Networks of Dynamic Allostery Regulate Enzyme Function

Structural Insights Into the Impact of the Glycine-Rich Loop Mutation in Noonan Syndrome on the ATP Binding Pocket of CRAF Kinase

The pathogenic G361A variant of CRAF, associated with increased intrinsic kinase activity in Noonan syndrome (NS), remains poorly understood in terms of its molecular and structural impact on kinase activity. To elucidate the mechanistic implications of the glycine to alanine substitution at residue 361 in CRAF, we employed molecular dynamics simulations. Our findings reveal that this mutation predominantly affects the ATP binding pocket and critical intermolecular interactions within the active cleft that favors the phosphate transfer reaction. Notably, our data highlight significant alterations in key interactions involving Lys470/Asp486 and ATP.Mg2+ in CRAFG361A that are absent in wild-type CRAF. Additionally, we identified a novel interaction mode between Lys431 and γ-phosphate in wild-type CRAF, a residue evolutionarily conserved in CRAFs but not in related kinases such as BRAF, ARAF, and KSR1/2. Furthermore, observed shifts in the αC-helix and G-loop relative to the wild-type correlate with an enlarged ATP-binding cavity in the mutant, reflecting structural adaptations due to these mutations. Overall, these structural insights underscore the elevated intrinsic kinase activity of the CRAFG361A variant and provide crucial mechanistic details that could inform the development of specific inhibitors targeting this variant.

Identifying and controlling inactive and active conformations of a serine protease

Serine proteases have been proposed to dynamically sample inactive and active conformations, but direct evidence at atomic resolution has remained elusive. Using nuclear magnetic resonance (NMR), we identified a single residue, D164, in exfoliative toxin A (ETA) that acts as a molecular "switch" to regulate global dynamic sampling. Mutations at this site shift the balance between inactive and active states, correlating directly with catalytic activity. Beyond identifying this dynamic switch, we demonstrate how it works in concert with other allosterically coupled sites to rationally control enzyme movements and catalytic function. This study provides a framework for linking conformational dynamics to function and paves the way for engineering enzymes, in particular, proteases, with tailored activities for applications in medicine and biotechnology.

Identification and understanding of allostery hotspots in proteins: Integration of deep mutational scanning and multi-faceted computational analyses

Motivated by recent deep mutational scanning (DMS) experiments, we have carried out a diverse set of computations to better understand the distribution and contributions of allostery hotspot residues in a transcription factor, TetR. These include extensive atomistic simulations and free energy computations for different functional states of TetR, machine learning analysis of the DMS data and a statistical thermodynamic model for the experimental induction data for the WT protein and a handful of hotspot mutants. Collectively, these computations provided insights into the structural and energetic basis of allostery in TetR, and the distinct contributions of allostery hotspots. The results highlight that the allostery function (i.e., the induction activity) of TetR can be modulated by perturbing both inter-domain coupling and intra-domain properties, such as the population of the binding-competent conformation of each domain. This mechanistic degeneracy qualitatively explains the broad distribution of allostery hotspots across the protein structure observed in the DMS experiments, and also informs the design of strategies aimed at identifying allostery hotspots. The mechanistic framework and the multi-faceted computational approaches are expected to be applicable to the analysis of other allostery systems, especially those sharing the similar two-domain structural topology, and to the design of allostery modulators.

Advances of Predicting Allosteric Mechanisms Through Protein Contact in New Technologies and Their Application

Allostery is an intriguing phenomenon wherein the binding activity of a biological macromolecule is modulated via non-canonical binding site, resulting in synchronized functional changes. The mechanics underlying allostery are relatively complex and this review is focused on common methodologies used to study allostery, such as X-ray crystallography, NMR spectroscopy, and HDXMS. Different methodological approaches are used to generate data in different scenarios. For example, X-ray crystallography provides high-resolution structural information, NMR spectroscopy offers dynamic insights into allosteric interactions in solution, and HDXMS provides information on protein dynamics. The residue transition state (RTS) approach has emerged as a critical tool in understanding the energetics and conformational changes associated with allosteric regulation. Allostery has significant implications in drug discovery, gene transcription, disease diagnosis, and enzyme catalysis. Enzymes' catalytic activity can be modulated by allosteric regulation, offering opportunities to develop novel therapeutic alternatives. Understanding allosteric mechanisms associated with infectious organisms like SARS-CoV and bacterial pathogens can aid in the development of new antiviral drugs and antibiotics. Allosteric mechanisms are crucial in the regulation of a variety of signal transduction and cell metabolism pathways, which in turn govern various cellular processes. Despite progress, challenges remain in identifying allosteric sites and characterizing their contribution to a variety of biological processes. Increased understanding of these mechanisms can help develop allosteric systems specifically designed to modulate key biological mechanisms, providing novel opportunities for the development of targeted therapeutics. Therefore, the current review aims to summarize common methodologies that are used to further our understanding of allosteric mechanisms. In conclusion, this review provides insights into the methodologies used for the study of allostery, its applications in in silico modeling, the mechanisms underlying antibody allostery, and the ongoing challenges and prospects in advancing our comprehension of this intriguing phenomenon.

