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

Computational scoring and experimental evaluation of enzymes generated by neural networks

In recent years, generative protein sequence models have been developed to sample novel sequences. However, predicting whether generated proteins will fold and function remains challenging. We evaluate a set of 20 diverse computational metrics to assess the quality of enzyme sequences produced by three contrasting generative models: ancestral sequence reconstruction, a generative adversarial network and a protein language model. Focusing on two enzyme families, we expressed and purified over 500 natural and generated sequences with 70-90% identity to the most similar natural sequences to benchmark computational metrics for predicting in vitro enzyme activity. Over three rounds of experiments, we developed a computational filter that improved the rate of experimental success by 50-150%. The proposed metrics and models will drive protein engineering research by serving as a benchmark for generative protein sequence models and helping to select active variants for experimental testing.

Structure and Activity of Reconstructed Pseudo-Ancestral Cyclotides

Cyclotides are cyclic peptides that are promising scaffolds for the design of drug candidates and chemical tools. However, despite there being hundreds of reported cyclotides, drug design studies have commonly focussed on a select few prototypic examples. Here, we explored whether ancestral sequence reconstruction could be used to generate new cyclotides for further optimization. We show that the reconstructed 'pseudo-ancestral' sequences, named Ancy-m (for the ancestral cyclotide of the Möbius sub-family) and Ancy-b (for the bracelet sub-family), have well-defined structures like their extant members, comprising the core structural feature of a cyclic cystine knot. This motif underpins efforts to re-engineer cyclotides for agrochemical and therapeutic applications. We further show that the reconstructed sequences are resistant to temperatures approaching boiling, bind to phosphatidyl-ethanolamine lipid bilayers at micromolar affinity, and inhibit the growth of insect cells at inhibitory concentrations in the micromolar range. Interestingly, the Ancy-b cyclotide had a higher oxidative folding yield than its comparator cyclotide cyO2, which belongs to the bracelet cyclotide subfamily known to be notoriously difficult to fold. Overall, this study provides new cyclotide sequences not yet found naturally that could be valuable starting points for the understanding of cyclotide evolution and for further optimization as drug leads.

Stability Increase of Phenolic Acid Decarboxylase by a Combination of Protein and Solvent Engineering Unlocks Applications at Elevated Temperatures

Enzymatic decarboxylation of biobased hydroxycinnamic acids gives access to phenolic styrenes for adhesive production. Phenolic acid decarboxylases are proficient enzymes that have been applied in aqueous systems, organic solvents, biphasic systems, and deep eutectic solvents, which makes stability a key feature. Stabilization of the enzyme would increase the total turnover number and thus reduce the energy consumption and waste accumulation associated with biocatalyst production. In this study, we used ancestral sequence reconstruction to generate thermostable decarboxylases. Investigation of a set of 16 ancestors resulted in the identification of a variant with an unfolding temperature of 78.1 °C and a half-life time of 45 h at 60 °C. Crystal structures were determined for three selected ancestors. Structural attributes were calculated to fit different regression models for predicting the thermal stability of variants that have not yet been experimentally explored. The models rely on hydrophobic clusters, salt bridges, hydrogen bonds, and surface properties and can identify more stable proteins out of a pool of candidates. Further stabilization was achieved by the application of mixtures of natural deep eutectic solvents and buffers. Our approach is a straightforward option for enhancing the industrial application of the decarboxylation process.

