides (CSP) after simulated gastrointestinal digestion (<3 kDa) were fractioned by RP-HPLC and their enzyme-inhibition activity towards elastase and tyrosinase was evaluated in vitro. CSP inhibited elastase (IC₅₀ = 6.2 mg/mL) and tyrosinase (IC₅₀ = 6.1 mg/mL), while the hydrophobic fraction-VI (0.2 mg/mL) showed the highest inhibition towards elastase (93%) and tyrosinase (67%). The peptide fraction with the highest inhibition was further characterized by a multilevel in silico workflow, including physicochemical descriptor calculations, antioxidant activity predictions, and molecular dynamics-ensemble docking towards elastase and tyrosinase. To gain insights into the skin permeation process during molecular dynamics simulations, based on their docking scores, five peptides (GGWH, VPPH, EGLEPNHRVE, FLPH, and RPVNKYTPPQ) were identified to have favorable intermolecular interactions, such as hydrogen bonding of polar residues (W, H, and K) to lipid polar groups and 2–3 Å van der Waals close contact of hydrophobic aliphatic residues (P, V, and L). These interactions can play a critical role for the passive insertion of peptides into stratum corneum model skin-membranes, suggesting a promising application of CSP for skin-aging treatments. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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16 pages, 2416 KiB

Open AccessArticle

MD–Ligand–Receptor: A High-Performance Computing Tool for Characterizing Ligand–Receptor Binding Interactions in Molecular Dynamics Trajectories

by Michele Pieroni, Francesco Madeddu, Jessica Di Martino, Manuel Arcieri, Valerio Parisi, Paolo Bottoni and Tiziana Castrignanò

Int. J. Mol. Sci. 2023, 24(14), 11671; https://doi.org/10.3390/ijms241411671 - 19 Jul 2023

Cited by 16 | Viewed by 3228

Abstract

Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand–receptor binding interactions (lrbi) to be studied. In this study, we present MD–ligand–receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand–receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand–receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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13 pages, 3096 KiB

Open AccessArticle

Impact of E484Q and L452R Mutations on Structure and Binding Behavior of SARS-CoV-2 B.1.617.1 Using Deep Learning AlphaFold2, Molecular Docking and Dynamics Simulation

by Yanqi Jiao, Yichen Xing and Yao Sun

Int. J. Mol. Sci. 2023, 24(14), 11564; https://doi.org/10.3390/ijms241411564 - 17 Jul 2023

Cited by 1 | Viewed by 1815

Abstract

During the outbreak of COVID-19, many SARS-CoV-2 variants presented key amino acid mutations that influenced their binding abilities with angiotensin-converting enzyme 2 (hACE2) and neutralizing antibodies. For the B.1.617 lineage, there had been fears that two key mutations, i.e., L452R and E484Q, would have additive effects on the evasion of neutralizing antibodies. In this paper, we systematically investigated the impact of the L452R and E484Q mutations on the structure and binding behavior of B.1.617.1 using deep learning AlphaFold2, molecular docking and dynamics simulation. We firstly predicted and verified the structure of the S protein containing L452R and E484Q mutations via the AlphaFold2-calculated pLDDT value and compared it with the experimental structure. Next, a molecular simulation was performed to reveal the structural and interaction stabilities of the S protein of the double mutant variant with hACE2. We found that the double mutations, L452R and E484Q, could lead to a decrease in hydrogen bonds and higher interaction energy between the S protein and hACE2, demonstrating the lower structural stability and the worse binding affinity in the long dynamic evolutional process, even though the molecular docking showed the lower binding energy score of the S1 RBD of the double mutant variant with hACE2 than that of the wild type (WT) with hACE2. In addition, docking to three approved neutralizing monoclonal antibodies (mAbs) showed a reduced binding affinity of the double mutant variant, suggesting a lower neutralization ability of the mAbs against the double mutant variant. Our study helps lay the foundation for further SARS-CoV-2 studies and provides bioinformatics and computational insights into how the double mutations lead to immune evasion, which could offer guidance for subsequent biomedical studies. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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13 pages, 793 KiB

Open AccessArticle

The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction

by Dan Parkin and Mitsunori Takano

Int. J. Mol. Sci. 2023, 24(5), 4700; https://doi.org/10.3390/ijms24054700 - 28 Feb 2023

Viewed by 1675

Abstract

The generalized Born (GB) model is an extension of the continuum dielectric theory of Born solvation energy and is a powerful method for accelerating the molecular dynamic (MD) simulations of charged biological molecules in water. While the effective dielectric constant of water that varies as a function of the separation distance between solute molecules is incorporated into the GB model, adjustment of the parameters is indispensable for accurate calculation of the Coulomb (electrostatic) energy. One of the key parameters is the lower limit of the spatial integral of the energy density of the electric field around a charged atom, known as the intrinsic radius

ρ

. Although ad hoc adjustment of

ρ

has been conducted to improve the Coulombic (ionic) bond stability, the physical mechanism by which

ρ

affects the Coulomb energy remains unclear. Via energetic analysis of three differently sized systems, here, we clarify that the Coulomb bond stability increases with increasing

