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 In silico profiling of histone deacetylase inhibitory activity of compounds isolated from Cajanus cajan

2022 ◽  
Vol 11 (1) ◽  
Author(s):  
Kayode Adewole ◽  
Adebayo Ishola ◽  
Ige Olaoye
Keyword(s):  
Betulinic Acid ◽  
Hdac Inhibitor ◽  
In Silico ◽  
Histone Deacetylases ◽  
Cajanus Cajan ◽  
Molecular Mechanisms ◽  
Hdac Inhibitors ◽  
High Morbidity ◽  
Discovery Studio ◽  
Potential Inhibitors

Abstract Background Cancer is responsible for high morbidity and mortality globally. Because the overexpression of histone deacetylases (HDACs) is one of the molecular mechanisms associated with the development and progression of some diseases such as cancer, studies are now considering inhibition of HDAC as a strategy for the treatment of cancer. In this study, a receptor-based in silico screening was exploited to identify potential HDAC inhibitors among the compounds isolated from Cajanus cajan, since reports have earlier confirmed the antiproliferative properties of compounds isolated from this plant. Results Cajanus cajan-derived phytochemicals were docked with selected HDACs, with givinostat as the reference HDAC inhibitor, using AutodockVina and Discovery Studio Visualizer, BIOVIA, 2020. Furthermore, absorption, distribution, metabolism and excretion (ADME) drug-likeness analysis was done using the Swiss online ADME web tool. From the results obtained, 4 compounds; betulinic acid, genistin, orientin and vitexin, were identified as potential inhibitors of the selected HDACs, while only 3 compounds (betulinic acid, genistin and vitexin) passed the filter of drug-likeness. The molecular dynamic result revealed the best level of flexibility on HDAC1 and HDAC3 compared to the wild-type HDACs and moderate flexibility of HDAC7 and HDAC8. Conclusions The results of molecular docking, pharmacokinetics and molecular dynamics revealed that betulinic acid might be a suitable HDAC inhibitor worthy of further investigation in order to be used for regulating conditions associated with overexpression of HDACs. This knowledge can be used to guide experimental investigation on Cajanus cajan-derived compounds as potential HDAC inhibitors.

scholarly journals Design and in silico screening of aryl allyl mercaptan analogs as potential histone deacetylases (HDAC) inhibitors

Heliyon ◽  
2020 ◽  
Vol 6 (5) ◽  
pp. e03517 ◽  
Author(s):  
Sugandha Singhal ◽  
Mallika Pathak ◽  
Paban K. Agrawala ◽  
Himanshu Ojha
Keyword(s):  
In Silico ◽  
Histone Deacetylases ◽  
Hdac Inhibitors ◽  
In Silico Screening ◽  
Allyl Mercaptan

scholarly journals Combination of Curcumin from Curcuma longa and Procyanidin from Tamarindus indica in Inhibiting Cyclooxygenases for Primary Dysmenorrhea Therapy: In silico study

2020 ◽  
Vol 11 (1) ◽  
pp. 7460-7467
Keyword(s):  
Binding Affinity ◽  
Bioactive Compounds ◽  
In Silico ◽  
Curcuma Longa ◽  
Complex Form ◽  
Bioactive Compound ◽  
Primary Dysmenorrhea ◽  
Tamarindus Indica ◽  
Ligand Interaction ◽  
Discovery Studio

Turmeric (Curcuma longa) and Tamarind (Tamarindus indica) are known for the anti-inflammatory and antioxidant activity. The major bioactive compound found in turmeric is curcumin, and tamarind is procyanidin. Both compounds could reduce prostaglandin concentration, leading to the reduction of primary dysmenorrhea by inhibiting COXs. This study aims to identify the interaction of tamarind and turmeric bioactive compounds as single isolated compound and complex compounds to COXs using in silico as a model study. Proteins and bioactive compounds were obtained from PDB database and Pubchem, respectively. Both proteins and ligands will be prepared using Discovery Studio Client 3.5 and PyRx 0.8. The interaction will be performed by docking using Autodock Vina in PyRx 0.8. It showed that turmeric and tamarind bioactive compounds in single isolated form have potency in inhibiting COX-1/COX-2, and both ligands bind to the catalytic site of proteins. Binding sites are surrounding the binding site of the natural substrate with an efficient binding affinity. In the complex form of turmeric-tamarind, the binding affinity is not as efficient as single compounds. However, its complex form of both compounds provides strong inhibition. This study suggested that complex forms of curcumin and procyanidin can reduce prostaglandin concentration and stabilize protein-ligand interaction lead to healing dysmenorrhea.