Substitution Models of Protein Evolution with Selection on Enzymatic Activity

Substitution models of evolution are necessary for diverse evolutionary analyses including phylogenetic tree and ancestral sequence reconstructions. At the protein level, empirical substitution models are traditionally used due to their simplicity, but they ignore the variability of substitution patterns among protein sites. Next, in order to improve the realism of the modeling of protein evolution, a series of structurally constrained substitution models were presented, but still they usually ignore constraints on the protein activity. Here, we present a substitution model of protein evolution with selection on both protein structure and enzymatic activity, and that can be applied to phylogenetics. In particular, the model considers the binding affinity of the enzyme-substrate complex as well as structural constraints that include the flexibility of structural flaps, hydrogen bonds, amino acids backbone radius of gyration, and solvent-accessible surface area that are quantified through molecular dynamics simulations. We applied the model to the HIV-1 protease and evaluated it by phylogenetic likelihood in comparison with the best-fitting empirical substitution model and a structurally constrained substitution model that ignores the enzymatic activity. We found that accounting for selection on the protein activity improves the fitting of the modeled functional regions with the real observations, especially in data with high molecular identity, which recommends considering constraints on the protein activity in the development of substitution models of evolution.

An archaeal nitrile hydratase from the halophilic archaeon A07HB70 exhibits high tolerance to 3-cyanopyridine and nicotinamide

Nitrile hydratase (NHase, EC 4.2.1.84) is widely used in the industrial production of biosynthetic amide compounds. NHases obtained from prokaryotic and eukaryotic sources have been widely studied, while the NHases derived from archaeal sources have not been reported. Here, we focused on a distinctive NHase derived from a halophilic archaeon (archaeon A07HB70, A.r NHase) that thrives in high-salt environments. A notable feature of this enzyme is the natural fusion of the α subunit with the activator. A.r NHase retained 89.14 % of its activity after exposure to 4.0 M substrate and 97.52 % of its activity after exposure to 4.0 M product. These findings indicate that A.r NHase exhibits significantly higher tolerance to both substrate and product compared to NHases derived from other sources, which may be due to its unique genetic structure. The investigation of such highly stable archaeal NHase can offer a theoretical foundation for modifying NHase derived from other sources. This, in turn, would enhance the potential industrial application of NHase.

Recent Developments and Applications of Biocatalytic and Chemoenzymatic Synthesis for the Generation of Diverse Classes of Drugs

Biocatalytic and chemoenzymatic biosynthesis are powerful methods of organic chemistry that use enzymes to execute selective reactions and allow the efficient production of organic compounds. The advantages of these approaches include high selectivity, mild reaction conditions, and the ability to work with complex substrates. The utilization of chemoenzymatic techniques for the synthesis of complicated compounds has lately increased dramatically in the area of organic chemistry. Biocatalytic technologies and modern synthetic methods are utilized synergistically in a multi-step approach to a target molecule under this paradigm. Chemoenzymatic techniques are promising for simplifying access to essential bioactive compounds because of the remarkable regio- and stereoselectivity of enzymatic transformations and the reaction diversity of modern organic chemistry. Enzyme kits may include ready-to-use, reproducible biocatalysts. Its use opens up new avenues for the synthesis of active therapeutic compounds and aids in drug development by synthesizing active components to construct scaffolds in a targeted and preparative manner. This study summarizes current breakthroughs as well as notable instances of biocatalytic and chemoenzymatic synthesis. To assist organic chemists in the use of enzymes for synthetic applications, it also provides some basic guidelines for selecting the most appropriate enzyme for a targeted reaction while keeping aspects like cofactor requirement, solvent tolerance, use of whole cell or isolated enzymes, and commercial availability in mind.

Ancestral Reconstruction and the Evolution of Protein Energy Landscapes

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies. Expected final online publication date for the Annual Review of Biophysics, Volume 53 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

MEnTaT: A machine-learning approach for the identification of mutations to increase protein stability

Enhancing protein thermal stability is important for biomedical and industrial applications as well as in the research laboratory. Here, we describe a simple machine-learning method which identifies amino acid substitutions that contribute to thermal stability based on comparison of the amino acid sequences of homologous proteins derived from bacteria that grow at different temperatures. A key feature of the method is that it compares the sequences based not simply on the amino acid identity, but rather on the structural and physicochemical properties of the side chain. The method accurately identified stabilizing substitutions in three well-studied systems and was validated prospectively by experimentally testing predicted stabilizing substitutions in a polyamine oxidase. In each case, the method outperformed the widely used bioinformatic consensus approach. The method can also provide insight into fundamental aspects of protein structure, for example, by identifying how many sequence positions in a given protein are relevant to temperature adaptation.

