Unveiling α-Amylase Inhibition: A Bioinformatics Perspective on Peptide Properties and Amino Acid Contributions

Ainolsyakira Mohd Rodhi, Pei Gee Yap, Olusegun Abayomi Olalere, Chee Yuen Gan

Research output: Contribution to journalReview articlepeer-review

3 Citations (SciVal)

Abstract

α-Amylase (AA) inhibitory peptides are a new class of anti-diabetic therapeutic agents. A high number of peptides with different amino acid sequences were identified by researchers. However, the mechanism and the properties of the peptides are yet to be explored. In this review, AA inhibitory peptides were randomly chosen from the BioPEP-UWM database and recent publications. Subsequently, they were categorized into three groups (i.e. short peptide (SP), medium peptide (MP) and long peptide (LP)) based on the peptide length, followed by evaluation based on structure-activity relationship by using in silico approach. The AA hotspots were initially reviewed from the SAR analysis result, and found that four substrate analogues (Trp58, Trp59, Tyr62 and His299) and one catalytic residue (Asp300) were highly bound by these peptides, in general. However, the peptide length played a crucial factor in which SP has one less preferred hotspot (His299), whereas LP showed 2 additional hotspots more (Asp96 and Arg195). When reviewing the properties of the peptides, it was found that these peptides were highly hydrophobic, which contained amino acids with aliphatic side chains, followed by polar neutral regardless of peptide length. In general, proline, leucine, and serine were the top 3 reactive amino acid residues in the peptides. However, different prevalent amino acids were found in SP (proline, leucine and serine), MP (proline and leucine) and LP (glutamine, alanine and serine). When the terminal positions (i.e. ultimate (N1 and C1), penultimate (N2 and C2) and antepenultimate (N3 and C3) positions) were assessed, the data showed different preferences in the amino acid residues based on the peptide length. The details of interaction were also elaborated in this review based on the molecular docking analysis, in which hydrophobic interactions, salt bridges and hydrogen bonds were involved. In conclusion, this review provided the way of identifying the AA inhibitory peptides and offered fundamental and practical information for designing or discovering the peptide-based AA inhibitory agent.

Original languageEnglish
Article number137768
JournalJournal of Molecular Structure
Volume1305
Early online date9 Feb 2024
DOIs
Publication statusPublished - 5 Jun 2024

Data Availability Statement

Data will be made available on request.

Funding

No funding acknowledged.

Keywords

  • Inhibitor peptide property
  • Molecular docking
  • Structure-activity relationship
  • Terminal residue preference
  • α-amylase hotspots
  • α-amylase inhibitor

ASJC Scopus subject areas

  • Analytical Chemistry
  • Spectroscopy
  • Organic Chemistry
  • Inorganic Chemistry

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