Prediction of the Anti-Parkinson’s Effect of Phytoconstituents from Mucuna Pruriens with the use of Prediction of Activities Spectra of Substances Software

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Published: November 10, 2022
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Authors

  • Sakshi Sharma
  • Navneet Khurana
  • Vikas Sharma
  • Soumik Chaudhury
  • Samriti, Talluri Sriram
  • Neha Sharma
DOI Number
https://doi.org/10.15415/jptrm.2022.102008
Keywords
Parkinson’s disease, Levodopa, Prediction of activities spectra of substances software

Abstract

Mucuna pruriens Linn is the most popular plant which has been used for a long time for treating many diseases. The plants shows wide pharmacological activities like antidiabetic, antineoplastic, antiepileptic, aphrodisiac, antimicrobial activities etc. It has wide use in the treatment of the Parkinson’s disease. The rationale behind this study is to discover the maximum activities over the selected phytoconstituent of the plant Mucuna pruriens which can be used in Parkinson’s disease. With the help of Prediction of activities spectra of substances (PASS) software activities which are useful in the management of Parkinson’s disease can be recognized. The mol file of the compounds was downloaded from Pubchem and the activity of the various compounds was speculated in the PASS software. From the data we have noted the Pa values of the compounds and the related activities of the compounds then we have predicted the reported activities of the compounds and from the table and graph we have observed the higher and lowest value of the compounds showing different activities and also observed which are the compounds which does not show the activities.

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How to Cite

Sakshi Sharma, Navneet Khurana, Vikas Sharma, Soumik Chaudhury, Samriti, Talluri Sriram and Neha Sharma. Prediction of the Anti-Parkinson’s Effect of Phytoconstituents from Mucuna Pruriens with the use of Prediction of Activities Spectra of Substances Software. J. Pharm. Technol. Res. Manag.. 2022, 10, 181-199
Prediction of the Anti-Parkinson’s Effect of Phytoconstituents from Mucuna Pruriens with the use of Prediction of Activities Spectra of Substances Software

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