Rational modulation of conformational fluctuations in adenylate kinase reveals a local unfolding mechanism for allostery and functional adaptation in proteins

Evolutionary-Scale Enzymology Enables Biochemical Constant Prediction Across a Multi-Peaked Catalytic Landscape

Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function, evolution, and design. Here, we expand an emerging microfluidic platform to measure catalytic constants-k cat and K M-for hundreds of diverse naturally occurring sequences and mutants of the model enzyme Adenylate Kinase (ADK). This enables us to dissect the sequence-catalysis landscape's topology, navigability, and mechanistic underpinnings, revealing distinct catalytic peaks organized by structural motifs. These results challenge long-standing hypotheses in enzyme adaptation, demonstrating that thermophilic enzymes are not slower than their mesophilic counterparts. Combining the rich representations of protein sequences provided by deep-learning models with our custom high-throughput kinetic data yields semi-supervised models that significantly outperform existing models at predicting catalytic parameters of naturally occurring ADK sequences. Our work demonstrates a promising strategy for dissecting sequence-catalysis landscapes across enzymatic evolution and building family-specific models capable of accurately predicting catalytic constants, opening new avenues for enzyme engineering and functional prediction.

Enzyme activation by urea reveals the interplay between conformational dynamics and substrate binding: a single-molecule FRET study

Proteins often harness extensive motions of domains and subunits to promote their function. Deciphering how these movements impact activity is key for understanding life's molecular machinery. The enzyme adenylate kinase is an intriguing example for this relationship; it ensures efficient catalysis by large-scale domain motions that lead to the enclosure of the bound substrates ATP and AMP. At high concentrations, AMP also operates as an allosteric inhibitor of the protein. Surprisingly, the enzyme is activated by urea, a compound commonly acting as a denaturant. Combining single-molecule FRET spectroscopy and enzymatic activity studies, we find that urea interferes with two key mechanisms that contribute to enzyme efficacy. First, urea promotes the open conformation of the enzyme, aiding the proper positioning of the substrates. Second, urea decreases AMP affinity, paradoxically facilitating a more efficient progression towards the catalytically active complex. These results signify the important interplay between conformational dynamics and chemical steps, including binding, in the activity of enzymes. State-of-the-art tools, such as single-molecule fluorescence spectroscopy, offer new insights into how enzymes balance different conformations to regulate activity.

Magnesium induced structural reorganization in the active site of adenylate kinase

Phosphoryl transfer is a fundamental reaction in cellular signaling and metabolism that requires Mg2+ as an essential cofactor. While the primary function of Mg2+ is electrostatic activation of substrates, such as ATP, the full spectrum of catalytic mechanisms exerted by Mg2+ is not known. In this study, we integrate structural biology methods, molecular dynamic (MD) simulations, phylogeny, and enzymology assays to provide molecular insights into Mg2+-dependent structural reorganization in the active site of the metabolic enzyme adenylate kinase. Our results demonstrate that Mg2+ induces a conformational rearrangement of the substrates (ATP and ADP), resulting in a 30° adjustment of the angle essential for reversible phosphoryl transfer, thereby optimizing it for catalysis. MD simulations revealed transitions between conformational substates that link the fluctuation of the angle to large-scale enzyme dynamics. The findings contribute detailed insight into Mg2+ activation of enzymes and may be relevant for reversible and irreversible phosphoryl transfer reactions.

NMR and Single-Molecule FRET Insights into Fast Protein Motions and Their Relation to Function

Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.

Towards the understanding of molecular motors and its relationship with local unfolding

Molecular motors are machines essential for life since they convert chemical energy into mechanical work. However, the precise mechanism by which nucleotide binding, catalysis, or release of products is coupled to the work performed by the molecular motor is still not entirely clear. This is due, in part, to a lack of understanding of the role of force in the mechanical-structural processes involved in enzyme catalysis. From a mechanical perspective, one promising hypothesis is the Haldane-Pauling hypothesis which considers the idea that part of the enzymatic catalysis is strain-induced. It suggests that enzymes cannot be efficient catalysts if they are fully complementary to the substrates. Instead, they must exert strain on the substrate upon binding, using enzyme-substrate energy interaction (binding energy) to accelerate the reaction rate. A novel idea suggests that during catalysis, significant strain energy is built up, which is then released by a local unfolding/refolding event known as 'cracking'. Recent evidence has also shown that in catalytic reactions involving conformational changes, part of the heat released results in a center-of-mass acceleration of the enzyme, raising the possibility that the heat released by the reaction itself could affect the enzyme's integrity. Thus, it has been suggested that this released heat could promote or be linked to the cracking seen in proteins such as adenylate kinase (AK). We propose that the energy released as a consequence of ligand binding/catalysis is associated with the local unfolding/refolding events (cracking), and that this energy is capable of driving the mechanical work.

Conformational dynamics of adenylate kinase in crystals

Adenylate kinase is a ubiquitous enzyme in living systems and undergoes dramatic conformational changes during its catalytic cycle. For these reasons, it is widely studied by genetic, biochemical, and biophysical methods, both experimental and theoretical. We have determined the basic crystal structures of three differently liganded states of adenylate kinase from Methanotorrus igneus, a hyperthermophilic organism whose adenylate kinase is a homotrimeric oligomer. The multiple copies of each protomer in the asymmetric unit of the crystal provide a unique opportunity to study the variation in the structure and were further analyzed using advanced crystallographic refinement methods and analysis tools to reveal conformational heterogeneity and, thus, implied dynamic behaviors in the catalytic cycle.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase

Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. The mutation of multiple conserved residues reduces substrate inhibition, suggesting that substrate inhibition is an evolutionary well conserved feature in AK. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity.