Molecular determinants of protein evolvability

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

An Inferred Ancestral CotA Laccase with Improved Expression and Kinetic Efficiency

Laccases are widely used in industrial production due to their broad substrate availability and environmentally friendly nature. However, the pursuit of laccases with superior stability and increased heterogeneous expression to meet industry demands appears to be an ongoing challenge. To address this challenge, we resurrected five ancestral sequences of laccase BsCotA and their homologues. All five variants were successfully expressed in soluble and functional forms with improved expression levels in Escherichia coli. Among the five variants, three exhibited higher catalytic rates, thermal stabilities, and acidic stabilities. Notably, AncCotA2, the best-performing variant, displayed a k_cat/K_M of 7.5 × 10⁵ M^-1·s^-1, 5.2-fold higher than that of the wild-type BsCotA, an improved thermo- and acidic stability, and better dye decolorization ability. This study provides a laccase variant with high application potential and presents a new starting point for future enzyme engineering.

Topiary: Pruning the manual labor from ancestral sequence reconstruction

Ancestral sequence reconstruction (ASR) is a powerful tool to study the evolution of proteins and thus gain deep insight into the relationships among protein sequence, structure, and function. A major barrier to its broad use is the complexity of the task: it requires multiple software packages, complex file manipulations, and expert phylogenetic knowledge. Here we introduce topiary, a software pipeline that aims to overcome this barrier. To use topiary, users prepare a spreadsheet with a handful of sequences. Topiary then: (1) Infers the taxonomic scope for the ASR study and finds relevant sequences by BLAST; (2) Does taxonomically informed sequence quality control and redundancy reduction; (3) Constructs a multiple sequence alignment; (4) Generates a maximum-likelihood gene tree; (5) Reconciles the gene tree to the species tree; (6) Reconstructs ancestral amino acid sequences; and (7) Determines branch supports. The pipeline returns annotated evolutionary trees, spreadsheets with sequences, and graphical summaries of ancestor quality. This is achieved by integrating modern phylogenetics software (Muscle5, RAxML-NG, GeneRax, and PastML) with online databases (NCBI and the Open Tree of Life). In this paper, we introduce non-expert readers to the steps required for ASR, describe the specific design choices made in topiary, provide a detailed protocol for users, and then validate the pipeline using datasets from a broad collection of protein families. Topiary is freely available for download: https://github.com/harmslab/topiary.

Engineering functional thermostable proteins using ancestral sequence reconstruction

Natural proteins are often only slightly more stable in the native state than the denatured state, and an increase in environmental temperature can easily shift the balance towards unfolding. Therefore, the engineering of proteins to improve protein stability is an area of intensive research. Thermostable proteins are required to withstand industrial process conditions, for increased shelf-life of protein therapeutics, for developing robust 'biobricks' for synthetic biology applications, and for research purposes (e.g. structure determination). In addition, thermostability buffers the often destabilizing effects of mutations introduced to improve other properties. Rational design approaches to engineering thermostability require structural information, but even with advanced computational methods, it is challenging to predict or parameterize all the relevant structural factors with sufficient precision to anticipate the results of a given mutation. Directed evolution is an alternative when structures are unavailable but requires extensive screening of mutant libraries. Recently however, bioinspired approaches based on phylogenetic analyses have shown great promise. Leveraging the rapid expansion in sequence data and bioinformatic tools, ancestral sequence reconstruction (ASR) can generate highly stable folds for novel applications in industrial chemistry, medicine, and synthetic biology. This review provides an overview of the factors important for successful inference of thermostable proteins by ASR and what it can reveal about the determinants of stability in proteins.

