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

The scientific community needs to speak up loudly to support colleagues who are persecuted and imprisoned for political reasons.

Polyethylene terephthalate (PET) is the most common polyester plastic in the packaging industry, and a major source of environmental pollution due to its single use. Several enzymes, termed PET hydrolases (PETases), have been found to hydrolyze this polymer at different temperatures, with the enzyme from I. sakaiensis (IsPETase) having optimal catalytic activity at 40ºC. Crystal structures of IsPETase have revealed that the side chain of a conserved tryptophan residue within an active site loop (W185) shifts between 3 conformations to enable substrate binding and product release. This is facilitated by two residues unique to IsPETase, S214 and I218 (S/I). When these residues are inserted into other PETases in place of the otherwise strictly conserved His/Phe (H/F) residues found at their respective positions, they enhance activity and decrease Topt. Herein, we combine conventional molecular dynamics and well-tempered metadynamics simulations to investigate dynamic changes of the S/I and H/F variants of IsPETase, as well as three other mesophilic and thermophilic PETases, at their respective temperature and pH optima. Our simulations show that the S/I insertion both increases the flexibility of active site loop regions harboring key catalytic residues and the conserved Trp, as well as expanding the conformational plasticity of this Trp side chain, allowing the conformational transitions that allow for substrate binding and product release in IsPETase. The observed catalytic enhancement caused by this substitution in other PETases appears to be due to conformational selection, by capturing the conformational ensemble observed in IsPETase.

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

This academic thought piece provides an overview of the history of, and current trends in, publishing practices in the scientific fields known to the authors (chemical sciences, social sciences and humanities), as well as a discussion of how open access mandates such as Plan S from cOAlition S will affect these practices. It begins by summarizing the evolution of scientific publishing, in particular how it was shaped by the learned societies, and highlights how important quality assurance and scientific management mechanisms are being challenged by the recent introduction of ever more stringent open access mandates. The authors then discuss the various reactions of the researcher community to the introduction of Plan S, and elucidate a number of concerns: that it will push researchers towards a pay-to-publish system which will inevitably create new divisions between those who can afford to get their research published and those who cannot; that it will disrupt collaboration between researchers on the different sides of cOAlition S funding; and that it will have an impact on academic freedom of research and publishing. The authors analyse the dissemination of, and responses to, an open letter distributed and signed in reaction to the introduction of Plan S, before concluding with some thoughts on the potential for evolution of open access in scientific publishing.

A few suggestions and advice to increase the success chances of your grant application. [Image: see text]

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

Manipulating Conformational Dynamics To Repurpose Ancient Proteins for Modern Catalytic Functions

GTP hydrolysis is central to biology, being involved in regulating a wide range of cellular processes. However, the mechanisms by which GTPases hydrolyze this critical reaction remain controversial, with multiple mechanistic possibilities having been proposed based on analysis of experimental and computational data. In this mini-review, we discuss advances in our understanding of biological GTP hydrolysis based on recent computational studies and argue in favor of solvent-assisted hydrolysis as a conserved mechanism among GTPases. A concrete understanding of the fundamental mechanisms by which these enzymes facilitate GTP hydrolysis will have significant impact both for drug discovery efforts and for unraveling the role of oncogenic mutations.

The ubiquity of phospho-ligands suggests that phosphate binding emerged at the earliest stage of protein evolution. To evaluate this hypothesis and unravel its details, we identified all phosphate-binding protein lineages in the Evolutionary Classification of Protein Domains database. We found at least 250 independent evolutionary lineages that bind small molecule cofactors and metabolites with phosphate moieties. For many lineages, phosphate binding emerged later as a niche functionality, but for the oldest protein lineages, phosphate binding was the founding function. Across some 4 billion y of protein evolution, side-chain binding, in which the phosphate moiety does not interact with the backbone at all, emerged most frequently. However, in the oldest lineages, and most characteristically in αβα sandwich enzyme domains, N-helix binding sites dominate, where the phosphate moiety sits atop the N terminus of an α-helix. This discrepancy is explained by the observation that N-helix binding is uniquely realized by short, contiguous sequences with reduced amino acid diversity, foremost Gly, Ser, and Thr. The latter two amino acids preferentially interact with both the backbone amide and the side-chain hydroxyl (bidentate interaction) to promote binding by short sequences. We conclude that the first αβα sandwich domains emerged from shorter and simpler polypeptides that bound phospho-ligands via N-helix sites.

