Cold Adaptation of Triosephosphate Isomerase

Resistance to freezing conditions of endemic Antarctic polychaetes is enhanced by cryoprotective proteins produced by their microbiome

The microbiome plays a key role in the health of all metazoans. Whether and how the microbiome favors the adaptation processes of organisms to extreme conditions, such as those of Antarctica, which are incompatible with most metazoans, is still unknown. We investigated the microbiome of three endemic and widespread species of Antarctic polychaetes: Leitoscoloplos geminus, Aphelochaeta palmeri, and Aglaophamus trissophyllus. We report here that these invertebrates contain a stable bacterial core dominated by Meiothermus and Anoxybacillus, equipped with a versatile genetic makeup and a unique portfolio of proteins useful for coping with extremely cold conditions as revealed by pangenomic and metaproteomic analyses. The close phylosymbiosis between Meiothermus and Anoxybacillus and these Antarctic polychaetes indicates a connection with their hosts that started in the past to support holobiont adaptation to the Antarctic Ocean. The wide suite of bacterial cryoprotective proteins found in Antarctic polychaetes may be useful for the development of nature-based biotechnological applications.

Harnessing generative AI to decode enzyme catalysis and evolution for enhanced engineering

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. Generative models could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, catalytic activity and stability, rationalizing the laboratory evolution of de novo enzymes, and decoding protein sequence semantics and their application in enzyme engineering. Notably, the prediction of catalytic activity and stability of enzymes using natural protein sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

Helping proteins come in from the cold: 5 burning questions about cold-active enzymes

Enzymes from psychrophilic (cold-loving) organisms have attracted considerable interest over the past decades for their potential in various low-temperature industrial processes. However, we still lack large-scale commercialization of their activities. Here, we review their properties, limitations and potential. Our review is structured around answers to 5 central questions: 1. How do cold-active enzymes achieve high catalytic rates at low temperatures? 2. How is protein flexibility connected to cold-activity? 3. What are the sequence-based and structural determinants for cold-activity? 4. How does the thermodynamic stability of psychrophilic enzymes reflect their cold-active capabilities? 5. How do we effectively identify novel cold-active enzymes, and can we apply them in an industrial context? We conclude that emerging screening technologies combined with big-data handling and analysis make it reasonable to expect a bright future for our understanding and exploitation of cold-active enzymes.

Harnessing Generative AI to Decode Enzyme Catalysis and Evolution for Enhanced Engineering

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. By applying generative models, we could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, activity, and stability, rationalizing the laboratory evolution of de novo enzymes, decoding protein sequence semantics, and its applications in enzyme engineering. Notably, the prediction of enzyme activity and stability using natural enzyme sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

Efficient Empirical Valence Bond Simulations with GROMACS

We describe a protocol to perform empirical valence bond (EVB) simulations using GROMACS software. EVB is a fast and reliable method that allows one to determine the reaction free-energy profiles in complex systems, such as enzymes, by employing classical force fields to represent a chemical reaction. Therefore, running EVB simulations is basically as fast as any classical molecular dynamics simulation, and the method uses standard free-energy calculations to map the free-energy change along a given reaction path. To exemplify and validate our EVB implementation, we replicated two cases of our earlier enzyme simulations. One of these addresses the decomposition of the activation free energy into its enthalpic and entropic components, and the other is focused on calculating the overall catalytic effect of the enzyme compared to the same reaction in water. These two examples give virtually identical results to those obtained with programs that were specifically designed for EVB simulations and show that the GROMACS implementation is robust and can be used for very large systems.

A general overview of the multifactorial adaptation to cold: biochemical mechanisms and strategies

