Uncovering One-Dimensional Reaction Coordinate that Underlies Structure-Function Relationship of Proteins

Understanding the mechanism of functional protein dynamics is critical to understanding protein functions. Reaction coordinates is a central topic in protein dynamics and the grail is to find the one-dimensional reaction coordinate that can fully determine the value of committor (i.e. the reaction probability in configuration space) for any protein configuration. We present a powerful new method that can, for the first time, identify the rigorous one-dimensional reaction coordinate in complex molecules. This one-dimensional reaction coordinate is determined by a fundamental mechanical operator--the generalized work functional. This method only requires modest computational cost and can be readily applied to large molecules. Most importantly, the generalized work functional is the physical origin of the collectivity in functional protein dynamics and provides a tentative roadmap that connects the structure of a protein to its function.

B-factor accuracy in protein crystal structures

The accuracy of B factors in protein crystal structures has been determined by comparing the same atoms in numerous, independent crystal structures of Gallus gallus lysozyme. Both B-factor absolute differences and normal probability plots indicate that the estimated B-factor errors are quite large, close to 9 Å2 in ambient-temperature structures and to 6 Å2 in low-temperature structures, and surprisingly are comparable to values estimated two decades ago. It is well known that B factors are not due to local movements only but reflect several, additional factors from crystal defects, large-scale disorder, diffraction data quality etc. It therefore remains essential to normalize B factors when comparing different crystal structures, although it has clearly been shown that they provide useful information about protein dynamics. Improved, quantitative analyses of raw B factors require novel experimental and computational tools that are able to disaggregate local movements from other features and properties that affect B factors.

A Layered View on Focal Adhesions

The cytoskeleton provides structure to cells and supports intracellular transport. Actin fibres are crucial to both functions. Focal Adhesions (FAs) are large macromolecular multiprotein assemblies at the ends of specialised actin fibres linking these to the extracellular matrix. FAs translate forces on actin fibres into forces contributing to cell migration. This review will discuss recent insights into FA protein dynamics and their organisation within FAs, made possible by advances in fluorescence imaging techniques and data analysis methods. Over the last decade, evidence has accumulated that FAs are composed of three layers parallel to the plasma membrane. We focus on some of the most frequently investigated proteins, two from each layer, paxillin and FAK (bottom, integrin signalling layer), vinculin and talin (middle, force transduction layer) and zyxin and VASP (top, actin regulatory layer). Finally, we discuss the potential impact of this layered nature on different aspects of FA behaviour.

The influence of the extracellular domains on the dynamic behavior of membrane proteins

The dynamic behavior of the plasma membrane proteins mediates various cellular processes, such as cell-cell interactions, transmembrane transport and signaling. It is widely accepted that the dynamics of the membrane proteins is determined either by the interactions of the transmembrane domain with the surrounding lipids or by the interaction of the intracellular domain with cytosolic components such as cortical actin. However, the impact of the extracellular domains (ECDs) on the dynamics of membrane proteins is rather unexplored. Here, we investigate how the ECD size influences protein dynamics in lipid bilayer. We reconstitute ECDs of different molecular weights and heights in model membrane systems and analyze ECD-driven protein sorting in lipid domains as well as protein mobility. We observe that increasing the ECD size leads to a decrease in ordered domain partitioning as well as diffusivity. Our data suggests a critical role of the ECDs on membrane protein behavior in the plasma membrane and paves the way to a more complete understanding of membrane protein dynamics that includes interaction with the extracellular matrix and glycocalyx in health and disease.

PASSer2.0: Accurate Prediction of Protein Allosteric Sites Through Automated Machine Learning

Allostery is a fundamental process in regulating proteins’ activity. The discovery, design and development of allosteric drugs demand for better identification of allosteric sites. Several computational methods have been developed previously to predict allosteric sites using static pocket features and protein dynamics. Here, we present a computational model using automated machine learning for allosteric site prediction. Our model, PASSer2.0, advanced the previous results and performed well across multiple indicators with 89.2% of allosteric pockets appeared among the top 3 positions. The trained machine learning model has been integrated with the Protein Allosteric Sites Server (https://passer.smu.edu) to facilitate allosteric drug discovery.