Enzymes are conformationally dynamic, and their dynamical properties play an important role in regulating their specificity and evolvability. In this context, substantial attention has been paid to the role of ligand-gated conformational changes in enzyme catalysis; however, such studies have focused on tremendously proficient enzymes such as triosephosphate isomerase and orotidine 5'-monophosphate decarboxylase, where the rapid (μs timescale) motion of a single loop dominates the transition between catalytically inactive and active conformations. In contrast, the (βα)

Enzymes are conformationally dynamic, and their dynamical properties play an important role in regulating their specificity and evolvability. In this context, substantial attention has been paid to the role of ligand-gated conformational changes in enzyme catalysis; however, such studies have focused on tremendously proficient enzymes such as triosephosphate isomerase and orotidine 5’-monophosphate decarboxylase, where the rapid (μs timescale) motion of a single loop dominates the transition between catalytically inactive and active conformations. In contrast, the (βα)8-barrels of tryptophan and histidine biosynthesis, such as the specialist isomerase enzymes HisA and TrpF, and the bifunctional isomerase PriA, are decorated by multiple long loops that undergo conformational transitions on the ms (or slower) timescale. Studying the interdependent motions of multiple slow loops, and their role in catalysis, poses a significant computational challenge. This work combines conventional and enhanced molecular dynamics simulations with empirical valence bond simulations to provide rich detail of the conformational behavior of the catalytic loops in HisA, PriA and TrpF, and the role of their plasticity in facilitating bifunctionality in PriA and evolved HisA variants. In addition, we demonstrate that, similar to other enzymes activated by ligand-gated conformational changes, loops 3 and 4 of HisA and PriA act as gripper loops, facilitating the isomerization of the large bulky substrate ProFAR, albeit now on much slower timescales. This hints at convergent evolution on these different (βα)8-barrel scaffolds. Finally, our work highlights the potential of engineering loop dynamics as a powerful tool to artificially manipulate the diverse catalytic repertoire of TIM-barrel proteins.

The cooperative interplay between the functional devices of a preorganized active site is fundamental to enzyme catalysis. An in-depth understanding of this phenomenon is central to elucidating the remarkable efficiency of natural enzymes and provides an essential benchmark for enzyme design and engineering. Here, we study the functional interconnectedness of the catalytic nucleophile (His18) in an acid phosphatase by analyzing the consequences of its replacement with aspartate. We present crystallographic, biochemical, and computational evidence for a conserved mechanistic pathway via a phospho-enzyme intermediate on Asp18. Linear free-energy relationships for phosphoryl transfer from phosphomonoester substrates to His18/Asp18 provide evidence for the cooperative interplay between the nucleophilic and general-acid catalytic groups in the wild-type enzyme, and its substantial loss in the H18D variant. As an isolated factor of phosphatase efficiency, the advantage of a histidine compared to an aspartate nucleophile is similar to 10(4)-fold. Cooperativity with the catalytic acid adds >= 10(2)-fold to that advantage. Empirical valence bond simulations of phosphoryl transfer from glucose 1-phosphate to His and Asp in the enzyme explain the loss of activity of the Asp18 enzyme through a combination of impaired substrate positioning in the Michaelis complex, as well as a shift from early to late protonation of the leaving group in the H18D variant. The evidence presented furthermore suggests that the cooperative nature of catalysis distinguishes the enzymatic reaction from the corresponding reaction in solution and is enabled by the electrostatic preorganization of the active site. Our results reveal sophisticated discrimination in multifunctional catalysis of a highly proficient phosphatase active site.

