scholarly journals Identification of Immunodominant Epitopes in Allelic Variants VK210 and VK247 of Pakistani based Plasmodium Vivax Circumsporozoite Immunogen

2021 ◽  
Author(s):  
Shumaila Naz ◽  
Sajjad Ahmad ◽  
Sumra Wajid Abbasi ◽  
Saba Ismail ◽  
Shahid Waseem ◽  
...  
Keyword(s):  
Plasmodium Vivax ◽  
Binding Free Energy ◽  
Expression System ◽  
Three Dimensional ◽  
Cell Epitope ◽  
Docking Simulation ◽  
Free Energy Calculations ◽  
Experimental Investigations ◽  
Allelic Variants ◽  
Tropical Regions

Abstract Plasmodium vivax-induced malaria is one of the leading causes of morbidity and mortality in sub-tropical and tropical regions and known to infect 2.85 billion people globally. The continual rise and propagation of resistance against anti-malarial drugs is a prerequisite to identify a possible vaccine candidate for Plasmodium vivax (P. vivax). Circumsporozoite protein (CSP) is an important immunogen of malaria parasite that has conserved the CSP structure as an immune dominant B-cell epitope. In the current study, we focused on designing multi-epitope vaccines (MEVs) using various immunoinformatics tools against Pakistani based allelic variants VK210 and VK247 of P. vivax CSP (PvCSP) gene. Antigenicity, allergic potential and physicochemical parameters of both PvCSP variants were assessed for the designed MEVs and are within acceptable range suitable for post experimental investigations. The three-dimensional structures of both MEV shave been predicted ab initio, optimized, and validated by using different online servers. Structure and from residues perspectives, the MEVs are stable and are free from aggregation-prone regions. The stability of both MEVs has been improved by a disulfide engineering approach. To estimate the binding energy and stability of the MEVs, molecular docking simulation and binding free energy calculations with TLR-4 immune receptor have been conducted. The expression of both MEVs produced in Escherichia coli K12 expression system by in silico cloning was significant. Immune simulation revealed that the proposed MEVs induce strong humoral and cellular immunological responses, in addition to significant production of interleukins and cytokines. In conclusions, we believed that the MEVs proposed in current research, using combine approach of immunoinformatics, structural biology and biophysical approaches, could induce protective and effective immune responses against P. vivax and the experimental validation of our findings could contribute to the development of potential malaria vaccine.

scholarly journals Alkaloids with Anti-Onchocercal Activity from Voacanga africana Stapf (Apocynaceae): Identification and Molecular Modeling

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 70 ◽  
Author(s):  
Smith B. Babiaka ◽  
Conrad V. Simoben ◽  
Kennedy O. Abuga ◽  
James A. Mbah ◽  
Rajshekhar Karpoormath ◽  
...  
Keyword(s):  
Binding Free Energy ◽  
Thioredoxin Reductase ◽  
Docking Simulation ◽  
Stem Bark ◽  
Free Energy Calculations ◽  
Dependent Manner ◽  
Adult Males ◽  
Traditional Use ◽  
Drug Concentrations ◽  
Ic50 Values

A new iboga-vobasine-type isomeric bisindole alkaloid named voacamine A (1), along with eight known compounds—voacangine (2), voacristine (3), coronaridine (4), tabernanthine (5), iboxygaine (6), voacamine (7), voacorine (8) and conoduramine (9)—were isolated from the stem bark of Voacangaafricana. The structures of the compounds were determined by comprehensive spectroscopic analyses. Compounds 1, 2, 3, 4, 6, 7 and 8 were found to inhibit the motility of both the microfilariae (Mf) and adult male worms of Onchocerca ochengi, in a dose-dependent manner, but were only moderately active on the adult female worms upon biochemical assessment at 30 μM drug concentrations. The IC50 values of the isolates are 2.49–5.49 µM for microfilariae and 3.45–17.87 µM for adult males. Homology modeling was used to generate a 3D model of the O. ochengi thioredoxin reductase target and docking simulation, followed by molecular dynamics and binding free energy calculations attempted to offer an explanation of the anti-onchocercal structure–activity relationship (SAR) of the isolated compounds. These alkaloids are new potential leads for the development of antifilarial drugs. The results of this study validate the traditional use of V. africana in the treatment of human onchocerciasis.

scholarly journals Potential Ebola drug targets – filling the gap: a critical step forward towards the design and discovery of potential drugs