Use of engineered cytochromes P450 for accelerating drug discovery and development

Numerous steps in drug development, including the generation of authentic metabolites and late-stage functionalization of candidates, necessitate the modification of often complex molecules, such as natural products. While it can be challenging to make the required regio- and stereoselective alterations to a molecule using purely chemical catalysis, enzymes can introduce changes to complex molecules with a high degree of stereo- and regioselectivity. Cytochrome P450 enzymes are biocatalysts of unequalled versatility, capable of regio- and stereoselective functionalization of unactivated CH bonds by monooxygenation. Collectively they catalyze over 60 different biotransformations on structurally and functionally diverse organic molecules, including natural products, drugs, steroids, organic acids and other lipophilic molecules. This catalytic versatility and substrate range makes them likely candidates for application as potential biocatalysts for industrial chemistry. However, several aspects of the P450 catalytic cycle and other characteristics have limited their implementation to date in industry, including: their lability at elevated temperature, in the presence of solvents, and over lengthy incubation times; the typically low efficiency with which they metabolize non-natural substrates; and their lack of specificity for a single metabolic pathway. Protein engineering by rational design or directed evolution provides a way to engineer P450s for industrial use. Here we review the progress made to date toward engineering the properties of P450s, especially eukaryotic forms, for industrial application, and including the recent expansion of their catalytic repertoire to include non-natural reactions.

A cocktail of protein engineering strategies: breaking the enzyme bottleneck one by one for high UTP production in vitro

The pyrimidine metabolic pathway is tightly regulated in microorganisms, allowing limited success in metabolic engineering for the production of pathway-related substances. Here, we constructed a four-enzyme coupled system for the in vitro production of uridine triphosphate (UTP). The enzymes used include nucleoside kinase, uridylate kinase, nucleoside diphosphate kinase, and polyphosphate kinase for energy regeneration. All these enzymes are derived from extremophiles. To increase the total and unit time yield of the product, three enzymes other than polyphosphate kinase were modified separately by multiple protein engineering strategies. A nucleoside kinase variant with increased specific activity from 2.7 U/mg to 36.5 U/mg, a uridylate kinase variant (specific activity of 37.1 U/mg) with a 5.2-fold increase in thermostability, and a nucleoside diphosphate kinase variant with a 2-fold increase in specific activity to over 900 U/mg were obtained, respectively. The reaction conditions of the coupled system were further optimized, and a two-stage method was taken to avoid the problem of enzymatic pH adaptation mismatch. Under optimal conditions, this system can produce more than 65 mM UTP (31.5 g/L) in 3.0 h. The substrate conversion rate exceeded 98% and the maximum UTP productivity reached 40 mM/h. This article is protected by copyright. All rights reserved.

HIV Protease and Integrase Empirical Substitution Models of Evolution: Protein-Specific Models Outperform Generalist Models

Diverse phylogenetic methods require a substitution model of evolution that should mimic, as accurately as possible, the real substitution process. At the protein level, empirical substitution models have traditionally been based on a large number of different proteins from particular taxonomic levels. However, these models assume that all of the proteins of a taxonomic level evolve under the same substitution patterns. We believe that this assumption is highly unrealistic and should be relaxed by considering protein-specific substitution models that account for protein-specific selection processes. In order to test this hypothesis, we inferred and evaluated four new empirical substitution models for the protease and integrase of HIV and other viruses. We found that these models more accurately fit, compared with any of the currently available empirical substitution models, the evolutionary process of these proteins. We conclude that evolutionary inferences from protein sequences are more accurate if they are based on protein-specific substitution models rather than taxonomic-specific (generalist) substitution models. We also present four new empirical substitution models of protein evolution that could be useful for phylogenetic inferences of viral protease and integrase.

