Allostery Frustrates the Experimentalist

Proteins interact with other proteins, with nucleic acids, lipids, carbohydrates and various small molecules in the living cell. These interactions have been quantified and structurally characterized in numerous studies such that we today have a comprehensive picture of protein structure and function. However, proteins are dynamic and even folded proteins are likely more heterogeneous than they appear in most descriptions. One property of proteins that relies on dynamics and heterogeneity is allostery, the ability of a protein to change structure and function upon ligand binding to an allosteric site. Over the last decades the concept of allostery was broadened to embrace all types of long-range interactions across a protein including purely entropic changes without a conformational change in single protein domains. But with this re-definition came a problem: How do we measure allostery? In this opinion, we discuss some caveats arising from the quantitative description of single-domain allostery from an experimental perspective and how the limitations cannot be separated from the definition of allostery per se. Furthermore, we attempt to tie together allostery with the concept of frustration in an effort to investigate the links between these two complex, and yet general, properties of proteins. We arrive at the conclusion that the sensitivity to perturbation of allosteric networks in single protein domains is too large for the networks to be of significant biological relevance.

Distinct conformational dynamics and allosteric networks in alpha tryptophan synthase during active catalysis

Experimental observations of enzymes under active turnover conditions have brought new insight into the role of protein motions and allosteric networks in catalysis. Many of these studies characterize enzymes under dynamic chemical equilibrium conditions, in which the enzyme is actively catalyzing both the forward and reverse reactions during data acquisition. We have previously analyzed conformational dynamics and allosteric networks of the alpha subunit of tryptophan synthase under such conditions using NMR. We have proposed that this working state represents a four to one ratio of the enzyme bound with the indole-3-glycerol phosphate substrate (E:IGP) to the enzyme bound with the products indole and glyceraldehyde-3-phosphate (E:indole:G3P). Here, we analyze the inactive D60N variant to deconvolute the contributions of the substrate- and products-bound states to the working state. While the D60N substitution itself induces small structural and dynamic changes, the D60N E:IGP and E:indole:G3P states cannot entirely account for the conformational dynamics and allosteric networks present in the working state. The act of chemical bond breakage and/or formation, or possibly the generation of an intermediate, may alter the structure and dynamics present in the working state. As the enzyme transitions from the substrate-bound to the products-bound state, millisecond conformational exchange processes are quenched and new allosteric connections are made between the alpha active site and the surface which interfaces with the beta subunit. The structural ordering of the enzyme and these new allosteric connections may be important in coordinating the channeling of the indole product into the beta subunit.

Patterns of coevolving amino acids unveil structural and dynamical domains

Patterns of interacting amino acids are so preserved within protein families that the sole analysis of evolutionary comutations can identify pairs of contacting residues. It is also known that evolution conserves functional dynamics, i.e., the concerted motion or displacement of large protein regions or domains. Is it, therefore, possible to use a pure sequence-based analysis to identify these dynamical domains? To address this question, we introduce here a general coevolutionary coupling analysis strategy and apply it to a curated sequence database of hundreds of protein families. For most families, the sequence-based method partitions amino acids into a few clusters. When viewed in the context of the native structure, these clusters have the signature characteristics of viable protein domains: They are spatially separated but individually compact. They have a direct functional bearing too, as shown for various reference cases. We conclude that even large-scale structural and functionally related properties can be recovered from inference methods applied to evolutionary-related sequences. The method introduced here is available as a software package and web server (spectrus.sissa.it/spectrus-evo_webserver).