scholarly journals Zika virus phosphoproteome through the computational looking-glass and what we found there?

2016 ◽  
Author(s):  
Zarrin Basharat ◽  
Tabeer Khan ◽  
Azra Yasmin
Keyword(s):  
Viral Replication ◽  
Zika Virus ◽  
Preliminary Data ◽  
In Silico ◽  
Scientific Community ◽  
Twilight Zone ◽  
Post Translational Modification ◽  
Phosphorylation Potential ◽  
Wet Lab ◽  
Looking Glass

Computational phospho-mining and related post translational modification analyses using in silico methods is debateable. For some wet lab scientists, it is similar to the twilight zone, where nothing might be quite what it seems. We certainly agree that the wet lab is critical for validation but computational assays rapidly generate preliminary data for assessment and aid wet lab. Zika virus is wrecking a havoc and it is the need of the hour to rapidly assess various phenomenon associated with its pathogenicity and disseminate it to the scientific community for assessment. Phosphorylation assists in viral replication and its association with host receptors. Here, we present a vignette of the phosphorylation potential of Zika virus proteins.

scholarly journals Zika virus phosphoproteome through the computational looking-glass and what we found there?

2016 ◽  
Author(s):  
Zarrin Basharat ◽  
Tabeer Khan ◽  
Azra Yasmin
Keyword(s):  
Viral Replication ◽  
Zika Virus ◽  
Congenital Anomalies ◽  
Scientific Community ◽  
Viral Proteins ◽  
Computational Approach ◽  
Phosphorylation Potential ◽  
Looking Glass

Zika virus (ZIKV), a mosquito borne disease, has been linked to congenital anomalies in humans. Recent outbreaks of ZIKV have caused the scientific community to focus on this previously neglected pathogen. Information regarding phosphorylation potential of ZIKV proteins has yet to be elucidated. Deciphering phosphorylation potential of viral proteins is important because it assists in viral replication and its association with host receptors. Here, we present a vignette of the phosphorylation potential of ZIKV proteins using computational approach.

scholarly journals Zika virus phosphoproteome through the computational looking-glass and what we found there?

2016 ◽  
Author(s):  
Zarrin Basharat ◽  
Tabeer Khan ◽  
Azra Yasmin
Keyword(s):  
Viral Replication ◽  
Zika Virus ◽  
Congenital Anomalies ◽  
Scientific Community ◽  
Viral Proteins ◽  
Computational Approach ◽  
Phosphorylation Potential ◽  
Looking Glass

Zika virus (ZIKV), a mosquito borne disease, has been linked to congenital anomalies in humans. Recent outbreaks of ZIKV have caused the scientific community to focus on this previously neglected pathogen. Information regarding phosphorylation potential of ZIKV proteins has yet to be elucidated. Deciphering phosphorylation potential of viral proteins is important because it assists in viral replication and its association with host receptors. Here, we present a vignette of the phosphorylation potential of ZIKV proteins using computational approach.

Zika virus drug targets: a missing link in drug design and discovery – a route map to fill the gap

RSC Advances ◽  
2016 ◽  
Vol 6 (73) ◽  
pp. 68719-68731 ◽  
Author(s):  
Pritika Ramharack ◽  
Mahmoud E. S. Soliman
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Viral Replication ◽  
Zika Virus ◽  
In Silico ◽  
Drug Targets ◽  
Missing Link ◽  
Potential Inhibitors

This review depicts anin silicoroute map for ZIKV drug discovery, thus revealing novel potential inhibitors of viral replication.

Exploring PLAC1 Structure and Underlying Mechanisms to Design a Derivative Vaccine Against Breast Cancer Progression; In-Silico Study

2020 ◽  
Vol 17 (5) ◽  
pp. 379-391
Author(s):  
Farzaneh Afzali ◽  
Parisa Ghahremanifard ◽  
Mohammad Mehdi Ranjbar ◽  
Mahdieh Salimi
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
In Silico ◽  
Tertiary Structure ◽  
Specific Antigen ◽  
Docking Simulation ◽  
Post Translational Modification ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Underlying Mechanisms

Background: The tolerogenic homeostasis in Breast Cancer (BC) can be surpassed by rationally designed immune-encouraging constructs against tumor-specific antigens through immunoinformatics approach. Objective: Availability of high throughput data providing the underlying concept of diseases and awarded computational simulations, lead to screening the potential medications and strategies in less time and cost. Despite the extensive effects of Placenta Specific 1 (PLAC1) in BC progression, immune tolerance, invasion, cell cycle regulation, and being a tumor-specific antigen the fundamental mechanisms and regulatory factors were not fully explored. It is also worth to design an immune response inducing construct to surpass the hurdles of traditional anti-cancer treatments. Methods and Result: The study was initiated by predicting and modelling the PLAC1 secondary and tertiary structures and then engineering the fusion pattern of PLAC1 derived immunodominant predicted CD8+ and B-cell epitopes to form a multi-epitope immunogenic construct. The construct was analyzed considering the physiochemical characterization, safety, antigenicity, post-translational modification, solubility, and intrinsically disordered regions. After modelling its tertiary structure, proteinprotein docking simulation was carried out to ensure the attachment of construct with Toll-Like Receptor 4 (TLR4) as an immune receptor. To guarantee the highest expression of the designed construct in E. coli k12 as an expressional host, the codon optimization and in-silico cloning were performed. The PLAC1 related miRNAs in BC were excavated and validated through TCGA BC miRNA-sequencing and databases; the common pathways then were introduced as other probable mechanisms of PLAC1 activity. Conclusion: Regarding the obtained in-silico results, the designed anti-PLAC1 multi-epitope construct can probably trigger humoral and cellular immune responses and inflammatory cascades, therefore may have the potential of halting BC progression and invasion engaging predicted pathways.

