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1. Structurally distributed surface sites tune allosteric regulation

   https://doi.org/10.7554/eLife.68346  

   McCormick, James W; Russo, Marielle AX; Thompson, Samuel; Blevins, Aubrie; Reynolds, Kimberly A (June 2021, eLife)

   Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another. When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states. More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located. To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery. After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects. McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like. 

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2. Establishing the allosteric mechanism in CRISPR‐Cas9

   https://doi.org/10.1002/wcms.1503  

   Nierzwicki, Łukasz; Arantes, Pablo Ricardo; Saha, Aakash; Palermo, Giulia (October 2020, WIREs Computational Molecular Science)

   Abstract Allostery is a fundamental property of proteins, which regulates biochemical information transfer between spatially distant sites. Here, we report on the critical role of molecular dynamics (MD) simulations in discovering the mechanism of allosteric communication within CRISPR‐Cas9, a leading genome editing machinery with enormous promises for medicine and biotechnology. MD revealed how allostery intervenes during at least three steps of the CRISPR‐Cas9 function: affecting DNA recognition, mediating the cleavage and interfering with the off‐target activity. An allosteric communication that activates concerted DNA cleavages was found to led through the L1/L2 loops, which connect the HNH and RuvC catalytic domains. The identification of these “allosteric transducers” inspired the development of novel variants of the Cas9 protein with improved specificity, opening a new avenue for controlling the CRISPR‐Cas9 activity. Discussed studies also highlight the critical role of the recognition lobe in the conformational activation of the catalytic HNH domain. Specifically, the REC3 region was found to modulate the dynamics of HNH by sensing the formation of the RNA:DNA hybrid. The role of REC3 was revealed to be particularly relevant in the presence of DNA mismatches. Indeed, interference of REC3 with the RNA:DNA hybrid containing mismatched pairs at specific positions resulted in locking HNH in an inactive “conformational checkpoint” conformation, thereby hampering off‐target cleavages. Overall, MD simulations established the fundamental mechanisms underlying the allosterism of CRISPR‐Cas9, aiding engineering strategies to develop new CRISPR‐Cas9 variants for improved genome editing. This article is categorized under:Structure and Mechanism > Computational Biochemistry and Biophysics 

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3. The quaternary question: Determining allostery in spastin through dynamics classification learning and bioinformatics

   https://doi.org/10.1063/5.0139273  

   Kelly, Maria S.; Macke, Amanda C.; Kahawatte, Shehani; Stump, Jacob E.; Miller, Abigail R.; Dima, Ruxandra I. (March 2023, The Journal of Chemical Physics)

   The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling. 

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4. Analysis of coordinated NMR chemical shifts to map allosteric regulatory networks in proteins

   https://doi.org/10.1016/j.ymeth.2022.12.002  

   Skeens, Erin; Lisi, George P. (January 2023, Methods)

   The exquisite sensitivity of the NMR chemical shift to local environment makes it an ideal probe to assess atomic level perturbations in proteins of all sizes and structural compositions. Recent advances in solution and solid-state NMR spectroscopy of biomolecules have leveraged the chemical shift to report on short- and long-range couplings between individual amino acids to establish “networks” of residues that form the basis of allosteric pathways that transmit chemical signals through the protein matrix to induce functional responses. The simple premise that thermodynamically and functionally coupled regions of a protein (i.e. active and allosteric sites) should be reciprocally sensitive to structural or dynamic perturbations has enabled NMR spectroscopy, the premier method for molecular resolution of protein structural fluctuations, to occupy a place at the forefront of investigations into protein allostery. Here, we detail several key methods of NMR chemical shift analysis to extract mechanistic information about long-range chemical signaling in a protein, focusing on practical methodological aspects and the circumstances under which a given approach would be relevant. We also detail some of the experimental considerations that should be made when applying these methods to specific protein systems. 

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5. Entropy, Fluctuations, and Disordered Proteins

   https://doi.org/10.3390/e21080764  

   Faraggi, Eshel; Dunker, A. Keith; Jernigan, Robert L.; Kloczkowski, Andrzej (August 2019, Entropy)

   Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of fluctuations at a given MSA site and used these as representative of the sequence and structure entropy at that site. In general, we found a tendency for negative correlations between disorder and structure, and significant positive correlations between disorder and the fluctuations in the system. We also found evidence for residue-type conservation for those residues proximate to potentially disordered sites. Mutation at the disorder site itself appear to be allowed. In addition, we found positive correlation for disorder and accessible surface area, validating that disordered residues occur in exposed regions of proteins. Finally, we also found that fluctuations in the dihedral angles at the original mutated residue and disorder are positively correlated while dihedral angle fluctuations in spatially proximal residues are negatively correlated with disorder. Our results seem to indicate permissible variability in the disordered site, but greater rigidity in the parts of the protein with which the disordered site interacts. This is another indication that disordered residues are involved in protein function. 

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