Adaptive Evolution in TRIF Leads to Discordance between Human and Mouse Innate Immune Signaling

The TIR domain-containing adapter inducing IFN-β (TRIF) protein is an innate immune system protein that mediates the MyD88-independent toll-like receptor response pathway in mice and humans. Previously, we identified positive selection at seven distinct residues in mouse TRIF (mTRIF), as compared with human and other mammalian orthologs, thus predicting protein functional shift in mTRIF. We reconstructed TRIF for the most recent common ancestor of mouse and human, and mutated this at the seven sites to their extant mouse/human states. We overexpressed these TRIF mutants in immortalized human and mouse cell lines and monitored TRIF-dependent cytokine production and gene expression induction. We show that optimal TRIF function in human and mouse is dependent on the identity of the positively selected sites. These data provide us with molecular data relating observed differences in response between mouse and human MyD88-independent signaling in the innate immune system with protein functional change.

uPIC-M: Efficient and Scalable Preparation of Clonal Single Mutant Libraries for High-Throughput Protein Biochemistry

New high-throughput biochemistry techniques complement selection-based approaches and provide quantitative kinetic and thermodynamic data for thousands of protein variants in parallel. With these advances, library generation rather than data collection has become rate-limiting. Unlike pooled selection approaches, high-throughput biochemistry requires mutant libraries in which individual sequences are rationally designed, efficiently recovered, sequence-validated, and separated from one another, but current strategies are unable to produce these libraries at the needed scale and specificity at reasonable cost. Here, we present a scalable, rapid, and inexpensive approach for creating User-designed Physically Isolated Clonal-Mutant (uPIC-M) libraries that utilizes recent advances in oligo synthesis, high-throughput sample preparation, and next-generation sequencing. To demonstrate uPIC-M, we created a scanning mutant library of SpAP, a 541 amino acid alkaline phosphatase, and recovered 94% of desired mutants in a single iteration. uPIC-M uses commonly available equipment and freely downloadable custom software and can produce a 5000 mutant library at 1/3 the cost and 1/5 the time of traditional techniques.

Catalytic mechanism of ancestral L-lysine oxidase assigned by sequence data mining

A large number of protein sequences are registered in public databases such as PubMed. Functionally uncharacterized enzymes are included in these databases, some of which likely have potential for industrial applications. However, assignment of the enzymes remained difficult tasks for now. In this study, we assigned a total of 28 original sequences to uncharacterized enzymes in the FAD-dependent oxidase family expressed in some species of bacteria including Chryseobacterium, Flavobacterium, and Pedobactor. Progenitor sequence of the assigned 28 sequences was generated by ancestral sequence reconstruction, and the generated sequence exhibited L-lysine oxidase activity; thus, we named the enzyme AncLLysO. Crystal structures of ligand-free and ligand-bound forms of AncLLysO were determined, indicating that the enzyme recognizes L-Lys by hydrogen bond formation with R76 and E383. The binding of L-Lys to AncLLysO induced dynamic structural change at a plug loop formed by residues 251 to 254. Biochemical assays of AncLLysO variants revealed the functional importance of these substrate recognition residues and the plug loop. R76A and E383D variants were also observed to lose their activity, and the kcat/Km value of G251P and Y253A mutations were approximately 800- to 1800-fold lower than that of AncLLysO, despite the indirect interaction of the substrates with the mutated residues. Taken together, our data demonstrate that combinational approaches to sequence classification from database and ancestral sequence reconstruction may be effective not only to find new enzymes using databases of unknown sequences but also to elucidate their functions.

State-of-the-Art Biocatalysis

The use of enzyme-mediated reactions has transcended ancient food production to the laboratory synthesis of complex molecules. This evolution has been accelerated by developments in sequencing and DNA synthesis technology, bioinformatic and protein engineering tools, and the increasingly interdisciplinary nature of scientific research. Biocatalysis has become an indispensable tool applied in academic and industrial spheres, enabling synthetic strategies that leverage the exquisite selectivity of enzymes to access target molecules. In this Outlook, we outline the technological advances that have led to the field's current state. Integration of biocatalysis into mainstream synthetic chemistry hinges on increased access to well-characterized enzymes and the permeation of biocatalysis into retrosynthetic logic. Ultimately, we anticipate that biocatalysis is poised to enable the synthesis of increasingly complex molecules at new levels of efficiency and throughput.

