scholarly journals In Silico Study of Rotavirus VP7 Surface Accessible Conserved Regions for Antiviral Drug/Vaccine Design

PLoS ONE ◽  
2012 ◽  
Vol 7 (7) ◽  
pp. e40749 ◽  
Author(s):  
Ambarnil Ghosh ◽  
Shiladitya Chattopadhyay ◽  
Mamta Chawla-Sarkar ◽  
Papiya Nandy ◽  
Ashesh Nandy
Keyword(s):  
In Silico ◽  
Antiviral Drug ◽  
Vaccine Design ◽  
Conserved Regions ◽  
In Silico Study

An in silico study: Novel targets for potential drug and vaccine design against drug resistant H. pylori

2018 ◽  
Vol 122 ◽  
pp. 156-161 ◽  
Author(s):  
Chiranjeevi Pasala ◽  
Chandra Sekhar Reddy Chilamakuri ◽  
Sudheer Kumar Katari ◽  
Ravina Madhulitha Nalamolu ◽  
Aparna R. Bitla ◽  
...  
Keyword(s):  
In Silico ◽  
Vaccine Design ◽  
Drug Resistant ◽  
Potential Drug ◽  
In Silico Study ◽  
Novel Targets ◽  
H Pylori

scholarly journals In Silico Study of 1,5-Bis(4-Hydroxy-3-Methoxyphenyl)-1,4-Pentadiene-3-One (Deketene Curcumin) on Crystallized Protein Structures of SARS-CoV-2

2020 ◽  
Author(s):  
Vraj shah ◽  
Jaydip Bhaliya ◽  
Dhwani Shah
Keyword(s):  
In Silico ◽  
Low Cost ◽  
Protein Structures ◽  
Antiviral Drug ◽  
Good Choice ◽  
World Health ◽  
Effective Vaccine ◽  
Steric Interaction ◽  
Molegro Virtual Docker ◽  
In Silico Study

<p>World Health Organization (WHO) reveals total number of coronavirus cases are 5,684,802 and 352,225 deaths till today worldwide. Coronavirus instances are nevertheless surging due to its speedy spreading through infected patients. Therefore, in order to find potent vaccine almost every researcher is doing hard work to find it. However, until today there is not any availability of effective vaccine or drug for the treatment of COVID-19. In this case, the computational approach is the good choice to identify effective drugs and could be very useful due to its low cost, less error and less time consumption. Here, Deketene curcumin has taken for docking study because of its lots of biological applications such as antiviral, antimicrobial, anti-inflammatory, antioxidant, antibiotic, and to a name of few, it is a derivative of curcumin. In this study, five main protease crystallized COVID-19 structures (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81) have been taken for simulation against deketene curcumin. Required procedure for this in silico study done through Molegro virtual docker (MVD) and Molegro Molecular Viewer (MMV) used for visualization. The results showed H-bonding and steric interaction between Deketene Curcumin with COVID-19 (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81). Moldock scores of Deketene Curcumin Observed -134.198 kcal/mol, -151.972 kcal/mol, -109.224 kcal/mol, -140.741 kcal/mol and -126.562 kcal/mol with PDB Id 6LU7, 5R7Z, 5R7Y, 5R80 and 5R81 respectively. As per our results, it can be say that Deketene Curcumin has effective as a lead compound to find new antiviral drug candidates against COVID-19 for possible medicinal agent.</p>

scholarly journals In Silico Study of 1,5-Bis(4-Hydroxy-3-Methoxyphenyl)-1,4-Pentadiene-3-One (Deketene Curcumin) on Crystallized Protein Structures of SARS-CoV-2

2020 ◽  
Author(s):  
Vraj shah ◽  
Jaydip Bhaliya ◽  
Dhwani Shah
Keyword(s):  
In Silico ◽  
Low Cost ◽  
Protein Structures ◽  
Antiviral Drug ◽  
Good Choice ◽  
World Health ◽  
Effective Vaccine ◽  
Steric Interaction ◽  
Molegro Virtual Docker ◽  
In Silico Study