scholarly journals Dual targeting of cytokine storm and viral replication in COVID-19 by plant-derived steroidal pregnanes: an in silico perspective

2021 ◽  
pp. 104406
Author(s):  
Gideon A. Gyebi ◽  
Oludare M. Ogunyemi ◽  
Ibrahim M. Ibrahim ◽  
Saheed O. Afolabi ◽  
Joseph O. Adebayo
Keyword(s):  
Viral Replication ◽  
In Silico ◽  
Cytokine Storm ◽  
Dual Targeting

scholarly journals In silico prediction of a highly immunogenic and conserved epitope against Zika Virus

2021 ◽  
pp. 100613
Author(s):  
Debasish Paul ◽  
Imdadul Haque Sharif ◽  
Abu Sayem ◽  
Hossain Ahmed ◽  
Abu Saleh ◽  
...  
Keyword(s):  
Zika Virus ◽  
In Silico ◽  
In Silico Prediction ◽  
Conserved Epitope

scholarly journals Super Resolution Microscopy and Deep Learning Identify Zika Virus Reorganization of the Endoplasmic Reticulum

2020 ◽  
Author(s):  
Rory K. M. Long ◽  
Kathleen P. Moriarty ◽  
Ben Cardoen ◽  
Guang Gao ◽  
A. Wayne Vogl ◽  
...  
Keyword(s):  
Endoplasmic Reticulum ◽  
Deep Learning ◽  
Viral Replication ◽  
Zika Virus ◽  
Deep Neural Networks ◽  
Super Resolution ◽  
Zikv Infection ◽  
Subcellular Organelle ◽  
Infected Cells ◽  
Super Resolution Microscopy

AbstractThe endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of endoplasmic reticulum (ER) membranes to facilitate viral replication. Here, using 3D super resolution microscopy, ZIKV infection is shown to induce the formation of dense tubular matrices associated with viral replication in the central ER. Viral non-structural proteins NS4B and NS2B associate with replication complexes within the ZIKV-induced tubular matrix and exhibit distinct ER distributions outside this central ER region. Deep neural networks trained to identify ZIKV-infected versus mock-infected cells successfully identified ZIKV-induced central ER tubular matrices as a determinant of viral infection. Super resolution microscopy and deep learning are therefore able to identify and localize morphological features of the ER and may be of use to screen for inhibitors of infection by ER-reorganizing viruses.

scholarly journals A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260054
Author(s):  
Safayat Mahmud Khan ◽  
Ar-Rafi Md. Faisal ◽  
Tasnin Akter Nila ◽  
Nabila Nawar Binti ◽  
Md. Ismail Hosen ◽  
...  
Keyword(s):  
Protein Structure ◽  
T Cell ◽  
Protein Stability ◽  
In Silico ◽  
Catalytic Domain ◽  
Cell Lymphoma ◽  
Computational Study ◽  
Solvent Accessibility ◽  
T Cell Lymphoma ◽  
Post Translational Modification

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5’ and 3’ untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.

In silico approaches to Zika virus drug discovery

2018 ◽  
Vol 13 (9) ◽  
pp. 825-835 ◽  
Author(s):  
Alessandro Sinigaglia ◽  
Silvia Riccetti ◽  
Marta Trevisan ◽  
Luisa Barzon
Keyword(s):  
Drug Discovery ◽  
Zika Virus ◽  
In Silico

IN SILICO CHARACTERIZATION, MOLECULAR DOCKING, AND IN VITRO EVALUATION OF TRIAZOLE DERIVATIVES AS POTENTIAL ANTICANCER AGENTS

2021 ◽  
pp. 22-28
Author(s):  
HARSHITHA T ◽  
VINAY KUMAR T ◽  
VINEETHA T
Keyword(s):  
Molecular Docking ◽  
Anticancer Activity ◽  
Anticancer Agents ◽  
In Silico ◽  
Docking Studies ◽  
Pharmacokinetic Parameters ◽  
Pancreatic Cell ◽  
Triazole Derivatives ◽  
Wet Lab

Objective: The objective of the study was to perform in silico molecular docking and in vitro anticancer studies of proposed 1,2,4-triazole derivatives for the determination of their anticancer activity. Methods: A series of 10 triazole compounds with different substituents were drawn in ACD Lab ChemSketch software. Molecular and biological properties were identified using Molinspiration software. The compounds that obeyed Lipinski rule of five are subjected for pharmacokinetic parameters prediction and docking analysis. SwissDock ADME software is used for the prediction of absorption, distribution, metabolism, and elimination. Then, the compounds are docked with target enzymes in Chimera software 1.14 version. The molecular docking studies revealed favorable molecular interactions and binding energies. The compounds that showed good docking results were synthesized through wet lab synthesis and further preceded for in vitro anticancer studies. Results: Three compounds are selected for wet lab synthesis due to their good docking results compared to other compounds. The synthesized compounds are subjected to different in vitro anticancer studies and found to be having potential anticancer activity. Conclusion: The pharmacokinetic and docking studies conclude that the triazole compounds have potential as anticancer agents. The in vitro anticancer studies revealed that the triazole derivatives are having high potency of anticancer activity against pancreatic cell lines.

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