SUSCEPTIBILITY OF COMMERCIAL NEURAMINIDASE INHIBITORS AGAINST 2013 A/H7N9 INFLUENZA VIRUS: A DOCKING AND MOLECULAR DYNAMICS STUDY

2013 ◽  
Vol 12 (07) ◽  
pp. 1350069 ◽  
Author(s):  
ZHIWEI YANG ◽  
FEI WU ◽  
JUNXING LIU ◽  
SHUQIU WANG ◽  
XIAOHUI YUAN
Keyword(s):  
Molecular Dynamics ◽  
Influenza A ◽  
Continuous Monitoring ◽  
Antiviral Drug ◽  
Binding Affinities ◽  
The Novel ◽  
Novel Virus ◽  
H7n9 Influenza ◽  
Dynamics Simulations ◽  
Human Infections

The latest influenza A ( H 7 N 9) virus attracted a worldwide attention due to the first report of human infections and the continuing reported cases in China. In this work, homology modeling, docking and molecular dynamics simulations were combined to study the interactions between neuraminidase ( N 9_2013, from novel A/ H 7 N 9 virus) and agents zanamivir, oseltamivir, peramivir. It was found that N 9_2013 protein is structurally close to the template (PDB code: 1F8B), especially the active site. The binding properties of N 9_2013 protein were nearly identical to those of template. As a result, the three available drugs should be still efficacious for the new emerging A ( H 7 N 9) virus. However, the stabilities of docked complexes and binding affinities (Eint) were slightly reduced, in contrast to the corresponding inhibitor-template complexes, with the values of -82.27 (-84.30), -78.84 (-80.28) and -77.52 (-81.94) kcal mol-1, respectively. Besides, R292K mutation might induce the resistance of the novel virus to the commercial inhibitors. Thus, it arouses the need for continuous monitoring of antiviral drug susceptibilities.

scholarly journals Molecular Dynamics Simulation reveals the mechanism by which the Influenza Cap-dependent Endonuclease acquires resistance against Baloxavir marboxil

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ryunosuke Yoshino ◽  
Nobuaki Yasuo ◽  
Masakazu Sekijima
Keyword(s):  
Molecular Dynamics ◽  
Aromatic Ring ◽  
Influenza A ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Complex Structure ◽  
Antiviral Drug ◽  
Rna Replication ◽  
Dynamics Simulation ◽  
Dependent Endonuclease

AbstractBaloxavir marboxil (BXM), an antiviral drug for influenza virus, inhibits RNA replication by binding to RNA replication cap-dependent endonuclease (CEN) of influenza A and B viruses. Although this drug was only approved by the FDA in October 2018, drug resistant viruses have already been detected from clinical trials owing to an I38 mutation of CEN. To investigate the reduction of drug sensitivity by the I38 mutant variants, we performed a molecular dynamics (MD) simulation on the CEN-BXM complex structure to analyze variations in the mode of interaction. Our simulation results suggest that the side chain methyl group of I38 in CEN engages in a CH-pi interaction with the aromatic ring of BXM. This interaction is abolished in various I38 mutant variants. Moreover, MD simulation on various mutation models and binding free energy prediction by MM/GBSA method suggest that the I38 mutation precludes any interaction with the aromatic ring of BXA and thereby reduces BXA sensitivity.

scholarly journals Parameterization of Boronates Using VFFDT and Paramfit for Molecular Dynamics Simulation

Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2196
Author(s):  
Barış Kurt ◽  
Hamdi Temel
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Ab Initio ◽  
Biologically Active ◽  
Dynamics Simulation ◽  
The Novel ◽  
Ab Initio Method ◽  
Crystallographic Structures ◽  
Dynamics Simulations ◽  
Experimental Structure

