Ancestral sequence reconstruction for protein engineers

Enhancing the Catalytic Activity of Geranylgeranyl Diphosphate Synthase through Ancestral Sequence Reconstruction and Semirational Design

Geranylgeranyl diphosphate synthase (GGPPS) is the crucial bottleneck in carotenoid biosynthesis. However, low activity limits the broad application of GGPPS. In this study, OsGGPPS1 in rice was engineered based on ancestral sequence reconstruction (ASR) and semirational design to improve the catalytic performances of existing GGPPS. The better mutant of A22R/A26P with improved enzyme activity was generated based on ASR. Additionally, the improved enzyme activity of mutants as V162A/M218S/F227Y was designed using a semirational design. The combinatorial assembly of the d-OsGGPPS1 mutant (A22R/A26P/V162A/M218S/F227Y) exhibited higher conversion of IPP and each cosubstrate of DMAPP for 9.8-fold in GPP production, GPP for 6.4-fold in FPP production, and FPP for 1.4-fold in GGPP production relative to wild-type OsGGPPS1 at 25 °C, which showed higher conversion than wild-type OsGGPPS1 at temperatures as high as 50 °C. The successful design of OsGGPPS1 was representative of protein engineering, which will shed new light on GGPPS engineering and active plant pigment resource utilization.

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.

Pseudo-perplexity in One Fell Swoop for Protein Fitness Estimation

Protein language models trained on the masked language modeling objective learn to predict the identity of hidden amino acid residues within a sequence using the remaining observable sequence as context. They do so by embedding the residues into a high dimensional space that encapsulates the relevant contextual cues. These embedding vectors serve as an informative context-sensitive representation that not only aids with the defined training objective, but can also be used for other tasks by downstream models. We propose a scheme to use the embeddings of an unmasked sequence to estimate the corresponding masked probability vectors for all the positions in a single forward pass through the language model. This One Fell Swoop (OFS) approach allows us to efficiently estimate the pseudo-perplexity of the sequence, a measure of the model's uncertainty in its predictions, that can also serve as a fitness estimate. We find that ESM2 OFS pseudo-perplexity performs nearly as well as the true pseudo-perplexity at fitness estimation, and more notably it defines a new state of the art on the ProteinGym Indels benchmark. The strong performance of the fitness measure prompted us to investigate if it could be used to detect the elevated stability reported in reconstructed ancestral sequences. We find that this measure ranks ancestral reconstructions as more fit than extant sequences. Finally, we show that the computational efficiency of the technique allows for the use of Monte Carlo methods that can rapidly explore functional sequence space.

Engineering a Robust UDP-Glucose Pyrophosphorylase for Enhanced Biocatalytic Synthesis via ProteinMPNN and Ancestral Sequence Reconstruction

UDP-glucose is a key metabolite in carbohydrate metabolism and plays a vital role in glycosyl transfer reactions. Its significance spans across the food and agricultural industries. This study focuses on UDP-glucose synthesis via multienzyme catalysis using dextrin, incorporating UTP production and ATP regeneration modules to reduce costs. To address thermal stability limitations of the key UDP-glucose pyrophosphorylase (UGP), a deep learning-based protein sequence design approach and ancestral sequence reconstruction are employed to engineer a thermally stable UGP variant. The engineered UGP variant is significantly 500-fold more thermally stable at 60 °C and has a half-life of 49.8 h compared to the wild-type enzyme. MD simulations and umbrella sampling calculations provide insights into the mechanism behind the enhanced thermal stability. Experimental validation demonstrates that the engineered UGP variant can produce 52.6 mM UDP-glucose within 6 h in an in vitro cascade reaction. This study offers practical insights for efficient UDP-glucose synthesis methods.

Engineering the next-generation synthetic cell factory driven by protein engineering

Synthetic cell factory offers substantial advantages in economically efficient production of biofuels, chemicals, and pharmaceutical compounds. However, to create a high-performance synthetic cell factory, precise regulation of cellular material and energy flux is essential. In this context, protein components including enzymes, transcription factor-based biosensors and transporters play pivotal roles. Protein engineering aims to create novel protein variants with desired properties by modifying or designing protein sequences. This review focuses on summarizing the latest advancements of protein engineering in optimizing various aspects of synthetic cell factory, including: enhancing enzyme activity to eliminate production bottlenecks, altering enzyme selectivity to steer metabolic pathways towards desired products, modifying enzyme promiscuity to explore innovative routes, and improving the efficiency of transporters. Furthermore, the utilization of protein engineering to modify protein-based biosensors accelerates evolutionary process and optimizes the regulation of metabolic pathways. The remaining challenges and future opportunities in this field are also discussed.

