Protein–protein interaction networks studies and importance of 3D structure knowledge

Abstract

Protein–protein interaction networks (PPINs) are a powerful tool to study biological processes in living cells. In this review, we present the progress of PPIN studies from abstract to more detailed representations. We will focus on 3D interactome networks, which offer detailed information at the atomic level. This information can be exploited in understanding not only the underlying cellular mechanisms, but also how human variants and disease-causing mutations affect protein functions and complexes’ stability. Recent studies have used structural information on PPINs to also understand the molecular mechanisms of binding partner selection. We will address the challenges in generating 3D PPINs due to the restricted number of solved protein structures. Finally, some of the current use of 3D PPINs will be discussed, highlighting their contribution to the studies in genotype–phenotype relationships and in the optimization of targeted studies to design novel chemical compounds for medical treatments.

Keywords::

• 3D protein–protein interaction networks
• disease-causing mutations
• drug design
• nsSNPs
• protein complexes interface regions
• protein–protein interaction networks

Financial & competing interests disclosure

H-C Lu acknowledges support from King's College London (London, UK). A Fornili and F Fraternali acknowledge support from the British Heart Foundation. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties

No writing assistance was utilized in the production of this manuscript.

Key issues

• • Currently, the number of solved protein structures is relatively small when compared with the number of known proteins for each species. Although homologous structure modeling could narrow the gap, a close-to-complete map of biological system requires a higher number of available structures.

• • Modeling protein complexes remains challenging.

• • Some types of proteins are significantly under-represented in protein structure databases such as membrane proteins. These proteins are also determinant for cellular signaling and drug target studies.

• • It is now timely to develop methods and tools to extract useful information from the large amount of data generated by large-scale genome, metabolome, transcriptome and proteome projects.