scholarly journals In Silico End-to-End Protein–Ligand Interaction Characterization Pipeline: The Case of SARS-CoV-2

2021 ◽  
Author(s):  
Nícia Rosário-Ferreira ◽  
Salete J. Baptista ◽  
Carlos A. V. Barreto ◽  
Filipe E. P. Rodrigues ◽  
Tomás F. D. Silva ◽  
...  
Keyword(s):  
In Silico ◽  
Ligand Interaction ◽  
Protein Ligand Interaction ◽  
End To End

In-silico analysis of angiotensin converting enzyme 2 (ACE2) of livestock, pet and poultry animals to determine its susceptibility to SARS–CoV- 2 infection

2020 ◽  
Vol 23 ◽  
Author(s):  
Aman Kumar ◽  
Anil Panwar ◽  
Kanisht Batra ◽  
Sachinandan Dey ◽  
Sushila Maan
Keyword(s):  
In Silico ◽  
Binding Capacity ◽  
In Silico Analysis ◽  
Ligand Interaction ◽  
Angiotensin Converting Enzyme 2 ◽  
Animal Management ◽  
In Silico Study ◽  
Protein Ligand Interaction ◽  
Novel Coronavirus ◽  
Almost All

Background: Novel coronavirus SARS-CoV-2 is responsible of COVID-19 pandemic. It was first reported in Wuhan, China in December, 2019 and despite the tremendous efforts to control the disease, it has now spread almost all over the world.The interaction of SARS-CoV-2spike protein and its acceptor protein ACE2 is an important issue in determining viralhost range and cross-species infection, while the binding capacity of spike protein toACE2 of different species is unknown. Objective: The present study has been conducted to determine the susceptibility of livestock, poultry and pets to SARSCoV-2. Methods: We evaluated the receptor-utilizing capability of ACE2sfrom various species by sequence alignment,phylogenetic clustering and protein-ligand interaction studies with the currently knownACE2s utilized by SARS-CoV-2. Result: In-silico study predicted that SARS-CoV-2 tends to utilize ACE2s ofvarious animal species with varied possible interactions and theprobability ofthe receptor utilization will be greater in horse and poor in chicken followed by ruminants. Conclusion: Present studypredicted that SARS-CoV-2 tends to utilize ACE2s ofvarious livestock and poultry species with greater probability in equine and poor in chicken. Study may provide important insights into the animal models for SARSCoV-2 and animal management for COVID-19 control.

Identification of potential histone deacetylase inhibitory biflavonoids from Garcinia kola (Guttiferae) using in silico protein-ligand interaction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Kayode E. Adewole ◽  
Ahmed A. Ishola ◽  
Blessing O. Omolaso
Keyword(s):  
In Silico ◽  
Histone Deacetylases ◽  
Hdac Inhibitors ◽  
Intimate Relationship ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Garcinia Kola ◽  
Discovery Studio ◽  
Limited Success ◽  
Protein Ligand Interaction

Abstract Overactivity of histone deacetylases (HDACs) is the underlying cause of some cancers, thus, inhibiting their overactivities is a rational treatment option. However, endeavors to employ current anti-HDACs agents in cancer treatment have yielded limited success. Consequently, there is need to explore anti-HDACs natural products, especially from plants sources, because of the intimate relationship plant products and drug discovery have enjoyed over the centuries. To identify possible HDACs inhibitors, Garcinia kola (Guttiferae) seed-derived compounds were screened in silico for HDAC-inhibitory tendencies because of their reported anticancer potentials. Fifteen G. kola-derived compounds and givinostat were docked with five selected HDACs using AutodockVina, while the binding interactions of the compounds with high binding affinities for the five HDACs were viewed with Discovery Studio Visualizer BIOVIA, 2016. Results indicated that four of the compounds studied, including amentoflavone, Garcinia biflavonoid 1, Garcinia biflavonoid 2 and kolaflavanone have higher binding propensity for all the five HDACs relative to givinostat, the standard HDAC inhibitor. This study indicated that inhibition of HDAC might be another key mechanism accountable for the bioactivities of G. kola and its intrinsic compounds. The results from this study implied that the compounds could be further investigated as drugable HDAC inhibitors with potential pharmacological applications in the treatment of cancers.

scholarly journals Two Rules on the Protein-Ligand Interaction

2008 ◽  
Author(s):  
Xiaodong Pang ◽  
Linxiang Zhou ◽  
Lily Zhang ◽  
Lina Xu ◽  
Xinyi Zhang
Keyword(s):  
Ligand Interaction ◽  
Protein Ligand Interaction

scholarly journals In Silico Molecular Docking and Interaction Analysis of Traditional Chinese Medicines Against SARS-CoV-2 Receptor

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110150
Author(s):  
Gang Li ◽  
Wei Zhou ◽  
Xiurong Zhao ◽  
Ying Xie
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Interaction Analysis ◽  
Herbal Remedies ◽  
Receptor Protein ◽  
Stable Complex ◽  
Traditional Chinese Medicines ◽  
Ligand Interaction ◽  
Chinese Medicines ◽  
In Silico Molecular Docking

The novel coronavirus, 2019-nCoV, has led to a major pandemic in 2020 and is responsible for more than 2.9 million officially recorded deaths worldwide. As well as synthetic anti-viral drugs, there is also a need to explore natural herbal remedies. The Traditional Chinese Medicines (TCMs) system has been used for thousands of years for the prevention, diagnosis, and treatment of several chronic diseases. In this paper, we performed an in silico molecular docking and interaction analysis of TCMs against SARS-CoV-2 receptor RNA-dependent RNA polymerase (RdRp). We obtained the 5 most effective plant compounds which had a better binding affinity towards the target receptor protein. These compounds areforsythoside A, rutin, ginkgolide C, icariside II, and nolinospiroside E. The top-ranked compound, based on docking score, was nolinospiroside, a glycoside found in Ophiopogon japonicas that has antioxidant properties. Protein-ligand interaction analysis discerned that nolinospiroside formed a strong bond between ARG 349 of the protein receptor and the carboxylate group of the ligand, forming a stable complex. Hence, nolinospiroside could be deployed as a lead compound against SARS-CoV-2 infection that can be further investigated for its potential benefits in curbing the viral infection.

scholarly journals Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional

2021 ◽  
Author(s):  
Lennart Gundelach ◽  
Christofer S Tautermann ◽  
Thomas Fox ◽  
Chris-Kriton Skylaris
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Dft Calculations ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Ligand Interaction ◽  
Exchange Correlation ◽  
Ligand Free ◽  
Protein Ligand Interaction ◽  
Binding Free Energies

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of...

scholarly journals Fragment-centric topographic mapping method guides the understanding of ABCG2-inhibitor interactions

RSC Advances ◽  
2019 ◽  
Vol 9 (14) ◽  
pp. 7757-7766 ◽  
Author(s):  
Yao Wu ◽  
Xin-Ying Gao ◽  
Xin-Hui Chen ◽  
Shao-Long Zhang ◽  
Wen-Juan Wang ◽  
...  
Keyword(s):  
Mapping Method ◽  
Topographic Mapping ◽  
Ligand Interaction ◽  
Mapping Tool ◽  
Protein Ligand Interaction ◽  
Insight Into ◽  
Computational Strategy

Our study gains insight into the development of novel specific ABCG2 inhibitors, and develops a comprehensive computational strategy to understand protein ligand interaction with the help of AlphaSpace, a fragment-centric topographic mapping tool.

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