| Title |
In Silico Investigations of Chemical Constituents of Clerodendrum colebrookianum in the Anti-Hypertensive Drug Targets: ROCK, ACE, and PDE5
|
|---|---|
| Published in |
Interdisciplinary Sciences: Computational Life Sciences, June 2017
|
| DOI | 10.1007/s12539-017-0243-6 |
| Pubmed ID | |
| Authors |
Hemant Arya, Safiulla Basha Syed, Sorokhaibam Sureshkumar Singh, Dinakar R. Ampasala, Mohane Selvaraj Coumar |
| Abstract |
Understanding the molecular mode of action of natural product is a key step for developing drugs from them. In this regard, this study is aimed to understand the molecular-level interactions of chemical constituents of Clerodendrum colebrookianum Walp., with anti-hypertensive drug targets using computational approaches. The plant has ethno-medicinal importance for the treatment of hypertension and reported to show activity against anti-hypertensive drug targets-Rho-associated coiled-coil protein kinase (ROCK), angiotensin-converting enzyme, and phosphodiesterase 5 (PDE5). Docking studies showed that three chemical constituents (acteoside, martinoside, and osmanthuside β6) out of 21 reported from the plant to interact with the anti-hypertensive drug targets with good glide score. In addition, they formed H-bond interactions with the key residues Met156/Met157 of ROCK I/ROCK II and Gln817 of PDE5. Further, molecular dynamics (MD) simulation of protein-ligand complexes suggest that H-bond interactions between acteoside/osmanthuside β6 and Met156/Met157 (ROCK I/ROCK II), acteoside and Gln817 (PDE5) were stable. The present investigation suggests that the anti-hypertensive activity of the plant is due to the interaction of acteoside and osmanthuside β6 with ROCK and PDE5 drug targets. The identified molecular mode of binding of the plant constituents could help to design new drugs to treat hypertension. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 21% |
| Student > Master | 4 | 12% |
| Researcher | 4 | 12% |
| Student > Doctoral Student | 3 | 9% |
| Lecturer | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 11 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 21% |
| Biochemistry, Genetics and Molecular Biology | 7 | 21% |
| Agricultural and Biological Sciences | 3 | 9% |
| Nursing and Health Professions | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 15 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 June 2017.
All research outputs
#20,428,633
of 22,981,247 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#207
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Outputs of similar age
#254,066
of 291,513 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#6
of 7 outputs
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