Anti-Obesity Therapeutic Targets Studied In Silico and In Vivo: A Systematic Review

Wendjilla F de Medeiros1, Ana Francisca T Gomes1, Ana Júlia F C Aguiar2

  • 1Nutrition Postgraduate Program, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil.

Insights

This systematic review identified therapeutic targets for obesity using computational methods. Human Pancreatic Lipase was the most studied target, highlighting the potential of in silico approaches for drug discovery.

Area of Science:

  • Pharmacology
  • Computational Biology
  • Obesity Research

Background:

  • Obesity is a complex global health issue requiring novel therapeutic strategies.
  • Information technology and computational tools offer new avenues for identifying drug targets.

Purpose of the Study:

  • To systematically review and identify therapeutic targets for obesity evaluated using in silico methods and validated in vivo.
  • To assess the methodologies and outcomes of computational approaches in obesity drug target identification.

Main Methods:

  • Systematic review following PRISMA guidelines, guided by PECo framework.
  • Searched multiple databases (PubMed, Scopus, etc.) for studies on in silico and in vivo obesity targets.
  • Included 12 articles from 1142 initial results, with 7 providing both in silico and in vivo data.

Main Results:

  • Identified several potential therapeutic targets, with Human Pancreatic Lipase (HPL) being the most frequently studied (n=4).
  • Molecular docking was the predominant in silico methodology.
  • Over 50% of studies had an 'unclear risk of bias' due to insufficient methodological details.

Conclusions:

  • Integrating in silico methodologies is a valuable tool for discovering new therapeutic agents for obesity.
  • Further research with detailed methodologies is needed to strengthen the reliability of in silico findings.
  • Computational approaches show promise in addressing the challenges of obesity control.