Cooperative interplay between the functional devices of a preorganized active site is fundamental to enzyme catalysis. A deepened understanding of this phenomenon is central to elucidating the remarkable efficiency of natural enzymes, and provides an essential benchmark for enzyme design and engineering. Here, we study the functional interconnectedness of the catalytic nucleophile (His18) in an acid phosphatase by analyzing the consequences of its replacement with aspartate. We present crystallographic, biochemical and computational evidence for a conserved mechanistic pathway via a phospho-enzyme intermediate on Asp18. Linear free-energy relationships for phosphoryl transfer from phosphomonoester substrates to His18/Asp18 provide evidence for cooperative interplay between the nucleophilic and general-acid catalytic groups in the wildtype enzyme, and its substantial loss in the H18D variant. As an isolated factor of phosphatase efficiency, the advantage of a histidine compared to an aspartate nucleophile is around 10^4-fold. Cooperativity with the catalytic acid adds ≥10^2-fold to that advantage. Empirical valence bond simulations of phosphoryl transfer from glucose 1-phosphate to His and Asp in the enzyme explain the loss of activity of the Asp18 enzyme through a combination of impaired substrate positioning in the Michaelis complex, as well as a shift from early to late protonation of the leaving group in the H18D variant. The evidence presented furthermore suggests that the cooperative nature of catalysis distinguishes the enzymatic reaction from the corresponding reaction in solution and is enabled by the electrostatic preorganization of the active site. Our results reveal sophisticated discrimination in multifunctional catalysis of a highly proficient phosphatase active site.

Protein tyrosine phosphatases (PTPs) possess a mobile, conserved catalytic loop, the WPD-loop, which brings an aspartic acid into the active site where it acts as an acid/base catalyst. Prior experimental and computational studies, focused on the human enzyme PTP1B and the PTP from Yersinia pestis, YopH, suggested that loop conformational dynamics are important in regulating both catalysis and evolvability. Also, work on Chimeras of YopH bearing parts of the WPD-loop sequence from PTP1B demonstrated unusual structural perturbations and reduced activity. In the present study, we have generated a chimeric protein in which the WPD-loop of YopH is transposed into PTP1B, and eight chimeras that systematically restored the loop sequence back to native PTP1B. Of these, four chimeras were soluble and were subjected to detailed biochemical and structural characterization, and a computational analysis of their WPD-loop dynamics in catalysis. These chimeras maintain backbone structural integrity, with somewhat slower rates than either wild-type parent, despite unaltered chemical mechanisms and transition states. The chimeric proteins’ WPD-loops differ significantly in their relative stability and rigidity. In particular, the open WPD-loops sample multiple metastable and interconverting conformations. The time required for interconversion, coupled with electrostatic effects revealed by simulations, likely accounts for the activity differences between chimeras, and relative to the native enzymes. These differences in loop dynamics affect both the pH dependency of catalysis and turnover rate. Our results further the understanding of connections between enzyme activity and the dynamics of catalytically important groups, particularly the effects of non-catalytic residues on key conformational equilibria.

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We need more openness about age‐related infertility as it is a particular risk for many female scientists in academia who feel that they have to delay having children. [Image: see text]

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

This chapter provides an overview of AI methods as applied to selected areas of analytical chemistry and bioanalysis. We first present a brief historical perspective prior to discussing the applications of ML in chemistry, developing this to neural networks, swarm optimisation methods and additional data treatment and analysis methodologies. We present component analysis techniques and random forest with examples from the literature and offer a perspective on the future of such applications, with advances in computing power and quantum computing methodologies.