Biologia ◽  
2017 ◽  
Vol 72 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Marissa Balmith ◽  
Mahmoud E.S. Soliman
Keyword(s):  
Binding Site ◽  
Active Site ◽  
Active Sites ◽  
Binding Free Energy ◽  
Three Dimensional ◽  
Computational Prediction ◽  
Homology Model ◽  
Free Energy Calculations ◽  
Biologically Active ◽  
World Health

AbstractAmong the classified neglected infectious diseases, the Ebola virus (EboV) remains a challenging epidemic. This deadly virus has been reported as a category A bioweapon organism by the World Health Organization due to the serious threat it poses. To date, Ebola drug discovery proves challenging. Proteins need to be targeted at the relevant biologically active site for drug or inhibitor binding to be effective. Due to insufficient experimental data to confirm the biologically active binding site for novel protein targets, researchers often rely on computational prediction methods to identify binding sites. Many computational studies have attempted to identify the biological active site for EboV proteins, however, the methods employed are not sufficiently validated. This has prompted us to provide a comprehensive molecular understanding of the various targets of the EboV, including three-dimensional structures, active site identification and further validation. Herein we report the account of a three-dimensional homology model of the unresolved EboV RNA-dependent RNA polymerase (RdRp), as well as a comprehensive analysis of the binding site residues of all proteins of the EboV. Docking-aided active site determination was carried out to identify possible active sites on the homology model of RdRp. Binding free energy calculations revealed subtle differences in the binding at each site. These results can also provide some potential clues for further design of novel inhibitors to treat this killer virus and is a critical cornerstone of research into the EboV.

A computational Grid framework for immunological applications

2009 ◽  
Vol 367 (1898) ◽  
pp. 2705-2716 ◽  
Author(s):  
Mark D. Halling-Brown ◽  
David S. Moss ◽  
Clare E. Sansom ◽  
Adrian J. Shepherd
Keyword(s):  
T Cell ◽  
Three Dimensional ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Computational Grid ◽  
Free Energy Calculations ◽  
Class I ◽  
T Cell Epitope ◽  
The European Union ◽  
Grid Middleware

We have developed a computational Grid that enables us to exploit through a single interface a range of local, national and international resources. It insulates the user as far as possible from issues concerning administrative boundaries, passwords and different operating system features. This work has been undertaken as part of the European Union ImmunoGrid project whose aim is to develop simulations of the immune system at the molecular, cellular and organ levels. The ImmunoGrid consortium has members with computational resources on both sides of the Atlantic. By making extensive use of existing Grid middleware, our Grid has enabled us to exploit consortium and publicly available computers in a unified way, notwithstanding the diverse local software and administrative environments. We took 40 000 polypeptide sequences from 4000 avian and mammalian influenza strains and used a neural network for class I T-cell epitope prediction tools for 120 class I alleles and haplotypes to generate over 14 million high-quality protein–peptide binding predictions that we are mapping onto the three-dimensional structures of the proteins. By contrast, the Grid is also being used for developing new methods for class T-cell epitope predictions, where we have running batches of 120 molecular dynamics free-energy calculations.

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Author(s):  
Christina Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculation ◽  
Large Scale Assessment ◽  
New Public ◽  
Binding Free Energy Calculations

Here we present an evaluation of the binding affinity prediction accuracy of the free energy calculation method FEP+ on internal active drug discovery projects and on a large new public benchmark set.<br>

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

scholarly journals Structural Characterization of Receptor–Receptor Interactions in the Allosteric Modulation of G Protein-Coupled Receptor (GPCR) Dimers

2021 ◽  
Vol 22 (6) ◽  
pp. 3241
Author(s):  
Raudah Lazim ◽  
Donghyuk Suh ◽  
Jai Woo Lee ◽  
Thi Ngoc Lan Vu ◽  
Sanghee Yoon ◽  
...  
Keyword(s):  
G Protein ◽  
Protein Interactions ◽  
Metabotropic Glutamate Receptor ◽  
Three Dimensional ◽  
Allosteric Modulation ◽  
Experimental Investigations ◽  
G Protein Coupled Receptor ◽  
Metabotropic Glutamate ◽  
Gpcr Activation ◽  
G Protein Coupled