Unlocking the potential of enzyme engineering via rational computational design strategies

Enzymes play a pivotal role in various industries by enabling efficient, eco-friendly, and sustainable chemical processes. However, the low turnover rates and poor substrate selectivity of enzymes limit their large-scale applications. Rational computational enzyme design, facilitated by computational algorithms, offers a more targeted and less labor-intensive approach. There has been notable advancement in employing rational computational protein engineering strategies to overcome these issues, it has not been comprehensively reviewed so far. This article reviews recent developments in rational computational enzyme design, categorizing them into three types: structure-based, sequence-based, and data-driven machine learning computational design. Case studies are presented to demonstrate successful enhancements in catalytic activity, stability, and substrate selectivity. Lastly, the article provides a thorough analysis of these approaches, highlights existing challenges and potential solutions, and offers insights into future development directions.

Designing cytochrome P450 enzymes for use in cancer gene therapy

Cancer is a significant global socioeconomic burden, as millions of new cases and deaths occur annually. In 2020, almost 10 million cancer deaths were recorded worldwide. Advancements in cancer gene therapy have revolutionized the landscape of cancer treatment. An approach with promising potential for cancer gene therapy is introducing genes to cancer cells that encode for chemotherapy prodrug metabolizing enzymes, such as Cytochrome P450 (CYP) enzymes, which can contribute to the effective elimination of cancer cells. This can be achieved through gene-directed enzyme prodrug therapy (GDEPT). CYP enzymes can be genetically engineered to improve anticancer prodrug conversion to its active metabolites and to minimize chemotherapy side effects by reducing the prodrug dosage. Rational design, directed evolution, and phylogenetic methods are some approaches to developing tailored CYP enzymes for cancer therapy. Here, we provide a compilation of genetic modifications performed on CYP enzymes aiming to build highly efficient therapeutic genes capable of bio-activating different chemotherapeutic prodrugs. Additionally, this review summarizes promising preclinical and clinical trials highlighting engineered CYP enzymes' potential in GDEPT. Finally, the challenges, limitations, and future directions of using CYP enzymes for GDEPT in cancer gene therapy are discussed.

Enhancing PET Degrading Enzymes: A Combinatory Approach

Plastic waste has become a substantial environmental issue. A potential strategy to mitigate this problem is to use enzymatic hydrolysis of plastics to depolymerize post-consumer waste and allow it to be reused. Over the last few decades, the use of enzymatic PET-degrading enzymes has shown promise as a great solution for creating a circular plastic waste economy. PsPETase from Piscinibacter sakaiensis has been identified as an enzyme with tremendous potential for such applications. But to improve its efficiency, enzyme engineering has been applied aiming at enhancing its thermal stability, enzymatic activity, and ease of production. Here, we combine different strategies such as structure-based rational design, ancestral sequence reconstruction and machine learning to engineer a more highly active Combi-PETase variant with a melting temperature of 70 °C and optimal performance at 60 °C. Furthermore, this study demonstrates that these approaches, commonly used in other works of enzyme engineering, are most effective when utilized in combination, enabling the improvement of enzymes for industrial applications.

Ancestral terpene cyclases: From fundamental science to applications in biosynthesis

Terpenes constitute one of the largest family of natural products with potent applications as renewable platform chemicals and medicines. The low activity, selectivity and stability displayed by terpene biosynthetic machineries can constitute an obstacle towards achieving expedient biosynthesis of terpenoids in processes that adhere to the 12 principles of green chemistry. Accordingly, engineering of terpene synthase enzymes is a prerequisite for industrial biotechnology applications, but obstructed by their complex catalysis that depend on reactive carbocationic intermediates that are prone to undergo bifurcation mechanisms. Rational redesign of terpene synthases can be tedious and requires high-resolution structural information, which is not always available. Furthermore, it has proven difficult to link sequence space of terpene synthase enzymes to specific product profiles. Herein, the author shows how ancestral sequence reconstruction (ASR) can favorably be used as a protein engineering tool in the redesign of terpene synthases without the need of a structure, and without excessive screening. A detailed workflow of ASR is presented along with associated limitations, with a focus on applying this methodology on terpene synthases. From selected examples of both class I and II enzymes, the author advocates that ancestral terpene cyclases constitute valuable assets to shed light on terpene-synthase catalysis and in enabling accelerated biosynthesis.

Engineering Biocatalysts for the C-H Activation of Fatty Acids by Ancestral Sequence Reconstruction

Selective, one-step C-H activation of fatty acids from biomass is an attractive concept in sustainable chemistry. Biocatalysis has shown promise for generating high-value hydroxy acids, but to date enzyme discovery has relied on laborious screening and produced limited hits, which predominantly oxidise the subterminal positions of fatty acids. Herein we show that ancestral sequence reconstruction (ASR) is an effective tool to explore the sequence-activity landscape of a family of multidomain, self-sufficient P450 monooxygenases. We resurrected 11 catalytically active CYP116B ancestors, each with a unique regioselectivity fingerprint that varied from subterminal in the older ancestors to mid-chain in the lineage leading to the extant, P450-TT. In lineages leading to extant enzymes in thermophiles, thermostability increased from ancestral to extant forms, as expected if thermophily had arisen de novo. Our studies show that ASR can be applied to multidomain enzymes to develop active, self-sufficient monooxygenases as regioselective biocatalysts for fatty acid hydroxylation.