AI-integrated network for RNA complex structure and dynamic prediction

RNA complexes are essential components in many cellular processes. The functions of these complexes are linked to their tertiary structures, which are shaped by detailed interface information, such as binding sites, interface contact, and dynamic conformational changes. Network-based approaches have been widely used to analyze RNA complex structures. With their roots in the graph theory, these methods have a long history of providing insight into the static and dynamic properties of RNA molecules. These approaches have been effective in identifying functional binding sites and analyzing the dynamic behavior of RNA complexes. Recently, the advent of artificial intelligence (AI) has brought transformative changes to the field. These technologies have been increasingly applied to studying RNA complex structures, providing new avenues for understanding the complex interactions within RNA complexes. By integrating AI with traditional network analysis methods, researchers can build more accurate models of RNA complex structures, predict their dynamic behaviors, and even design RNA-based inhibitors. In this review, we introduce the integration of network-based methodologies with AI techniques to enhance the understanding of RNA complex structures. We examine how these advanced computational tools can be used to model and analyze the detailed interface information and dynamic behaviors of RNA molecules. Additionally, we explore the potential future directions of how AI-integrated networks can aid in the modeling and analyzing RNA complex structures.

Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins

An explicit analytic solution is given for the Langevin equation applied to the Gaussian Network Model of a protein subjected to both a random and a deterministic periodic force. Synchronous and asynchronous components of time correlation functions are derived and an expression for phase differences in the time correlations of residue pairs is obtained. The synchronous component enables the determination of dynamic communities within the protein structure. The asynchronous component reveals causality, where the time correlation function between residues i and j differs depending on whether i is observed before j or vice versa, resulting in directional information flow. Driver and driven residues in the allosteric process of cyclophilin A and human NAD-dependent isocitrate dehydrogenase are determined by a perturbation-scanning technique. Factors affecting phase differences between fluctuations of residues, such as network topology, connectivity, and residue centrality, are identified. Within the constraints of the isotropic Gaussian Network Model, our results show that asynchronicity increases with viscosity and distance between residues, decreases with increasing connectivity, and decreases with increasing levels of eigenvector centrality.

Validating the 15N-1H HSQC-ROESY experiment for detecting 1HN exchange broadening in proteated proteins

It is advantageous to investigate milli-to-micro-second conformational exchange data contained in the solution NMR protein relaxation data other than 15N nuclei. Not only does one search under another lamp post, one also looks at dynamics at other time scales. The HSQC-ROESY 1HN relaxation dispersion experiment for amide protons as introduced by Ishima, et al (1998). J. Am. Soc. 120, 10534-10542, is such an experiment, but has by the authors been advised to only be used for perdeuterated proteins to avoid complication with the 1H-1H multiple-spin effects. This is regretful, since not all proteins can be perdeuterated. Here we analyze in detail the 1HN relaxation terms for this experiment for a fully proteated protein. Indeed, the 1HN relaxation theory is in this case complex and includes dipolar-dipolar relaxation interference and TOCSY transfers. With simulate both of these effects and show that the interference can be exploited for detecting exchange broadening. The TOCSY effect is shown to minor, and when it is not, a solution is provided. We apply the HSQC-ROESY experiment, with a small modification to suppress ROESY crosspeaks, to a 7 kDa GB1 protein that is just 15N and 13C labeled. At 10 °C we cannot detect any conformational exchange broadening: the 1HN R2 relaxation rates with 1.357 kHz spinlock field not larger than those recorded with a 12.136 kHz spinlock field. This means that there is no exchange broadening that can be differentially suppressed with the applied fields. Either there is no broadening, or the broadening is effectively suppressed by all fields, or the broadening cannot be suppressed by either of the fields. While initially this seems to be a disappointing result, we feel that this work establishes that the HSQC-ROESY experiment is very robust. It can indeed be utilized for proteated proteins upto about 30 kDa. This could be opening the study the milli-microsecond conformational dynamics as reported by 1HN exchange broadening for many more proteins.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.

Proteostatic remodeling of small heat shock chaperones - crystallins by Ran-binding protein 2 and the peptidyl-prolyl cis-trans isomerase and chaperone activities of its cyclophilin domain

Disturbances in phase transitions and intracellular partitions of nucleocytoplasmic shuttling substrates promote protein aggregation - a hallmark of neurodegenerative diseases. The modular Ran-binding protein 2 (Ranbp2) is a cytosolic molecular hub for rate-limiting steps of disassembly and phase transitions of Ran-GTP-bound protein ensembles exiting nuclear pores. Chaperones also play central roles in phase transitions and proteostasis by suppressing protein aggregation. Ranbp2 haploinsufficiency promotes the age-dependent neuroprotection of the chorioretina against photo-oxidative stress by proteostatic regulations of Ranbp2 substrates and by countering the build-up of poly-ubiquitylated substrates. Further, the peptidyl-prolyl cis-trans isomerase (PPIase) and chaperone activities of the cyclophilin domain (CY) of Ranbp2 modulate the proteostasis of selective neuroprotective substrates, such as hnRNPA2B1, STAT3, HDAC4 or L/M-opsin, while promoting a decline of ubiquitylated substrates. However, links between CY PPIase activity on client substrates and its effect(s) on ubiquitylated substrates are unclear. Here, proteomics of genetically modified mice with deficits of Ranbp2 uncovered the regulation of the small heat shock chaperones - crystallins by Ranbp2 in the chorioretina. Loss of CY PPIase of Ranbp2 up-regulates αA-crystallin proteostasis, which is repressed in non-lenticular tissues. Conversely, the αA-crystallin's substrates, γ-crystallins, are down-regulated by impairment of CY's C-terminal chaperone activity. These CY-dependent effects cause the age-dependent decline of ubiquitylated substrates without overt chorioretinal morphological changes. A model emerges whereby the Ranbp2 CY-dependent remodeling of crystallins' proteostasis subdues molecular aging and preordains chorioretinal neuroprotection by augmenting the chaperone buffering capacity and the decline of ubiquitylated substrates against proteostatic impairments. Further, CY's moonlighting activity holds pan -therapeutic potential against neurodegeneration.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.

