Friends and relatives: insight into conformational regulation from orthologues and evolutionary lineages using KIF and KIN.

Noncovalent interaction networks provide a powerful means to represent and analyze protein structure. Such networks can represent both static structures and dynamic conformational ensembles. We have recently developed two tools for analyzing such interaction networks and generating hypotheses for protein engineering. Here, we apply these tools to the conformational regulation of substrate specificity in class A ß-lactamases, particularly the evolutionary development from generalist to specialist catalytic function and how that can be recapitulated or reversed by protein engineering. These tools, KIF and KIN, generate a set of prioritized residues and interactions as targets for experimental protein engineering.

Sequence - dynamics - function relationships in protein tyrosine phosphatases.

Protein tyrosine phosphatases (PTPs) are crucial regulators of cellular signaling. Their activity is regulated by the motion of a conserved loop, the WPD-loop, from a catalytically inactive open to a catalytically active closed conformation. WPD-loop motion optimally positions a catalytically critical residue into the active site, and is directly linked to the turnover number of these enzymes. Crystal structures of chimeric PTPs constructed by grafting parts of the WPD-loop sequence of PTP1B onto the scaffold of YopH showed WPD-loops in a wide-open conformation never previously observed in either parent enzyme. This wide-open conformation has, however, been observed upon binding of small molecule inhibitors to other PTPs, suggesting the potential of targeting it for drug discovery efforts. Here, we have performed simulations of both enzymes and show that there are negligible energetic differences in the chemical step of catalysis, but significant differences in the dynamical properties of the WPD-loop. Detailed interaction network analysis provides insight into the molecular basis for this population shift to a wide-open conformation. Taken together, our study provides insight into the links between loop dynamics and chemistry in these YopH variants specifically, and how WPD-loop dynamic can be engineered through modification of the internal protein interaction network.

Key interaction networks: Identifying evolutionarily conserved non-covalent interaction networks across protein families.

Protein structure (and thus function) is dictated by non-covalent interaction networks. These can be highly evolutionarily conserved across protein families, the members of which can diverge in sequence and evolutionary history. Here we present KIN, a tool to identify and analyze conserved non-covalent interaction networks across evolutionarily related groups of proteins. KIN is available for download under a GNU General Public License, version 2, from https://www.github.com/kamerlinlab/KIN. KIN can operate on experimentally determined structures, predicted structures, or molecular dynamics trajectories, providing insight into both conserved and missing interactions across evolutionarily related proteins. This provides useful insight both into protein evolution, as well as a tool that can be exploited for protein engineering efforts. As a showcase system, we demonstrate applications of this tool to understanding the evolutionary-relevant conserved interaction networks across the class A ß-lactamases.

Promiscuous recognition of MR1 drives self-reactive mucosal-associated invariant T cell responses.

Mucosal-associated invariant T (MAIT) cells use canonical semi-invariant T cell receptors (TCR) to recognize microbial riboflavin precursors displayed by the antigen-presenting molecule MR1. The extent of MAIT TCR crossreactivity toward physiological, microbially unrelated antigens remains underexplored. We describe MAIT TCRs endowed with MR1-dependent reactivity to tumor and healthy cells in the absence of microbial metabolites. MAIT cells bearing TCRs crossreactive toward self are rare but commonly found within healthy donors and display T-helper-like functions in vitro. Experiments with MR1-tetramers loaded with distinct ligands revealed significant crossreactivity among MAIT TCRs both ex vivo and upon in vitro expansion. A canonical MAIT TCR was selected on the basis of extremely promiscuous MR1 recognition. Structural and molecular dynamic analyses associated promiscuity to unique TCRß-chain features that were enriched within self-reactive MAIT cells of healthy individuals. Thus, self-reactive recognition of MR1 represents a functionally relevant indication of MAIT TCR crossreactivity, suggesting a potentially broader role of MAIT cells in immune homeostasis and diseases, beyond microbial immunosurveillance.

KIF-Key Interactions Finder: A program to identify the key molecular interactions that regulate protein conformational changes.

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.

Q-RepEx: A Python pipeline to increase the sampling of empirical valence bond simulations.

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation/umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate.

Insights into the importance of WPD-loop sequence for activity and structure in protein tyrosine phosphatases.

