Background: Metabolic disorders comprise a set of different disorders varying from
epidemic diseases such as diabetes mellitus to inborn metabolic orphan diseases such as phenylketonuria.
Despite considerable evidence showing the importance of the computational methods
in discovery and development of new pharmaceuticals, there are no systematic reviews outlining
how they are utilized in the field of metabolic disorders. This review aims to discuss the
necessity of the development of web-based tools and databases by integration of available information
for solving Big Data problems in network pharmacology of metabolic disorders.
Methods: We undertook a structured search of bibliographic databases for peer-reviewed research
literature using a focused review question and inclusion/exclusion criteria. The quality of
retrieved papers was appraised using standard tools.
Results: The alterations in metabolic pathways cause various cardiovascular, hematological, neurological,
gastrointestinal, immune disorders and cancer. In this regard, informatics, Big Data and
modeling techniques aid in the design of novel therapeutic agents for metabolic diseases by addressing
various Big Data problems in the network polypharmacology (drugs/pharmaceutical
agents, proteins, genes, diseases, bioassays, ADMET and metabolic pathways), identification of
privileged scaffolds, developing new diagnostic biomarkers, understanding the pathophysiology
of disease and progress in personalized medicine.
Conclusion: The recent advances of developing pharmaceutical agents for various metabolic disorders
by considering their pathogenesis, mechanisms of action, therapeutic and adverse effects
have been summarized. We have highlighted the role of computational techniques, drug repurposing,
and network-based polypharmacological approaches in the identification of new/existing
medicines with improved drug-likeness properties for the rare metabolic disorders.