Targeted protein modification as a paradigm shift in drug discovery

Targeted Protein Modification (TPM) is an umbrella term encompassing numerous tools and approaches that use bifunctional agents to induce a desired modification over the POI. The most well-known TPM mechanism is PROTAC-directed protein ubiquitination. PROTAC-based targeted degradation offers several advantages over conventional small-molecule inhibitors, has shifted the drug discovery paradigm, and is acquiring increasing interest as over ten PROTACs have entered clinical trials in the past few years. Targeting the protein of interest for proteasomal degradation by PROTACS was the pioneer of various toolboxes for selective protein degradation. Nowadays, the ever-increasing number of tools and strategies for modulating and modifying the POI has expanded far beyond protein degradation, which phosphorylation and de-phosphorylation of the protein of interest, targeted acetylation, and selective modification of protein O-GlcNAcylation are among them. These novel strategies have opened new avenues for achieving more precise outcomes while remaining feasible and minimizing side effects. This field, however, is still in its infancy and has a long way to precede widespread use and translation into clinical practice. Herein, we investigate the pros and cons of these novel strategies by exploring the latest advancements in this field. Ultimately, we briefly discuss the emerging potential applications of these innovations in cancer therapy, neurodegeneration, viral infections, and autoimmune and inflammatory diseases.

Temperature as a modulator of allosteric motions and crosstalk in mesophilic and thermophilic enzymes

Mesophilic and thermophilic enzyme counterparts are often studied to understand how proteins function under harsh conditions. To function well outside of standard temperature ranges, thermophiles often tightly regulate their structural ensemble through intra-protein communication (via allostery) and altered interactions with ligands. It has also become apparent in recent years that the enhancement or diminution of allosteric crosstalk can be temperature-dependent and distinguish thermophilic enzymes from their mesophilic paralogs. Since most studies of allostery utilize chemical modifications from pH, mutations, or ligands, the impact of temperature on allosteric function is comparatively understudied. Here, we discuss the biophysical methods, as well as critical case studies, that dissect temperature-dependent function of mesophilic-thermophilic enzyme pairs and their allosteric regulation across a range of temperatures.

Reactivity Tracking of an Enzyme Progress Coordinate

The reactivity of individual solvent-coupled protein configurations is used to track and resolve the progress coordinate for the core reaction sequence of substrate radical rearrangement and hydrogen atom transfer in the ethanolamine ammonia-lyase (EAL) enzyme from Salmonella enterica. The first-order decay of the substrate radical intermediate is the monitored reaction. Heterogeneous confinement from sucrose hydrates in the mesophase solvent surrounding the cryotrapped protein introduces distributed kinetics in the non-native decay of the substrate radical pair capture substate, which arise from an ensemble of configurational microstates. Reaction rates increase by >103-fold across the distribution to approach that for the native enabled substate for radical rearrangement, which reacts with monotonic kinetics. The native progress coordinate thus involves a collapse of the configuration space to generate optimized reactivity. Reactivity tracking reveals fundamental features of solvent-protein-reaction configurational coupling and leads to a model that refines the ensemble paradigm of enzyme catalysis for strongly adiabatic chemical steps.

Identifying structural and dynamic changes during the Biliverdin Reductase B catalytic cycle

Biliverdin Reductase B (BLVRB) is an NADPH-dependent reductase that catalyzes the reduction of multiple substrates and is therefore considered a critical cellular redox regulator. In this study, we sought to address whether both structural and dynamics changes occur between different intermediates of the catalytic cycle and whether these were relegated to just the active site or the entirety of the enzyme. Through X-ray crystallography, we determined the apo BLVRB structure for the first time, revealing subtle global changes compared to the holo structure and identifying the loss of a critical hydrogen bond that "clamps" the R78-loop over the coenzyme. Amide and Cα chemical shift perturbations were used to identify environmental and secondary structural changes between intermediates, with more distant global changes observed upon coenzyme binding compared to substrate interactions. NMR relaxation rate measurements provided insights into the dynamic behavior of BLVRB during the catalytic cycle. Specifically, the inherently dynamic R78-loop that becomes ordered upon coenzyme binding persists through the catalytic cycle while similar regions experience dynamic exchange. However, the dynamic exchange processes were found to differ through the catalytic cycle with several groups of residues exhibiting similar dynamic responses. Finally, both local and distal structural and dynamic changes occur within BLVRB that are dependent solely on the oxidative state of the coenzyme. Thus, through a comprehensive analysis here, this study revealed structural and dynamic alterations in BLVRB through its catalytic cycle that are not simply relegated to the active site, but instead, are allosterically coupled throughout the enzyme.

Relaxation and single site multiple mutations to identify and control allosteric networks

Advances in Nuclear Magnetic Resonance (NMR) spectroscopy have allowed for the identification and characterization of movements in enzymes over the last 20 years that has also revealed the complexities of allosteric coupling. For example, many of the inherent movements of enzymes, and proteins in general, have been shown to be highly localized but nonetheless still coupled over long distances. Such partial couplings provide challenges to both identifying allosteric networks of dynamic communication and determining their roles in catalytic function. We have developed an approach to help identify and engineer enzyme function, called Relaxation And Single Site Multiple Mutations (RASSMM). This approach is a powerful extension of mutagenesis and NMR that is based on the observation that multiple mutations to a single site distal to the active site allosterically induces different effects to networks. Such an approach generates a panel of mutations that can also be subjected to functional studies in order to match catalytic effects with changes to coupled networks. In this review, the RASSMM approach is briefly outlined together with two applications that include cyclophilin-A and Biliverdin Reductase B.