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.

Improving the Quality of Wheat Flour Bread by a Thermophilic Xylanase with Ultra Activity and Stability Reconstructed by Ancestral Sequence and Computational-Aided Analysis

Xylanase is an essential component used to hydrolyze the xylan in wheat flour to enhance the quality of bread. Presently, cold-activated xylanase is popularly utilized to aid in the development of dough. In this study, ancestral sequence reconstruction and molecular docking of xylanase and wheat xylan were used to enhance the activity and stability of a thermophilic xylanase. The results indicated that the ancestral enzyme TmxN3 exhibited significantly improved activity and thermal stability. The Vmax increased by 2.7 times, and the catalytic efficiency (Kcat/Km) increased by 1.7 times in comparison to TmxB. After being incubated at 100 °C for 120 min, it still retained 87.3% of its activity, and the half-life in 100 °C was 330 min, while the wild type xylanase was only 55 min. This resulted in an improved shelf life of bread, while adding TmxN3 considerably enhanced its quality with excellent volume and reduced hardness, chewiness, and gumminess. The results showed that the hardness was reduced by 55.2%, the chewiness was reduced by 40.11%, and the gumminess was reduced by 53.52%. To facilitate its industrial application, we further optimized the production conditions in a 5L bioreactor, and the xylanase activity reached 1.52 × 106 U/mL culture.

Rugged fitness landscapes minimize promiscuity in the evolution of transcriptional repressors

How a protein's function influences the shape of its fitness landscape, smooth or rugged, is a fundamental question in evolutionary biochemistry. Smooth landscapes arise when incremental mutational steps lead to a progressive change in function, as commonly seen in enzymes and binding proteins. On the other hand, rugged landscapes are poorly understood because of the inherent unpredictability of how sequence changes affect function. Here, we experimentally characterize the entire sequence phylogeny, comprising 1,158 extant and ancestral sequences, of the DNA-binding domain (DBD) of the LacI/GalR transcriptional repressor family. Our analysis revealed an extremely rugged landscape with rapid switching of specificity, even between adjacent nodes. Further, the ruggedness arises due to the necessity of the repressor to simultaneously evolve specificity for asymmetric operators and disfavors potentially adverse regulatory crosstalk. Our study provides fundamental insight into evolutionary, molecular, and biophysical rules of genetic regulation through the lens of fitness landscapes.

Extant Sequence Reconstruction: The Accuracy of Ancestral Sequence Reconstructions Evaluated by Extant Sequence Cross-Validation

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term "extant sequence reconstruction" (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

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.

Engineering the thermal stability of a polyphosphate kinase by ancestral sequence reconstruction to expand the temperature boundary for an industrially applicable ATP regeneration system

ATP-dependent energy-consuming enzymatic reactions are widely used in cell-free biocatalysis. However, the direct addition of large amounts of expensive ATP can greatly increase cost, and enzymatic production is often difficult to achieve as a result. Although a polyphosphate kinase (PPK)-polyphosphate-based ATP regeneration system has the potential to solve this challenge, the generally poor thermal stability of PPKs limits the widespread use of this method. In this paper, we evaluated the thermal stability of a PPK from Sulfurovum lithotrophicum (SlPPK2). After directed evolution and computation-supported design, we found that SlPPK2 is very recalcitrant and cannot acquire beneficial mutations. Inspired by the usually outstanding stability of ancestral enzymes, we reconstructed the ancestral sequence of the PPK family and used it as a guide to construct three heat-stable variants of SlPPK2, of which the L35F/T144S variant has a half-life of more than 14 h at 60°C. Molecular dynamics simulations were performed on all enzymes to analyze the reasons for the increased thermal stability. The results showed that mutations at these two positions act synergistically from the interior and surface of the protein, leading to a more compact structure. Finally, the robustness of the L35F/T144S variant was verified in the synthesis of nucleotides at high temperature. In practice, the use of this high-temperature ATP regeneration system can effectively avoid byproduct accumulation. Our work extends the temperature boundary of ATP regeneration and has great potential for industrial applications.IMPORTANCEATP regeneration is an important basic applied study in the field of cell-free biocatalysis. Polyphosphate kinase (PPK) is an enzyme tool widely used for energy regeneration during enzymatic reactions. However, the thermal stability of the PPKs reported to date that can efficiently regenerate ATP is usually poor, which greatly limits their application. In this study, the thermal stability of a difficult-to-engineer PPK from Sulfurovum lithotrophicum was improved, guided by an ancestral sequence reconstruction strategy. The optimal variant has a 4.5-fold longer half-life at 60°C than the wild-type enzyme, thus enabling the extension of the temperature boundary for ATP regeneration. The ability of this variant to regenerate ATP was well demonstrated during high-temperature enzymatic production of nucleotides.