Boric acid, borate esters, and hydroxy derivatives are biologically active molecules. Thus, performing molecular dynamics simulations of these molecules is vital in terms of drug design, but it is difficult to find directly generated Amber parameters based on an ab initio method for these kinds of molecules in the literature. In this study, Amber parameters for such molecules containing boron were generated based on ab initio calculations using the paramfit program, which applies a combination of genetic and simplex algorithms, and the Visual Force Field Derivation Toolkit (VFFDT) program containing the Seminario method. The minimized structure, after obtaining novel parameters and using the sander program, was compared with the experimental crystallographic structures, and it was observed that the root-mean-square deviation (RMSD) value between the experimental structure and minimized structure agreed reasonably well. In addition, the molecule was heated, and the molecular dynamics simulation was successfully obtained with the novel parameters.

scholarly journals The SARS-CoV-2 exerts a distinctive strategy for interacting with the ACE2 human receptor

2020 ◽  
Author(s):  
Esther S. Brielle ◽  
Dina Schneidman-Duhovny ◽  
Michal Linial
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Cell Receptor ◽  
Host Recognition ◽  
Interface Residue ◽  
Binding Affinities ◽  
Temporal Dimension ◽  
Binding Interface ◽  
Residue Contacts ◽  
Dynamics Simulations

AbstractThe COVID-19 disease has plagued over 110 countries and has resulted in over 4,000 deaths within 10 weeks. We compare the interaction between the human ACE2 receptor and the SARS-CoV-2 spike protein with that of other pathogenic coronaviruses using molecular dynamics simulations. SARS-CoV, SARS-CoV-2, and HCoV-NL63 recognize ACE2 as the natural receptor but present a distinct binding interface to ACE2 and a different network of residue-residue contacts. SARS-CoV and SARS-CoV-2 have comparable binding affinities achieved by balancing energetics and dynamics. The SARS-CoV-2–ACE2 complex contains a higher number of contacts, a larger interface area, and decreased interface residue fluctuations relative to SARS-CoV. These findings expose an exceptional evolutionary exploration exerted by coronaviruses toward host recognition. We postulate that the versatility of cell receptor binding strategies has immediate implications on therapeutic strategies.One Sentence SummaryMolecular dynamics simulations reveal a temporal dimension of coronaviruses interactions with the host receptor.

scholarly journals Interrogating RNA-small molecule interactions with structure probing and AI augmented-molecular simulations

2021 ◽  
Author(s):  
Yihang Wang ◽  
Shaifaly Parmar ◽  
John S. Schneekloth ◽  
Pratyush Tiwary
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Ligand Recognition ◽  
Binding Affinities ◽  
Structure Probing ◽  
Mutational Profiling ◽  
In Vitro Measurements ◽  
Molecule Interactions ◽  
Dynamics Simulations

While there is increasing interest in the study of RNA as a therapeutic target, efforts to understand RNA-ligand recognition at the molecular level lag far behind our understanding of protein-ligand recognition. This problem is complicated due to the more than ten orders of magnitude in timescales involved in RNA dynamics and ligand binding events, making it not straightforward to design experiments or simulations. Here we make use of artificial intelligence (AI)-augmented molecular dynamics simulations to directly observe ligand dissociation for cognate and synthetic ligands from a riboswitch system. The site-specific flexibility profiles from our simulations are in excellent agreement with in vitro measurements of flexibility using Selective 2' Hydroxyl Acylation analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP). Our simulations reproduce known binding affinity profiles for the cognate and synthetic ligands, and pinpoint how both ligands make use of different aspects of riboswitch flexibility. On the basis of our dissociation trajectories, we also make and validate predictions of pairs of mutations for both the ligand systems that would show differing binding affinities. These mutations are distal to the binding site and could not have been predicted solely on the basis of structure. The methodology demonstrated here shows how molecular dynamics simulations with all-atom force-fields have now come of age in making predictions that complement existing experimental techniques and illuminate aspects of systems otherwise not trivial to understand.

scholarly journals Interaction of a sarcolipin pentamer and monomer with the sarcoplasmic reticulum calcium pump, SERCA

2019 ◽  
Author(s):  
J. P. Glaves ◽  
J. O. Primeau ◽  
P. A. Gorski ◽  
L. M. Espinoza-Fonseca ◽  
M. J. Lemieux ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Sarcoplasmic Reticulum ◽  
Molecular Dynamics Simulations ◽  
Maximal Activity ◽  
Protein Docking ◽  
The Novel ◽  
Wild Type ◽  
Transmembrane Segment ◽  
Dynamics Simulations ◽  
Sarcoplasmic Reticulum Calcium

