scholarly journals In silico analysis of phytochemicals as potential inhibitors of proteases involved in SARS-CoV-2 infection

2020 ◽  
pp. 1-9
Author(s):  
Palaniyandi Umadevi ◽  
Subramanian Manivannan ◽  
Abdulkabeer Muhammed Fayad ◽  
Sreekumar Shelvy
Keyword(s):  
In Silico ◽  
In Silico Analysis ◽  
Potential Inhibitors ◽  
Silico Analysis

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 In silico analysis of SARS-CoV-2 papain-like protease potential inhibitors

RSC Advances ◽  
2021 ◽  
Vol 11 (61) ◽  
pp. 38616-38631
Author(s):  
Samia A. Elseginy ◽  
Manal M. Anwar
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
In Silico ◽  
In Silico Analysis ◽  
Potential Inhibitors ◽  
Silico Analysis

The emergent outbreak caused by severe acute respiratory syndrome coronavirus 2 continues spreading and causing huge social and economic disruption.

scholarly journals Identifying amine fragments as potential inhibitors of acetylcholinesterase and butyrylcholinesterase through in silico analysis and validation through in vitro enzyme inhibition analysis

2021 ◽  
Vol 17 (S9) ◽  
Author(s):  
Saravanan Kandasamy ◽  
Chitra Loganathan ◽  
Penislusshiyan Sakayanathan ◽  
Karthikeyan Subramani ◽  
Dinesh Kumar Marimuthu ◽  
...  
Keyword(s):  
Enzyme Inhibition ◽  
In Silico ◽  
In Silico Analysis ◽  
Potential Inhibitors ◽  
Silico Analysis ◽  
Inhibition Analysis

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

In-Silico Analysis of Chromone Containing Sulfonamide Derivatives as Human Carbonic Anhydrase Inhibitors

2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas
Keyword(s):  
Carbonic Anhydrase ◽  
In Silico ◽  
In Silico Analysis ◽  
Carbonic Anhydrase Inhibitors ◽  
Human Carbonic Anhydrase ◽  
Silico Analysis
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