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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 glucagon-like peptide 1 receptor (GLP-1R) is a member of the family (or class) B G-protein-coupled receptor (GPCR). The receptor is a regulator of insulin and a key target in treating Type 2 diabetes mellitus. In this investigation, computational chemistry techniques such as molecular docking were combined with in silico ADME/Tox predictions to determine the position and structure of the allosteric binding site, as well as to examine how the allosteric modulators bind to the binding site. In silico evaluation was used to evaluate the ADME/Tox properties of the allosteric modulators. The findings of the ligand docking studies suggest that the allosteric binding site is situated around the transmembrane (TM) domain TM 6 of the receptor in the active state. ADME/Tox characterisation of the allosteric modulators demonstrate that compounds 1–3 (2,6,7-trichloro-3-(trifluoromethyl)quinoxaline, 1-(5-(4-(tert-butyl)phenyl)-1,3,4-oxadiazol-2-yl)-6,6-dimethyl-3-(methylsulfonyl)-6,7-dihydrobenzo[c]thiophen-4(5H)-one, 2-((4-chlorophenyl)thio)-3-(trifluoromethyl)quinoxaline, respectively) complied with the traditional method of evaluating drug-likeness; Lipinski’s rule of 5. The allosteric modulator compound 4 (3-(8-chloro-6-(trifluoromethyl)imidazo[1,2-a]pyridin-2-yl)phenyl cyclohexanecarboxylate) failed to comply with Lipinski’s rule of five as a result of having a logP value of over 5.6. Moreover, molecular docking studies provide insights into potential allosteric binding sites and possible interactions. Finally, the in silico ADME/Tox study results are described as relevant to developing a viable drug candidate.

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.

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

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.

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.

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies. Shared first authorship: Gaspar P. Pinto and Marina Corbella

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.

What are PIs looking for when they hire postdocs? [Image: see text]

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.

Structural and biochemical studies on diverse enzymes have highlighted the importance of ligand-gated conformational changes in enzyme catalysis, where the intrinsic binding energy of the common phosphoryl group of their substrates is used to drive energetically unfavorable conformational changes in catalytic loops, from inactive open to catalytically competent closed conformations. However, computational studies have historically been unable to capture the activating role of these conformational changes. Here, we discuss recent experimental and computational studies, which can remarkably pinpoint the role of ligand-gated conformational changes in enzyme catalysis, even when not modeling the loop dynamics explicitly. Finally, through our joint analyses of these data, we demonstrate how the synergy between theory and experiment is crucial for furthering our understanding of enzyme catalysis.

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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]

Sulfonate ester hydrolysis has been the subject of recent debate, with experimental evidence interpreted in terms of both stepwise and concerted mechanisms. In particular, a recent study of the alkaline hydrolysis of a series of benzene arylsulfonates (Babtie et al., Org. Biomol. Chem. 10, 2012, 8095) presented a nonlinear Brønsted plot, which was explained in terms of a change from a stepwise mechanism involving a pentavalent intermediate for poorer leaving groups to a fully concerted mechanism for good leaving groups and supported by a theoretical study. In the present work, we have performed a detailed computational study of the hydrolysis of these compounds and find no computational evidence for a thermodynamically stable intermediate for any of these compounds. Additionally, we have extended the experimental data to include pyridine-3-yl benzene sulfonate and its N-oxide and N-methylpyridinium derivatives. Inclusion of these compounds converts the Brønsted plot to a moderately scattered but linear correlation and gives a very good Hammett correlation. These data suggest a concerted pathway for this reaction that proceeds via an early transition state with little bond cleavage to the leaving group, highlighting the care that needs to be taken with the interpretation of experimental and especially theoretical data.

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.

[EN] 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., his work was supported by Human Frontier Science Program Grant RGP0041 (J.M.S.-R., E.A.G., B.S., and S.C.L.K.), NIH grant R01AR069137 (E.A.G.), Department of Defense grant MURI W911NF-16-1-0372 (E.A.G.), the Swedish Research Council (2019-03499) (S.C.L.K.), the Knut and Alice Wallenberg Foundation (2018.0140 and 2019.0431) (S.C.L.K.), Spanish Ministry of Economy and Competitiveness/FEDER Funds Grants BIO2015-66426-R (J.M.S.-R.) RTI2018-097142-B-100 (J.M.S.-R.) and BIO2016-74875-P (J.A.G.). The simulations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX partially funded by the Swedish Research Council through grant agreement no. 2016-07213. We acknowledge the Spanish Synchrotron Radiation Facility (ALBA, Barcelona) for the provision of synchrotron radiation facilities and the staff at XALOC beamline for their invaluable support. We are also grateful to Victoria Longobardo Polanco (Proteomic Unit, Institute of Parasitology and Biomedicine “López-Neyra”) for help with mass spectrometry experiments and data analyses and to Juan Román Luque Ortega (Molecular Interactions Facility, Centro de Investigaciones Biológicas Margarita Salas) for help with ultracentrifugation experiments and data analyses.

