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.
Abstract:
In the age of information technology and the additional computational search tools and software available, this systematic review aimed to identify potential therapeutic targets for obesity, evaluated in silico and subsequently validated in vivo. The systematic review was initially guided by the research question "What therapeutic targets have been used in in silico analysis for the treatment of obesity?" and structured based on the acronym PECo (P, problem; E, exposure; Co, context). The systematic review protocol was formulated and registered in PROSPERO (CRD42022353808) in accordance with the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis Protocols (PRISMA-P), and the PRISMA was followed for the systematic review. The studies were selected according to the eligibility criteria, aligned with PECo, in the following databases: PubMed, ScienceDirect, Scopus, Web of Science, BVS, and EMBASE. The search strategy yielded 1142 articles, from which, based on the evaluation criteria, 12 were included in the systematic review. Only seven these articles allowed the identification of both in silico and in vivo reassessed therapeutic targets. Among these targets, five were exclusively experimental, one was exclusively theoretical, and one of the targets presented an experimental portion and a portion obtained by modeling. The predominant methodology used was molecular docking and the most studied target was Human Pancreatic Lipase (HPL) (n = 4). The lack of methodological details resulted in more than 50% of the papers being categorized with an "unclear risk of bias" across eight out of the eleven evaluated criteria. From the current systematic review, it seems evident that integrating in silico methodologies into studies of potential drug targets for the exploration of new therapeutic agents provides an important tool, given the ongoing challenges in controlling obesity.
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.
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