Over the last decades, network science has been applied to the study of various complex systems in numerous domains, such as sociology, telecommunication, but also biology and chemistry. Particularly, network science opened the way to a new understanding of the structural and dynamics properties of biological systems at different spatial and temporal scales. The aim of the review is to report typical examples of network science applications in the field of small peptides and protein structure, dynamics, and function. After an introduction on the importance of networks to today’s science, the review focuses on network analyses of static protein structures as topological features of protein structure networks are related to their relevant functional aspects. Then, the review describes how dynamical properties of proteins, such as complex conformational changes, can be tracked by networking molecular simulations data or by using dynamical networks. In this context, we discuss strong relationships between network science and coarse-grained modelling. Next, we describe how network modularization techniques could pave the way to innovative multiscale and modular models of proteins. Regarding our contributions in the field of network science, we (i) very briefly resume several applications using graphs to consider inorganic 3D networks and small organic molecules, (ii) show graph reductions of three-dimensional molecular fields are helpful for alignments of ligands and their subsequent molecular similarity evaluation in general, and (iii) summarize our studies on the intrinsic flexibility properties of a protein through the design of original multiscale coarse-grained Elastic Network Models. The µ opioid receptor, a G protein-coupled receptor (GPCR), the target of most used anesthesia, is taken into account as example structure for most concepts and ideas reviewed all along the manuscript.
|Title of host publication||Methods and Principles in Medicinal Chemistry series |
|Subtitle of host publication||Biomolecular Simulations in Structure-based Drug Discovery|
|Editors||Francesco L. Gervasio, Vojtech Spiwok, Raimund Mannhold, Helmut Buschmann, Jörg Holenz|
|Publication status||Published - 2018|