Molecular analyses of the C-terminal CRAF variants associated with cardiomyopathy reveal their opposing impacts on the active conformation of the kinase domain

The germline mutations in the C-terminus of CRAF kinase, particularly L603, and S612T/L613V, are associated with congenital heart disorders, for example, dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). The experimental data suggest that genetic alternation at position 603 impairs, while those at positions 612/613 enhance the CRAF kinase activity. However, the underlying mechanistic details by which these mutations increase or decrease kinase activity remain elusive. Therefore, we applied molecular dynamic simulation to investigate the impacts of these point mutations on the conformation of the CRAF kinase domain. The results revealed that the substitution of Leucine 603 for proline transits the kinase domain to a state that exhibits the molecular hallmarks of an inactive kinase, for example, a closed activation loop, 'αC-helix out' conformation and a distorted regulatory hydrophobic spine. However, two HCM-associated variants (S612T and L613V) show features of an active conformation, such as an open activation loop conformation, 'αC-helix in', the assembly of the hydrophobic spine, and more surface-exposed catalytic residues of phosphoryl transfer reaction. Overall, our study provides a mechanistic basis for the contradictory effects of the CRAF variants associated with HCM and DCM.

Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase

Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase (PaDADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of PaDADH. Molecular dynamics showed that the conformational dynamics of PaDADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association (k₁), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex (k₂), and a 24-fold decrease in the rate constant of product release (k₅), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in PaDADH.

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct "enhanced network models", describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. "Ab-initio network models" combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.

MptpA Kinetics Enhanced by Allosteric Control of an Active Conformation

Understanding allostery in the Mycobacterium tuberculosis low molecular weight protein tyrosine phosphatase (MptpA) is a subject of great interest since MptpA is one of two protein tyrosine phosphatases (PTPs) from the pathogenic organism Mycobacterium tuberculosis expressed during host cell infection. Here, we combine computational modeling with solution NMR spectroscopy and we find that Q75 is an allosteric site. Removal of the polar side chain of Q75 by mutation to leucine results in a cascade of events that reposition the acid loop over the active site and relocates the catalytic aspartic acid (D126) at an optimal position for proton donation to the leaving aryl group of the substrate and for subsequent hydrolysis of the thiophosphoryl intermediate. The computational analysis is consistent with kinetic data, and NMR spectroscopy, showing that the Q75L mutant exhibits enhanced reaction kinetics with similar substrate binding affinity. We anticipate that our findings will motivate further studies on the possibility that MptpA remains passivated during the chronic state of infection and increases its activity as part of the pathogenic life cycle of M. tuberculosis possibly via allosteric means.

Mechanical Allosteric Couplings of Redox-Induced Conformational Changes in Respiratory Complex I

We apply linear response theory to calculate mechanical allosteric couplings in respiratory complex I between the iron sulfur cluster N2, located in the catalytic cavity, and the membrane part of the enzyme, separated from it by more than 50 Å. According to our hypothesis, the redox reaction of ubiquinone in the catalytic cavity of the enzyme generates an unbalanced charge that via repulsion of the charged redox center N2 produces local mechanical stress that transmits into the membrane part of the enzyme where it induces proton pumping. Using coarse-grained simulations of the enzyme, we calculated mechanistic allosteric couplings that reveal the pathways of the mechanical transmission of the stress along the enzyme. The results shed light on the recent experimental studies where a stabilization of the enzyme with an introduced disulfide bridge resulted in the abolishing of proton pumping. Simulation of the disulfide bond action indicates a dramatic change of the mechanistic coupling pathways in line with experimental findings.

Characterization of Amyloidogenic Peptide Aggregability in Helical Subspace

Prototypical amyloidogenic peptides amyloid-β (Aβ) and α-synuclein (αS) can undergo helix-helix associations via partially folded helical conformers, which may influence pathological progression to Alzheimer's (AD) and Parkinson's disease (PD), respectively. At the other extreme, stable folded helical conformers have been reported to resist self-assembly and amyloid formation. Experimental characterisation of such disparities in aggregation profiles due to subtle differences in peptide stabilities is precluded by the conformational heterogeneity of helical subspace. The diverse physical models used in molecular simulations allow sampling distinct regions of the phase space and are extensive in capturing the ensemble of rich helical subspace. Robust and powerful computational predictive methods utilizing network theory and free energy mapping can model the origin of helical population shifts in amyloidogenic peptides, which highlight their inherent aggregability. In this chapter, we discuss computational models, methods, design rules, and strategies to identify the driving force behind helical self-assembly and the molecular origin of aggregation resistance in helical intermediates of Aβ42 and αS. By extensive multiscale mapping of intrapeptide interactions, we show that the computational models can capture features that are otherwise imperceptible to experiments. Our models predict that targeting terminal residues may allow modulation and control of initial pathogenic aggregability of amyloidogenic peptides.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

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Evolution of protein structures occurs at the level of global interaction network.

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More than 70% of the protein residues are weakly or marginally coupled.

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Functional ‘sector’ regions are a manifestation of marginal coupling.

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Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

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The proposed methodology can be used to understand allostery and epistasis.

F/G Region Rigidity is Inversely Correlated to Substrate Promiscuity of Human CYP Isoforms Involved in Metabolism

Of 57 human cytochrome P450 (CYP) enzymes, 12 metabolize 90% of xenobiotics. To our knowledge, no study has addressed the relation between enzyme dynamics and substrate promiscuity for more than three CYPs. Here, we show by constraint dilution simulations with the Constraint Network Analysis for the 12 isoforms that structural rigidity of the F/G region is significantly inversely correlated to the enzymes' substrate promiscuity. This highlights the functional importance of structural dynamics of the substrate tunnel.