G protein-coupled receptor (GPCR) oligomerization, while contentious, continues to attract the attention of researchers. Numerous experimental investigations have validated the presence of GPCR dimers, and the relevance of dimerization in the effectuation of physiological functions intensifies the attractiveness of this concept as a potential therapeutic target. GPCRs, as a single entity, have been the main source of scrutiny for drug design objectives for multiple diseases such as cancer, inflammation, cardiac, and respiratory diseases. The existence of dimers broadens the research scope of GPCR functions, revealing new signaling pathways that can be targeted for disease pathogenesis that have not previously been reported when GPCRs were only viewed in their monomeric form. This review will highlight several aspects of GPCR dimerization, which include a summary of the structural elucidation of the allosteric modulation of class C GPCR activation offered through recent solutions to the three-dimensional, full-length structures of metabotropic glutamate receptor and γ-aminobutyric acid B receptor as well as the role of dimerization in the modification of GPCR function and allostery. With the growing influence of computational methods in the study of GPCRs, we will also be reviewing recent computational tools that have been utilized to map protein–protein interactions (PPI).

scholarly journals In Silico Exploration of Phytoconstituents From Phyllanthus emblica and Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp

2021 ◽  
Vol 15 ◽  
pp. 117793222110274
Author(s):  
Khushboo Pandey ◽  
Kiran Bharat Lokhande ◽  
K Venkateswara Swamy ◽  
Shuchi Nagar ◽  
Manjusha Dake
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Simulation Analysis ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Molecular Field ◽  
Hydroxyl Groups ◽  
Phyllanthus Emblica ◽  
Inhibitory Potential ◽  
Novel Drug

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100 ns molecular dynamics (MD) simulation followed by post-simulation analysis. Furthermore, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that EBDGp possesses a stronger binding affinity (−23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (−19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity toward SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.

Assessment of Unsteady Flows in Turbines

1992 ◽  
Vol 114 (1) ◽  
pp. 79-90 ◽  
Author(s):  
O. P. Sharma ◽  
G. F. Pickett ◽  
R. H. Ni
Keyword(s):  
Unsteady Flow ◽  
Three Dimensional ◽  
Flow Simulation ◽  
Experimental Investigations ◽  
Flow Parameters ◽  
Research Activities ◽  
Flow Features ◽  
Computational Fluid Dynamics Cfd ◽  
Turbine Design ◽  
The Impact

The impacts of unsteady flow research activities on flow simulation methods used in the turbine design process are assessed. Results from experimental investigations that identify the impact of periodic unsteadiness on the time-averaged flows in turbines and results from numerical simulations obtained by using three-dimensional unsteady Computational Fluid Dynamics (CFD) codes indicate that some of the unsteady flow features can be fairly accurately predicted. Flow parameters that can be modeled with existing steady CFD codes are distinguished from those that require unsteady codes.

scholarly journals Molecular modeling study on the drug resistance mechanism of NS5B polymerase to TMC647055

2016 ◽  
Vol 94 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Huiqun Wang ◽  
Wei Cui ◽  
Chenchen Guo ◽  
Bo-Zhen Chen ◽  
Mingjuan Ji
Keyword(s):  
Drug Resistance ◽  
Free Energy ◽  
Rational Design ◽  
Binding Free Energy ◽  
Resistance Mechanism ◽  
Free Energy Calculations ◽  
Side Chain ◽  
Free Energy Decomposition ◽  
Hcv Ns5b ◽  
Ns5b Polymerase

NS5B polymerase plays an important role in viral replication machinery. TMC647055 (TMC) is a novel and potent non-nucleoside inhibitor of the HCV NS5B polymerase. However, mutations that result in drug resistance to TMC have been reported. In this study, we used molecular dynamics (MD) simulations, binding free energy calculations, and free energy decomposition to investigate the drug resistance mechanism of HCV to TMC resulting from L392I, P495T, P495S, and P495L mutations in NS5B polymerase. From the calculated results we determined that the decrease in the binding affinity between TMC and NS5BL392I polymerase is mainly caused by the extra methyl group at the CB atom of Ile. The polarity of the side-chain of residue 495 has no distinct influence on residue 495 binding with TMC, whereas the smaller size of the side-chain of residue 495 causes a substantial decrease in the van der Walls interaction between TMC and residue 495. Moreover, the longer length of the side-chain of residue 495 has a significant effect on the electrostatic interaction between TMC and Arg-503. Finally, we performed the same calculations and detailed analysis on other 3 mutations (L392V, P495V, and P495I). The results further confirmed our conclusions. The computational results not only reveal the drug resistance mechanism between TMC647055 and NS5B polymerase, but also provide valuable information for the rational design of more potent non-nucleoside inhibitors targeting HCV NS5B polymerase.

Sign in / Sign up

Export Citation Format

Share Document