Protein tyrosine phosphatases (PTPs) possess a conserved mobile catalytic loop, the WPD-loop, which brings an aspartic acid into the active site where it acts as an acid/base catalyst. Prior experimental and computational studies, focused on the human enzyme PTP1B and the PTP from Yersinia pestis, YopH, suggested that loop conformational dynamics are important in regulating both catalysis and evolvability. We have generated a chimeric protein in which the WPD-loop of YopH is transposed into PTP1B, and eight chimeras that systematically restored the loop sequence back to native PTP1B. Of these, four chimeras were soluble and were subjected to detailed biochemical and structural characterization, and a computational analysis of their WPD-loop dynamics. The chimeras maintain backbone structural integrity, with somewhat slower rates than either wild-type parent, and show differences in the pH dependency of catalysis, and changes in the effect of Mg2+. The chimeric proteins' WPD-loops differ significantly in their relative stability and rigidity. The time required for interconversion, coupled with electrostatic effects revealed by simulations, likely accounts for the activity differences between chimeras, and relative to the native enzymes. Our results further the understanding of connections between enzyme activity and the dynamics of catalytically important groups, particularly the effects of non-catalytic residues on key conformational equilibria.

Essential Functional Interplay of the Catalytic Groups in Acid Phosphatase.

The cooperative interplay between the functional devices of a preorganized active site is fundamental to enzyme catalysis. An in-depth understanding of this phenomenon is central to elucidating the remarkable efficiency of natural enzymes and provides an essential benchmark for enzyme design and engineering. Here, we study the functional interconnectedness of the catalytic nucleophile (His18) in an acid phosphatase by analyzing the consequences of its replacement with aspartate. We present crystallographic, biochemical, and computational evidence for a conserved mechanistic pathway via a phospho-enzyme intermediate on Asp18. Linear free-energy relationships for phosphoryl transfer from phosphomonoester substrates to His18/Asp18 provide evidence for the cooperative interplay between the nucleophilic and general-acid catalytic groups in the wild-type enzyme, and its substantial loss in the H18D variant. As an isolated factor of phosphatase efficiency, the advantage of a histidine compared to an aspartate nucleophile is ∼104-fold. Cooperativity with the catalytic acid adds ≥102-fold to that advantage. Empirical valence bond simulations of phosphoryl transfer from glucose 1-phosphate to His and Asp in the enzyme explain the loss of activity of the Asp18 enzyme through a combination of impaired substrate positioning in the Michaelis complex, as well as a shift from early to late protonation of the leaving group in the H18D variant. The evidence presented furthermore suggests that the cooperative nature of catalysis distinguishes the enzymatic reaction from the corresponding reaction in solution and is enabled by the electrostatic preorganization of the active site. Our results reveal sophisticated discrimination in multifunctional catalysis of a highly proficient phosphatase active site.

Reliable In Silico Ranking of Engineered Therapeutic TCR Binding Affinities with MMPB/GBSA.

Accurate and efficient in silico ranking of protein-protein binding affinities is useful for protein design with applications in biological therapeutics. One popular approach to rank binding affinities is to apply the molecular mechanics Poisson-Boltzmann/generalized Born surface area (MMPB/GBSA) method to molecular dynamics (MD) trajectories. Here, we identify protocols that enable the reliable evaluation of T-cell receptor (TCR) variants binding to their target, peptide-human leukocyte antigens (pHLAs). We suggest different protocols for variant sets with a few (≤4) or many mutations, with entropy corrections important for the latter. We demonstrate how potential outliers could be identified in advance and that just 5-10 replicas of short (4 ns) MD simulations may be sufficient for the reproducible and accurate ranking of TCR variants. The protocols developed here can be applied toward in silico screening during the optimization of therapeutic TCRs, potentially reducing both the cost and time taken for biologic development.

Chemical Mapping Exposes the Importance of Active Site Interactions in Governing the Temperature Dependence of Enzyme Turnover.

Uncovering the role of global protein dynamics in enzyme turnover is needed to fully understand enzyme catalysis. Recently, we have demonstrated that the heat capacity of catalysis, ΔC P ‡, can reveal links between the protein free energy landscape, global protein dynamics, and enzyme turnover, suggesting that subtle changes in molecular interactions at the active site can affect long-range protein dynamics and link to enzyme temperature activity. Here, we use a model promiscuous enzyme (glucose dehydrogenase from Sulfolobus solfataricus) to chemically map how individual substrate interactions affect the temperature dependence of enzyme activity and the network of motions throughout the protein. Utilizing a combination of kinetics, red edge excitation shift (REES) spectroscopy, and computational simulation, we explore the complex relationship between enzyme-substrate interactions and the global dynamics of the protein. We find that changes in ΔC P ‡ and protein dynamics can be mapped to specific substrate-enzyme interactions. Our study reveals how subtle changes in substrate binding affect global changes in motion and flexibility extending throughout the protein.

Single Residue on the WPD-Loop Affects the pH Dependency of Catalysis in Protein Tyrosine Phosphatases.

