Large-Scale Conformational Changes and Protein Function: Breaking the in silico Barrier.

Laura Orellana

doi:10.3389/fmolb.2019.00117

Abstract

Large-scale conformational changes are essential to link protein structures with their function at the cell and organism scale, but have been elusive both experimentally and computationally. Over the past few years developments in cryo-electron microscopy and crystallography techniques have started to reveal multiple snapshots of increasingly large and flexible systems, deemed impossible only short time ago. As structural information accumulates, theoretical methods become central to understand how different conformers interconvert to mediate biological function. Here we briefly survey current in silico methods to tackle large conformational changes, reviewing recent examples of cross-validation of experiments and computational predictions, which show how the integration of different scale simulations with biological information is already starting to break the barriers between the in silico, in vitro, and in vivo worlds, shedding new light onto complex biological problems inaccessible so far.

Highlights

Specialty section: This article was submitted to Biological Modeling and Simulation, a section of the journal Frontiers in Molecular Biosciences
A transition pathway should be ideally supported by direct structural data, this is often difficult and the only feasible option is to attempt indirect “soft” validation, either from distance parameters e.g., via single-molecule Förster Resonance Energy Transfer (FRET), FACS, or from functional assays, which can test predictions about protein activity, as we briefly review
We proposed to go beyond two- or threestate benchmarking by introducing ensemble-level analyses that consider all structural information available in the PDB for a given protein, extracting at the same time their intrinsic collective variables (CVs) using Principal Component Analysis (PCA) (Orellana et al, 2016)

Summary

Introduction

Specialty section: This article was submitted to Biological Modeling and Simulation, a section of the journal Frontiers in Molecular Biosciences. Coarse-grained (CG) methods like Elastic Network Models (ENMs; Mahajan and Sanejouand, 2015), are capable to predict with striking accuracy, just from the overall shape of a protein, the conformational changes observed experimentally and entire sequences of on-pathway intermediates (Orellana et al, 2016) This suggests that large-scale motions like those defining protein functional FELs may be better understood as collective, supra-atomistic and higher-scale phenomena. Whatever the theoretical framework chosen to explore this issue, the validation of in-silico predicted mechanisms is becoming a central question, as quantitative analysis become essential to rationalize the growing dynamical information from techniques like cryo-EM (Frank, 2018; Bonomi and Vendruscolo, 2019)

Objectives

Conclusion