Computation-Aided Phylogeny-Oriented Engineering of β-Xylosidase: Modification of "Blades" to Enhance Stability and Activity for the Bioconversion of Hemicellulose to Produce Xylose

Hemicellulose is a highly abundant, ubiquitous, and renewable natural polysaccharide, widely present in agricultural and forestry residues. The enzymatic hydrolysis of hemicellulose has generally been accomplished using β-xylosidases, but concomitantly increasing the stability and activity of these enzymes remains challenging. Here, we rationally engineered a β-xylosidase from Bacillus clausii to enhance its stability by computation-aided design combining ancestral sequence reconstruction and structural analysis. The resulting combinatorial mutant rXYLOM25I/S51L/S79E exhibited highly improved robustness, with a 6.9-fold increase of the half-life at 60 °C, while also exhibiting improved pH stability, catalytic efficiency, and hydrolytic activity. Structural analysis demonstrated that additional interactions among the propeller blades in the catalytic module resulted in a much more compact protein structure and induced the rearrangement of the opposing catalytic pocket to mediate the observed improvement of activity. Our work provides a robust biocatalyst for the hydrolysis of agricultural waste to produce various high-value-added chemicals and biofuels.

Improving plastic degrading enzymes via directed evolution

Plastic degrading enzymes have immense potential for use in industrial applications. Protein engineering efforts over the last decade have resulted in considerable enhancement of many properties of these enzymes. Directed evolution, a protein engineering approach that mimics the natural process of evolution in a laboratory, has been particularly useful in overcoming some of the challenges of structure-based protein engineering. For example, directed evolution has been used to improve the catalytic activity and thermostability of polyethylene terephthalate (PET)-degrading enzymes, although its use for the improvement of other desirable properties, such as solvent tolerance, has been less studied. In this review, we aim to identify some of the knowledge gaps and current challenges, and highlight recent studies related to the directed evolution of plastic-degrading enzymes.

Evolution and separation of actinobacterial pyranose and C-glycoside-3-oxidases

FAD-dependent pyranose oxidase (POx) and C-glycoside-3-oxidase (CGOx) are both members of the glucose-methanol-choline superfamily of oxidoreductases and belong to the same sequence space. Pyranose oxidases had been studied for their oxidation of monosaccharides such as D-glucose, but recently, a bacterial C-glycoside-3-oxidase that is phylogenetically related to POx and that reacts with C-glycosides such as carminic acid, mangiferin or puerarin has been described. Since these actinobacterial CGOx enzymes belong to the same sequence space as bacterial POx, they must have evolved from the same ancestor. Here, we performed a phylogenetic analysis of actinobacterial sequences and resurrected seven ancestral enzymes of the POx/CGOx sequence space to study the evolutionary trajectory of substrate preferences for monosaccharides and C-glycosides. Clade I, with its dimeric member POx from Kitasatospora aureofaciens, shows strict preference for monosaccharides (D-glucose and D-xylose) and does not react with any of the glycosides tested. No extant member of clade II has been studied to date. The two extant members of clades III and IV, monomeric POx/CGOx from Pseudoarthrobacter siccitolerans and Streptomyces canus, oxidized both monosaccharides as well as various C-glycosides (homoorientin, isovitexin, mangiferin, and puerarin). Steady-state kinetic parameters of several clades III and IV ancestral enzymes indicate that the generalist ancestor N35 slowly evolved to present-day enzymes with a much higher preference for C-glycosides than monosaccharides. Based on structural predictions of ancestors, we hypothesize that the strict specificity of bacterial clade I POx (and also fungal POx) is the result of oligomerization, which in turn results from the evolution of protein segments that were shown to be important for oligomerization, the arm, and the head domain.IMPORTANCEC-Glycosides often form active compounds in various plants. Breakage of the C-C bond in these glycosides to release the aglycone is challenging and proceeds via a two-step reaction, the oxidation of the sugar and subsequent cleavage of the C-C bond. Recently, an enzyme from a soil bacterium, FAD-dependent C-glycoside-3-oxidase (CGOx), was shown to catalyze the initial oxidation reaction. Here, we show that CGOx belongs to the same sequence space as pyranose oxidase (POx), and that an actinobacterial ancestor of the POx/CGOx family evolved into four clades, two of which show a high preference for C-glycosides.

Recent advances in structure-based enzyme engineering for functional reconstruction

Structural information can help engineer enzymes. Usually, specific amino acids in particular regions are targeted for functional reconstruction to enhance the catalytic performance, including activity, stereoselectivity, and thermostability. Appropriate selection of target sites is the key to structure-based design, which requires elucidation of the structure-function relationships. Here, we summarize the mutations of residues in different specific regions, including active center, access tunnels, and flexible loops, on fine-tuning the catalytic performance of enzymes, and discuss the effects of altering the local structural environment on the functions. In addition, we keep up with the recent progress of structure-based approaches for enzyme engineering, aiming to provide some guidance on how to take advantage of the structural information.

