scholarly journals Molecular Insights into Human Transmembrane Protease Serine-2 (TMPS2) Inhibitors against SARS-CoV2: Homology Modelling, Molecular Dynamics, and Docking Studies

Molecules ◽  
2020 ◽  
Vol 25 (21) ◽  
pp. 5007
Author(s):  
Safaa M. Kishk ◽  
Rania M. Kishk ◽  
Asmaa S. A. Yassen ◽  
Mohamed S. Nafie ◽  
Nader A. Nemr ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Serine Protease ◽  
Tertiary Structure ◽  
Virus Disease ◽  
Homology Modelling ◽  
3D Structure ◽  
Md Simulations ◽  
Homology Model ◽  
Docking Studies ◽  
In Silico Studies

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), which caused novel corona virus disease-2019 (COVID-19) pandemic, necessitated a global demand for studies related to genes and enzymes of SARS-CoV2. SARS-CoV2 infection depends on the host cell Angiotensin-Converting Enzyme-2 (ACE2) and Transmembrane Serine Protease-2 (TMPRSS2), where the virus uses ACE2 for entry and TMPRSS2 for S protein priming. The TMPRSS2 gene encodes a Transmembrane Protease Serine-2 protein (TMPS2) that belongs to the serine protease family. There is no crystal structure available for TMPS2, therefore, a homology model was required to establish a putative 3D structure for the enzyme. A homology model was constructed using SWISS-MODEL and evaluations were performed through Ramachandran plots, Verify 3D and Protein Statistical Analysis (ProSA). Molecular dynamics simulations were employed to investigate the stability of the constructed model. Docking of TMPS2 inhibitors, camostat, nafamostat, gabexate, and sivelestat, using Molecular Operating Environment (MOE) software, into the constructed model was performed and the protein-ligand complexes were subjected to MD simulations and computational binding affinity calculations. These in silico studies determined the tertiary structure of TMPS2 amino acid sequence and predicted how ligands bind to the model, which is important for drug development for the prevention and treatment of COVID-19.

scholarly journals Homology Modelling and Molecular Docking Studies of Selected Substituted Benzo[d]imidazol-1-yl)methyl)benzimidamide Scaffolds on Plasmodium falciparum Adenylosuccinate Lyase Receptor

2019 ◽  
Vol 13 ◽  
pp. 117793221986553 ◽  
Author(s):  
Gbolahan O Oduselu ◽  
Olayinka O Ajani ◽  
Yvonne U Ajamma ◽  
Benedikt Brors ◽  
Ezekiel Adebiyi
Keyword(s):  
Plasmodium Falciparum ◽  
Molecular Docking ◽  
In Silico ◽  
Homology Modelling ◽  
3D Structure ◽  
Docking Studies ◽  
Binding Energies ◽  
Benzimidazole Derivatives ◽  
Adenylosuccinate Lyase ◽  
In Silico Admet

Plasmodium falciparum adenylosuccinate lyase ( PfADSL) is an important enzyme in purine metabolism. Although several benzimidazole derivatives have been commercially developed into drugs, the template design as inhibitor against PfADSL has not been fully explored. This study aims to model the 3-dimensional (3D) structure of PfADSL, design and predict in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) of 8 substituted benzo[ d]imidazol-1-yl)methyl)benzimidamide compounds as well as predict the potential interaction modes and binding affinities of the designed ligands with the modelled PfADSL. PfADSL 3D structure was modelled using SWISS-MODEL, whereas the compounds were designed using ChemDraw Professional. ADMET predictions were done using OSIRIS Property Explorer and Swiss ADME, whereas molecular docking was done with AutoDock Tools. All designed compounds exhibited good in silico ADMET properties, hence can be considered safe for drug development. Binding energies ranged from −6.85 to −8.75 kcal/mol. Thus, they could be further synthesised and developed into active commercial antimalarial drugs.

scholarly journals Experimental accuracy in protein structure refinement via molecular dynamics simulations

2018 ◽  
Vol 115 (52) ◽  
pp. 13276-13281 ◽  
Author(s):  
Lim Heo ◽  
Michael Feig
Keyword(s):  
Molecular Dynamics ◽  
Protein Structure ◽  
Structure Prediction ◽  
Structure Refinement ◽  
Energy Landscape ◽  
Md Simulations ◽  
Homology Model ◽  
Experimental Accuracy ◽  
Markov State Modeling ◽  
Homology Models