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

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]

Background The coronavirus disease 19 (COVID-19) pandemic has spread globally, causing extensive illness and mortality. In advance of effective antiviral therapies, countries have applied different public health strategies to control spread and manage healthcare need. Sweden has taken a unique approach of not implementing strict closures, instead urging personal responsibility. We analyze the results of this and other potential strategies for pandemic control in Sweden. Methods We implemented individual-based modeling of COVID-19 spread in Sweden using population, employment, and household data. Epidemiological parameters for COVID-19 were validated on a limited date range; where substantial uncertainties remained, multiple parameters were tested. The effects of different public health strategies were tested over a 160-day period, analyzed for their effects on intensive care unit (ICU) demand and death rate, and compared with Swedish data for April 2020. Results Swedish mortality rates are intermediate between rates for European countries that quickly imposed stringent public health controls and those for countries that acted later. Models most closely reproducing reported mortality data suggest that large portions of the population voluntarily self-isolate. Swedish ICU use rates remained lower than predicted, but a large fraction of deaths occurred in non-ICU patients. This suggests that patient prognosis was considered in ICU admission, reducing healthcare load at a cost of decreased survival in patients not admitted. Conclusions The Swedish COVID-19 strategy has thus far yielded a striking result: mild mandates overlaid with voluntary measures can achieve results highly similar to late-onset stringent mandates. However, this policy causes more healthcare demand and more deaths than early stringent control and depends on continued public will.

Directed evolution has revolutionized protein engineering. Still, enzyme optimization by random library screening remains sluggish, in large part due to futile probing of mutations that are catalytically neutral and/or impair stability and folding. FuncLib is a novel approach which uses phylogenetic analysis and Rosetta design to rank enzyme variants with multiple mutations, on the basis of predicted stability. 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 system particularly challenging to optimize. Yet, experimental screening of a small number of active-site 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) for this anthropogenic reaction that compare favorably to those of modern natural enzymes. This result illustrates the promise of FuncLib as a powerful tool with which to speed up directed evolution, even on scaffolds that were not originally evolved for those functions, 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 enhanced activity is linked to better geometric preorganization of the active site. This raises the possibility of further enhancing the stabilityguidance of FuncLib by computational predictions of catalytic activity, as a generalized approach for computational enzyme design, Knut and Alice Wallenberg Foundation (Wallenberg Academy Fellowship) 2018.0140, Human Frontier Science Program RGP0041/2017, FEDER Funds/Spanish Ministry of Science, Innovation and Universities BIO2015-66426-R RTI2018-097142-B-100, FEDER/Junta de Andalucia - Consejeria de Economia y Conocimiento E.FQM.113.UGR18, Swedish National Infrastructure for computing (SNAC) 2018/2-3 2019/2-1

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.

Eight related alcohol dehydrogenases that had been originally isolated by laboratory evolution of ADH-A from Rhodococcus ruber DSM44541 for modified substrate scopes, were together with their parent wild-type, subjected to biochemical characterization of possible activities with a panel of chiral alcohols and pro-chiral ketones. Determinations of rates of catalyzed alcohol oxidations and ketone reductions, and of cofactor release, pointed out to the role of a W295A substitution as being decisive in steering enantioselectivity in the oxidation of arylated 1-methyl substituted alcohols. Molecular dynamics simulations of enzyme-substrate interactions in the Michaelis complexes of wild-type and a Y294F/W295A double mutant could rationalize the experimentally observed shift in enantioselectivity and differences in catalytic activity with 4-phenyl-2-butanol. Finally, we present herein evidence for apparent inter-dependency between substrate/product and the cofactor in the ternary complex, that directly affects the NADH dissociation rates, and thus that this substrate-coenzyme crosstalk plays a direct role in determining the turnover rates.