Impact of ancestral sequence reconstruction on mechanistic and structural enzymology

Ancestral sequence reconstruction (ASR) provides insight into the changes within a protein sequence across evolution. More specifically, it can illustrate how specific amino acid changes give rise to different phenotypes within a protein family. Over the last few decades it has established itself as a powerful technique for revealing molecular common denominators that govern enzyme function. Here, we describe the strength of ASR in unveiling catalytic mechanisms and emerging phenotypes for a range of different proteins, also highlighting biotechnological applications the methodology can provide.

Allostery, engineering and inhibition of tryptophan synthase

The final two steps of tryptophan biosynthesis are catalyzed by the enzyme tryptophan synthase (TS), composed of alpha (αTS) and beta (βTS) subunits. Recently, experimental and computational methods have mapped "allosteric networks" that connect the αTS and βTS active sites. In αTS, allosteric networks change across the catalytic cycle, which might help drive the conformational changes associated with its function. Directed evolution studies to increase catalytic function and expand the substrate profile of stand-alone βTS have also revealed the importance of αTS in modulating the conformational changes in βTS. These studies also serve as a foundation for the development of TS inhibitors, which can find utility against Mycobacterium tuberculosis and other bacterial pathogens.

Structural and functional analysis of hyper-thermostable ancestral L-amino acid oxidase that can convert Trp derivatives to D-forms by chemoenzymatic reaction

Production of D-amino acids (D-AAs) on a large-scale enables to provide precursors of peptide therapeutics. In this study, we designed a novel L-amino acid oxidase, HTAncLAAO2, by ancestral sequence reconstruction, exhibiting high thermostability and long-term stability. The crystal structure of HTAncLAAO2 was determined at 2.2 Å by X-ray crystallography, revealing that the enzyme has an octameric form like a "ninja-star" feature. Enzymatic property analysis demonstrated that HTAncLAAO2 exhibits three-order larger kcat/Km values towards four L-AAs (L-Phe, L-Leu, L-Met, and L-Ile) than that of L-Trp. Through screening the variants, we obtained the HTAncLAAO2(W220A) variant, which shows a > 6-fold increase in kcat value toward L-Trp compared to the original enzyme. This variant applies to synthesizing enantio-pure D-Trp derivatives from L- or rac-forms at a preparative scale. Given its excellent properties, HTAncLAAO2 would be a starting point for designing novel oxidases with high activity toward various amines and AAs.

Heme Pocket Structure and Its Functional Implications in an Ancestral Globin Protein

Proteins have undergone evolutionary processes to achieve optimal stability, increased functionality, and novel functions. Comparative analysis of existent and ancestral proteins provides insights into the factors that influence protein stability and function. Ancestral sequence reconstruction allows us to deduce the amino acid sequences of ancestral proteins. Here, we present the structural and functional characteristics of an ancestral protein, AncMH, reconstructed to be the last common ancestor of hemoglobins and myoglobins. Our findings reveal that AncMH harbors heme and that the heme binds oxygen. Furthermore, we demonstrate that the ferrous heme in AncMH is pentacoordinated, similar to that of human adult hemoglobin and horse myoglobin. A detailed comparison of the heme pocket structure indicates that the heme pocket in AncMH is more similar to that of hemoglobin than that of myoglobin. However, the autoxidation of AncMH is faster than that of both hemoglobin and myoglobin. Collectively, our results suggest that ancestral proteins of hemoglobins and myoglobins evolved in steps, including the hexa- to pentacoordination transition, followed by stabilization of the oxygen-bound form.

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.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Computer-Aided Lipase Engineering for Improving Their Stability and Activity in the Food Industry: State of the Art

As some of the most widely used biocatalysts, lipases have exhibited extreme advantages in many processes, such as esterification, amidation, and transesterification reactions, which causes them to be widely used in food industrial production. However, natural lipases have drawbacks in terms of organic solvent resistance, thermostability, selectivity, etc., which limits some of their applications in the field of foods. In this systematic review, the application of lipases in various food processes was summarized. Moreover, the general structure of lipases is discussed in-depth, and the engineering strategies that can be used in lipase engineering are also summarized. The protocols of some classical methods are compared and discussed, which can provide some information about how to choose methods of lipase engineering. Thermostability engineering and solvent tolerance engineering are highlighted in this review, and the basic principles for improving thermostability and solvent tolerance are summarized. In the future, comput er-aided technology should be more emphasized in the investigation of the mechanisms of reactions catalyzed by lipases and guide the engineering of lipases. The engineering of lipase tunnels to improve the diffusion of substrates is also a promising prospect for further enhanced lipase activity and selectivity.

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.

Ion-Powered Rotary Motors: Where Did They Come from and Where They Are Going?