Refinement is the last step in protein structure prediction pipelines to convert approximate homology models to experimental accuracy. Protocols based on molecular dynamics (MD) simulations have shown promise, but current methods are limited to moderate levels of consistent refinement. To explore the energy landscape between homology models and native structures and analyze the challenges of MD-based refinement, eight test cases were studied via extensive simulations followed by Markov state modeling. In all cases, native states were found very close to the experimental structures and at the lowest free energies, but refinement was hindered by a rough energy landscape. Transitions from the homology model to the native states require the crossing of significant kinetic barriers on at least microsecond time scales. A significant energetic driving force toward the native state was lacking until its immediate vicinity, and there was significant sampling of off-pathway states competing for productive refinement. The role of recent force field improvements is discussed and transition paths are analyzed in detail to inform which key transitions have to be overcome to achieve successful refinement.

scholarly journals Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Duy Phuoc Tran ◽  
Seiichi Tada ◽  
Akiko Yumoto ◽  
Akio Kitao ◽  
Yoshihiro Ito ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
De Novo ◽  
Homology Modelling ◽  
Md Simulations ◽  
Cell Penetrating Peptides ◽  
Generative Models ◽  
Cell Penetrating ◽  
Wet Lab ◽  
Dynamics Simulations ◽  
De Novo Peptide

AbstractCell-penetrating peptides have important therapeutic applications in drug delivery, but the variety of known cell-penetrating peptides is still limited. With a promise to accelerate peptide development, artificial intelligence (AI) techniques including deep generative models are currently in spotlight. Scientists, however, are often overwhelmed by an excessive number of unannotated sequences generated by AI and find it difficult to obtain insights to prioritize them for experimental validation. To avoid this pitfall, we leverage molecular dynamics (MD) simulations to obtain mechanistic information to prioritize and understand AI-generated peptides. A mechanistic score of permeability is computed from five steered MD simulations starting from different initial structures predicted by homology modelling. To compensate for variability of predicted structures, the score is computed with sample variance penalization so that a peptide with consistent behaviour is highly evaluated. Our computational pipeline involving deep learning, homology modelling, MD simulations and synthesizability assessment generated 24 novel peptide sequences. The top-scoring peptide showed a consistent pattern of conformational change in all simulations regardless of initial structures. As a result of wet-lab-experiments, our peptide showed better permeability and weaker toxicity in comparison to a clinically used peptide, TAT. Our result demonstrates how MD simulations can support de novo peptide design by providing mechanistic information supplementing statistical inference.

Molecular Dynamics Simulations of HLA-CW4-Β2M-KIR2DL1 Protein and Homology Modeling of a Complex Associated with Psoriasis Disease (HLA-CW6-Β 2M-KIR2DS1)

2021 ◽  
Author(s):  
Mansour H Almatarneh ◽  
Ahmad M Alqaisi ◽  
Enas K Ibrahim ◽  
Ghada G Kayed ◽  
Joshua W Hollett
Keyword(s):  
Molecular Dynamics ◽  
Conformational Changes ◽  
Complex Structure ◽  
3D Structure ◽  
Md Simulations ◽  
Salt Bridges ◽  
Small Peptide ◽  
Β2 Microglobulin ◽  
Dynamics Simulations ◽  
The Right

Molecular dynamics (MD) simulation was used to study the interactions of two immune proteins of HLA-Cw4-β2m-KIR2DL1 complex with small peptide QYDDAVYKL (nine amino acids) in an aqueous solution. This study aims to gain a detailed information about the conformational changes and the dynamics of the complex. The right parameters and force field for performing the MD simulations that was needed to calibrate the complex structure were determined. The non-bonded interactions (Electrostatic and van der Waals contributions), H-bond formation, and salt bridges between the ligand HLA-Cw4 and the receptor KIR2DL1 were estimated using the obtained MD trajectories. The buried surface area due to binding was calculated to get insight into the causes of specificity of receptor to ligand and explains mutations experiment. The study concluded that β2-microglobulin, one part of the complex, is not directly interacting with the peptide at the groove; therefore, it could be neglected from simulation. Our results showed that β2-microglobulin does not have any significant effect on the dynamics of the 3D-structure of the complex. This project will help in understanding to optimize candidate drug design, a small peptide that disrupts the interaction, for the optimal biological effect.

scholarly journals Inactivation and reactivation of ribonuclease A studied by computer simulation