Structural insights into the effect of mutations in the spike protein of SARS-CoV-2 on the binding with human furin protein

The SARS COV-2 and its variants are spreading around the world at an alarming speed, due to its higher transmissibility and the conformational changes caused by mutations. The resulting COVID-19 pandemic has imposed severe health consequences on human health. Several countries of the world including Pakistan have studied its genome extensively and provided productive findings. In the current study, the mCSM, DynaMut2, and I-Mutant servers were used to analyze the effect of identified mutations on the structural stability of spike protein however, the molecular docking and simulations approaches were used to evaluate the dynamics of the bonding network between the wild-type and mutant spike proteins with furin. We addressed the mutational modifications that have occurred in the spike protein of SARS-COV-2 that were found in 215 Pakistani's isolates of COVID-19 patients to study the influence of mutations on the stability of the protein and its interaction with the host cell. We found 7 single amino acid substitute mutations in various domains that reside in spike protein. The H49Y, N74K, G181V, and G446V were found in the S1 domain while the D614A, V622F, and Q677H mutations were found in the central helices of the spike protein. Based on the observation, G181V, G446V, D614A, and V622F mutants were found highly destabilizing and responsible for structural perturbation. Protein-protein docking and molecular simulation analysis with that of furin have predicted that all the mutants enhanced the binding efficiency however, the V622F mutant has greatly altered the binding capacity which is further verified by the K_D value (7.1 E^-14) and therefore may enhance the spike protein cleavage by Furin and increase the rate of infectivity by SARS-CoV-2. On the other hand, the total binding energy for each complex was calculated which revealed -50.57 kcal/mol for the wild type, for G181V -52.69 kcal/mol, for G446V -56.44 kcal/mol, for D614A -59.78 kcal/mol while for V622F the TBE was calculated to be -85.84 kcal/mol. Overall, the current finding shows that these mutations have increased the binding of Furin for spike protein and shows that D614A and V622F have significant effects on the binding and infectivity.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

Enzymatic Conjugation of Modified RNA Fragments by Ancestral RNA Ligase AncT4_2

Oligonucleotide therapeutics have great potential as a next-generation approach to treating intractable diseases. Large quantities of modified DNA/RNA containing xenobiotic nucleic acids (XNAs) must be synthesized before clinical application. In this study, the ancestral RNA ligase AncT4_2 was designed by ancestral sequence reconstruction (ASR) to perform the conjugation reaction of modified RNA fragments. AncT4_2 had superior properties to native RNA ligase 2 from T4 phage (T4Rnl2), including high productivity, a >2.5-fold-higher turnover number, and >10°C higher thermostability. One remarkable point is the broad substrate selectivity of AncT4_2; the activity of AncT4_2 toward 17 of the modified RNA fragments was higher than that of T4Rnl2. The activity was estimated by measuring the conjugation reaction of two RNA strands, 3'-OH (12 bp) and 5'-PO4 (12 bp), in which the terminal and penultimate positions of the 3'-OH fragment and the first and second positions of the 5'-PO4 fragment were substituted by 2'-fluoro, 2'-O-methyl, 2'-O-methoxyethyl, and 2'-H, respectively. The enzymatic properties of AncT4_2 allowed the enzyme to conjugate large quantities of double-stranded RNA coding for patisiran (>400 μM level), which was formed by four RNA fragments containing 2'-OMe-substituted nucleic acids. Structural analysis of modeled AncT4_2 suggested that protein dynamics were changed by mutation to Gly or indel during ASR and that this may positively impact the conjugation of modified RNA fragments with the enzyme. AncT4_2 is expected to be a key biocatalyst in synthesizing RNA therapeutics by an enzymatic reaction. IMPORTANCE RNA therapeutics is one of the next-generation medicines for treating various diseases. Our designed ancestral RNA ligase AncT4_2 exhibited excellent enzymatic properties, such as high thermal stability, productivity, specific activity, and broad substrate selectivity compared to native enzymes. These advantages create the potential for AncT4_2 to be applied in conjugating the modified RNA fragments containing various xenobiotic nucleic acids. In addition, patisiran, a known polyneuropathy therapeutic, could be synthesized from four fragmented oligonucleotides at a preparative scale. Taken together, these findings indicate AncT4_2 could open the door to synthesizing RNA therapeutics by enzymatic reaction at large-scale production.

Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an "Allosterized" Enzyme using Evolution Guided Punctual Mutations

We unveil the intimate relationship between protein dynamics and allostery by following the trajectories of model proteins in their conformational and sequence spaces. Starting from a nonallosteric hyperthermophilic malate dehydrogenase, we have tracked the role of protein dynamics in the evolution of the allosteric capacity. Based on a large phylogenetic analysis of the malate (MalDH) and lactate dehydrogenase (LDH) superfamily, we identified two amino acid positions that could have had a major role for the emergence of allostery in LDHs, which we targeted for investigation by site-directed mutagenesis. Wild-type MalDH and the single and double mutants were tested with respect to their substrate recognition profiles. The double mutant displayed a sigmoid-shaped profile typical of homotropic activation in LDH. By using molecular dynamics simulations, we showed that the mutations induce a drastic change in the protein sampling of its conformational landscape, making transiently T-like (inactive) conformers, typical of allosteric LDHs, accessible. Our data fit well with the seminal key concept linking protein dynamics and evolvability. We showed that the selection of a new phenotype can be achieved by a few key dynamics-enhancing mutations causing the enrichment of low-populated conformational substates.

Phenol sensing in nature is modulated via a conformational switch governed by dynamic allostery

The NtrC family of proteins senses external stimuli and accordingly stimulates stress and virulence pathways via activation of associated σ⁵⁴-dependent RNA polymerases. However, the structural determinants that mediate this activation are not well understood. Here, we establish using computational, structural, biochemical, and biophysical studies that MopR, an NtrC protein, harbors a dynamic bidirectional electrostatic network that connects the phenol pocket to two distal regions, namely the “G-hinge” and the “allosteric linker.” While the G-hinge influences the entry of phenol into the pocket, the allosteric linker passes the signal to the downstream ATPase domain. We show that phenol binding induces a rewiring of the electrostatic connections by eliciting dynamic allostery and demonstrates that perturbation of the core relay residues results in a complete loss of ATPase stimulation. Furthermore, we found a mutation of the G-hinge, ∼20 Å from the phenol pocket, promotes altered flexibility by shifting the pattern of conformational states accessed, leading to a protein with 7-fold enhanced phenol binding ability and enhanced transcriptional activation. Finally, we conducted a global analysis that illustrates that dynamic allostery-driven conserved community networks are universal and evolutionarily conserved across species. Taken together, these results provide insights into the mechanisms of dynamic allostery-mediated conformational changes in NtrC sensor proteins.

Cooperativity and Folding Kinetics in a Multidomain Protein with Interwoven Chain Topology

Although a large percentage of eukaryotic proteomes consist of proteins with multiple domains, not much is known about their assembly mechanism, especially those with intricate native state architectures. Some have a complex topology in which the structural elements along the sequence are interwoven in such a manner that the domains cannot be separated by cutting at any location along the sequence. Such proteins are multiply connected multidomain proteins (MMPs) with the three-domain (NMP, LID, and CORE) phosphotransferase enzyme adenylate kinase (ADK) being an example. We devised a coarse-grained model to simulate ADK folding initiated by changing either the temperature or guanidinium chloride (GdmCl) concentration. The simulations reproduce the experimentally measured melting temperatures (associated with two equilibrium transitions), FRET efficiency as a function of GdmCl concentration, and the folding times quantitatively. Although the NMP domain orders independently, cooperative interactions between the LID and the CORE domains are required for complete assembly of the enzyme. Kinetic simulations show that, on the collapse time scale, multiple interconnected metastable states are populated, attesting to the folding heterogeneity. The network of kinetically connected states reveals that the CORE domain folds only after the NMP and LID domains, reflecting the interwoven nature of the chain topology.