<p>World Health Organization (WHO) reveals total number of coronavirus cases are 5,684,802 and 352,225 deaths till today worldwide. Coronavirus instances are nevertheless surging due to its speedy spreading through infected patients. Therefore, in order to find potent vaccine almost every researcher is doing hard work to find it. However, until today there is not any availability of effective vaccine or drug for the treatment of COVID-19. In this case, the computational approach is the good choice to identify effective drugs and could be very useful due to its low cost, less error and less time consumption. Here, Deketene curcumin has taken for docking study because of its lots of biological applications such as antiviral, antimicrobial, anti-inflammatory, antioxidant, antibiotic, and to a name of few, it is a derivative of curcumin. In this study, five main protease crystallized COVID-19 structures (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81) have been taken for simulation against deketene curcumin. Required procedure for this in silico study done through Molegro virtual docker (MVD) and Molegro Molecular Viewer (MMV) used for visualization. The results showed H-bonding and steric interaction between Deketene Curcumin with COVID-19 (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81). Moldock scores of Deketene Curcumin Observed -134.198 kcal/mol, -151.972 kcal/mol, -109.224 kcal/mol, -140.741 kcal/mol and -126.562 kcal/mol with PDB Id 6LU7, 5R7Z, 5R7Y, 5R80 and 5R81 respectively. As per our results, it can be say that Deketene Curcumin has effective as a lead compound to find new antiviral drug candidates against COVID-19 for possible medicinal agent.</p>

scholarly journals In vitro and in silico study to evaluate the effectiveness of quercitrin as antiviral drug to dengue virus

2019 ◽  
Author(s):  
Beti Ernawati Dewi ◽  
Edianti Ratningpoeti ◽  
Hidayati Desti ◽  
Marissa Angelina
Keyword(s):  
Dengue Virus ◽  
In Silico ◽  
Antiviral Drug ◽  
In Silico Study

In Silico Study of Structural and Geometrical Requirements of Natural Sesquiterpene Lactones with Trypanocidal Activity

2013 ◽  
Vol 13 (10) ◽  
pp. 1407-1414 ◽  
Author(s):  
L. Fabian ◽  
V. Sulsen ◽  
F. Frank ◽  
S. Cazorla ◽  
E. Malchiodi ◽  
...  
Keyword(s):  
In Silico ◽  
Sesquiterpene Lactones ◽  
Trypanocidal Activity ◽  
In Silico Study

In Silico Study of 1, 4 Alpha Glucan Branching Enzyme and Substrate Docking Studies

2020 ◽  
Vol 17 (1) ◽  
pp. 40-50
Author(s):  
Farzane Kargar ◽  
Amir Savardashtaki ◽  
Mojtaba Mortazavi ◽  
Masoud Torkzadeh Mahani ◽  
Ali Mohammad Amani ◽  
...  
Keyword(s):  
Phylogenetic Tree ◽  
In Silico ◽  
Alpha Helix ◽  
In Silico Analysis ◽  
Glycogen Storage ◽  
Docking Studies ◽  
Random Coil ◽  
Special Topic ◽  
Industrial Biotechnology ◽  
In Silico Study

Background: The 1,4-alpha-glucan branching protein (GlgB) plays an important role in the glycogen biosynthesis and the deficiency in this enzyme has resulted in Glycogen storage disease and accumulation of an amylopectin-like polysaccharide. Consequently, this enzyme was considered a special topic in clinical and biotechnological research. One of the newly introduced GlgB belongs to the Neisseria sp. HMSC071A01 (Ref.Seq. WP_049335546). For in silico analysis, the 3D molecular modeling of this enzyme was conducted in the I-TASSER web server. Methods: For a better evaluation, the important characteristics of this enzyme such as functional properties, metabolic pathway and activity were investigated in the TargetP software. Additionally, the phylogenetic tree and secondary structure of this enzyme were studied by Mafft and Prabi software, respectively. Finally, the binding site properties (the maltoheptaose as substrate) were studied using the AutoDock Vina. Results: By drawing the phylogenetic tree, the closest species were the taxonomic group of Betaproteobacteria. The results showed that the structure of this enzyme had 34.45% of the alpha helix and 45.45% of the random coil. Our analysis predicted that this enzyme has a potential signal peptide in the protein sequence. Conclusion: By these analyses, a new understanding was developed related to the sequence and structure of this enzyme. Our findings can further be used in some fields of clinical and industrial biotechnology.

In Silico Study of Ethylene Biosynthesis: Seeking New Effectors of ACC Synthase and ACC Oxidase

2016 ◽  
Vol 11 (3) ◽  
pp. 346-356
Author(s):  
Nada Ayadi ◽  
Sarra Aloui ◽  
Rabeb Shaiek ◽  
Oussama Rokbani ◽  
Faten Raboud ◽  
...  
Keyword(s):  
In Silico ◽  
Acc Oxidase ◽  
Acc Synthase ◽  
Ethylene Biosynthesis ◽  
In Silico Study

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.

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