Cold environments are more frequent than people think. They include deep oceans, cold lakes, snow, permafrost, sea ice, glaciers, cold soils, cold deserts, caves, areas at elevations greater than 3000 m, and also artificial refrigeration systems. These environments are inhabited by a diversity of eukaryotic and prokaryotic organisms that must adapt to the hard conditions imposed by cold. This adaptation is multifactorial and includes (i) sensing the cold, mainly through the modification of the liquid-crystalline membrane state, leading to the activation of a two-component system that transduce the signal; (ii) adapting the composition of membranes for proper functions mainly due to the production of double bonds in lipids, changes in hopanoid composition, and the inclusion of pigments; (iii) producing cold-adapted proteins, some of which show modifications in the composition of amino acids involved in stabilizing interactions and structural adaptations, e.g., enzymes with high catalytic efficiency; and (iv) producing ice-binding proteins and anti-freeze proteins, extracellular polysaccharides and compatible solutes that protect cells from intracellular and extracellular ice. However, organisms also respond by reprogramming their metabolism and specifically inducing cold-shock and cold-adaptation genes through strategies such as DNA supercoiling, distinctive signatures in promoter regions and/or the action of CSPs on mRNAs, among others. In this review, we describe the main findings about how organisms adapt to cold, with a focus in prokaryotes and linking the information with findings in eukaryotes.

Advances in cold-adapted enzymes derived from microorganisms

Cold-adapted enzymes, produced in cold-adapted organisms, are a class of enzyme with catalytic activity at low temperatures, high temperature sensitivity, and the ability to adapt to cold stimulation. These enzymes are largely derived from animals, plants, and microorganisms in polar areas, mountains, and the deep sea. With the rapid development of modern biotechnology, cold-adapted enzymes have been implemented in human and other animal food production, the protection and restoration of environments, and fundamental biological research, among other areas. Cold-adapted enzymes derived from microorganisms have attracted much attention because of their short production cycles, high yield, and simple separation and purification, compared with cold-adapted enzymes derived from plants and animals. In this review we discuss various types of cold-adapted enzyme from cold-adapted microorganisms, along with associated applications, catalytic mechanisms, and molecular modification methods, to establish foundation for the theoretical research and application of cold-adapted enzymes.

Structure and Mechanism of a Cold-Adapted Bacterial Lipase

The structural origin of enzyme cold-adaptation has been the subject of considerable research efforts in recent years. Comparative studies of orthologous mesophilic-psychrophilic enzyme pairs found in nature are an obvious strategy for solving this problem, but they often suffer from relatively low sequence identity of the enzyme pairs. Small bacterial lipases adapted to distinctly different temperatures appear to provide an excellent model system for these types of studies, as they may show a very high degree of sequence conservation. Here, we report the first crystal structures of lipase A from the psychrophilic bacterium Bacillus pumilus, which confirm the high structural similarity to the mesophilic Bacillus subtilis enzyme, as indicated by their 81% sequence identity. We further employ extensive QM/MM calculations to delineate the catalytic reaction path and its energetics. The computational prediction of a rate-limiting deacylation step of the enzymatic ester hydrolysis reaction is verified by stopped-flow experiments, and steady-state kinetics confirms the psychrophilic nature of the B. pumilus enzyme. These results provide a useful benchmark for examining the structural basis of cold-adaptation and should now make it possible to disentangle the effects of the 34 mutations between the two enzymes on catalytic properties and thermal stability.

The Activation Parameters of a Cold-Adapted Short Chain Dehydrogenase Are Insensitive to Enzyme Oligomerization

The structural principles of enzyme cold adaptation are of fundamental interest both for understanding protein evolution and for biotechnological applications. It has become clear in recent years that structural flexibility plays a major role in tuning enzyme activity at low temperatures, which is reflected by characteristic changes in the thermodynamic activation parameters for psychrophilic enzymes, compared to those of mesophilic and thermophilic ones. Hence, increased flexibility of the enzyme surface has been shown to lead to a lower enthalpy and a more negative entropy of activation, which leads to higher activity in the cold. This immediately raises the question of how enzyme oligomerization affects the temperature dependence of catalysis. Here, we address this issue by computer simulations of the catalytic reaction of a cold-adapted bacterial short chain dehydrogenase in different oligomeric states. Reaction free energy profiles are calculated at different temperatures for the tetrameric, dimeric, and monomeric states of the enzyme, and activation parameters are obtained from the corresponding computational Arrhenius plots. The results show that the activation free energy, enthalpy, and entropy are remarkably insensitive to the oligomeric state, leading to the conclusion that assembly of the subunit interfaces does not compromise cold adaptation, even though the mobilities of interfacial residues are indeed affected.