Protein tyrosine phosphatases (PTPs) play an important role in cellular signaling and have been implicated in human cancers, diabetes, and obesity. Despite shared catalytic mechanisms and transition states for the chemical steps of catalysis, catalytic rates within the PTP family vary over several orders of magnitude. These rate differences have been implied to arise from differing conformational dynamics of the closure of a protein loop, the WPD-Ioop, which carries a catalytically critical residue. The present work reports computational studies of the human protein tyrosine phosphatase 1B (PTP1B) and YopH from Yersinia pestis, for which NMR has demonstrated a link between their respective rates of WPD-Ioop motion and catalysis rates, which differ by an order of magnitude. We have performed detailed structural analysis, both conventional and enhanced sampling simulations of their loop dynamics, as well as empirical valence bond simulations of the chemical step of catalysis. These analyses revealed the key residues and structural features responsible for these differences, as well as the residues and pathways that facilitate allosteric communication in these enzymes. Curiously, our wild-type YopH simulations also identify a catalytically incompetent hyper-open conformation of its WPD-loop, sampled as a rare event, previously only experimentally observed in YopH-based chimeras. The effect of differences within the WPD-loop and its neighboring loops on the modulation of loop dynamics, as revealed in this work, may provide a facile means for the family of PTP enzymes to respond to environmental changes and regulate their catalytic activities. Correction in: JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, Volume 144, Issue 22, Page 10091-10093, DOI 10.1021/jacs.2c04624

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

DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-specific changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step towards the efficient design of anti-virulence agents that target these proteins.

Mandates with the aim to enforce Open Access publishing, such as Plan S, need to respect researchers’ needs and should contribute to the broader goal of Open Science.[Image: see text]

Glycerol-3-phosphate dehydrogenase is a biomedically important enzyme that plays a crucial role in lipid biosynthesis. It is activated by a ligand-gated conformational change that is necessary for the enzyme to reach a catalytically competent conformation capable of efficient transition-state stabilization. While the human form (hlGPDH) has been the subject of extensive structural and biochemical studies, corresponding computational studies to support and extend experimental observations have been lacking. We perform here detailed empirical valence bond and Hamiltonian replica exchange molecular dynamics simulations of wild-type hlGPDH and its variants, as well as providing a crystal structure of the binary hlGPDH center dot NAD R269A variant where the enzyme is present in the open conformation. We estimated the activation free energies for the hydride transfer reaction in wild-type and substituted hlGPDH and investigated the effect of mutations on catalysis from a detailed structural study. In particular, the K120A and R269A variants increase both the volume and solvent exposure of the active site, with concomitant loss of catalytic activity. In addition, the R269 side chain interacts with both the Q295 side chain on the catalytic loop, and the substrate phosphodianion. Our structural data and simulations illustrate the critical role of this side chain in facilitating the closure of hlGPDH into a catalytically competent conformation, through modulating the flexibility of a key catalytic loop (292-LNGQKL-297). This, in turn, rationalizes a tremendous 41,000 fold decrease experimentally in the turnover number, k(cat), upon truncating this residue, as loop closure is essential for both correct positioning of key catalytic residues in the active site, as well as sequestering the active site from the solvent. Taken together, our data highlight the importance of this ligand-gated conformational change in catalysis, a feature that can be exploited both for protein engineering and for the design of allosteric inhibitors targeting this biomedically important enzyme.

Glycosidases are phylogenetically widely distributed enzymes that are crucial for the cleavage of glycosidic bonds. Here, we present the exceptional properties of a putative ancestor of bacterial and eukaryotic family-1 glycosidases. The ancestral protein shares the TIM-barrel fold with its modern descendants but displays large regions with greatly enhanced conformational flexibility. Yet, the barrel core remains comparatively rigid and the ancestral glycosidase activity is stable, with an optimum temperature within the experimental range for thermophilic family-1 glycosidases. None of the ~5500 reported crystallographic structures of ~1400 modern glycosidases show a bound porphyrin. Remarkably, the ancestral glycosidase binds heme tightly and stoichiometrically at a well-defined buried site. Heme binding rigidifies this TIM-barrel and allosterically enhances catalysis. Our work demonstrates the capability of ancestral protein reconstructions to reveal valuable but unexpected biomolecular features when sampling distant sequence space. The potential of the ancestral glycosidase as a scaffold for custom catalysis and biosensor engineering is discussed.