Molecular Dynamics Simulations Establish the Molecular Basis for the Broad Allostery Hotspot Distributions in the Tetracycline Repressor

It is imperative to identify the network of residues essential to the allosteric coupling for the purpose of rationally engineering allostery in proteins. Deep mutational scanning analysis has emerged as a function-centric approach for identifying such allostery hotspots in a comprehensive and unbiased fashion, leading to observations that challenge our understanding of allostery at the molecular level. Specifically, a recent deep mutational scanning study of the tetracycline repressor (TetR) revealed an unexpectedly broad distribution of allostery hotspots throughout the protein structure. Using extensive molecular dynamics simulations (up to 50 μs) and free energy computations, we establish the molecular and energetic basis for the strong anticooperativity between the ligand and DNA binding sites. The computed free energy landscapes in different ligation states illustrate that allostery in TetR is well described by a conformational selection model, in which the apo state samples a broad set of conformations, and specific ones are selectively stabilized by either ligand or DNA binding. By examining a range of structural and dynamic properties of residues at both local and global scales, we observe that various analyses capture different subsets of experimentally identified hotspots, suggesting that these residues modulate allostery in distinct ways. These results motivate the development of a thermodynamic model that qualitatively explains the broad distribution of hotspot residues and their distinct features in molecular dynamics simulations. The multifaceted strategy that we establish here for hotspot evaluations and our insights into their mechanistic contributions are useful for modulating protein allostery in mechanistic and engineering studies.

Correlating the Local and Global Dynamics of an Enzyme in the Crowded Milieu

Enzymes are dynamic biological macromolecules, with their catalytic function(s) being largely influenced by the changes in local fluctuations of amino acid side chains as well as global structural modulations that the enzyme undergoes. Such local and global motions can be highly affected inside the crowded physiological interior of the cell. Here, we have addressed the role of dynamic structural flexibility in affecting the activation energy barrier of a flexible multidomain enzyme adenylate kinase (AK3L1, UniProtKB: Q9UIJ7). Activation energy profiles of both local (at three different sites along the polypeptide backbone) and global dynamics of the enzyme have been monitored using solvation studies on the subnanosecond time scale and tryptophan quenching studies over the temperature range of 278-323 K, respectively, under crowded conditions (Ficoll 70, Dextran 40, Dextran 70, and PEG 8). This study not only provides the site-specific mapping of dynamics but reveals that the activation energies associated with these local motions undergo a significant decrease in the presence of macromolecular crowders, providing new insights into how crowding affects internal protein dynamics. The crowded scenario also aids in enhancing the coupling between the local and global motions of the enzyme. Moreover, select portions/regions of the enzyme when taken together can well mirror the overall dynamics of the biomolecule, showing possible energy hotspots along the polypeptide backbone.

SenseNet, a tool for analysis of protein structure networks obtained from molecular dynamics simulations

Computational methods play a key role for investigating allosteric mechanisms in proteins, with the potential of generating valuable insights for innovative drug design. Here we present the SenseNet (“Structure ENSEmble NETworks”) framework for analysis of protein structure networks, which differs from established network models by focusing on interaction timelines obtained by molecular dynamics simulations. This approach is evaluated by predicting allosteric residues reported by NMR experiments in the PDZ2 domain of hPTP1e, a reference system for which previous computational predictions have shown considerable variance. We applied two models based on the mutual information between interaction timelines to estimate the conformational influence of each residue on its local environment. In terms of accuracy our prediction model is comparable to the top performing model published for this system, but by contrast benefits from its independence from NMR structures. Our results are complementary to experimental data and the consensus of previous predictions, demonstrating the potential of our new analysis tool SenseNet. Biochemical interpretation of our model suggests that allosteric residues in the PDZ2 domain form two distinct clusters of contiguous sidechain surfaces. SenseNet is provided as a plugin for the network analysis software Cytoscape, allowing for ease of future application and contributing to a system of compatible tools bridging the fields of system and structural biology.

A thermodynamic atlas of proteomes reveals energetic innovation across the tree of life

Protein stability is a fundamental molecular property enabling organisms to adapt to their biological niches. How this is facilitated and whether there are kingdom specific or more general universal strategies is not known. A principal obstacle to addressing this issue is that the vast majority of proteins lack annotation, specifically thermodynamic annotation, beyond the amino acid and chromosome information derived from genome sequencing. To address this gap and facilitate future investigation into large-scale patterns of protein stability and dynamics within and between organisms, we applied a unique ensemble-based thermodynamic characterization of protein folds to a substantial portion of extant sequenced genomes. Using this approach, we compiled a database resource focused on the position-specific variation in protein stability. Interrogation of the database reveals; 1) domains of life exhibit distinguishing thermodynamic features, with eukaryotes particularly different from both archaea and bacteria, 2) the optimal growth temperature of an organism is proportional to the average apolar enthalpy of its proteome, 3) intrinsic disorder content is also proportional to the apolar enthalpy (but unexpectedly not the predicted stability at 25 °C), and 4) secondary structure and global stability information of individual proteins is extractable. We hypothesize that wider access to residue-specific thermodynamic information of proteomes will result in deeper understanding of mechanisms driving functional adaptation and protein evolution. Our database is free for download at https://afc-science.github.io/thermo-env-atlas/.

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.

Conformational equilibria in allosteric control of Hsp70 chaperones

Heat-shock proteins of 70 kDa (Hsp70s) are vital for all life and are notably important in protein folding. Hsp70s use ATP binding and hydrolysis at a nucleotide-binding domain (NBD) to control the binding and release of client polypeptides at a substrate-binding domain (SBD); however, the mechanistic basis for this allostery has been elusive. Here, we first characterize biochemical properties of selected domain-interface mutants in bacterial Hsp70 DnaK. We then develop a theoretical model for allosteric equilibria among Hsp70 conformational states to explain the observations: a restraining state, Hsp70_R-ATP, restricts ATP hydrolysis and binds peptides poorly, whereas a stimulating state, Hsp70_S-ATP, hydrolyzes ATP rapidly and has high intrinsic substrate affinity but rapid binding kinetics. We support this model for allosteric regulation with DnaK structures obtained in the postulated stimulating state S with biochemical tests of the S-state interface and with improved peptide-binding-site definition in an R-state structure.