MDContactCom: a tool to identify differences of protein molecular dynamics from two MD simulation trajectories in terms of interresidue contacts

SUMMARY

Comparing results from multiple MD simulations performed under different conditions is essential during the initial stages of analysis. We propose a tool called MD Contact Comparison (MDContactCom) that compares residue-residue contact fluctuations of two MD trajectories, quantifies the differences, identifies sites that exhibit large differences and visualizes those sites on the protein structure. Using this method, it is possible to identify sites affected by varying simulation conditions and reveal the path of propagation of the effect even when differences between the 3D structure of the molecule and the fluctuation RMSF of each residue is unclear. MDContactCom can monitor differences in complex protein dynamics between two MD trajectories and identify candidate sites to be analyzed in more detail. As such, MDContactCom is a versatile software package for analyzing most MD simulations.

AVAILABILITY AND IMPLEMENTATION

MDContactCom is freely available for download on GitLab. The software is implemented in Python3. https://gitlab.com/chiemotono/mdcontactcom.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Promiscuous Esterases Counterintuitively Are Less Flexible than Specific Ones

Understanding mechanisms of promiscuity is increasingly important from a fundamental and application point of view. As to enzyme structural dynamics, more promiscuous enzymes generally have been recognized to also be more flexible. However, examples for the opposite received much less attention. Here, we exploit comprehensive experimental information on the substrate promiscuity of 147 esterases tested against 96 esters together with computationally efficient rigidity analyses to understand the molecular origin of the observed promiscuity range. Unexpectedly, our data reveal that promiscuous esterases are significantly less flexible than specific ones, are significantly more thermostable, and have a significantly increased specific activity. These results may be reconciled with a model according to which structural flexibility in the case of specific esterases serves for conformational proofreading. Our results signify that an esterase sequence space can be screened by rigidity analyses for promiscuous esterases as starting points for further exploration in biotechnology and synthetic chemistry.

Structure, dynamics and function of the evolutionarily changing biliverdin reductase B family

Biliverdin reductase B (BLVRB) family members are general flavin reductases critical in maintaining cellular redox with recent findings revealing that BLVRB alone can dictate cellular fate. However, as opposed to most enzymes, the BLVRB family remains enigmatic with an evolutionarily changing active site and unknown structural and functional consequences. Here, we applied a multi-faceted approach that combines X-ray crystallography, NMR and kinetics methods to elucidate the structural and functional basis of the evolutionarily changing BLVRB active site. Using a panel of three BLVRB isoforms (human, lemur and hyrax) and multiple human BLVRB mutants, our studies reveal a novel evolutionary mechanism where coenzyme 'clamps' formed by arginine side chains at two co-evolving positions within the active site serve to slow coenzyme release (Positions 14 and 78). We find that coenzyme release is further slowed by the weaker binding substrate, resulting in relatively slow turnover numbers. However, different BLVRB active sites imposed by either evolution or mutagenesis exhibit a surprising inverse relationship between coenzyme release and substrate turnover that is independent of the faster chemical step of hydride transfer also measured here. Collectively, our studies have elucidated the role of the evolutionarily changing BLVRB active site that serves to modulate coenzyme release and has revealed that coenzyme release is coupled to substrate turnover.

Modulating Enzyme Function via Dynamic Allostery within Biliverdin Reductase B

The biliverdin reductase B (BLVRB) class of enzymes catalyze the NADPH-dependent reduction of multiple flavin substrates and are emerging as critical players in cellular redox regulation. However, the role of dynamics and allostery have not been addressed, prompting studies here that have revealed a position 15 Å away from the active site within human BLVRB (T164) that is inherently dynamic and can be mutated to control global micro-millisecond motions and function. By comparing the inherent dynamics through nuclear magnetic resonance (NMR) relaxation approaches of evolutionarily distinct BLVRB homologues and by applying our previously developed Relaxation And Single Site Multiple Mutations (RASSMM) approach that monitors both the functional and dynamic effects of multiple mutations to the single T164 site, we have discovered that the most dramatic mutagenic effects coincide with evolutionary changes and these modulate coenzyme binding. Thus, evolutionarily changing sites distal to the active site serve as dynamic "dials" to globally modulate motions and function. Despite the distal dynamic and functional coupling modulated by this site, micro-millisecond motions span an order of magnitude in their apparent kinetic rates of motions. Thus, global dynamics within BLVRB are a collection of partially coupled motions tied to catalytic function.

Transient association between proteins elicits alteration of dynamics at sites far away from interfaces

Proteins are known to undergo structural changes upon binding to partner proteins. However, the prevalence, extent, location, and function of change in protein dynamics due to transient protein-protein interactions is not well documented. Here, we have analyzed a dataset of 58 protein-protein complexes of known three-dimensional structure and structures of their corresponding unbound forms to evaluate dynamics changes induced by binding. Fifty-five percent of cases showed significant dynamics change away from the interfaces. This change is not always accompanied by an observed structural change. Binding of protein partner is found to alter inter-residue communication within the tertiary structure in about 90% of cases. Also, residue motions accessible to proteins in unbound form were not always maintained in the bound form. Further analyses revealed functional roles for the distant site where dynamics change was observed. Overall, the results presented here strongly suggest that alteration of protein dynamics due to binding of a partner protein commonly occurs.