Open Biology ◽  
2012 ◽  
Vol 2 (7) ◽  
pp. 120088 ◽  
Author(s):  
Gavin M. Seddon ◽  
Robert P. Bywater
Keyword(s):  
Molecular Dynamics ◽  
Computer Simulation ◽  
In Silico ◽  
Tertiary Structure ◽  
Md Simulations ◽  
Globular Proteins ◽  
Ribonuclease A ◽  
Amino Acid Residues ◽  
Constituent Amino Acid ◽  
Single Protein

The year 2011 marked the half-centenary of the publication of what came to be known as the Anfinsen postulate, that the tertiary structure of a folded protein is prescribed fully by the sequence of its constituent amino acid residues. This postulate has become established as a credo , and, indeed, no contradictions seem to have been found to date. However, the experiments that led to this postulate were conducted on only a single protein, bovine ribonuclease A (RNAse). We conduct molecular dynamics (MD) simulations on this protein with the aim of mimicking this experiment as well as making the methodology available for use with basically any protein. There have been many attempts to model denaturation and refolding processes of globular proteins in silico using MD, but only a few examples where disulphide-bond containing proteins were studied. We took the view that if the reductive deactivation and oxidative reactivation processes of RNAse could be modelled in silico, this would provide valuable insights into the workings of the classical Anfinsen experiment.

scholarly journals How and why plants and human N-glycans are different: Insight from molecular dynamics into the “glycoblocks” architecture of complex carbohydrates

2020 ◽  
Vol 16 ◽  
pp. 2046-2056 ◽  
Author(s):  
Carl A Fogarty ◽  
Aoife M Harbison ◽  
Amy R Dugdale ◽  
Elisa Fadda
Keyword(s):  
Molecular Dynamics ◽  
3D Structure ◽  
Md Simulations ◽  
Structural Disorder ◽  
Dynamic Features ◽  
Structural Dynamic ◽  
Alternative Description ◽  
Spatial Environment ◽  
3D Architecture ◽  
Complex Carbohydrates

The N-glycosylation is one of the most abundant and diverse post-translational modifications of proteins, implicated in protein folding and structural stability, and mediating interactions with receptors and with the environment. All N-glycans share a common core from which linear or branched arms stem from, with functionalization specific to different species and to the cells’ health and disease state. This diversity generates a rich collection of structures, all diversely able to trigger molecular cascades and to activate pathways, which also include adverse immunogenic responses. These events are inherently linked to the N-glycans’ 3D architecture and dynamics, which remain for the large part unresolved and undetected because of their intrinsic structural disorder. In this work we use molecular dynamics (MD) simulations to provide insight into N-glycans’ 3D structure by analysing the effects of a set of very specific modifications found in plants and invertebrate N-glycans, which are immunogenic in humans. We also compare these structural motifs and combine them with mammalian N-glycan motifs to devise strategies for the control of the N-glycan 3D structure through sequence. Our results suggest that the N-glycans’ architecture can be described in terms of the local spatial environment of groups of monosaccharides. We define these “glycoblocks” as self-contained 3D units, uniquely identified by the nature of the residues they comprise, their linkages and structural/dynamic features. This alternative description of glycans’ 3D architecture can potentially lead to an easier prediction of sequence-to-structure relationships in complex carbohydrates, with important implications in glycoengineering design.

scholarly journals Three-dimensional structure of Megabalanus rosa Cement Protein 20 revealed by multi-dimensional NMR and molecular dynamics simulations

2019 ◽  
Vol 374 (1784) ◽  
pp. 20190198 ◽  
Author(s):  
Harini Mohanram ◽  
Akshita Kumar ◽  
Chandra S. Verma ◽  
Konstantin Pervushin ◽  
Ali Miserez
Keyword(s):  
Molecular Dynamics ◽  
Disulfide Bonds ◽  
Molecular Mechanisms ◽  
Tertiary Structure ◽  
Three Dimensional ◽  
Md Simulations ◽  
Dimensional Structure ◽  
Nmr Studies ◽  
Dynamics Simulations ◽  
Cement Protein

