Research Articles

2019  |  Vol: 5(6)  |  Issue: 6 (November-December)  |
Recent activities predicted by pass software online for hypertrophic cardiomyopathy

Abhay Tharmatt* Manisha Sharma

Department of Pharmaceutical Sciences Guru Nanak Dev University, Amritsar (143001) India

*Address for correspondence

Abhay Tharmatt

Department of Pharmaceutical Sciences,

Guru Nanak Dev University, Amritsar, India (143005)



Background: Hypertrophic Cardiomyopathy (HCM) is a cardiovascular disorder that is associated with major heart disorders. It is responsible for 60-80% of Heart failure cases. There is an urgent need for the discovery and development of newer drugs that could delay the progression of the disease as current pharmacotherapy offers only symptomatic liberation. Objective: Prediction of activity spectra of substances (PASS) is a valuable interface that should be adopted as an archetypal tool for predicting the potential anti-HCM capability of molecules and to predict the biological activity of certain phytoconstituents for their anti-HCM effects. Materials and Methods: Several phytoconstituents were nominated on the basis of the reported literature. The anti-HCM activities of selected phytoconstituents were predicted by engaging the canonical simplified molecular-input line-entry system obtained from followed by using PASS online. Results: Several phytoconstituents were predicted to have effects better than marketed drugs under some or the other out of the chosen areas of pharmacological mediation. On the other hand, several new paths were predicted in which the in vitro and in vivo evaluation of the phytoconstituents can be made on the basis of PASS predicted activities. Conclusion: PASS is an important tool for effectively showing the compounds of interest for the biological actions of interest. This helps the researchers to rationalize the research. However, PASS has its own share of limitations amidst a multitude of merits.

Keywords: Hypertrophic cardiomyopathy, phytoconstituents, Prediction of activity spectra of substances (PASS)

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