Directed evolution has revolutionized protein engineering. Still, enzyme optimization by random library screening remains a sluggish process, in large part due to futile probing of mutations that are catalytically neutral and/or impair stability and folding. FuncLib (funclib-weizmann.ac.il) is a novel automated computational procedure which uses phylogenetic analysis and Rosetta design to rank enzyme variants with multiple mutations, on the basis of a stability metric. Here, we use it to target the active site region of a minimalist-designed, de novo Kemp eliminase. The similarity between the Michaelis complex and transition state for the enzymatic reaction makes this a particularly challenging system to optimize. Yet, experimental screening of a very small number of active-site, multi-point variants at the top of the predicted stability ranking leads to catalytic efficiencies and turnover numbers (~2·104 M-1 s-1 and ~102 s-1) that compare well with modern natural enzymes, and that approach the catalysis levels for the best Kemp eliminases derived from extensive screening. This result illustrates the promise of FuncLib as a powerful tool with which to speed up directed evolution, by guiding screening to regions of the sequence space that encode stable and catalytically diverse enzymes. Empirical valence bond calculations reproduce the experimental activation energies for the optimized eliminases to within ~2 kcal·mol-1 and indicate that the improvements in activity are linked to better geometric preorganization of the active site. This raises the possibility of further enhancing the stability-guidance of FuncLib by EVB-based computational predictions of catalytic activity, as a generalized approach for computational enzyme design.

Evolutionary trajectories are deemed largely irreversible. In a newly diverged protein, reversion of mutations that led to the functional switch typically results in loss of both the new and the ancestral functions. Nonetheless, evolutionary transitions where reversions are viable have also been described. The structural and mechanistic causes of reversion compatibility versus incompatibility therefore remain unclear. We examined two laboratory evolution trajectories of mammalian paraoxonase-1, a lactonase with promiscuous organophosphate hydrolase (OPH) activity. Both trajectories began with the same active-site mutant, His115Trp, which lost the native lactonase activity and acquired higher OPH activity. A neo-functionalization trajectory amplified the promiscuous OPH activity, whereas the re-functionalization trajectory restored the native activity, thus generating a new lactonase that lacks His115. The His115 revertants of these trajectories indicated opposite trends. Revertants of the neo-functionalization trajectory lost both the evolved OPH and the original lactonase activity. Revertants of the trajectory that restored the original lactonase function were, however, fully active. Crystal structures and molecular simulations show that in the newly diverged OPH, the reverted His115 and other catalytic residues are displaced, thus causing loss of both the original and the new activity. In contrast, in the re-functionalization trajectory, reversion compatibility of the original lactonase activity derives from mechanistic versatility whereby multiple residues can fulfill the same task. This versatility enables unique sequence-reversible compositions that are inaccessible when the active site was repurposed toward a new function.

Steroidal sulfate esters play a central role in many physiological processes. They serve as the reservoir for endogenous sex hormones and form a significant fraction of the steroid metabolite pool. The analysis of steroid sulfates is thus essential in fields such as medical science and sports drug testing. Although the direct detection of steroid sulfates can be readily achieved using liquid chromatography–mass spectrometry, many analytical approaches, including gas chromatography–mass spectrometry, are hampered due to the lack of suitable enzymatic or chemical methods for sulfate ester hydrolysis prior to analysis. Enhanced methods of steroid sulfate hydrolysis would expand analytical possibilities for the study of these widely occurring metabolites. The arylsulfatase from Pseudomonas aeruginosa (PaS) is a purified enzyme capable of hydrolyzing steroid sulfates. However, this enzyme requires improvement to hydrolytic activity and substrate scope in order to be useful in analytical applications. These imp...