The activity and stability of a cold-active acylaminoacyl peptidase rely on its dimerization by domain swapping

The study of enzymes from extremophiles arouses interest in Protein Science because of the amazing solutions these proteins adopt to cope with extreme conditions. Recently solved, the structure of the psychrophilic acyl aminoacyl peptidase from Sporosarcina psychrophila (SpAAP) pinpoints a mechanism of dimerization unusual for this class of enzymes. The quaternary structure of SpAAP relies on a domain-swapping mechanism involving the N-terminal A1 helix. The A1 helix is conserved among homologous mesophilic and psychrophilic proteins and its deletion causes the formation of a monomeric enzyme, which is inactive and prone to aggregate. Here, we investigate the dimerization mechanism of SpAAP through the analysis of chimeric heterodimers where a protomer lacking the A1 helix combines with a protomer carrying the inactivated catalytic site. Our results indicate that the two active sites are independent, and that a single A1 helix is sufficient to partially recover the quaternary structure and the activity of chimeric heterodimers. Since catalytically competent protomers are unstable and inactive unless they dimerize, SpAAP reveals as an "obligomer" for both structural and functional reasons.

Exploring the Cold-Adaptation Mechanism of Serine Hydroxymethyltransferase by Comparative Molecular Dynamics Simulations

Cold-adapted enzymes feature a lower thermostability and higher catalytic activity compared to their warm-active homologues, which are considered as a consequence of increased flexibility of their molecular structures. The complexity of the (thermo)stability-flexibility-activity relationship makes it difficult to define the strategies and formulate a general theory for enzyme cold adaptation. Here, the psychrophilic serine hydroxymethyltransferase (pSHMT) from Psychromonas ingrahamii and its mesophilic counterpart, mSHMT from Escherichia coli, were subjected to μs-scale multiple-replica molecular dynamics (MD) simulations to explore the cold-adaptation mechanism of the dimeric SHMT. The comparative analyses of MD trajectories reveal that pSHMT exhibits larger structural fluctuations and inter-monomer positional movements, a higher global flexibility, and considerably enhanced local flexibility involving the surface loops and active sites. The largest-amplitude motion mode of pSHMT describes the trends of inter-monomer dissociation and enlargement of the active-site cavity, whereas that of mSHMT characterizes the opposite trends. Based on the comparison of the calculated structural parameters and constructed free energy landscapes (FELs) between the two enzymes, we discuss in-depth the physicochemical principles underlying the stability-flexibility-activity relationships and conclude that (i) pSHMT adopts the global-flexibility mechanism to adapt to the cold environment and, (ii) optimizing the protein-solvent interactions and loosening the inter-monomer association are the main strategies for pSHMT to enhance its flexibility.

The Energetic Origin of Different Catalytic Activities in Temperature-Adapted Trypsins

Psychrophilic enzymes were always observed to have higher catalytic activity (k cat) than their mesophilic homologs at room temperature, while the origin of this phenomenon remains obscure. Here, we used two different temperature-adapted trypsins, the psychrophilic Atlantic cod trypsin (ACT) and the mesophilic bovine trypsin (BT), as a model system to explore the energetic origin of their different catalytic activities using computational methods. The results reproduce the characteristic changing trends in the activation free energy, activation enthalpy, and activation entropy between the psychrophilic and mesophilic enzymes, where, in particular, the slightly decreased activation free energy of ACT is determined by its considerably reduced activation enthalpy rather than by its more negative activation entropy compared to BT. The calculated electrostatic contributions to the solvation free energies in the reactant state/ground sate (RS/GS) and transition state (TS) show that, going from BT to ACT, the TS stabilization has a predominant effect over the RS stabilization on lowering the activation enthalpy of ACT. Comparison between the solvation energy components reveals a more optimized electrostatic preorganization to the TS in ACT, which provides a larger stabilization to the TS through reducing the reorganization energy, thus resulting in the lower activation enthalpy and hence lower activation free energy of ACT. Thus, it can be concluded that it is the difference in the protein electrostatic environment, and hence its different stabilizing effects on the TS, that brings about the different catalytic activities of different temperature-adapted trypsins.

Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties

Enzymes have high catalytic efficiency and low environmental impact, and are therefore potentially useful tools for various industrial processes. Crucially, however, natural enzymes do not always have the properties required for specific processes. It may be necessary, therefore, to design, engineer, and evolve enzymes with properties that are not found in natural enzymes. In particular, the creation of enzymes that are thermally stable and catalytically active at low temperature is desirable for processes involving both high and low temperatures. In the current study, we designed two ancestral sequences of 3-isopropylmalate dehydrogenase by an ancestral sequence reconstruction technique based on a phylogenetic analysis of extant homologous amino acid sequences. Genes encoding the designed sequences were artificially synthesized and expressed in Escherichia coli. The reconstructed enzymes were found to be slightly more thermally stable than the extant thermophilic homologue from Thermus thermophilus. Moreover, they had considerably higher low-temperature catalytic activity as compared with the T. thermophilus enzyme. Detailed analyses of their temperature-dependent specific activities and kinetic properties showed that the reconstructed enzymes have catalytic properties similar to those of mesophilic homologues. Collectively, our study demonstrates that ancestral sequence reconstruction can produce a thermally stable enzyme with catalytic properties adapted to low-temperature reactions.

Computer simulations explain the anomalous temperature optimum in a cold-adapted enzyme

Cold-adapted enzymes from psychrophilic species show the general characteristics of being more heat labile, and having a different balance between enthalpic and entropic contributions to free energy barrier of the catalyzed reaction compared to mesophilic orthologs. Among cold-adapted enzymes, there are also examples that show an enigmatic inactivation at higher temperatures before unfolding of the protein occurs. Here, we analyze these phenomena by extensive computer simulations of the catalytic reactions of psychrophilic and mesophilic α-amylases. The calculations yield temperature dependent reaction rates in good agreement with experiment, and also elicit the anomalous rate optimum for the cold-adapted enzyme, which occurs about 15 °C below the melting point. This result allows us to examine the structural basis of thermal inactivation, which turns out to be caused by breaking of a specific enzyme-substrate interaction. This type of behaviour is also likely to be relevant for other enzymes displaying such anomalous temperature optima.

The role of ligand-gated conformational changes in enzyme catalysis

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.

Towards Rational Computational Engineering of Psychrophilic Enzymes

Cold-adapted enzymes from psychrophilic species achieve their high catalytic efficiency at low temperature by a different partitioning of the activation free energy into its enthalpic and entropic components, compared to orthologous mesophilic enzymes. Their lower activation enthalpy, partly compensated by an increased entropic penalty, has been suggested to originate from changes in flexibility of the protein surface. Multiple sequence alignments of psychrophilic and mesophilic enzymes also show characteristic motifs located in surface loops of the protein. Here, we use computer simulations to examine the effects of a number of designed surface mutations of psychrophilic and mesophilic elastases on the temperature dependence of the catalyzed peptide cleavage reaction. For each of 14 mutant enzyme variants we report calculations of their thermodynamic activation parameters. The results show that substitution of psychrophilic loop residues into the mesophilic enzyme consistently changes both the activation parameters and loop flexibilities towards the former, and vice versa for opposite substitutions.

Uncovering the Role of Key Active-Site Side Chains in Catalysis: An Extended Brønsted Relationship for Substrate Deprotonation Catalyzed by Wild-Type and Variants of Triosephosphate Isomerase

We report results of detailed empirical valence bond simulations that model the effect of several amino acid substitutions on the thermodynamic (ΔG°) and kinetic activation (ΔG^⧧) barriers to deprotonation of dihydroxyacetone phosphate (DHAP) and d-glyceraldehyde 3-phosphate (GAP) bound to wild-type triosephosphate isomerase (TIM), as well as to the K12G, E97A, E97D, E97Q, K12G/E97A, I170A, L230A, I170A/L230A, and P166A variants of this enzyme. The EVB simulations model the observed effect of the P166A mutation on protein structure. The E97A, E97Q, and E97D mutations of the conserved E97 side chain result in ≤1.0 kcal mol^-1 decreases in the activation barrier for substrate deprotonation. The agreement between experimental and computed activation barriers is within ±1 kcal mol^-1, with a strong linear correlation between ΔG^⧧ and ΔG° for all 11 variants, with slopes β = 0.73 (R² = 0.994) and β = 0.74 (R² = 0.995) for the deprotonation of DHAP and GAP, respectively. These Brønsted-type correlations show that the amino acid side chains examined in this study function to reduce the standard-state Gibbs free energy of reaction for deprotonation of the weak α-carbonyl carbon acid substrate to form the enediolate phosphate reaction intermediate. TIM utilizes the cationic side chain of K12 to provide direct electrostatic stabilization of the enolate oxyanion, and the nonpolar side chains of P166, I170, and L230 are utilized for the construction of an active-site cavity that provides optimal stabilization of the enediolate phosphate intermediate relative to the carbon acid substrate.