Molecular motors are found in many living organisms. One such molecular machine, the ion-powered rotary motor (IRM), requires the movement of ions across a membrane against a concentration gradient to drive rotational movement. The bacterial flagellar motor (BFM) is an example of an IRM which relies on ion movement through the stator proteins to generate the rotation of the flagella. There are many ions which can be used by the BFM stators to power motility and different ions can be used by a single bacterium expressing multiple stator variants. The use of ancestral sequence reconstruction (ASR) and functional analysis of reconstructed stators shows promise for understanding how these proteins evolved and when the divergence in ion use may have occurred. In this review, we discuss extant BFM stators and the ions that power them as well as recent examples of the use of ASR to study ion-channel selectivity and how this might be applied to further study of the BFM stator complex.

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.

Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design

The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.

Ancestral Sequence Reconstruction Identifies Structural Changes Underlying the Evolution of Ideonella sakaiensis PETase and Variants with Improved Stability and Activity

The improved production, recycling, and removal of plastic waste, such as polyethylene terephthalate (PET), are pressing environmental and economic issues for society. Biocatalytic (enzymatic) PET depolymerization is potentially a sustainable, low-energy solution to PET recycling, especially when compared with current disposal methods such as landfills, incineration, or gasification. IsPETase has been extensively studied for its use in PET depolymerization; however, its evolution from cutinases is not fully understood, and most engineering studies have neglected the majority of the available sequence space remote from the active site. In this study, ancestral protein reconstruction (ASR) has been used to trace the evolutionary trajectory from ancient serine hydrolases to IsPETase, while ASR and the related design approach, protein repair one-stop shop, were used to identify enzyme variants with improved activity and stability. Kinetic and structural characterization of these variants reveals new insights into the evolution of PETase activity and the role of second-shell mutations around the active site. Among the designed and reconstructed variants, we identified several with melting points 20 °C higher than that of IsPETase and two variants with significantly higher catalytic activity.

Protein Stability: Enhancement and Measurement

This chapter defines protein stability, emphasizes its importance, and surveys the field of protein stabilization, with summary reference to a selection of 2014-2021 publications. One can enhance stability, particularly by protein engineering strategies but also by chemical modification and by other means. General protocols are set out on how to measure a given protein's (i) kinetic thermal stability and (ii) oxidative stability and (iii) how to undertake chemical modification of a protein in solution.

Enzymatic Conjugation of Modified RNA Fragments by Ancestral RNA Ligase AncT4_2

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

Directed reconstruction of a novel ancestral alcohol dehydrogenase featuring shifted pH-profile, enhanced thermostability and expanded substrate spectrum

Ancestral enzymes are promising for industrial biotechnology due to high stability and catalytic promiscuity. An effective protocol was developed for the directed resurrection of ancestral enzymes. Employing genome mining with diaryl alcohol dehydrogenase KpADH as the probe, descendant enzymes D10 and D11 were firstly identified. Then through ancestral sequence reconstruction, A64 was resurrected with a specific activity of 4.3 U·mg^-1. The optimum pH of A64 was 7.5, distinct from 5.5 of D10. The T15 50 and T_m values of A64 were 57.5 °C and 61.7 °C, significantly higher than those of the descendant counterpart. Substrate spectrum of A64 was quantitively characterized with a Shannon-Wiener index of 2.38, more expanded than D10, especially, towards bulky ketones in Group A and B. A64 also exhibited higher enantioselectivity. This study provides an effective protocol for constructing of ancestral enzymes and an efficient ancestral enzyme of industrial relevance for asymmetric synthesis of chiral alcohols.

Reconstructing CO2 fixation from the past

Analysis of Rubisco evolution could inform how to engineer a better enzyme.

Ancestral sequence reconstruction as a tool to study the evolution of wood decaying fungi

The study of evolution is limited by the techniques available to do so. Aside from the use of the fossil record, molecular phylogenetics can provide a detailed characterization of evolutionary histories using genes, genomes and proteins. However, these tools provide scarce biochemical information of the organisms and systems of interest and are therefore very limited when they come to explain protein evolution. In the past decade, this limitation has been overcome by the development of ancestral sequence reconstruction (ASR) methods. ASR allows the subsequent resurrection in the laboratory of inferred proteins from now extinct organisms, becoming an outstanding tool to study enzyme evolution. Here we review the recent advances in ASR methods and their application to study fungal evolution, with special focus on wood-decay fungi as essential organisms in the global carbon cycling.