scholarly journals Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1952 ◽  
Author(s):  
Hajar Sirous ◽  
Giuseppe Campiani ◽  
Simone Brogi ◽  
Vincenzo Calderone ◽  
Giulia Chemi
Keyword(s):  
In Silico ◽  
Histone Deacetylases ◽  
Predictive Power ◽  
Hdac Inhibitors ◽  
3D Qsar ◽  
Qsar Model ◽  
Large Set ◽  
Roc Curve Analysis ◽  
Histone Deacetylase 1 ◽  
Highly Active

Histone deacetylases (HDACs) are a class of epigenetic modulators overexpressed in numerous types of cancers. Consequently, HDAC inhibitors (HDACIs) have emerged as promising antineoplastic agents. Unfortunately, the most developed HDACIs suffer from poor selectivity towards a specific isoform, limiting their clinical applicability. Among the isoforms, HDAC1 represents a crucial target for designing selective HDACIs, being aberrantly expressed in several malignancies. Accordingly, the development of a predictive in silico tool employing a large set of HDACIs (aminophenylbenzamide derivatives) is herein presented for the first time. Software Phase was used to derive a 3D-QSAR model, employing as alignment rule a common-features pharmacophore built on 20 highly active/selective HDAC1 inhibitors. The 3D-QSAR model was generated using 370 benzamide-based HDACIs, which yielded an excellent correlation coefficient value (R2 = 0.958) and a satisfactory predictive power (Q2 = 0.822; Q2F3 = 0.894). The model was validated (r2ext_ts = 0.794) using an external test set (113 compounds not used for generating the model), and by employing a decoys set and the receiver-operating characteristic (ROC) curve analysis, evaluating the Güner–Henry score (GH) and the enrichment factor (EF). The results confirmed a satisfactory predictive power of the 3D-QSAR model. This latter represents a useful filtering tool for screening large chemical databases, finding novel derivatives with improved HDAC1 inhibitory activity.

In Silico Screening Reveals Histone Deacetylase 7 and ERK1/2 as Potential Targets for Artemisinin Dimer and Artemisinin Dimer Hemisuccinate

2020 ◽  
Vol 17 (5) ◽  
pp. 725-734
Author(s):  
Ahmed A. Ishola ◽  
Kayode E. Adewole
Keyword(s):  
Histone Deacetylase ◽  
Anticancer Drug ◽  
In Silico ◽  
Great Promise ◽  
Binding Affinities ◽  
Target Proteins ◽  
Discovery Studio ◽  
Artemisinin Derivatives ◽  
Anticancer Properties ◽  
Extracellular Signal

Background: Recent studies have observed overexpression of histone deacetylase 7 (HDAC7) and overactivity of extracellular signal-regulated kinases 1/2 (ERK1/2) in many tumors; therefore, pharmacological interventions to inhibit overexpression of HDAC7 and overactivity of ERK1/2 in cancerous cells holds great promise in cancer treatment. The promising anticancer properties of artemisinin and artemisinin-derivatives (ARTs) have been validated by various experimental reports, including advanced pre-clinical trials. Objective: Our aim in this in silico study is to identify additional inhibitors of HDAC7, ERK1 and ERK2 as potential anticancer drug agents and provide insight into the molecular level of interactions of such ligands relative to known standards. Methods: To achieve this aim, the binding affinities of ulixertinib (the standard ERK inhibitor), apicidin (the standard HDAC7 inhibitor) as well as 49 ARTs for HDAC7, ERK1 and ERK2 were evaluated using AutodockVina. The molecular binding interactions of compounds with remarkable binding affinity for all the 3 target proteins, relative to their respective standards, were viewed with Discovery Studio Visualizer, BIOVIA, 2016. Results: Out of the 49 ARTs, our study identified 2 compounds, artemisinin dimer and artemisinin dimer hemisuccinate, as having higher binding affinities for all the target proteins compared to their respective standard inhibitors. Conclusion: These findings suggest that artemisinin dimer and artemisinin dimer hemisuccinate could be promising anticancer drug agents, with better therapeutic efficacy than ulixertinib and apicidin for the treatment of cancer via inhibition of HDAC7, ERK1 and ERK2.

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.

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