Catalysis by protein tyrosine phosphatases (PTPs) relies on the motion of a flexible protein loop (the WPD-loop) that carries a residue acting as a general acid/base catalyst during the PTP-catalyzed reaction. The orthogonal substitutions of a noncatalytic residue in the WPD-loops of YopH and PTP1B result in shifted pH-rate profiles from an altered kinetic pK a of the nucleophilic cysteine. Compared to wild type, the G352T YopH variant has a broadened pH-rate profile, similar activity at optimal pH, but significantly higher activity at low pH. Changes in the corresponding PTP1B T177G variant are more modest and in the opposite direction, with a narrowed pH profile and less activity in the most acidic range. Crystal structures of the variants show no structural perturbations but suggest an increased preference for the WPD-loop-closed conformation. Computational analysis confirms a shift in loop conformational equilibrium in favor of the closed conformation, arising from a combination of increased stability of the closed state and destabilization of the loop-open state. Simulations identify the origins of this population shift, revealing differences in the flexibility of the WPD-loop and neighboring regions. Our results demonstrate that changes to the pH dependency of catalysis by PTPs can result from small changes in amino acid composition in their WPD-loops affecting only loop dynamics and conformational equilibrium. The perturbation of kinetic pK a values of catalytic residues by nonchemical processes affords a means for nature to alter an enzyme's pH dependency by a less disruptive path than altering electrostatic networks around catalytic residues themselves.

Loop Dynamics and Enzyme Catalysis in Protein Tyrosine Phosphatases.

Protein tyrosine phosphatases (PTPs) play an important role in cellular signaling and have been implicated in human cancers, diabetes, and obesity. Despite shared catalytic mechanisms and transition states for the chemical steps of catalysis, catalytic rates within the PTP family vary over several orders of magnitude. These rate differences have been implied to arise from differing conformational dynamics of the closure of a protein loop, the WPD-loop, which carries a catalytically critical residue. The present work reports computational studies of the human protein tyrosine phosphatase 1B (PTP1B) and YopH from Yersinia pestis, for which NMR has demonstrated a link between their respective rates of WPD-loop motion and catalysis rates, which differ by an order of magnitude. We have performed detailed structural analysis, both conventional and enhanced sampling simulations of their loop dynamics, as well as empirical valence bond simulations of the chemical step of catalysis. These analyses revealed the key residues and structural features responsible for these differences, as well as the residues and pathways that facilitate allosteric communication in these enzymes. Curiously, our wild-type YopH simulations also identify a catalytically incompetent hyper-open conformation of its WPD-loop, sampled as a rare event, previously only experimentally observed in YopH-based chimeras. The effect of differences within the WPD-loop and its neighboring loops on the modulation of loop dynamics, as revealed in this work, may provide a facile means for the family of PTP enzymes to respond to environmental changes and regulate their catalytic activities.

Ground-State Destabilization by Active-Site Hydrophobicity Controls the Selectivity of a Cofactor-Free Decarboxylase.

Bacterial arylmalonate decarboxylase (AMDase) and evolved variants have become a valuable tool with which to access both enantiomers of a broad range of chiral arylaliphatic acids with high optical purity. Yet, the molecular principles responsible for the substrate scope, activity, and selectivity of this enzyme are only poorly understood to date, greatly hampering the predictability and design of improved enzyme variants for specific applications. In this work, empirical valence bond and metadynamics simulations were performed on wild-type AMDase and variants thereof to obtain a better understanding of the underlying molecular processes determining reaction outcome. Our results clearly reproduce the experimentally observed substrate scope and support a mechanism driven by ground-state destabilization of the carboxylate group being cleaved by the enzyme. In addition, our results indicate that, in the case of the nonconverted or poorly converted substrates studied in this work, increased solvent exposure of the active site upon binding of these substrates can disturb the vulnerable network of interactions responsible for facilitating the AMDase-catalyzed cleavage of CO2. Finally, our results indicate a switch from preferential cleavage of the pro-(R) to the pro-(S) carboxylate group in the CLG-IPL variant of AMDase for all substrates studied. This appears to be due to the emergence of a new hydrophobic pocket generated by the insertion of the six amino acid substitutions, into which the pro-(S) carboxylate binds. Our results allow insight into the tight interaction network determining AMDase selectivity, which in turn provides guidance for the identification of target residues for future enzyme engineering.

Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy.

Immuno-oncology approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Additionally, we performed molecular dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiological binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addition of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive analysis of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.

Harnessing Conformational Plasticity to Generate Designer Enzymes.