Preparation and Characterization of an Ancient Aminopeptidase Obtained from Ancestral Sequence Reconstruction for L-Carnosine Synthesis

As a biologically active peptide, L-carnosine has been widely used in the pharmaceutical, cosmetic and health care industries due to its various physiological properties. However, relatively little research is available regarding L-carnosine's enzymatic synthesis function. In this study, a potential enzyme sequence with the function of carnosine synthesizing was screened out using the ancestral sequence reconstruction (ASR) technique. Identified with L-carnosine synthesis activity, this enzyme was further confirmed using autoproteolytic phenomenon via Western blot and N-terminal sequencing. After purification, the enzymatic properties of LUCA-DmpA were characterized. The melting temperature (T_m) and denaturation enthalpy (ΔH) of LUCA-DmpA were 60.27 ± 1.24 °C and 1306.00 ± 26.73 kJ·mol^-1, respectively. Circular dichroism (CD) spectroscopy results showed that this ancestral enzyme was composed of α-helix (35.23 ± 0.06%), β-sheet (11.06 ± 0.06%), β-turn (23.67 ± 0.06%) and random coil (32.03 ± 0.06%). The enzyme was characterized with the optimal temperature and pH of 45 °C and 9.0, respectively. Notably, LUCA-DmpA was also characterized with remarkable pH tolerance based on the observation of more than 85% remaining enzymatic activity after incubation at different pH buffers (pH = 6-11) for 12 h. Additionally, rather than being improved or inhibited by metal ions, its enzymatic activity was found to be promoted by introducing organic solvent with a larger log P value. Based on these homology modeling results, the screened LUCA-DmpA is suggested to have further optimization potential, and thereafter to be offered as a promising candidate for real industrial applications.

Clostridium as microbial cell factory to enable the sustainable utilization of three generations of feedstocks

The sustainable production of chemicals and biofuels from non-fossil carbon sources is considered key to reducing greenhouse gas (GHG) emissions. Clostridium sp. can convert various substrates, including the 1st-generation (biomass crops), the 2nd-generation (lignocellulosic biomass), and the 3rd-generation (C1 gases) feedstocks, into high-value products, which makes Clostridia attractive for biorefinery applications. However, the complexity of lignocellulosic catabolism and C1 gas utilization make it difficult to construct efficient production routes. Accordingly, this review highlights the advances in the development of three generations of feedstocks with Clostridia as cell factories. At the same time, more attention was given to using agro-industrial wastes (lignocelluloses and C1 gases) as the feedstocks, for which metabolic and process engineering efforts were comprehensively analyzed. In addition, the challenges of using agro-industrial wastes are also discussed. Lastly, several new synthetic biology tools and regulatory strategies are emphasized as promising technologies to be developed to address the aforementioned challenges in Clostridia and realize the efficient utilization of agro-industrial wastes.

Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Ancestral sequence reconstruction is a technique that is gaining widespread use in molecular evolution studies and protein engineering. Accurate reconstruction requires the ability to handle appropriately large numbers of sequences, as well as insertion and deletion (indel) events, but available approaches exhibit limitations. To address these limitations, we developed Graphical Representation of Ancestral Sequence Predictions (GRASP), which efficiently implements maximum likelihood methods to enable the inference of ancestors of families with more than 10,000 members. GRASP implements partial order graphs (POGs) to represent and infer insertion and deletion events across ancestors, enabling the identification of building blocks for protein engineering. To validate the capacity to engineer novel proteins from realistic data, we predicted ancestor sequences across three distinct enzyme families: glucose-methanol-choline (GMC) oxidoreductases, cytochromes P450, and dihydroxy/sugar acid dehydratases (DHAD). All tested ancestors demonstrated enzymatic activity. Our study demonstrates the ability of GRASP (1) to support large data sets over 10,000 sequences and (2) to employ insertions and deletions to identify building blocks for engineering biologically active ancestors, by exploring variation over evolutionary time.

Enzyme- and Chemo-enzyme-Catalyzed Stereodivergent Synthesis

Multiple stereoisomers can be found when a substance contains chiral carbons in its chemical structure. To obtain the desired stereoisomers, asymmetric synthesis was proposed in the 1970s and developed rapidly at the beginning of this century. Stereodivergent synthesis, an extension of asymmetric synthesis in organic synthesis with the hope to produce all stereoisomers of chiral substances in high conversion and selectivity, enriches the variety of available products and serves as a reference suggestion for the synthesis of their derivatives and other compounds. Since biocatalysis has outstanding advantages of economy, environmental friendliness, high efficiency, and reaction at mild conditions, the biocatalytic reaction is regarded as an efficient strategy to perform stereodivergent synthesis. Thus, in this review, we summarize the stereodivergent synthesis catalyzed by enzymes or chemo-enzymes in cases where a compound contains two or three chiral carbons, i.e., at most four or eight stereoisomers are present. The types of reactions, including reduction of substituent ketones, cyclization reactions, olefin addition, and nonredox transesterification reactions, are also discussed for the understanding of the progress and application of biocatalysis in stereodivergent synthesis.

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.