The amphiphilic nature of the amyloid-β (Aβ) peptide associated with Alzheimer's disease facilitates various interactions with biomolecules such as lipids and proteins, with effects on both structure and toxicity of the peptide. Here, we investigate these peptide-amphiphile interactions by experimental and computational studies of Aβ(1-40) in the presence of surfactants with varying physicochemical properties. Our findings indicate that electrostatic peptide-surfactant interactions are required for coclustering and structure induction in the peptide and that the strength of the interaction depends on the surfactant net charge. Both aggregation-prone peptide-rich coclusters and stable surfactant-rich coclusters can form. Only Aβ(1-40) monomers, but not oligomers, are inserted into surfactant micelles in this surfactant-rich state. Surfactant headgroup charge is suggested to be important as electrostatic peptide-surfactant interactions on the micellar surface seems to be an initiating step toward insertion. Thus, no peptide insertion or change in peptide secondary structure is observed using a nonionic surfactant. The hydrophobic peptide-surfactant interactions instead stabilize the Aβ monomer, possibly by preventing self-interaction between the peptide core and C-terminus, thereby effectively inhibiting the peptide aggregation process. These findings give increased understanding regarding the molecular driving forces for Aβ aggregation and the peptide interaction with amphiphilic biomolecules.

Diamine oxidase (DAO) is an enzyme involved in the regulation of cell proliferation and the immune response. This enzyme performs oxidative deamination in the catabolism of biogenic amines, including, among others, histamine, putrescine, spermidine, and spermine. The mechanistic details underlying the reductive half-reaction of the DAO-catalyzed oxidative deamination which leads to the reduced enzyme cofactor and the aldehyde product are, however, still under debate. The catalytic mechanism was proposed to involve a prototropic shift from the substrateSchiff base to the product-Schiff base, which includes the ratelimiting cleavage of the C alpha-H bond by the conserved catalytic aspartate. Our detailed mechanistic study, performed using a combined quantum chemical cluster approach with empirical valence bond simulations, suggests that the rate-limiting cleavage of the C alpha-H bond involves direct hydride transfer to the topaquinone cofactor. a mechanism that does not involve the formation of a Schiff base. Additional investigation of the D373E and D373N variants supported the hypothesis that the conserved catalytic aspartate is indeed essential for the reaction; however, it does not appear to serve as the catalytic base, as previously suggested. Rather, the electrostatic contributions of the most significant residues (including D373), together with the proximity of the Cu2+ cation to the reaction site, lower the activation barrier to drive the chemical reaction.

Triosephosphate isomerase (TIM) is a proficient catalyst of the reversible isomerization of dihydroxyacetone phosphate (DHAP) to d-glyceraldehyde phosphate (GAP), via general base catalysis by E165. Historically, this enzyme has been an extremely important model system for understanding the fundamentals of biological catalysis. TIM is activated through an energetically demanding conformational change, which helps position the side chains of two key hydrophobic residues (I170 and L230), over the carboxylate side chain of E165. This is critical both for creating a hydrophobic pocket for the catalytic base and for maintaining correct active site architecture. Truncation of these residues to alanine causes significant falloffs in TIM’s catalytic activity, but experiments have failed to provide a full description of the action of this clamp in promoting substrate deprotonation. We perform here detailed empirical valence bond calculations of the TIM-catalyzed deprotonation of DHAP and GAP by both wild-type TIM and its I170A, L230A, and I170A/L230A mutants, obtaining exceptional quantitative agreement with experiment. Our calculations provide a linear free energy relationship, with slope 0.8, between the activation barriers and Gibbs free energies for these TIM-catalyzed reactions. We conclude that these clamping side chains minimize the Gibbs free energy for substrate deprotonation, and that the effects on reaction driving force are largely expressed at the transition state for proton transfer. Our combined analysis of previous experimental and current computational results allows us to provide an overview of the breakdown of ground-state and transition state effects in enzyme catalysis in unprecedented detail, providing a molecular description of the operation of a hydrophobic clamp in triosephosphate isomerase.