An Ancestry Perspective of the Evolution of PBS1 Proteins in Plants

The AVRPPHB SUSCEPTIBLE1 (PBS1) and RESISTANCE TO PSEUDOMONAS SYRINGAE 5 (RPS5) proteins are involved in signal transduction to evoke innate plant immune response. In Arabidopsis, PBS1 is cleaved by the AvrPphB (Pseudomonas phaseolicola Avirulence protein B) protease, activating RPS5 and turning in a hypersensitive response (HR). We searched for PBS1 orthologs to trace their origin and evolution. PBS1 orthologs were found in embryophytes and in other plant taxa but with lower similarity. PBS1 phylogenetic analysis indicates high divergence, suggesting that the decoy function described for Arabidopsis PBS1 might be associated with a small fraction of orthologs. Ancestral reconstruction analysis suggests an elevated diversity in the amino acid sequence within the described motifs. All the orthologs contain the conserved PBS1 kinase subdomains, whereas the cleavage motif is present in several embryophyte orthologs but absent in most other taxa. The putative resistance recognition motifs in PBS1 orthologs are highly diverse. PBS1 cleavage site motif is exposed in some 3D structure predictions, whereas it is not in others, suggesting different modes of regulation and functions in PBS1 orthologs. Our findings suggest that PBS1 originated in the lineage that gave rise to embryophytes, with the angiosperm sequences forming a separate clade from pteridophyte proteins.

From Enzyme Stability to Enzymatic Bioelectrode Stabilization Processes

Bioelectrocatalysis using redox enzymes appears as a sustainable way for biosensing, electricity production, or biosynthesis of fine products. Despite advances in the knowledge of parameters that drive the efficiency of enzymatic electrocatalysis, the weak stability of bioelectrodes prevents large scale development of bioelectrocatalysis. In this review, starting from the understanding of the parameters that drive protein instability, we will discuss the main strategies available to improve all enzyme stability, including use of chemicals, protein engineering and immobilization. Considering in a second step the additional requirements for use of redox enzymes, we will evaluate how far these general strategies can be applied to bioelectrocatalysis.

Recent advancements in the synthesis of novel thermostable biocatalysts and their applications in commercially important chemoenzymatic conversion processes

Thermostable enzymes are a field of growing interest in bioremediation, pharmaceuticals, food industry etc., due to their ability to catalyze bio reactions at high temperatures. This review aims to provide an overview on extremophiles with a special focus on thermophiles and enzymes produced from extremophilic bacteria. Novel thermostable catalysts, used in producing commercially important chemicals, are discussed in this review. Various classes of enzymes produced by microbes, synthesis of thermozymes and comparison with enzymes produced at optimal conditions are critically discussed. A detailed discussion on immobilized enzymes in comparisons with free enzymes, produced by extremozymes, is included. Different parameters which affect enzyme production are also discussed. The current industrial trends along with the future of biocatalysts in the production of chemicals using efficient methods are also discussed.

Evolution of Protein Structure and Stability in Global Warming

This review focuses on the molecular signatures of protein structures in relation to evolution and survival in global warming. It is based on the premise that the power of evolutionary selection may lead to thermotolerant organisms that will repopulate the planet and continue life in general, but perhaps with different kinds of flora and fauna. Our focus is on molecular mechanisms, whereby known examples of thermoresistance and their physicochemical characteristics were noted. A comparison of interactions of diverse residues in proteins from thermophilic and mesophilic organisms, as well as reverse genetic studies, revealed a set of imprecise molecular signatures that pointed to major roles of hydrophobicity, solvent accessibility, disulfide bonds, hydrogen bonds, ionic and π-electron interactions, and an overall condensed packing of the higher-order structure, especially in the hydrophobic regions. Regardless of mutations, specialized protein chaperones may play a cardinal role. In evolutionary terms, thermoresistance to global warming will likely occur in stepwise mutational changes, conforming to the molecular signatures, such that each "intermediate" fits a temporary niche through punctuated equilibrium, while maintaining protein functionality. Finally, the population response of different species to global warming may vary substantially, and, as such, some may evolve while others will undergo catastrophic mass extinction.