Barnacles employ a protein-based cement to firmly attach to immersed substrates. The cement proteins (CPs) have previously been identified and sequenced. However, the molecular mechanisms of adhesion are not well understood, in particular, because the three-dimensional molecular structure of CPs remained unknown to date. Here, we conducted multi-dimensional nuclear magnetic resonance (NMR) studies and molecular dynamics (MD) simulations of recombinant Megabalanus rosa Cement Protein 20 ( r MrCP20). Our NMR results show that r MrCP20 contains three main folded domain regions intervened by two dynamic loops, resulting in multiple protein conformations that exist in equilibrium. We found that 12 out of 32 Cys in the sequence engage in disulfide bonds that stabilize the β -sheet domains owing to their placement at the extremities of β -strands. Another feature unveiled by NMR is the location of basic residues in turn regions that are exposed to the solvent, playing an important role for intermolecular contact with negatively charged surfaces. MD simulations highlight a highly stable and conserved β -motif ( β 7- β 8), which may function as nuclei for amyloid-like nanofibrils previously observed in the cured adhesive cement. To the best of our knowledge, this is the first report describing the tertiary structure of an extracellular biological adhesive protein at the molecular level. This article is part of the theme issue ‘Transdisciplinary approaches to the study of adhesion and adhesives in biological systems’.

scholarly journals Investigating the conformational dynamics of Zika virus NS4B protein

2021 ◽  
Author(s):  
Taniya Bhardwaj ◽  
Prateek Kumar ◽  
Rajanish Giri
Keyword(s):  
Molecular Dynamics ◽  
Zika Virus ◽  
Conformational Dynamics ◽  
3D Structure ◽  
Md Simulations ◽  
Cd Spectroscopy ◽  
Host Immune System ◽  
Genome Replication ◽  
Intrinsically Disordered ◽  
Ns4b Protein

Zika virus (ZIKV) NS4B protein is a membranotropic protein having multifunctional roles such as evasion of host-immune system, and induction of host membrane rearrangement for viral genome replication and processing of polyprotein. Despite its versatile functioning, its topology and dynamics are not entirely understood. Presently, there is no NMR or X-ray crystallography-based structure available for any flaviviral NS4B protein. Therefore, in this study, we have investigated the structural dynamics of Zika Virus NS4B protein through 3D structure models using molecular dynamics (MD) simulations approach and experiments. Subsequently, we employed a reductionist approach to understand the dynamics of ZIKV NS4B protein. For this, we studied its N-terminal (residues 1-38), C-terminal (residues 194-251), and cytosolic (residues 131-169) regions in isolation. Further, we have performed experiments to prove the maximum dynamics in its cytosolic region. Using a combination of computational tools and circular dichroism (CD) spectroscopy, we validate the cytosolic region as an intrinsically disordered protein region (IDR). The microsecond-long all atoms molecular dynamics and replica-exchange MD simulations complement the experimental observations. We have also analysed its behaviour under the influence of differently charged liposomes and macromolecular crowding agents which may have significance on its overall dynamics. Lastly, we have proposed a ZIKV NS4B protein model illustrating its putative topology consisting of various membrane-spanning and non-membranous regions.

Identification of the mutated sites present in the transmembrane regions of SCN1A_HUMAN (Sodium Voltage-Gated Channel Alpha Subunit 1) using Insilico techniques

2020 ◽  
Vol 5 (1) ◽  
pp. 1-6
Author(s):  
Balaji Munivelan
Keyword(s):  
Amino Acids ◽  
Outer Membrane ◽  
Structure Prediction ◽  
Homology Modelling ◽  
Transmembrane Helix ◽  
3D Structure ◽  
Docking Studies ◽  
Alpha Subunit ◽  
Voltage Gated ◽  
Gated Channel

Mutations in numerous genes which encode for voltage-gated sodium channels give rise to various epilepsy syndromes in humans. Our research investigation mainly focuses on the identification of the integral membrane protein of the SCN1A (Sodium Voltage-Gated Channel Alpha Subunit 1) in humans. Secondary, we focus on the transmembrane membrane (TP) amino acids directly involved in the epilepsy-involved mutated regions. Using Insilico protocols, we identify the TP proteins and amino acids and elucidate the Transmembrane Helix and the inside and outside amino acids regions of the SCN1A. With the help of Insilico proteomics server, the amino acids in the mutated regions involved in the TP were identified. Finally, 3D structure prediction was performed using homology modelling server and the modelled structure was cross validated for the TP and validated. The identified results were validated using molecular visualization tools. We prove that the mutated amino acids are present in the outer membrane of the TP regions. Thus, the outer membrane of sodium channel and the amino acids present in the outer membrane (T875M, R859C, and R1648H) play a vital role in Structure-Based Drug Designing and Drug Docking studies.

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