A ground-breaking empirical valence bond study for a soluble transition-metal complex is presented. The full reaction of catalyst monomers approaching and reacting in the Ru-V oxidation state were studied. Analysis of the solvation shell in the reactant and along the reaction coordinate revealed that the oxo itself is hydrophobic, which adds a significant driving force to form the dimer. The effect of the solvent on the reaction between the prereactive dimer and the product was small. The solvent seems to lower the barrier for the isoquinoline (isoq) complex while it is increased for pyridines. By comparing the reaction in the gas phase and solution, the proposed p-stacking interaction of the isoq ligands is found to be entirely driven by the water medium.

Serum paraoxonase 1 (PON1) is a native lactonase capable of promiscuously hydrolyzing a broad range of substrates, including organophosphates, esters, and carbonates. Structurally, PON1 is a six-bladed beta-propeller with a flexible loop (residues 70-81) covering the active site. This loop contains a functionally critical Tyr at position 71. We have performed detailed experimental and computational analyses of the role of selected Y71 variants in the active site stability and catalytic activity in order to probe the role of Y71 in PON1's lactonase and organophosphatase activities. We demonstrate that the impact of Y71 substitutions on PON1's lactonase activity is minimal, whereas the k(cat) for the paraoxonase activity is negatively perturbed by up to 100-fold, suggesting greater mutational robustness of the native activity. Additionally, while these substitutions modulate PON1's active site shape, volume, and loop flexibility, their largest effect is in altering the solvent accessibility of the active site by expanding the active site volume, allowing additional water molecules to enter. This effect is markedly more pronounced in the organophosphatase activity than the lactonase activity. Finally, a detailed comparison of PON1 to other organophosphatases demonstrates that either a similar "gating loop" or a highly buried solvent excluding active site is a common feature of these enzymes. We therefore posit that modulating the active site hydrophobicity is a key element in facilitating the evolution of organophosphatase activity. This provides a concrete feature that can be utilized in the rational design of next-generation organophosphate hydrolases that are capable of selecting a specific reaction from a pool of viable substrates.

Manuscript and supporting information outlining an analysis of an extended Brønsted relationship obtained from empirical valence bond simulations of substrate deprotonation catalyzed by wild-type and mutant variants of triosephosphate isomerase.

Manuscript and supporting information outlining an analysis of an extended Brønsted relationship obtained from empirical valence bond simulations of substrate deprotonation catalyzed by wild-type and mutant variants of triosephosphate isomerase.

GTP hydrolysis is a biologically crucial reaction, being involved in regulating almost all cellular processes. As a result, the enzymes that catalyze this reaction are among the most important drug targets. Despite their vital importance and decades of substantial research effort, the fundamental mechanism of enzyme-catalyzed GTP hydrolysis by GTPases remains highly controversial. Specifically, how do these regulatory proteins hydrolyze GTP without an obvious general base in the active site to activate the water molecule for nucleophilic attack? To answer this question, we perform empirical valence bond simulations of GTPase-catalyzed GTP hydrolysis, comparing solvent- and substrate-assisted pathways in three distinct GTPases, Ras, Rab, and the G

[Image: see text] Transcriptional repressor EthR from Mycobacterium tuberculosis is a valuable target for antibiotic booster drugs. We previously reported a virtual screening campaign to identify EthR inhibitors for development. Two ligand binding orientations were often proposed, though only the top scoring pose was utilized for filtering of the large data set. We obtained biophysically validated hits, some of which yielded complex crystal structures. In some cases, the crystallized binding mode and top scoring mode agree, while for others an alternate ligand binding orientation was found. In this contribution, we combine rigid docking, molecular dynamics simulations, and the linear interaction energy method to calculate binding free energies and derive relative binding energies for a number of EthR inhibitors in both modes. This strategy allowed us to correctly predict the most favorable orientation. Therefore, this widely applicable approach will be suitable to triage multiple binding modes within EthR and other potential drug targets with similar characteristics.

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'} Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse grained and atomistic simulations of transcription factor-DNA recognition, in order to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs μs-timescale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA, and in the presence of both specific and non-specific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and non-specific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to non-specific complexes), that may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.

