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A Comparative Chemoinformatics Analysis of compounds extracted from Nyctanthes arbor-tristis.
Kotharkar, Nandini; Bapat, Sanket; Vyas, Renu; Pathak, Pranav.
Afiliação
  • Kotharkar N; MIT School of Bioengineering Sciences & Research Bio-engineering Pune India.
  • Bapat S; MIT School of Bioengineering Sciences & Research Bio-engineering Pune India.
  • Vyas R; MIT School of Bioengineering Sciences & Research Bio-engineering Pune India.
  • Pathak P; MIT School of Bioengineering Sciences & Research Bio-engineering Pune India.
Article em En | MEDLINE | ID: mdl-37073156
ABSTRACT

INTRODUCTION:

Natural products are a rich source of diverse chemical compounds with interesting therapeutic properties. There is a need for in-depth investigation of this reservoir with in-silico tools to assert the molecular diversity with respect to clinical significance. Although studies have been reported on plants such as Nyctanthes arbor-tristis(NAT) and its medicinal importance. A comprehensive study on comparative analysis of all phyto-constituents has not been carried out.

AIM:

In the present work, we have carried out a comparative study of compounds obtained from the ethanolic extracts of various parts such as calyx, corolla, leaf, and bark of the NAT plant.

METHODS:

The extracted compounds were characterized by LCMS and GCMS studies. This was further corroborated by the network analysis, docking, and dynamic simulation studies with validated anti-arthritic targets.

RESULTS:

The most significant observation from LCMS and GCMS was that the compounds from calyx and corolla were closer in chemical space to the anti-arthritic compounds. To further expand and explore chemical space, the common scaffolds were seeded to enumerate a virtual library. The virtual molecules were prioritized based on the drug-like, leadlike scores and docked against anti-arthritic targets to reveal identical interactions in the pocket region.

CONCLUSION:

The comprehensive study will be of immense value to medicinal chemists for the rational synthesis of molecules as well as bioinformatics professionals for getting useful insight into identifying rich diverse molecules from plant sources.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article