ρ

and that the increased stability is caused by the interaction energy term, not by the self-energy (desolvation energy) term, as was supposed previously. Our results suggest that the use of larger values for the intrinsic radii of hydrogen and oxygen atoms, together with the use of a relatively small value for the spatial integration cutoff in the GB model, can better reproduce the Coulombic attraction between protein molecules. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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12 pages, 3250 KiB

Open AccessArticle

Atomistic Study for the Tantalum and Tantalum–Tungsten Alloy Threshold Displacement Energy under Local Strain

by Mohammad Bany Salman, Minkyu Park and Mosab Jaser Banisalman

Int. J. Mol. Sci. 2023, 24(4), 3289; https://doi.org/10.3390/ijms24043289 - 7 Feb 2023

Cited by 7 | Viewed by 2291

Abstract

The threshold displacement energy (TDE) is an important measure of the extent of a material’s radiation damage. In this study, we investigate the influence of hydrostatic strains on the TDE of pure tantalum (Ta) and Ta–tungsten (W) alloy with a W content ranging from 5% to 30% in 5% intervals. Ta–W alloy is commonly used in high-temperature nuclear applications. We found that the TDE decreased under tensile strain and increased under compressive strain. When Ta was alloyed with 20 at% W, the TDE increased by approximately 15 eV compared to pure Ta. The directional-strained TDE (E_d,i) appears to be more influenced by complex ⟨i j k⟩ directions rather than soft directions, and this effect is more prominent in the alloyed structure than in the pure one. Our results suggest that radiation defect formation is enhanced by tensile strain and suppressed by compressive strain, in addition to the effects of alloying. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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13 pages, 5892 KiB

Open AccessArticle

Theoretical Study of Charge Mobility in Crystal Porphine and a Computer Design of a Porphine-Based Semiconductive Discotic Liquid Mesophase

by Liana Savintseva, Alexander Avdoshin, Stanislav Ignatov and Alexander Novikov

Int. J. Mol. Sci. 2023, 24(1), 736; https://doi.org/10.3390/ijms24010736 - 1 Jan 2023

Cited by 2 | Viewed by 1875

Abstract

Organic semiconductors are the focus of numerous studies; they are used in electronic devices. Modern research involves the production of neuromorphic organic materials, including those based on liquid crystal materials. The purpose of this work involves the theoretical modeling of molecules (the “core with branches” type) to construct a discotic mesophase capable of performing the functions of a neuromorphic material. For this purpose, the conductivity of crystal porphine, which can act as the nucleus of a molecule of the “core with branches” type, was investigated. The Marcus theory charge mobility values for the hole and electron were 0.148 and 0.088 cm²/V·s, respectively (the MOO method for calculating transfer integrals), and 0.561 and 0.160 cm²/V·s (DIPRO method). Based on TD-HF (HF-3c level of theory) calculations, possible structures of molecules for the formation of a discotic mesophase are proposed. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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18 pages, 5476 KiB

Open AccessArticle

Dynamical and Structural Properties of Comb Long-Chain Branched Polymer in Shear Flow

by Deyin Wang, Xiaohui Wen, Dong Zhang and Jiajun Tang

Int. J. Mol. Sci. 2022, 23(19), 11290; https://doi.org/10.3390/ijms231911290 - 25 Sep 2022

Cited by 2 | Viewed by 1627

Abstract

Using hybrid multi-particle collision dynamics (MPCD) and a molecular dynamics (MD) method, we investigate the effect of arms and shear flow on dynamical and structural properties of the comb long-chain branched (LCB) polymer with dense arms. Firstly, we analyze dynamical properties of the LCB polymer by tracking the temporal changes on the end-to-end distance of both backbones and arms as well as the orientations of the backbone in the flow-gradient plane. Simultaneously, the rotation and tumbling behaviors with stable frequencies are observed. In other words, the LCB polymer undergoes a process of periodic stretched–folded–stretched state transition and rotation, whose period is obtained by fitting temporal changes on the orientation to a periodic function. In addition, the impact induced by random and fast motions of arms and the backbone will descend as the shear rate increases. By analyzing the period of rotation behavior of LCB polymers, we find that arms have a function in keeping the LCB polymer’s motion stable. Meanwhile, we find that the rotation period of the LCB polymer is mainly determined by the conformational distribution and the non-shrinkable state of the structure along the velocity-gradient direction. Secondly, structural properties are numerically characterized by the average gyration tensor of the LCB polymer. The changes in gyration are in accordance with the LCB polymer rolling when varying the shear rate. By analyzing the alignment of the LCB polymer and comparing with its linear and star counterparts, we find that the LCB polymer with very long arms, like the corresponding linear chain, has a high speed to reach its configuration expansion limit in the flow direction. However, the comb polymer with shorter arms has stronger resistance on configuration expansion against the imposed flow field. Moreover, with increasing arm length, the comb polymer in shear flow follows change from linear-polymer-like to capsule-like behavior. Full article

(This article belongs to the Special Issue Research on Molecular Dynamics)

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