Minimizing Pervasive Artifacts in 4D Covariance Maps for Protein Side Chain NMR Assignments

Nuclear magnetic resonance (NMR) is a mainstay of biophysical studies that provides atomic level readouts to formulate molecular mechanisms. Side chains are particularly important to derive mechanisms involving proteins as they carry functional groups, but NMR studies of side chains are often limited by challenges in assigning their signals. Here, we designed a novel computational method that combines spectral derivatives and matrix square-rooting to produce reliable 4D covariance maps from routinely acquired 3D spectra and facilitates side chain resonance assignments. Thus, we generate two 4D maps from 3D-HcccoNH and 3D-HCcH-TOCSY spectra that each help overcome signal overlap or sensitivity losses. These 4D maps feature HC-HSQCs of individual side chains that can be paired to assigned backbone amide resonances of individual aliphatic signals, and both are obtained from a single modified covariance calculation. Further, we present 4D maps produced using conventional triple resonance experiments to easily assign asparagine side chain amide resonances. The 4D covariance maps encapsulate the lengthy manual pattern recognition used in traditional assignment methods and distill the information as correlations that can be easily visualized. We showcase the utility of the 4D covariance maps with a 10 kDa peptidyl carrier protein and a 52 kDa cyclization domain from a nonribosomal peptide synthetase.

Structural basis of the pleiotropic and specific phenotypic consequences of missense mutations in the multifunctional NAD(P)H:quinone oxidoreductase 1 and their pharmacological rescue

The multifunctional nature of human flavoproteins is critically linked to their ability to populate multiple conformational states. Ligand binding, post-translational modifications and disease-associated mutations can reshape this functional landscape, although the structure-function relationships of these effects are not well understood. Herein, we characterized the structural and functional consequences of two mutations (the cancer-associated P187S and the phosphomimetic S82D) on different ligation states which are relevant to flavin binding, intracellular stability and catalysis of the disease-associated NQO1 flavoprotein. We found that these mutations affected the stability locally and their effects propagated differently through the protein structure depending both on the nature of the mutation and the ligand bound, showing directional preference from the mutated site and leading to specific phenotypic manifestations in different functional traits (FAD binding, catalysis and inhibition, intracellular stability and pharmacological response to ligands). Our study thus supports that pleitropic effects of disease-causing mutations and phosphorylation events on human flavoproteins may be caused by long-range structural propagation of stability effects to different functional sites that depend on the ligation-state and site-specific perturbations. Our approach can be of general application to investigate these pleiotropic effects at the flavoproteome scale in the absence of high-resolution structural models.

Biochemical, structural and dynamical studies reveal strong differences in the thermal-dependent allosteric behavior of two extremophilic lactate dehydrogenases

In this work, we combined biochemical and structural investigations with molecular dynamics (MD) simulations to analyze the very different thermal-dependent allosteric behavior of two lactate dehydrogenases (LDH) from thermophilic bacteria. We found that the enzyme from Petrotoga mobilis (P. mob) necessitates an absolute requirement of the allosteric effector (fructose 1, 6-bisphosphate) to ensure functionality. In contrast, even without allosteric effector, the LDH from Thermus thermophilus (T. the) is functional when the temperature is raised. We report the crystal structure of P. mob LDH in the Apo state solved at 1.9 Å resolution. We used this structure and the one from T. the, obtained previously, as a starting point for MD simulations at various temperatures. We found clear differences between the thermal dynamics, which accounts for the behavior of the two enzymes. Our work demonstrates that, within an allosteric enzyme, some areas act as local gatekeepers of signal transmission, allowing the enzyme to populate either the T-inactive or the R-active states with different degrees of stringency.

Moving beyond static snapshots: Protein dynamics and the Protein Data Bank

Proteins are the molecular machines of living systems. Their dynamics are an intrinsic part of their evolutionary selection in carrying out their biological functions. Although the dynamics are more difficult to observe than a static, average structure, we are beginning to observe these dynamics and form sound mechanistic connections between structure, dynamics, and function. This progress is highlighted in case studies from myoglobin and adenylate kinase to the ribosome and molecular motors where these molecules are being probed with a multitude of techniques across many timescales. New approaches to time-resolved crystallography are allowing simple “movies” to be taken of proteins in action, and new methods of mapping the variations in cryo-electron microscopy are emerging to reveal a more complete description of life’s machines. The results of these new methods are aided in their dissemination by continual improvements in curation and distribution by the Protein Data Bank and their partners around the world.

Integrating Rigidity Analysis into the Exploration of Protein Conformational Pathways Using RRT* and MC

To understand how proteins function on a cellular level, it is of paramount importance to understand their structures and dynamics, including the conformational changes they undergo to carry out their function. For the aforementioned reasons, the study of large conformational changes in proteins has been an interest to researchers for years. However, since some proteins experience rapid and transient conformational changes, it is hard to experimentally capture the intermediate structures. Additionally, computational brute force methods are computationally intractable, which makes it impossible to find these pathways which require a search in a high-dimensional, complex space. In our previous work, we implemented a hybrid algorithm that combines Monte-Carlo (MC) sampling and RRT*, a version of the Rapidly Exploring Random Trees (RRT) robotics-based method, to make the conformational exploration more accurate and efficient, and produce smooth conformational pathways. In this work, we integrated the rigidity analysis of proteins into our algorithm to guide the search to explore flexible regions. We demonstrate that rigidity analysis dramatically reduces the run time and accelerates convergence.

Reductionism in the study of enzyme adaptation

One of the principal goals of comparative biology is the elucidation of mechanisms by which organisms adapt to different environments. The study of enzyme structure, function, and stability has contributed significantly to this effort, by revealing adaptation at a molecular level. Comparative biochemistry, including enzymology, necessarily pursues a reductionist approach in describing the function and structure of biomolecules, allowing more straightforward study of molecular systems by removing much of the complexity of their biological milieu. Although this reductionism has allowed a remarkable series of discoveries linking chemical processes to metabolism and to whole-organism function in the context of the environment, it also has the potential to mislead when careful consideration is not made of the simplifying assumptions inherent to such research. In this review, a brief history of the growth of enzymology, its reliance on a reductionist philosophy, and its contributions to our understanding of biological systems is given. Examples then are provided of research techniques, based on a reductionist approach, that have advanced our knowledge about enzyme adaptation to environmental stresses, including stability assays, enzyme kinetics, and the impact of solute composition on enzyme function. In each case, the benefits of the reductionist nature of the approach is emphasized, notable advances are described, but potential drawbacks due to inherent oversimplification of the study system are also identified.