Recent years have witnessed an explosion of interest in understanding the role of conformational dynamics both in the evolution of new enzymatic activities from existing enzymes and in facilitating the emergence of enzymatic activity de novo on scaffolds that were previously non-catalytic. There are also an increasing number of examples in the literature of targeted engineering of conformational dynamics being successfully used to alter enzyme selectivity and activity. Despite the obvious importance of conformational dynamics to both enzyme function and evolvability, many (although not all) computational design approaches still focus either on pure sequence-based approaches or on using structures with limited flexibility to guide the design. However, there exist a wide variety of computational approaches that can be (re)purposed to introduce conformational dynamics as a key consideration in the design process. Coupled with laboratory evolution and more conventional existing sequence- and structure-based approaches, these techniques provide powerful tools for greatly expanding the protein engineering toolkit. This Perspective provides an overview of evolutionary studies that have dissected the role of conformational dynamics in facilitating the emergence of novel enzymes, as well as advances in computational approaches that allow one to target conformational dynamics as part of enzyme design. Harnessing conformational dynamics in engineering studies is a powerful paradigm with which to engineer the next generation of designer biocatalysts.

Specificity of bispecific T cell receptors and antibodies targeting peptide-HLA.

Tumor-associated peptide-human leukocyte antigen complexes (pHLAs) represent the largest pool of cell surface-expressed cancer-specific epitopes, making them attractive targets for cancer therapies. Soluble bispecific molecules that incorporate an anti-CD3 effector function are being developed to redirect T cells against these targets using 2 different approaches. The first achieves pHLA recognition via affinity-enhanced versions of natural TCRs (e.g., immune-mobilizing monoclonal T cell receptors against cancer [ImmTAC] molecules), whereas the second harnesses an antibody-based format (TCR-mimic antibodies). For both classes of reagent, target specificity is vital, considering the vast universe of potential pHLA molecules that can be presented on healthy cells. Here, we made use of structural, biochemical, and computational approaches to investigate the molecular rules underpinning the reactivity patterns of pHLA-targeting bispecifics. We demonstrate that affinity-enhanced TCRs engage pHLA using a comparatively broad and balanced energetic footprint, with interactions distributed over several HLA and peptide side chains. As ImmTAC molecules, these TCRs also retained a greater degree of pHLA selectivity, with less off-target activity in cellular assays. Conversely, TCR-mimic antibodies tended to exhibit binding modes focused more toward hot spots on the HLA surface and exhibited a greater degree of crossreactivity. Our findings extend our understanding of the basic principles that underpin pHLA selectivity and exemplify a number of molecular approaches that can be used to probe the specificity of pHLA-targeting molecules, aiding the development of future reagents.

Peptide cargo tunes a network of correlated motions in human leucocyte antigens.

Most biomolecular interactions are typically thought to increase the (local) rigidity of a complex, for example, in drug-target binding. However, detailed analysis of specific biomolecular complexes can reveal a more subtle interplay between binding and rigidity. Here, we focussed on the human leucocyte antigen (HLA), which plays a crucial role in the adaptive immune system by presenting peptides for recognition by the αß T-cell receptor (TCR). The role that the peptide plays in tuning HLA flexibility during TCR recognition is potentially crucial in determining the functional outcome of an immune response, with obvious relevance to the growing list of immunotherapies that target the T-cell compartment. We have applied high-pressure/temperature perturbation experiments, combined with molecular dynamics simulations, to explore the drivers that affect molecular flexibility for a series of different peptide-HLA complexes. We find that different peptide sequences affect peptide-HLA flexibility in different ways, with the peptide cargo tuning a network of correlated motions throughout the pHLA complex, including in areas remote from the peptide-binding interface, in a manner that could influence T-cell antigen discrimination.

Exposing the Interplay Between Enzyme Turnover, Protein Dynamics, and the Membrane Environment in Monoamine Oxidase B.

There is an increasing realization that structure-based drug design may show improved success by understanding the ensemble of conformations accessible to an enzyme and how the environment affects this ensemble. Human monoamine oxidase B (MAO-B) catalyzes the oxidation of amines and is inhibited for the treatment of both Parkinson's disease and depression. Despite its clinical importance, its catalytic mechanism remains unclear, and routes to drugging this target would be valuable. Evidence of a radical in either the transition state or the resting state of MAO-B is present throughout the literature and is suggested to be a flavin semiquinone, a tyrosyl radical, or both. Here we see evidence of a resting-state flavin semiquinone, via absorption redox studies and electron paramagnetic resonance, suggesting that the anionic semiquinone is biologically relevant. On the basis of enzyme kinetic studies, enzyme variants, and molecular dynamics simulations, we find evidence for the importance of the membrane environment in mediating the activity of MAO-B and that this mediation is related to the protein dynamics of MAO-B. Further, our MD simulations identify a hitherto undescribed entrance for substrate binding, membrane modulated substrate access, and indications for half-site reactivity: only one active site is accessible to binding at a time. Our study combines both experimental and computational evidence to illustrate the subtle interplay between enzyme activity and protein dynamics and the immediate membrane environment. Understanding key biomedical enzymes to this level of detail will be crucial to inform strategies (and binding sites) for rational drug design for these targets.