ABSTRACTThe sequential rise and fall of cytosolic calcium underlies the contraction-relaxation cycle of muscle cells. While contraction is initiated by the release of calcium from the sarcoplasmic reticulum, muscle relaxation involves the active transport of calcium back into the sarcoplasmic reticulum. This re-uptake of calcium is catalysed by the sarco-endoplasmic reticulum Ca2+-ATPase (SERCA), which plays a lead role in muscle contractility. The activity of SERCA is regulated by small membrane protein subunits, most well-known being phospholamban (PLN) and sarcolipin (SLN). SLN physically interacts with SERCA and differentially regulates contractility in skeletal and atrial muscle. SLN has also been implicated in skeletal muscle thermogenesis. Despite these important roles, the structural mechanisms by which SLN modulates SERCA-dependent contractility and thermogenesis remain unclear. Here, we functionally characterized wild-type SLN and a pair of mutants, Asn4-Ala and Thr5-Ala, which yielded gain-of-function behavior comparable to what has been found for PLN. Next, we analyzed twodimensional crystals of SERCA in the presence of wild-type SLN by electron cryo-microscopy. The fundamental units of the crystals are anti-parallel dimer ribbons of SERCA, known for decades as an assembly of calcium-free SERCA molecules induced by the addition of decavanadate. A projection map of the SERCA-SLN complex was determined to a resolution of 8.5 Å, which allowed the direct visualization of a SLN pentamer. The SLN pentamer was found to interact with transmembrane segment M3 of SERCA, though the interaction appeared to be indirect and mediated by an additional density consistent with a SLN monomer. This SERCA-SLN complex correlated with the ability of SLN to decrease the maximal activity of SERCA, which is distinct from the ability of PLN to increase the maximal activity of SLN. Protein-protein docking and molecular dynamics simulations provided models for the SLN pentamer and the novel interaction between SERCA and a SLN monomer.STATEMENT OF SIGNIFICANCEThis research article describes a novel complex of the sarcoplasmic reticulum calcium pump SERCA and its regulatory subunit sarcolipin. Given the potential role of sarcolipin in skeletal muscle non-shivering thermogenesis, the interactions between SERCA and sarcolipin are of critical importance. Using complementary approaches of functional analysis, electron crystallography, and molecular dynamics simulations, we demonstrate an inherent interaction between SERCA, a sarcolipin monomer, and a sarcolipin pentamer. The interaction involves transmembrane segment M3 of SERCA, which allows sarcolipin to decrease the maximal activity or turnover rate of SERCA. Protein-protein docking and molecular dynamics simulations provided models for the SLN pentamer and the novel interaction between SERCA and a SLN monomer.

scholarly journals Promising Acyclovir and its derivatives to inhibit the protease of SARS-CoV-2: Molecular Docking and Molecular Dynamics simulations

2020 ◽  
Author(s):  
Durgesh Kumar ◽  
Kamlesh Kumari ◽  
Indra Bahadur ◽  
Prashant Singh
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Antiviral Drug ◽  
Amber Force Field ◽  
New Beginning ◽  
Dynamics Simulations ◽  
Cytomegalovirus Infections ◽  
Relative Change