Higher binding affinity of furin for SARS-CoV-2 spike (S) protein D614G mutant could be associated with higher SARS-CoV-2 infectivity

Objective

The coronavirus disease 2019 (COVID-19) pandemic has caused an exponential rise in death rates and hospitalizations. The aim of this study was to characterize the D614G substitution in the severe acute respiratory syndome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S protein), which may affect viral infectivity.

Methods

The effect of D614G substitution on the structure and thermodynamic stability of the S protein was analyzed with use of DynaMut and SCooP. HDOCK and PRODIGY were used to model furin protease binding to the S protein RRAR cleavage site and calculate binding affinities. Molecular dynamics simulations were used to predict the S protein apo structure, the S protein–furin complex structure, and the free binding energy of the complex.

Results

The D614G substitution in the G clade of SARS-CoV-2 strains introduced structural mobility and decreased the thermal stability of the S protein (ΔΔG = −0.086 kcal mol⁻¹). The substitution resulted in stronger binding affinity (K_d = 1.6 × 10⁻⁸) for furin, which may enhance S protein cleavage. The results were corroborated by molecular dynamics simulations demonstrating higher binding energy of furin and the S protein D614G mutant (−61.9 kcal mol⁻¹ compared with −56.78 kcal mol⁻¹ for wild-type S protein).

Conclusions

The D614G substitution in the G clade induced flexibility of the S protein, resulting in increased furin binding, which may enhance S protein cleavage and infiltration of host cells. Therefore, the SARS-CoV-2 D614G substitution may result in a more virulent strain.

Structural analysis of ACE2 variant N720D demonstrates a higher binding affinity to TMPRSS2

Aims

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel member of the betacoronaviruses family affecting the lower respiratory tract mainly through binding to angiotensin converting enzyme 2 (ACE2) via its S-protein. Genetic analysis of (ACE2) gene revealed several variants that have been suggested to regulate the interaction with S protein. This study investigates the N720D variant, positioned in the collectrin-like domain (CLD) at proximity to type II transmembrane serine protease (TMPRSS2) cleavage site.

Main methods

The effect of N720D variant on ACE2 structure and thermodynamic stability was studied by DynaMut. HDOCK was utilised to model TMPRSS2 protease binding to ACE2 WT and D720 variant cleavage site. PRODIGY was used to calculate binding affinities and MD simulation tools calculated the at 100 ns for ACE2 apo structure and the ACE2-TMPRSS2 complex.

Key findings

The N720D variant is a more dynamic structure with a free energy change (ΔΔG): −0.470 kcal/mol. As such, introducing a tighter binding affinity of K_d = 3.2 × 10⁻¹⁰ M between TMPRSS2 and N720D variant. RMSD, RMSF calculations showed the N720D variant is less stable, however, RMSF values of the D720-TMPRSS2 complex reflected a slower dynamic motion.

Significance

The hotspot N720D variant in the CLD of ACE2 affected the stability and flexibility of ACE2 by increasing the level of motion in the loop region, resulting in a more favourable site for TMPRSS2 binding and cleavage. Consequently, this would facilitate S-protein binding and can potentially increase viral entry highlighting the importance of variants affecting the ACE2-TMPRSS2 complex.

An allosteric pathway explains beneficial fitness in yeast for long-range mutations in an essential TIM barrel enzyme

Protein evolution proceeds by a complex response of organismal fitness to mutations that can simultaneously affect protein stability, structure, and enzymatic activity. To probe the relationship between genotype and phenotype, we chose a fundamental paradigm for protein evolution, folding, and design, the (βα)₈ TIM barrel fold. Here, we demonstrate the role of long-range allosteric interactions in the adaptation of an essential hyperthermophilic TIM barrel enzyme to mesophilic conditions in a yeast host. Beneficial fitness effects observed with single and double mutations of the canonical βα-hairpin clamps and the α-helical shell distal to the active site revealed an underlying energy network between opposite faces of the cylindrical β-barrel. We experimentally determined the fitness of multiple mutants in the energetic phase plane, contrasting the energy barrier of the chemical reaction and the folding free energy of the protein. For the system studied, the reaction energy barrier was the primary determinant of organism fitness. Our observations of long-range epistatic interactions uncovered an allosteric pathway in an ancient and ubiquitous enzyme that may provide a novel way of designing proteins with a desired activity and stability profile.

Allosteric Modulation of Neurotransmitter Transporters as a Therapeutic Strategy

Neurotransmitter transporters (NTTs) are involved in the fine-tuning of brain neurotransmitter homeostasis. As such, they are implicated in a plethora of complex behaviors, including reward, movement, and cognition. During recent decades, compounds that modulate NTT functions have been developed. Some of them are in clinical use for the management of different neuropsychiatric conditions. The majority of these compounds have been found to selectively interact with the orthosteric site of NTTs. Recently, diverse allosteric sites have been described in a number of NTTs, modulating their function. A more complex NTT pharmacology may be useful in the development of novel therapeutics. Here, we summarize current knowledge on such modulatory allosteric sites, with specific focus on their pharmacological and therapeutic potential.

Molecular docking investigation of the amantadine binding to the enzymes upregulated or downregulated in Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disease. Levodopa in combination with amantadine has a demonstrated efficacy in motility impairment. An extensive investigation of some enzymes described to be upregulated or downregulated in PD was made - adenylate kinase (AK), adenine phosphoribosyltransferase (APRT), ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1), nucleoside-diphosphate kinase 3 (NDK3), purine nucleoside phosphorylase 1 (PNP1), and ecto-5'-nucleotidase (NT5E). Also, creatine kinase (CK) was included in the study because it is one of the main enzymes involved in the regulation of the nucleotide ratio in energy metabolism. To date, there is no proven link between amantadine treatment of PD and these enzymes. Because there are many AKs isoforms modified in PD, the AK was the first investigated. The molecular docking experiments allow the analysis of the selective binding of amantadine - unionized (with -NH₂ group) and ionized form (with -NH₃ ⁺ group) - to the AKs' isoforms implicated in PD. Using available X-ray 3D structures of human AKs in closed-conformation, it was demonstrated that there are notable differences between the interactions of the two forms of amantadine for the zebrafish AK1 (5XZ2), human AK2 (2C9Y), human AK5 (2BWJ), and AK from B.stearothermophilus. The cytosolic human AK1 and human AK2 mostly interact with ionized amantadine by AMP binding residues. The human AK5 interaction with ionized amantadine does not involve the residues from the catalytic site. Among other enzymes tested in the present study, APRT revealed the best results in respect of binding amantadine ionized form. The results offer a new perspective for further investigation of the connections between amantadine treatment of PD and some enzymes involved in purine metabolism.

