NMR and computational methods for molecular resolution of allosteric pathways in enzyme complexes

Abstract

Allostery is a ubiquitous biological mechanism in which a distant binding site is coupled to and drastically alters the function of a catalytic site in a protein. Allostery provides a high level of spatial and temporal control of the integrity and activity of biomolecular assembles composed of proteins, nucleic acids, or small molecules. Understanding the physical forces that drive allosteric coupling is critical to harnessing this process for use in bioengineering, de novo protein design, and drug discovery. Current microscopic models of allostery highlight the importance of energetics, structural rearrangements, and conformational fluctuations, and in this review, we discuss the synergistic use of solution NMR spectroscopy and computational methods to probe these phenomena in allosteric systems, particularly protein-nucleic acid complexes. This combination of experimental and theoretical techniques facilitates an unparalleled detection of subtle changes to structural and dynamic equilibria in biomolecules with atomic resolution, and we provide a detailed discussion of specialized NMR experiments as well as the complementary methods that provide valuable insight into allosteric pathways in silico. Lastly, we highlight two case studies to demonstrate the adaptability of this approach to enzymes of varying size and mechanistic complexity.

A new decade for Biophysical Reviews and a look into the future of biophysics

“…The tenth Review discusses the use of modern biophysical approaches to shine new light on one of the oldest phenomena in enzymology-namely, that of the allosteric regulation of enzyme activity through the binding of a ligand to a site external to the catalytic site (East et al 2020). The article begins by introducing time and distance scales relevant to a discussion of protein motion and its action as an enzyme catalyst.…”

“…From the computational side, a number of procedures based on long time-scale molecular dynamics (MD) are discussed such as those involving enhanced sampling (such as Gaussian assisted MD) or those utilizing model free analysis (such as network methods based on assessment of generalized covariance between residues). Examples showing advantageous joint use of NMR and computational methods for the exposition of protein allostery are provided by published studies of the endonuclease Cas9 in complex with a guide RNA and target DNA (East et al 2020).…”

Driving Protein Conformational Cycles in Physiology and Disease: “Frustrated” Amino Acid Interaction Networks Define Dynamic Energy Landscapes

“…[ 37 ] A number of experimental and computational methods have been used to gain insight into the higher energy, less populated conformations. [ 5,18,22,30,37 ] Nuclear magnetic resonance (NMR) spectroscopy has proven to be an especially powerful experimental approach to gain insight into the conformational ensemble, given its ability to interrogate protein conformational dynamics across many timescales (picosecond to more than a second). [ 3,38–41 ] In particular, NMR provides methods to interrogate low‐lying excited conformational substates, which may be “invisible” to other structural methods.…”

“…Here, we propose a general framework by which interactions within a protein, and/or interactions between the protein and a binding partner, will promote the desired conformational cycle. We imagine that proteins are held together by a web or network of noncovalent interactions, [ 16–18 ] but those network connections change as the protein progresses through its conformational cycle. Each change in network connections then favors the next required structural change, leading to additional network changes and the promotion of subsequent structural events.…”

“…Our intended audience is the general biology/chemistry community, and many of the concepts introduced here are covered in much greater depth in other reviews. [ 17,18,21–24 ] The examples here are also only illustrative, and not exhaustive, and we focus on our own recent studies, including on our work detailing dynamic networks in the alpha subunit of tryptophan synthase (TS). [ 25–28 ]…”