Establishment of mesophilic-like catalytic properties in a thermophilic enzyme without affecting its thermal stability

Thermophilic enzymes are generally more thermally stable but are less active at moderate temperatures than are their mesophilic counterparts. Thermophilic enzymes with improved low-temperature activity that retain their high stability would serve as useful tools for industrial processes especially when robust biocatalysts are required. Here we show an effective way to explore amino acid substitutions that enhance the low-temperature catalytic activity of a thermophilic enzyme, based on a pairwise sequence comparison of thermophilic/mesophilic enzymes. One or a combination of amino acid(s) in 3-isopropylmalate dehydrogenase from the extreme thermophile Thermus thermophilus was/were substituted by a residue(s) found in the Escherichia coli enzyme at the same position(s). The best mutant, which contained three amino acid substitutions, showed a 17-fold higher specific activity at 25 °C compared to the original wild-type enzyme while retaining high thermal stability. The kinetic and thermodynamic parameters of the mutant showed similar patterns along the reaction coordinate to those of the mesophilic enzyme. We also analyzed the residues at the substitution sites from a structural and phylogenetic point of view.

Loop Motion in Triosephosphate Isomerase Is Not a Simple Open and Shut Case

Conformational changes are crucial for the catalytic action of many enzymes. A prototypical and well-studied example is loop opening and closure in triosephosphate isomerase (TIM), which is thought to determine the rate of catalytic turnover in many circumstances. Specifically, TIM loop 6 "grips" the phosphodianion of the substrate and, together with a change in loop 7, sets up the TIM active site for efficient catalysis. Crystal structures of TIM typically show an open or a closed conformation of loop 6, with the tip of the loop moving ∼7 Å between conformations. Many studies have interpreted this motion as a two-state, rigid-body transition. Here, we use extensive molecular dynamics simulations, with both conventional and enhanced sampling techniques, to analyze loop motion in apo and substrate-bound TIM in detail, using five crystal structures of the dimeric TIM from Saccharomyces cerevisiae. We find that loop 6 is highly flexible and samples multiple conformational states. Empirical valence bond simulations of the first reaction step show that slight displacements away from the fully closed-loop conformation can be sufficient to abolish most of the catalytic activity; full closure is required for efficient reaction. The conformational change of the loops in TIM is thus not a simple "open and shut" case and is crucial for its catalytic action. Our detailed analysis of loop motion in a highly efficient enzyme highlights the complexity of loop conformational changes and their role in biological catalysis.

Catalytic Adaptation of Psychrophilic Elastase

The class I pancreatic elastase from Atlantic salmon is considered to be a cold-adapted enzyme in view of the cold habitat, the reduced thermostability of the enzyme, and the fact that it is faster than its mesophilic porcine counterpart at room temperature. However, no experimental characterization of its catalytic properties at lower temperatures has actually been reported. Here we use extensive computer simulations of its catalytic reaction, at different temperatures and with different peptide substrates, to compare its characteristics with those of porcine pancreatic elastase, with which it shares 67% sequence identity. We find that both enzymes have a preference for smaller aliphatic residues at the P1 position, while the reaction rate with phenylalanine at P1 is predicted to be substantially lower. With the former class of substrates, the calculated reaction rates for salmon enzyme are consistently higher than those of the porcine ortholog at all temperatures examined, and the difference is most pronounced at the lowest temperature. As observed for other cold-adapted enzymes, this is caused by redistribution of the activation free energy in terms of enthalpy and entropy and can be linked to differences in the mobility of surface-exposed loops in the two enzymes. Such mobility changes are found to be reflected by characteristic sequence conservation patterns in psychrophilic and mesophilic species. Hence, calculations of mutations in a single surface loop show that the temperature dependence of the catalytic reaction is altered in a predictable way.