Hunt for α-amylase from metagenome and strategies to improve its thermostability: a systematic review

With the advent of green chemistry, the use of enzymes in industrial processes serves as an alternative to the conventional chemical catalysts. A high demand for sustainable processes for catalysis has brought a significant attention to hunt for novel enzymes. Among various hydrolases, the α-amylase has a gamut of biotechnological applications owing to its pivotal role in starch-hydrolysis. Industrial demand requires enzymes with thermostability and to ameliorate this crucial property, various methods such as protein engineering, directed evolution and enzyme immobilisation strategies are devised. Besides the traditional culture-dependent approach, metagenome from uncultured bacteria serves as a bountiful resource for novel genes/biocatalysts. Exploring the extreme-niches metagenome, advancements in protein engineering and biotechnology tools encourage the mining of novel α-amylase and its stable variants to tap its robust biotechnological and industrial potential. This review outlines α-amylase and its genetics, its catalytic domain architecture and mechanism of action, and various molecular methods to ameliorate its production. It aims to impart understanding on mechanisms involved in thermostability of α-amylase, cover strategies to screen novel genes from futile habitats and some molecular methods to ameliorate its properties.

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.

Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme

The routine generation of enzymes with completely new active sites is a major unsolved problem in protein engineering. Advances in this field have thus far been modest, perhaps due, at least in part, to the widespread use of modern natural proteins as scaffolds for de novo engineering. Most modern proteins are highly evolved and specialized and, consequently, difficult to repurpose for completely new functionalities. Conceivably, resurrected ancestral proteins with the biophysical properties that promote evolvability, such as high stability and conformational diversity, could provide better scaffolds for de novo enzyme generation. Kemp elimination, a non-natural reaction that provides a simple model of proton abstraction from carbon, has been extensively used as a benchmark in de novo enzyme engineering. Here, we present an engineered ancestral β-lactamase with a new active site that is capable of efficiently catalyzing Kemp elimination. The engineering of our Kemp eliminase involved minimalist design based on a single function-generating mutation, inclusion of an extra polypeptide segment at a position close to the de novo active site, and sharply focused, low-throughput library screening. Nevertheless, its catalytic parameters (k_cat/K_M~2·10⁵ M⁻¹ s⁻¹, k_cat~635 s⁻¹) compare favorably with the average modern natural enzyme and match the best proton-abstraction de novo Kemp eliminases that are reported in the literature. The general implications of our results for de novo enzyme engineering are discussed.

Functions and biosynthesis of plant signaling metabolites mediating plant-microbe interactions

Covering: 2015-2022Plants and microbes have coevolved since their appearance, and their interactions, to some extent, define plant health. A reasonable fraction of small molecules plants produced are involved in mediating plant-microbe interactions, yet their functions and biosynthesis remain fragmented. The identification of these compounds and their biosynthetic genes will open up avenues for plant fitness improvement by manipulating metabolite-mediated plant-microbe interactions. Herein, we integrate the current knowledge on their chemical structures, bioactivities, and biosynthesis with the view of providing a high-level overview on their biosynthetic origins and evolutionary trajectory, and pinpointing the yet unknown and key enzymatic steps in diverse biosynthetic pathways. We further discuss the theoretical basis and prospects for directing plant signaling metabolite biosynthesis for microbe-aided plant health improvement in the future.

Insertions and deletions in protein evolution and engineering

Protein evolution or engineering studies are traditionally focused on amino acid substitutions and the way these contribute to fitness. Meanwhile, the insertion and deletion of amino acids is often overlooked, despite being one of the most common sources of genetic variation. Recent methodological advances and successful engineering stories have demonstrated that the time is ripe for greater emphasis on these mutations and their understudied effects. This review highlights the evolutionary importance and biotechnological relevance of insertions and deletions (indels). We provide a comprehensive overview of approaches that can be employed to include indels in random, (semi)-rational or computational protein engineering pipelines. Furthermore, we discuss the tolerance to indels at the structural level, address how domain indels can link the function of unrelated proteins, and feature studies that illustrate the surprising and intriguing potential of frameshift mutations.

Evo-velocity: Protein language modeling accelerates the study of evolution

Understanding how protein sequences have evolved is one of the defining challenges in modern biology. In this issue of Cell Systems, Hie et al. describe a novel phylogenetic approach, dubbed "evo-velocity," that exploits protein language modeling to overcome many limitations of traditional phylogenetic analysis.

Tools for computational design and high-throughput screening of therapeutic enzymes

Therapeutic enzymes are valuable biopharmaceuticals in various biomedical applications. They have been successfully applied for fibrinolysis, cancer treatment, enzyme replacement therapies, and the treatment of rare diseases. Still, there is a permanent demand to find new or better therapeutic enzymes, which would be sufficiently soluble, stable, and active to meet specific medical needs. Here, we highlight the benefits of coupling computational approaches with high-throughput experimental technologies, which significantly accelerate the identification and engineering of catalytic therapeutic agents. New enzymes can be identified in genomic and metagenomic databases, which grow thanks to next-generation sequencing technologies exponentially. Computational design and machine learning methods are being developed to improve catalytically potent enzymes and predict their properties to guide the selection of target enzymes. High-throughput experimental pipelines, increasingly relying on microfluidics, ensure functional screening and biochemical characterization of target enzymes to reach efficient therapeutic enzymes.