Abstract Till date, more than 40 million people are affected throughout the world due to the COVID-19. Therefore, there is an urgency to find a solution to cure this infection. It is is due to the SARS-CoV-2 infection and the authors have targetted the protease of the SARS-CoV-2 so the infection will not spread. Herein, the authors have selected the antiviral drug, acyclovir for the inhibition of protease of the SARS-CoV-2. Acyclovir is a popular and selective antiherpes agent and started a new beginning for the viral infection. The other name of acyclovir is aciclovir and is being used in the treatment of chickenpox, and shingles. Further, it can be used in avoidance of cytomegalovirus infections. Even, acyclovir can used to cure the patients suffering from cold scores, shingles and also decreases the pain.In the present work, acyclovir (CMPD1) and its two derivatives, the first derivative is Ganciclovir (CMPD2) and the second derivative is (CMPD3). These three molecules were used to inhibit the protease of SARS-CoV-2. It was studied through the molecular docking, molecular dynamics simulations etc. Herein, simulations method were used to calculate relative change in binding free energy under the influence of Amber force field through MM-GBSA. The structural behavior of complex system with acyclovir and its derivatives were observed in term of RMSD and RMSF for all residues. Authors observed that complex of CMPD3 with the protease is stable and has less fluctuation than the native protease. Further, CMPD3 follow the creteria of all drug likeness term and it showed good activity against SARS-CoV-2. It was suggested that CMPD3 may be used as a inhibitor for coronavirus activity to protect life of human being in world.

scholarly journals Triazavirine supramolecular complexes as modifiers of the peptide oligomeric structure

2017 ◽  
Author(s):  
Alexey V. Shvetsov ◽  
Yana A. Zabrodskaya ◽  
Peter A. Nekrasov ◽  
Vladimir V. Egorov
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Mechanism Of Action ◽  
Antiviral Drug ◽  
Supramolecular Structures ◽  
Supramolecular Complexes ◽  
Oligomeric Structure ◽  
Model Peptide ◽  
Adequate Explanation ◽  
Dynamics Simulations

AbstractIn this study we present molecular dynamics simulations of the antiviral drug triazavirine, that affects formation of amyloid-like fibrils of the model peptide (SI). According to our simulations, triazavirine is able to form linear supramolecular structures which can act as shields and prevent interactions between SI monomers. This model, as validated by simulations, provides an adequate explanation of triazavirine’s mechanism of action as it pertains to SI peptide fibril formation.

Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation

2020 ◽  
Vol 20 (24) ◽  
pp. 2146-2167 ◽  
Author(s):  
Anuraj Nayarisseri ◽  
Ravina Khandelwal ◽  
Maddala Madhavi ◽  
Chandrabose Selvaraj ◽  
Umesh Panwar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Protease Inhibitors ◽  
Dynamics Simulation ◽  
The Novel ◽  
Public Health Services ◽  
Dynamic Simulations ◽  
Disease Patterns ◽  
Novel Coronavirus ◽  
Dynamics Simulations

Background: The vast geographical expansion of novel coronavirus and an increasing number of COVID-19 affected cases have overwhelmed health and public health services. Artificial Intelligence (AI) and Machine Learning (ML) algorithms have extended their major role in tracking disease patterns, and in identifying possible treatments. Objective: This study aims to identify potential COVID-19 protease inhibitors through shape-based Machine Learning assisted by Molecular Docking and Molecular Dynamics simulations. Methods: 31 Repurposed compounds have been selected targeting the main coronavirus protease (6LU7) and a machine learning approach was employed to generate shape-based molecules starting from the 3D shape to the pharmacophoric features of their seed compound. Ligand-Receptor Docking was performed with Optimized Potential for Liquid Simulations (OPLS) algorithms to identify highaffinity compounds from the list of selected candidates for 6LU7, which were subjected to Molecular Dynamic Simulations followed by ADMET studies and other analyses. Results: Shape-based Machine learning reported remdesivir, valrubicin, aprepitant, and fulvestrant as the best therapeutic agents with the highest affinity for the target protein. Among the best shape-based compounds, a novel compound identified was not indexed in any chemical databases (PubChem, Zinc, or ChEMBL). Hence, the novel compound was named 'nCorv-EMBS'. Further, toxicity analysis showed nCorv-EMBS to be suitable for further consideration as the main protease inhibitor in COVID-19. Conclusion: Effective ACE-II, GAK, AAK1, and protease 3C blockers can serve as a novel therapeutic approach to block the binding and attachment of the main COVID-19 protease (PDB ID: 6LU7) to the host cell and thus inhibit the infection at AT2 receptors in the lung. The novel compound nCorv- EMBS herein proposed stands as a promising inhibitor to be evaluated further for COVID-19 treatment.

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