A Two-Ended Data-Driven Accelerated Sampling Method for Exploring the Transition Pathways between Two Known States of Protein

Conformational transitions of protein between different states are often associated with their biological functions. These dynamic processes, however, are usually not easy to be well characterized by experimental measurements, mainly because of inadequate temporal and spatial resolution. Meantime, sampling of configuration space with molecular dynamics (MD) simulations is still a challenge. Here we proposed a robust two-ended data-driven accelerated (teDA2) conformational sampling method, which drives the structural change in an adaptively updated feature space without introducing a bias potential. teDA2 was applied to explore adenylate kinase (ADK), a model with well characterized "open" and "closed" states. A single conformational transition event of ADK could be achieved within only a few or tens of nanoseconds sampled with teDA2. By analyzing hundreds of transition events, we reproduced different mechanisms and the associated pathways for domain motion of ADK reported in the literature. The multiroute characteristic of ADK was confirmed by the fact that some metastable states identified with teDA2 resemble available crystal structures determined at different conditions. This feature was further validated with Markov state modeling with independent MD simulations. Therefore, our work provides strong evidence for the conformational plasticity of protein, which is mainly due to the inherent degree of flexibility. As a reliable and efficient enhanced sampling protocol, teDA2 could be used to study the dynamics between functional states of various biomolecular machines.

Conformational Flexibility Drives Cold Adaptation in Pseudoalteromonas haloplanktis TAC125 Globins

Significance: Temperature is one of the most important drivers in shaping protein adaptations. Many biochemical and physiological processes are influenced by temperature. Proteins and enzymes from organisms living at low temperature are less stable in comparison to high-temperature adapted proteins. The lower stability is generally due to greater conformational flexibility. Recent Advances: Adaptive changes in the structure of cold-adapted proteins may occur at subunit interfaces, distant from the active site, thus producing energy changes associated with conformational transitions transmitted to the active site by allosteric modulation, valid also for monomeric proteins in which tertiary structural changes may play an essential role. Critical Issues: Despite efforts, the current experimental and computational methods still fail to produce general principles on protein evolution, since many changes are protein and species dependent. Environmental constraints or other biological cellular signals may override the ancestral information included in the structure of the protein, thus introducing inaccuracy in estimates and predictions on the evolutionary adaptations of proteins in response to cold adaptation. Future Directions: In this review, we describe the studies and approaches used to investigate stability and flexibility in the cold-adapted globins of the Antarctic marine bacterium Pseudoalteromonas haloplanktis TAC125. In fact, future research directions will be prescient on more detailed investigation of cold-adapted proteins and the role of fluctuations between different conformational states.

Theory of Allosteric Regulation in Hsp70 Molecular Chaperones

Heat-shock proteins of 70 kDa (Hsp70s) are ubiquitous molecular chaperones that function in protein folding as well as other vital cellular processes. They bind and hydrolyze ATP in a nucleotide-binding domain (NBD) to control the binding and release of client polypeptides in a substrate-binding domain (SBD). However, the molecular mechanism for this allosteric action has remained unclear. Here, we develop and experimentally quantify a theoretical model for Hsp70 allostery based on equilibria among Hsp70 conformational states. We postulate that, when bound to ATP, Hsp70 is in equilibrium between a restraining state (R) that restricts ATP hydrolysis and binds peptides poorly, if at all, and a stimulating state (S) that hydrolyzes ATP relatively rapidly and has high intrinsic substrate affinity but rapid binding kinetics; after the hydrolysis to ADP, NBD and SBD disengage into an uncoupled state (U) that binds peptide substrates tightly, but now with slow kinetics of exchange.

Protein tolerance to random circular permutation correlates with thermostability and local energetics of residue-residue contacts

Adenylate kinase (AK) orthologs with a range of thermostabilities were subjected to random circular permutation, and deep mutational scanning was used to evaluate where new protein termini were nondisruptive to activity. The fraction of circularly permuted variants that retained function in each library correlated with AK thermostability. In addition, analysis of the positional tolerance to new termini, which increase local conformational flexibility, showed that bonds were either functionally sensitive to cleavage across all homologs, differentially sensitive, or uniformly tolerant. The mobile AMP-binding domain, which displays the highest calculated contact energies, presented the greatest tolerance to new termini across all AKs. In contrast, retention of function in the lid and core domains was more dependent upon AK melting temperature. These results show that family permutation profiling identifies primary structure that has been selected by evolution for dynamics that are critical to activity within an enzyme family. These findings also illustrate how deep mutational scanning can be applied to protein homologs in parallel to differentiate how topology, stability, and local energetics govern mutational tolerance.

Circular permutation profiling by deep sequencing libraries created using transposon mutagenesis

Deep mutational scanning has been used to create high-resolution DNA sequence maps that illustrate the functional consequences of large numbers of point mutations. However, this approach has not yet been applied to libraries of genes created by random circular permutation, an engineering strategy that is used to create open reading frames that express proteins with altered contact order. We describe a new method, termed circular permutation profiling with DNA sequencing (CPP-seq), which combines a one-step transposon mutagenesis protocol for creating libraries with a functional selection, deep sequencing and computational analysis to obtain unbiased insight into a protein's tolerance to circular permutation. Application of this method to an adenylate kinase revealed that CPP-seq creates two types of vectors encoding each circularly permuted gene, which differ in their ability to express proteins. Functional selection of this library revealed that >65% of the sampled vectors that express proteins are enriched relative to those that cannot translate proteins. Mapping enriched sequences onto structure revealed that the mobile AMP binding and rigid core domains display greater tolerance to backbone fragmentation than the mobile lid domain, illustrating how CPP-seq can be used to relate a protein's biophysical characteristics to the retention of activity upon permutation.

