Affiliations 

  • 1 Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM), Indera Mahkota, Kuantan 25200, Pahang, Malaysia. [email protected]
  • 2 Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM), Indera Mahkota, Kuantan 25200, Pahang, Malaysia. [email protected]
  • 3 Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM), Indera Mahkota, Kuantan 25200, Pahang, Malaysia. [email protected]
  • 4 Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM), Indera Mahkota, Kuantan 25200, Pahang, Malaysia. [email protected]
  • 5 Laboratoire de Synthèse Organique Appliquée, Faculté des Sciences Exactes et Appliquées, Département de Chimie, Université Oran1, BP 1524 El Mnaoueur, 31000 Oran, Algérie. [email protected]
  • 6 Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM), Indera Mahkota, Kuantan 25200, Pahang, Malaysia. [email protected]
Molecules, 2018 06 13;23(6).
PMID: 29899270 DOI: 10.3390/molecules23061434

Abstract

Salak fruit (Salacca zalacca), commonly known as snake fruit, is used indigenously as food and for medicinal applications in Southeast Asia. This study was conducted to evaluate the α-glucosidase inhibitory activity of salak fruit extracts in correlation to its Fourier transform infrared spectroscopy (FT-IR) fingerprint, utilizing orthogonal partial least square. This calibration model was applied to develop a rapid analytical method tool for quality control of this fruit. A total of 36 extracts prepared with different solvent ratios of ethanol⁻water (100, 80, 60, 40.20, 0% v/v) and their α-glucosidase inhibitory activities determined. The FT-IR spectra of ethanol⁻water extracts measured in the region of 400 and 4000 cm−1 at a resolution of 4 cm−1. Multivariate analysis with a combination of orthogonal partial least-squares (OPLS) algorithm was used to correlate the bioactivity of the samples with the FT-IR spectral data. The OPLS biplot model identified several functional groups (C⁻H, C=O, C⁻N, N⁻H, C⁻O, and C=C) which actively induced α-glucosidase inhibitory activity.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.