Seeking the Source of Catalytic Efficiency of Lindane Dehydrochlorinase, LinA

Herein we present the results of an in-depth simulation study of LinA and its two variants. In our analysis, we combined the exploration of protein conformational dynamics with and without bound substrates (hexachlorocyclohexane (HCH) isomers) performed using molecular dynamics simulation followed by the extraction of the most frequently visited conformations and their characteristics with a detailed description of the interactions taking place in the active site between the respective HCH molecule and the first shell residues by using symmetry-adapted perturbation theory (SAPT) calculations. A detailed investigation of the conformational space of LinA substates has been accompanied by description of enzymatic catalytic steps carried out using a hybrid quantum mechanics/molecular mechanics (QM/MM) potential along with the computation of the potential of mean force (PMF) to estimate the free energy barriers for the studied transformations: dehydrochlorination of γ-, (-)-α-, and (+)-α-HCH by LinA-type I and -type II variants. The applied combination of computational techniques allowed us not only to characterize two LinA types but also to point to the most important differences between them and link their features to catalytic efficiency each of them possesses toward the respective ligand. More importantly it has been demonstrated that type I protein is more mobile, its active site has a larger volume, and the dehydrochlorination products are stabilized more strongly than in the case of type II enzyme, due to differences in the residues present in the active sites. Additionally, interaction energy calculations revealed very interesting patterns not predicted before but having the potential to be utilized in any attempts of improving LinA catalytic efficiency. On the basis of all these observations, LinA-type I protein seems to be more preorganized for the dehydrochlorination reaction it catalyzes than the type II variant.

Functional plasticity and evolutionary adaptation of allosteric regulation

Allostery is a fundamental regulatory mechanism of protein function. Despite notable advances, understanding the molecular determinants of allostery remains an elusive goal. Our current knowledge of allostery is principally shaped by a structure-centric view, which makes it difficult to understand the decentralized character of allostery. We present a function-centric approach using deep mutational scanning to elucidate the molecular basis and underlying functional landscape of allostery. We show that allosteric signaling exhibits a high degree of functional plasticity and redundancy through myriad mutational pathways. Residues critical for allosteric signaling are surprisingly poorly conserved while those required for structural integrity are highly conserved, suggesting evolutionary pressure to preserve fold over function. Our results suggest multiple solutions to the thermodynamic conditions of cooperativity, in contrast to the common view of a finely tuned allosteric residue network maintained under selection.

The anti-oxidant enzyme, Prdx6 might have cis-acting regulatory sequence(s)

Peroxiredoxin 6 (Prdx6) is a ubiquitously expressed 1-cysteine Peroxiredoxin found throughout all phyla. In mammals, under different physiological conditions, it has evolved from a peroxidase to a multifunctional enzyme. Among the mammalian Prdx6's, human and rat Prdx6's are the most extensively studied. Our study revealed that human and rat Prdx6's exhibit differences in their peroxidase activity. These two Prdx6's have only 8% difference in their primary sequence (with 19 amino acids) with no apparent modification at any of the key conserved residues. In the present communication, we have investigated the roles of thermodynamics, structure and internal flexibility of Prdx6 to account for the difference in their peroxidase activity. We discovered that these amino acid variations have led to structural alterations in human Prdx6 so that it shows enhanced intrinsic dynamics (or flexibility) than the rat protein. We could also identify the gain of intrinsic dynamics of the catalytic site in human Prdx6 due to relocation of an important active site residue (R132) to the loop region as the most plausible reason for high catalytic activity in the human protein as compared to rat variant. Since it is the thioredoxin fold that upholds the peroxidase function, certain structural alteration in the Prdx6 structure might help to regulate the efficiency of thioredoxin folds. Our results hint that Prdx6 might have a cis-acting regulatory sequence(s).

Recent advances suggest increased influence of selective pressure in allostery

Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.

A single amino acid substitution uncouples catalysis and allostery in an essential biosynthetic enzyme in Mycobacterium tuberculosis

Allostery exploits the conformational dynamics of enzymes by triggering a shift in population ensembles toward functionally distinct conformational or dynamic states. Allostery extensively regulates the activities of key enzymes within biosynthetic pathways to meet metabolic demand for their end products. Here, we have examined a critical enzyme, 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase (DAH7PS), at the gateway to aromatic amino acid biosynthesis in Mycobacterium tuberculosis, which shows extremely complex dynamic allostery: three distinct aromatic amino acids jointly communicate occupancy to the active site via subtle changes in dynamics, enabling exquisite fine-tuning of delivery of these essential metabolites. Furthermore, this allosteric mechanism is co-opted by pathway branchpoint enzyme chorismate mutase upon complex formation. In this study, using statistical coupling analysis, site-directed mutagenesis, isothermal calorimetry, small-angle X-ray scattering, and X-ray crystallography analyses, we have pinpointed a critical node within the complex dynamic communication network responsible for this sophisticated allosteric machinery. Through a facile Gly to Pro substitution, we have altered backbone dynamics, completely severing the allosteric signal yet remarkably, generating a nonallosteric enzyme that retains full catalytic activity. We also identified a second residue of prime importance to the inter-enzyme communication with chorismate mutase. Our results reveal that highly complex dynamic allostery is surprisingly vulnerable and provide further insights into the intimate link between catalysis and allostery.