Nucleation of an Activating Conformational Change by a Cation-π Interaction

As a key molecule in biology, adenosine triphosphate (ATP) has numerous crucial functions in, for instance, energetics, post-translational modifications, nucleotide biosynthesis, and cofactor metabolism. Here, we have discovered an intricate interplay between the enzyme adenylate kinase and its substrate ATP. The side chain of an arginine residue was found to be an efficient sensor of the aromatic moiety of ATP through the formation of a strong cation-π interaction. In addition to recognition, the interaction was found to have dual functionality. First, it nucleates the activating conformational transition of the ATP binding domain and also affects the specificity in the distant AMP binding domain. In light of the functional consequences resulting from the cation-π interaction, it is possible that the mode of ATP recognition may be a useful tool in enzyme design.

Dynamics of proteins in solution

The dynamics of proteins in solution includes a variety of processes, such as backbone and side-chain fluctuations, interdomain motions, as well as global rotational and translational (i.e. center of mass) diffusion. Since protein dynamics is related to protein function and essential transport processes, a detailed mechanistic understanding and monitoring of protein dynamics in solution is highly desirable. The hierarchical character of protein dynamics requires experimental tools addressing a broad range of time- and length scales. We discuss how different techniques contribute to a comprehensive picture of protein dynamics, and focus in particular on results from neutron spectroscopy. We outline the underlying principles and review available instrumentation as well as related analysis frameworks.

Structural and mutational analyses of psychrophilic and mesophilic adenylate kinases highlight the role of hydrophobic interactions in protein thermal stability

Protein thermal stability is an important field since thermally stable proteins are desirable in many academic and industrial settings. Information on protein thermal stabilization can be obtained by comparing homologous proteins from organisms living at distinct temperatures. Here, we report structural and mutational analyses of adenylate kinases (AKs) from psychrophilic Bacillus globisporus (AKp) and mesophilic Bacillus subtilis (AKm). Sequence and structural comparison showed suboptimal hydrophobic packing around Thr26 in the CORE domain of AKp, which was replaced with an Ile residue in AKm. Mutations that improved hydrophobicity of the Thr residue increased the thermal stability of the psychrophilic AKp, and the largest stabilization was observed for a Thr-to-Ile substitution. Furthermore, a reverse Ile-to-Thr mutation in the mesophilic AKm significantly decreased thermal stability. We determined the crystal structures of mutant AKs to confirm the impact of the residue substitutions on the overall stability. Taken together, our results provide a structural basis for the stability difference between psychrophilic and mesophilic AK homologues and highlight the role of hydrophobic interactions in protein thermal stability.

"Infostery" analysis of short molecular dynamics simulations identifies highly sensitive residues and predicts deleterious mutations

Characterizing a protein mutational landscape is a very challenging problem in Biology. Many disease-associated mutations do not seem to produce any effect on the global shape nor motions of the protein. Here, we use relatively short all-atom biomolecular simulations to predict mutational outcomes and we quantitatively assess the predictions on several hundreds of mutants. We perform simulations of the wild type and 175 mutants of PSD95’s third PDZ domain in complex with its cognate ligand. By recording residue displacements correlations and interactions, we identify “communication pathways” and quantify them to predict the severity of the mutations. Moreover, we show that by exploiting simulations of the wild type, one can detect 80% of the positions highly sensitive to mutations with a precision of 89%. Importantly, our analysis describes the role of these positions in the inter-residue communication and dynamical architecture of the complex. We assess our approach on three different systems using data from deep mutational scanning experiments and high-throughput exome sequencing. We refer to our analysis as “infostery”, from “info” - information - and “steric” - arrangement of residues in space. We provide a fully automated tool, COMMA2 (www.lcqb.upmc.fr/COMMA2), that can be used to guide medicinal research by selecting important positions/mutations.

Chromatographic separation strategies for precision mass spectrometry to study protein-protein interactions and protein phosphorylation

Investigating protein-protein interactions and protein phosphorylation can be of great significance when studying biological processes and human diseases at the molecular level. However, sample complexity, presence of low abundance proteins, and dynamic nature of the proteins often impede in achieving sufficient analytical depth in proteomics research. In this regard, chromatographic separation methodologies have played a vital role in the identification and quantification of proteins in complex sample mixtures. The combination of peptide and protein fractionation techniques with advanced high-performance mass spectrometry has allowed the researchers to successfully study the protein-protein interactions and protein phosphorylation. Several new fractionation strategies for large scale analysis of proteins and peptides have been developed to study protein-protein interactions and protein phosphorylation. These emerging chromatography methodologies have enabled the identification of several hundred protein complexes and even thousands of phosphorylation sites in a single study. In this review, we focus on current workflow strategies and chromatographic tools, highlighting their advantages and disadvantages, and examining their associated challenges and future potential.

How the Ligand-Induced Reorganization of Protein Internal Energies Is Coupled to Conformational Events

Here, we introduce a novel computational method to identify the protein substructures most likely to support the functionally oriented structural deformations that occur upon ligand-binding. To this aim, we study the modulation of protein energetics along the trajectory of a molecular dynamics simulation of different proteins in the presence and in the absence of their respective ligands, namely, human FGF, human second PDZ from human PTP1E/PTPL1, and the N terminal domain of human Hsp90. The method is based on the idea that a subset of protein residues (hotspots) may initiate the global response via the disassembly and reassembly of interactions, which is reflected in the modulation of the overall protein energetics. To identify structural hotspots and dynamic states linked to the onset of functionally relevant conformational transitions, we define an energy profile to monitor the protein energetics, based on a previously introduced approach that highlights the essential nonbonded couplings among all residues. The energy profiles are calculated along the trajectory to yield a time-dependent evolution, and their relative population in the presence and absence of the ligand is evaluated by means of a clustering procedure. It is found that interconversion between clusters, as well as their population and the density of specific energy profiles in the vicinity of structural transitions, provides specific information on the impact of the ligand in driving the protein conformational response. This analysis also highlights the hotspot residues that are most responsive to the presence of the ligand. Importantly, identified hotspots are in agreement with experimental evidence in the three considered systems. We propose that this approach can be generally used in the prediction of "allosteric hotspots" and ligand-induced conformational responses, as well as to select conformations more likely to support functional transitions (e.g., in the framework of adaptive sampling approaches).

Predicting allostery and microbial drug resistance with molecular simulations

Beta-lactamase enzymes mediate the most common forms of gram-negative antibiotic resistance affecting clinical treatment. They also constitute an excellent model system for the difficult problem of understanding how allosteric mutations can augment catalytic activity of already-competent enzymes. Multiple allosteric mutations have been identified that alter catalytic activity or drug-resistance spectrum in class A beta lactamases, but predicting these in advance continues to be challenging. Here, we review computational techniques based on structure and/or molecular simulation to predict such mutations. Structure-based techniques have been particularly helpful in developing graph algorithms for analyzing critical residues in beta-lactamase function, while classical molecular simulation has recently shown the ability to prospectively predict allosteric mutations increasing beta-lactamase activity and drug resistance. These will ultimately achieve the greatest power when combined with simulation methods that model reactive chemistry to calculate activation free energies directly.

