In Silico and in Vivo Analysis of HIV-1 Rev Regulatory Protein for Evaluation of a Multiepitope-based Vaccine Candidate

2021 ◽  
pp. 1-28
Author(s):  
Samaneh H. Shabani ◽  
Kimia Kardani ◽  
Alireza Milani ◽  
Azam Bolhassani
Keyword(s):  
In Silico ◽  
Vaccine Candidate ◽  
Regulatory Protein ◽  
In Vivo Analysis ◽  
Hiv 1

In Silico Identification of a Potent Arsenic Based Approved Drug Darinaparsin against SARS-CoV-2: Inhibitor of RNA Dependent RNA polymerase (RdRp) and Essential Proteases

2020 ◽  
Vol 20 ◽  
Author(s):  
Trinath Chowdhury ◽  
Gourisankar Roymahapatra ◽  
Santi M. Mandal
Keyword(s):  
Rna Polymerase ◽  
Viral Entry ◽  
In Silico ◽  
Rna Dependent Rna Polymerase ◽  
Replication Complex ◽  
In Silico Study ◽  
Life Threatening ◽  
In Vivo Analysis ◽  
3Cl Protease

Background: COVID-19 is a life threatening novel corona viral infection to our civilization and spreading rapidly. Terrific efforts are generous by the researchers to search for a drug to control SARS-CoV-2. Methods: Here, a series of arsenical derivatives were optimized and analyzed with in silico study to search the inhibitor of RNA dependent RNA polymerase (RdRp), the major replication factor of SARS-CoV-2. All the optimized derivatives were blindly docked with RdRp of SARS-CoV-2 using iGEMDOCK v2.1. Results: Based on the lower idock score in the catalytic pocket of RdRp, darinaparsin (-82.52 kcal/mol) revealed most effective among them. Darinaparsin strongly binds with both Nsp9 replicase protein (-8.77 kcal/mol) and Nsp15 endoribonuclease (-8.3 kcal/mol) of SARS-CoV-2 as confirmed from the AutoDock analysis. During infection, the ssRNA of SARS-CoV2 is translated into large polyproteins forming viral replication complex by specific proteases like 3CL protease and papain protease. This is also another target to control the virus infection where darinaparsin also perform the inhibitory role to proteases of 3CL protease (-7.69 kcal/mol) and papain protease (-8.43 kcal/mol). Conclusion: In host cell, the furin protease serves as a gateway to the viral entry and darinaparsin docked with furin protease which revealed a strong binding affinity. Thus, screening of potential arsenic drugs would help in providing the fast invitro to in-vivo analysis towards development of therapeutics against SARS-CoV-2.

In-Silico Analysis to Identify Potential Inhibitors Against the Protein NSP12 of SARS-CoV-2

2021 ◽  
Vol 6 (3) ◽  
pp. 48-60
Author(s):  
Hima Vyshnavi ◽  
Gayathri S. S. ◽  
Shahanas Naisam ◽  
Suvanish Kumar ◽  
Nidhin Sreekumar
Keyword(s):  
In Silico ◽  
Interaction Analysis ◽  
In Silico Analysis ◽  
Drug Efficacy ◽  
Drug Candidate ◽  
In Vivo Analysis ◽  
The Stability ◽  
Potential Inhibitors ◽  
Silico Analysis

In this pandemic condition, a drug candidate which is effective against COVID-19 is very much desired. This study initiates an in silico analysis to screen small molecules such as phytochemicals, drug metabolites, and natural metabolites against Nsp12 (a catalytic unit for RNA transcription and replication). Molecular interaction analysis of 6M71 was carried out against 2,860 ligands using Schrodinger Glide software. After docking analysis, the top 10 molecules (Glide score) were subjected to MD simulation for validating the stability. It resulted in top 10 compounds with high binding affinities with the target molecule NSP 12. Out of these, top 3 compounds including PSID_08_LIG3 (HMDB0133544), PSID_08_LIG4 (HMDB0132898), and PSID_08_LIG9 (HMDB0128199) show better Glide scores, better H-bond interaction, better MMGBSA value and stability on dynamic simulation after analysis of the results. The suggested ligands can be postulated as effective antiviral drugs against COVID-19. Further in vivo analysis is needed for validating the drug efficacy.

scholarly journals Environmental Restrictions: A New Concept Governing HIV-1 Spread Emerging from Integrated Experimental-Computational Analysis of Tissue-Like 3D Cultures

Cells ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 1112 ◽  
Author(s):  
Samy Sid Ahmed ◽  
Nils Bundgaard ◽  
Frederik Graw ◽  
Oliver Fackler
Keyword(s):  
In Silico ◽  
Computational Analysis ◽  
Virus Transmission ◽  
Target Cells ◽  
Virus Spread ◽  
Transmission Modes ◽  
3D Collagen ◽  
Cell Densities ◽  
Hiv 1

HIV-1 can use cell-free and cell-associated transmission modes to infect new target cells, but how the virus spreads in the infected host remains to be determined. We recently established 3D collagen cultures to study HIV-1 spread in tissue-like environments and applied iterative cycles of experimentation and computation to develop a first in silico model to describe the dynamics of HIV-1 spread in complex tissue. These analyses (i) revealed that 3D collagen environments restrict cell-free HIV-1 infection but promote cell-associated virus transmission and (ii) defined that cell densities in tissue dictate the efficacy of these transmission modes for virus spread. In this review, we discuss, in the context of the current literature, the implications of this study for our understanding of HIV-1 spread in vivo, which aspects of in vivo physiology this integrated experimental–computational analysis takes into account, and how it can be further improved experimentally and in silico.

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