Journal of Chemical Theory and Computation (2024). DOI: 10.1021/acs.jctc.4c00067″> Overview of the PSP pipeline. Following genomic sequencing, the primary amino acid sequence is determined. The experimental method then starts with expressing this protein by genetically modifying another organism with this new sequence. This organism will then translate these proteins, and the new protein of interest can be isolated, purified, and then solved using X-ray crystallography, NMR, or CryoEM. The in silico methods on the other hand, simply take the primary amino acid sequence as input and the structure is predicted by either a physics-based method (where the underlying biophysics is somehow simulated) or a template-based method (where machine learning algorithms predict structures based on patterns found in a training set of experimental templates). The method we adopt in this work falls under the category of physics-based algorithms. As an illustrated example, an in silico model and X-ray crystal structure of the SARS-CoV2 NSP13 helicase (PDB: 7NN0) are superimposed, along with a docked known inhibitor (colored in magenta). Credit: Journal of Chemical Theory and Computation (2024). DOI: 10.1021/acs.jctc.4c00067
Researchers from Cleveland Clinic and IBM have recently published findings in the Journal of Chemical Theory and Computation that could lay the groundwork for applying quantum computing methods to protein structure prediction.
For decades, researchers have leveraged computational approaches to predict protein structures. A protein folds itself into a structure that determines how it functions and binds to other molecules in the