Conservation of coactivator engagement mechanism enables small-molecule allosteric modulators

Transcriptional coactivators are a molecular recognition marvel because a single domain within these proteins, the activator binding domain or ABD, interacts with multiple compositionally diverse transcriptional activators. Also remarkable is the structural diversity among ABDs, which range from conformationally dynamic helical motifs to those with a stable core such as a β-barrel. A significant objective is to define conserved properties of ABDs that allow them to interact with disparate activator sequences. The ABD of the coactivator Med25 (activator interaction domain or AcID) is unique in that it contains secondary structural elements that are on both ends of the spectrum: helices and loops that display significant conformational mobility and a seven-stranded β-barrel core that is structurally rigid. Using biophysical approaches, we build a mechanistic model of how AcID forms binary and ternary complexes with three distinct activators; despite its static core, Med25 forms short-lived, conformationally mobile, and structurally distinct complexes with each of the cognate partners. Further, ternary complex formation is facilitated by allosteric communication between binding surfaces on opposing faces of the β-barrel. The model emerging suggests that the conformational shifts and cooperative binding is mediated by a flexible substructure comprised of two dynamic helices and flanking loops, indicating a conserved mechanistic model of activator engagement across ABDs. Targeting a region of this substructure with a small-molecule covalent cochaperone modulates ternary complex formation. Our data support a general strategy for the identification of allosteric small-molecule modulators of ABDs, which are key targets for mechanistic studies as well as therapeutic applications.

Biophysical and functional perturbation analyses at cancer-associated P187 and K240 sites of the multifunctional NADP(H):quinone oxidoreductase 1

Once whole-genome sequencing has reached the clinical practice, a main challenge ahead is the high-throughput and accurate prediction of the pathogenicity of genetic variants. However, current prediction tools do not consider explicitly a well-known property of disease-causing mutations: their ability to affect multiple functional sites distant in the protein structure. Here we carried out an extensive biophysical characterization of fourteen mutant variants at two cancer-associated sites of the enzyme NQO1, a paradigm of multi-functional protein. We showed that the magnitude of destabilizing effects, their molecular origins (structural vs. dynamic) and their efficient propagation through the protein structure gradually led to functional perturbations at different sites. Modulation of these structural perturbations also led to switches between molecular phenotypes. Our work supports that experimental and computational perturbation analyses would improve our understanding of the molecular basis of many loss-of-function genetic diseases as well as our ability to accurately predict the pathogenicity of genetic variants in a high-throughput fashion.

Dynamic allostery can drive cold adaptation in enzymes

Adaptation of organisms to environmental niches is a hallmark of evolution. One prevalent example is that of thermal adaptation, wherein two descendants evolve at different temperature extremes^1,2. Underlying the physiological differences between such organisms are changes in enzymes catalyzing essential reactions³, with orthologues from each organism undergoing adaptive mutations that preserve similar catalytic rates at their respective physiological temperatures ^4,5. The sequence changes responsible for these adaptive differences, however, are often at surface exposed sites distant from the substrate binding site, leaving the active site of the enzyme structurally unperturbed^6,7. How such changes are allosterically propagated to the active site, to modulate activity, is not known. Here we show that entropy-tuning changes can be engineered into distal sites of Escherichia coli adenylate kinase (AK) to quantitatively assess the role of dynamics in determining affinity, turnover, and the role in driving adaptation. The results not only reveal a dynamics-based allosteric tuning mechanism, but also uncover a spatial separation of the control of key enzymatic parameters. Fluctuations in one mobile domain (i.e. the LID) control substrate affinity, while dynamic attenuation in the other (i.e. the AMPbd) affects rate-limiting conformational changes governing enzyme turnover. Dynamics-based regulation may thus represent an elegant, widespread, and previously unrealized evolutionary adaptation mechanism that fine-tunes biological function without altering the ground state structure. Furthermore, because rigid-body conformational changes in both domains were thought to be rate limiting for turnover^8,9, these adaptation studies reveal a new paradigm for understanding the relationship between dynamics and turnover in AK.

Molecular Docking Evaluation of (E)-5-arylidene-2-thioxothiazolidin-4-one Derivatives as Selective Bacterial Adenylate Kinase Inhibitors

Multi-drug resistant microorganism infections with emerging problems that require not only a prevention strategy, but also the development of new inhibitory compounds. Six previously synthesized 5-arylidene-2-thioxothiazolidin-4-one derivatives 1a–f, were screened for inhibitory activity on adenylate kinases of different origins by molecular docking. The compounds 1c and 1d were the most efficient inhibitors of bacterial and some archean adenylate kinases. Hydrogen bond interactions were observed with the residues belonging to the ATP binding site. Moreover human adenylate kinases are poor targets, suggesting that this selectivity offers promising prospectives for refining the structure of our compounds.

Multiple Pathways and Time Scales for Conformational Transitions in apo-Adenylate Kinase

The open/close transition in adenylate kinase (AK) is regarded as a representative example for large-scale conformational transition in proteins, yet its mechanism remains unclear despite numerous experimental and computational studies. Using extensive (∼50 μs) explicit solvent atomistic simulations and Markov state analysis, we shed new lights on the mechanism of this transition in the apo form of AK. The closed basin of apo AK features an open NMP domain while the LID domain closes and rotates toward it. Therefore, although the computed structural properties of the closed ensemble are consistent with previously reported FRET and PRE measurements, our simulations suggest that NMP closure is likely to follow AMP binding, in contrast to the previous interpretation of FRET and PRE data that the apo state was able to sample the fully closed conformation for "ligand selection". The closed state ensemble is found to be kinetically heterogeneous; multiple pathways and time scales are associated with the open/close transition, providing new clues to the disparate time scales observed in different experiments. Besides interdomain interactions, a novel mutual information analysis identifies specific intradomain interactions that correlate strongly to transition kinetics, supporting observations from previous chimera experiments. While our results underscore the role of internal domain properties in determining the kinetics of open/close transition in apo AK, no evidence is observed for any significant degree of local unfolding during the transition. These observations about AK have general implications to our view of conformational states, transition pathways, and time scales of conformational changes in proteins. The key features and time scales of observed transition pathways are robust and similar from simulations using two popular fixed charge force fields.