Dynamic design: manipulation of millisecond timescale motions on the energy landscape of cyclophilin A

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they interconvert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov state modelling (MSM) to explore these 'excited' conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics, whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By efficiently exploring functionally relevant, but sparsely populated conformations with millisecond lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

Detecting Functional Dynamics in Proteins with Comparative Perturbed-Ensembles Analysis

Recent advances have made all-atom molecular dynamics (MD) a powerful tool to sample the conformational energy landscape. There are still however three major challenges in the application of MD to biological systems: accuracy of force field, time scale, and the analysis of simulation trajectories. Significant progress in addressing the first two challenges has been made and extensively reviewed previously. This Account focuses on strategies of analyzing simulation data of biomolecules that also covers ways to properly design simulations and validate simulation results. In particular, we examine an approach named comparative perturbed-ensembles analysis, which we developed to efficiently detect dynamics in protein MD simulations that can be linked to biological functions. In our recent studies, we implemented this approach to understand allosteric regulations in several disease-associated human proteins. The central task of a comparative perturbed-ensembles analysis is to compare two or more conformational ensembles of a system generated by MD simulations under distinct perturbation conditions. Perturbations can be different sequence variations, ligand-binding conditions, and other physical/chemical modifications of the system. Each simulation is long enough (e.g., microsecond-long) to ensure sufficient sampling of the local substate. Then, sophisticated bioinformatic and statistical tools are applied to extract function-related information from the simulation data, including principal component analysis, residue-residue contact analysis, difference contact network analysis (dCNA) based on the graph theory, and statistical analysis of side-chain conformations. Computational findings are further validated with experimental data. By comparing distinct conformational ensembles, functional micro- to millisecond dynamics can be inferred. In contrast, such a time scale is difficult to reach in a single simulation; even when reached for a single condition of a system, it is elusive as to what dynamical motions are related to functions without, for example, comparing free and substrate-bound proteins at the minimum. We illustrate our approach with three examples. First, we discuss using the approach to identify allosteric pathways in cyclophilin A (CypA), a member of a ubiquitous class of peptidyl-prolyl cis-trans isomerase enzymes. By comparing side-chain torsion-angle distributions of CypA in wild-type and mutant forms, we identified three pathways: two are consistent with recent nuclear magnetic resonance experiments, whereas the third is a novel pathway. Second, we show how the approach enables a dynamical-evolution analysis of the human cyclophilin family. In the analysis, both conserved and divergent conformational dynamics across three cyclophilin isoforms (CypA, CypD, and CypE) were summarized. The conserved dynamics led to the discovery of allosteric networks resembling those found in CypA. A residue wise determinant underlying the unique dynamics in CypD was also detected and validated with additional mutational MD simulations. In the third example, we applied the approach to elucidate a peptide sequence-dependent allosteric mechanism in human Pin 1, a phosphorylation-dependent peptidyl-prolyl isomerase. We finally present our outlook of future directions. Especially, we envisage how the approach could help open a new avenue in drug discovery.

Patterns of Dynamics Comprise a Conserved Evolutionary Trait

The importance of protein dynamics in function may suggest an evolutionary selection on large-scale protein motions. Here we systematically studied the dynamic characteristics in 2221 protein domains (58477 sequences) of the Pfam database. We defined the patterns of dynamics (PODs) based on the estimated NMR order parameters and the predicted degree of disorder, and found a significant correlation between them in families of both structured and disordered protein domains. We demonstrate that conservation of dynamic patterns frequently exceeds conservation of sequence and is comparable to the patterns of hydropathy and nonspecific interaction potential. Similarity of dynamic patterns is weakly correlated to structure similarity and to the degree of disorder. We illustrate that POD alignments could be applied to sequentially divergent or intrinsically disordered regions. We propose that patterns of dynamics comprise a conserved evolutionary trait, which could be used to infer evolutionary relationships as an alternative to sequence and structure.

Engineering Allostery into Proteins

Our ability to engineer protein structure and function has grown dramatically over recent years. Perhaps the next level in protein design is to develop proteins whose function can be regulated in response to various stimuli, including ligand binding, pH changes, and light. Endeavors toward these goals have tested and expanded on our understanding of protein function and allosteric regulation. In this chapter, we provide examples from different methods for developing new allosterically regulated proteins. These methods range from whole insertion of regulatory domains into new host proteins, to covalent attachment of photoswitches to generate light-responsive proteins, and to targeted changes to specific amino acid residues, especially to residues identified to be important for relaying allosteric information across the protein framework. Many of the examples we discuss have already found practical use in medical and biotechnology applications.

A Biophysical Perspective on Enzyme Catalysis

Even after a century of investigation, our understanding of how enzymes work remains far from complete. In particular, several factors that enable enzymes to achieve high catalytic efficiencies remain only poorly understood. A number of theories have been developed, which propose or reaffirm that enzymes work as structural scaffolds, serving to bring together and properly orient the participants so that the reaction can proceed; therefore, leading to enzymes being viewed as only passive participants in the catalyzed reaction. A growing body of evidence shows that enzymes are not rigid structures but are constantly undergoing a wide range of internal motions and conformational fluctuations. In this Perspective, on the basis of studies from our group, we discuss the emerging biophysical model of enzyme catalysis that provides a detailed understanding of the interconnection among internal protein motions, conformational substates, enzyme mechanisms, and the catalytic efficiency of enzymes. For a number of enzymes, networks of conserved residues that extend from the surface of the enzyme all the way to the active site have been discovered. These networks are hypothesized to serve as pathways of energy transfer that enables thermodynamical coupling of the surrounding solvent with enzyme catalysis and play a role in promoting enzyme function. Additionally, the role of enzyme structure and electrostatic effects has been well acknowledged for quite some time. Collectively, the recent knowledge gained about enzyme mechanisms suggests that the conventional paradigm of enzyme structure encoding function is incomplete and needs to be extended to structure encodes dynamics, and together these enzyme features encode function including catalytic rate acceleration.