There has been growing interest in applying the empirical valence bond approach to a range of (bio)chemical problems, primarily to study enzymatic and non-enzymatic catalysis, but also to studying other processes such as excited state chemistry and reaction dynamics. Despite its apparent theoretical simplicity, this approach is a powerful computational tool that can be used to reproduce and rationalize a wide range of experimental observables, such as linear free energy relationships, kinetic isotope effects, and temperature effects on reaction rates. We provide here both a theoretical background for this approach, as well as highlighting several of its broad applications in computational physical organic chemistry.

Characterizing the adaptive landscapes that encompass the emergence of novel enzyme functions can provide molecular insights into both enzymatic and evolutionary mechanisms. Here, we combine ancestral protein reconstruction with biochemical, structural and mutational analyses to characterize the functional evolution of methyl-parathion hydrolase (MPH), an organophosphate-degrading enzyme. We identify five mutations that are necessary and sufficient for the evolution of MPH from an ancestral dihydrocoumarin hydrolase. In-depth analyses of the adaptive landscapes encompassing this evolutionary transition revealed that the mutations form a complex interaction network, defined in part by higher-order epistasis, that constrained the adaptive pathways available. By also characterizing the adaptive landscapes in terms of their functional activities towards three additional organophosphate substrates, we reveal that subtle differences in the polarity of the substrate substituents drastically alter the network of epistatic interactions. Our work suggests that the mutations function collectively to enable substrate recognition via subtle structural repositioning.

Chalcone isomerases are plant enzymes that perform enantioselective oxa-Michael cyclizations of 2′-hydroxy-chalcones into flavanones. An X-ray crystal structure of an enzyme-product complex and molecular dynamics simulations reveal an enzyme mechanism wherein the guanidinium ion of a conserved arginine positions the nucleophilic phenoxide and activates the electrophilic enone for cyclization through Brønsted and Lewis acid interactions. The reaction terminates by asymmetric protonation of the carbanion intermediate syn to the guanidinium. Interestingly, bifunctional guanidine- and urea-based chemical reagents, increasingly used for asymmetric organocatalytic applications, are synthetic counterparts to this natural system. Comparative protein crystal structures and molecular dynamics simulations further demonstrate how two active site water molecules coordinate a hydrogen bond network that enables expanded substrate reactivity for 6′-deox-ychalcones in more recently evolved type-2 chalcone isomerases.

Recent years have seen an explosion of interest in both sequence- and structure-based approaches toward in silico-directed evolution. We recently developed a novel computational toolkit, CADEE, which facilitates the computer-aided directed evolution of enzymes. Our initial work (Amrein et al., IUCrJ 4:50-64, 2017) presented a pedagogical example of the application of CADEE to triosephosphate isomerase, to illustrate the CADEE workflow. In this contribution, we describe this workflow in detail, including code input/output snippets, in order to allow users to set up and execute CADEE simulations on any system of interest.

Recent years have seen an explosion of interest in both sequence- and structure-based approaches toward in silico-directed evolution. We recently developed a novel computational toolkit, CADEE, which facilitates the computer-aided directed evolution of enzymes. Our initial work (Amrein et al., IUCrJ 4:50-64, 2017) presented a pedagogical example of the application of CADEE to triosephosphate isomerase, to illustrate the CADEE workflow. In this contribution, we describe this workflow in detail, including code input/output snippets, in order to allow users to set up and execute CADEE simulations on any system of interest.

Recent years have seen an explosion of interest in understanding the mechanisms of phosphate ester hydrolysis in biological systems, using a range of computational approaches, each with different advantages and limitations. In this contribution, we present the empirical valence bond (EVB) approach as a powerful tool for modeling biochemical reactivity, using the example of organophosphate hydrolysis by diisopropyl fluorophosphatase as our model reaction. We walk the reader through the protocol for setting up and performing EVB simulations, as well as key technical considerations that need to be taken into account. Finally, we provide examples of the applications of the EVB approach to understanding different experimental observables.