In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models
Reviewartikel, 2017

The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising framework for uncovering the mechanistic relationship between genotype and phenotype. GEMs hereby enable uncovering associations between cellular physiology and pathology in a systematic manner. Here we review the current progress on reconstruction of human GEMs and how they have been employed as scaffold for interpreting multi-omics high-throughput data with the objective to identify disease-specific metabolic features. We further discuss recent achievements on how to apply these findings for potential target identification and therapeutic drug development. There are, however, challenges in developing models that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions.

Drug development

Human metabolism

Constraint-based analysis

Genome-scale metabolic model

Topological analysis

Författare

Jun Geng

Chalmers, Biologi och bioteknik, Systembiologi

Jens B Nielsen

Danmarks Tekniske Universitet (DTU)

Chalmers, Biologi och bioteknik, Systembiologi

Kungliga Tekniska Högskolan (KTH)

Current Opinion in Systems Biology

2452-3100 (ISSN) 2452-3100 (eISSN)

Vol. 2 29-38

Ämneskategorier

Farmaceutisk vetenskap

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi

DOI

10.1016/j.coisb.2017.01.001