Biliverdin Reductase B Dynamics Are Coupled to Coenzyme Binding

Biliverdin reductase B (BLVRB) is a newly identified cellular redox regulator that catalyzes the NADPH-dependent reduction of multiple substrates. Through mass spectrometry analysis, we identified high levels of BLVRB in mature red blood cells, highlighting the importance of BLVRB in redox regulation. The BLVRB conformational changes that occur during conezyme/substrate binding and the role of dynamics in BLVRB function, however, remain unknown. Through a combination of NMR, kinetics, and isothermal titration calorimetry studies, we determined that BLVRB binds its coenzyme 500-fold more tightly than its substrate. While the active site of apo BLVRB is highly dynamic on multiple timescales, active site dynamics are largely quenched within holo BLVRB, in which dynamics are redistributed to other regions of the enzyme. We show that a single point mutation of Arg78➔Ala leads to both an increase in active site micro-millisecond motions and an increase in the microscopic rate constants of coenzyme binding. This demonstrates that altering BLVRB active site dynamics can directly cause a change in functional characteristics. Our studies thus address the solution behavior of apo and holo BLVRB and identify a role of enzyme dynamics in coenzyme binding.

Role of conformational dynamics in the evolution of novel enzyme function

The free energy landscape concept that describes enzymes as an ensemble of differently populated conformational sub-states in dynamic equilibrium is key for evaluating enzyme activity, enantioselectivity, and specificity. Mutations introduced in the enzyme sequence can alter the populations of the pre-existing conformational states, thus strongly modifying the enzyme ability to accommodate alternative substrates, revert its enantiopreferences, and even increase the activity for some residual promiscuous reactions. In this feature article, we present an overview of the current experimental and computational strategies to explore the conformational free energy landscape of enzymes. We provide a series of recent publications that highlight the key role of conformational dynamics for the enzyme evolution towards new functions and substrates, and provide some perspectives on how conformational dynamism should be considered in future computational enzyme design protocols.

Ligand-Induced Variations in Structural and Dynamical Properties Within an Enzyme Superfamily

Enzyme catalysis is a complex process involving several steps along the reaction coordinates, including substrate recognition and binding, chemical transformation, and product release. Evidence continues to emerge linking the functional and evolutionary role of conformational exchange processes in optimal catalytic activity. Ligand binding changes the conformational landscape of enzymes, inducing long-range conformational rearrangements. Using functionally distinct members of the pancreatic ribonuclease superfamily as a model system, we characterized the structural and conformational changes associated with the binding of two mononucleotide ligands. By combining NMR chemical shift titration experiments with the chemical shift projection analysis (CHESPA) and relaxation dispersion experiments, we show that biologically distinct members of the RNase superfamily display discrete chemical shift perturbations upon ligand binding that are not conserved even in structurally related members. Amino acid networks exhibiting coordinated chemical shift displacements upon binding of the two ligands are unique to each of the RNases analyzed. Our results reveal the contribution of conformational rearrangements to the observed chemical shift perturbations. These observations provide important insights into the contribution of the different ligand binding specificities and effects of conformational exchange on the observed perturbations associated with ligand binding for functionally diverse members of the pancreatic RNase superfamily.

Protein kinase Cα gain-of-function variant in Alzheimer's disease displays enhanced catalysis by a mechanism that evades down-regulation

Conventional protein kinase C (PKC) family members are reversibly activated by binding to the second messengers Ca²⁺ and diacylglycerol, events that break autoinhibitory constraints to allow the enzyme to adopt an active, but degradation-sensitive, conformation. Perturbing these autoinhibitory constraints, resulting in protein destabilization, is one of many mechanisms by which PKC function is lost in cancer. Here, we address how a gain-of-function germline mutation in PKCα in Alzheimer's disease (AD) enhances signaling without increasing vulnerability to down-regulation. Biochemical analyses of purified protein demonstrate that this mutation results in an ∼30% increase in the catalytic rate of the activated enzyme, with no changes in the concentrations of Ca²⁺ or lipid required for half-maximal activation. Molecular dynamics simulations reveal that this mutation has both localized and allosteric effects, most notably decreasing the dynamics of the C-helix, a key determinant in the catalytic turnover of kinases. Consistent with this mutation not altering autoinhibitory constraints, live-cell imaging studies reveal that the basal signaling output of PKCα-M489V is unchanged. However, the mutant enzyme in cells displays increased sensitivity to an inhibitor that is ineffective toward scaffolded PKC, suggesting the altered dynamics of the kinase domain may influence protein interactions. Finally, we show that phosphorylation of a key PKC substrate, myristoylated alanine-rich C-kinase substrate, is increased in brains of CRISPR-Cas9 genome-edited mice containing the PKCα-M489V mutation. Our results unveil how an AD-associated mutation in PKCα permits enhanced agonist-dependent signaling via a mechanism that evades the cell's homeostatic down-regulation of constitutively active PKCα.

Chemically induced proximity in biology and medicine

Proximity, or the physical closeness of molecules, is a pervasive regulatory mechanism in biology. For example, most posttranslational modifications such as phosphorylation, methylation, and acetylation promote proximity of molecules to play deterministic roles in cellular processes. To understand the role of proximity in biologic mechanisms, chemical inducers of proximity (CIPs) were developed to synthetically model biologically regulated recruitment. Chemically induced proximity allows for precise temporal control of transcription, signaling cascades, chromatin regulation, protein folding, localization, and degradation, as well as a host of other biologic processes. A systematic analysis of CIPs in basic research, coupled with recent technological advances utilizing CRISPR, distinguishes roles of causality from coincidence and allows for mathematical modeling in synthetic biology. Recently, induced proximity has provided new avenues of gene therapy and emerging advances in cancer treatment.