Computational Approaches for Interpreting Experimental Data and Understanding Protein Structure, Dynamics and Function Relationships

The three-dimensional (3D) structure and dynamics of a biomolecule are keys to understanding its function. A variety of experimental structural biology techniques have been developed, including X-ray crystallography, NMR, and cryoEM methods capable of determining biomolecular 3D structures and dynamics at atomic resolution. Using these methods, atomic coordinate sets for more than 180,000 biomolecules have been determined and archived in the worldwide Protein Data Bank (wwPDB). Sequences for billions of proteins are also available in genomic sequence databases. However, these data are only the starting point for structure-function studies aimed at testing specific hypotheses, and understanding mechanisms underlying biological processes. The exponential growth of computing power and algorithms now enables multiple computational approaches for interpretation of these data, and for simulation of biological processes.

Our knowledge-limits of important biological processes can be greatly expanded and the invisible world explored by interpreting experimental data using advanced computational methods. Methods of automated data analysis, computational modeling, molecular dynamics simulation, deep learning, and artificial intelligence can enable understanding of mechanisms of biological processes, elucidation of complex biomolecular structures, and simulations of dynamic processes. One important goal is to establish reproducible, easy-to-use integrated research environments, which can accelerate sustained and progressive scientific advances. By making advanced, reliable computational tools more accessible to the broad scientific community, we hope to enable novel, and in some cases unanticipated, scientific discovery.

We aim to cover promising, recent, and novel research and technology development interfacing experimental and computational methods directed to structural, dynamic, and functional studies of biomolecules. Areas to be covered in this Research Topic may include, but are not limited to:  

• Proteins, nucleic acids, carbohydrates, and lipids

• Data acquisition and analysis methods

• Combined computational and experimental techniques

• User-friendly User-Interfaces and User-Experiences (UI/UX design)

• Algorithms for data-informed computational modeling

• Algorithm for prediction of protein structure and dynamics 

• Multi-scale simulation method and application

Gaetano Montelione is the founder of Nexomics Biosciences. Other guest editors do not have any competing interests to declare.