NMR-guided directed evolution

Rational enzyme design by reducing the number of hotspots and library size

Biocatalysts that are eco-friendly, sustainable, and highly specific have great potential for applications in the production of fine chemicals, food, detergents, biofuels, pharmaceuticals, and more. However, due to factors such as low activity, narrow substrate scope, poor thermostability, or incorrect selectivity, most natural enzymes cannot be directly used for large-scale production of the desired products. To overcome these obstacles, protein engineering methods have been developed over decades and have become powerful and versatile tools for adapting enzymes with improved catalytic properties or new functions. The vastness of the protein sequence space makes screening a bottleneck in obtaining advantageous mutated enzymes in traditional directed evolution. In the realm of mathematics, there are two major constraints in the protein sequence space: (1) the number of residue substitutions (M); and (2) the number of codons encoding amino acids as building blocks (N). This feature review highlights protein engineering strategies to reduce screening efforts from two dimensions by reducing the numbers M and N, and also discusses representative seminal studies of rationally engineered natural enzymes to deliver new catalytic functions.

Dual client binding sites in the ATP-independent chaperone SurA

The ATP-independent chaperone SurA protects unfolded outer membrane proteins (OMPs) from aggregation in the periplasm of Gram-negative bacteria, and delivers them to the β-barrel assembly machinery (BAM) for folding into the outer membrane (OM). Precisely how SurA recognises and binds its different OMP clients remains unclear. Escherichia coli SurA comprises three domains: a core and two PPIase domains (P1 and P2). Here, by combining methyl-TROSY NMR, single-molecule Förster resonance energy transfer (smFRET), and bioinformatics analyses we show that SurA client binding is mediated by two binding hotspots in the core and P1 domains. These interactions are driven by aromatic-rich motifs in the client proteins, leading to SurA core/P1 domain rearrangements and expansion of clients from collapsed, non-native states. We demonstrate that the core domain is key to OMP expansion by SurA, and uncover a role for SurA PPIase domains in limiting the extent of expansion. The results reveal insights into SurA-OMP recognition and the mechanism of activation for an ATP-independent chaperone, and suggest a route to targeting the functions of a chaperone key to bacterial virulence and OM integrity.

Learning from Protein Engineering by Deconvolution of Multi-Mutational Variants

This review analyzes a development in biochemistry, enzymology and biotechnology that originally came as a surprise. Following the establishment of directed evolution of stereoselective enzymes in organic chemistry, the concept of partial or complete deconvolution of selective multi-mutational variants was introduced. Early deconvolution experiments of stereoselective variants led to the finding that mutations can interact cooperatively or antagonistically with one another, not just additively. During the past decade, this phenomenon was shown to be general. In some studies, molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) computations were performed in order to shed light on the origin of non-additivity at all stages of an evolutionary upward climb. Data of complete deconvolution can be used to construct unique multi-dimensional rugged fitness pathway landscapes, which provide mechanistic insights different from traditional fitness landscapes. Along a related line, biochemists have long tested the result of introducing two point mutations in an enzyme for mechanistic reasons, followed by a comparison of the respective double mutant in so-called double mutant cycles, which originally showed only additive effects, but more recently also uncovered cooperative and antagonistic non-additive effects. We conclude with suggestions for future work, and call for a unified overall picture of non-additivity and epistasis.

Advances in aldo-keto reductases immobilization for biocatalytic synthesis of chiral alcohols

Chiral alcohols are essential building blocks of numerous pharmaceuticals and fine chemicals. Aldo-keto reductases (AKRs) constitute a superfamily of oxidoreductases that catalyze the reduction of aldehydes and ketones to their corresponding alcohols using NAD(P)H as a coenzyme. Knowledge about the crucial roles of AKRs immobilization in the biocatalytic synthesis of chiral alcohols is expanding. Herein, we reviewed the characteristics of various AKRs immobilization approaches, the applications of different immobilization materials, and the prospects of continuous flow bioreactor construction by employing these immobilized biocatalysts for synthesizing chiral alcohols. Finally, the opportunities and ongoing challenges for AKR immobilization are discussed and the outlook for this emerging area is analyzed.

Multiple Functions of Compatible Solute Ectoine and Strategies for Constructing Overproducers for Biobased Production

Ectoine and its derivative 5-hydroxyectoine are compatible solutes initially found in the hyperhalophilic bacterium Ectothiorhodospira halochloris, which inhabits the desert in Egypt. The habitat of ectoine producers implies the primary function of ectoine as a cytoprotectant against harsh conditions such as high salinity, drought, and high radiation. More extensive and in-depth studies have revealed the multiple functions of ectoine in its native producer bacterial cells and other types of cells and its biomolecular components (such as proteins and DNA) as a general protective agent. Its chemical properties as a bio-based amino acid derivative make it attractive for basic scientific research and related industries, such as the food/agricultural industry, cosmetic manufacturing, biologics, and therapeutic agent preparation. This article first discusses the functions and applications of ectoine and 5-hydroxyectoine. Subsequently, more emphasis was placed on advances in bio-based ectoine and/or 5-hydroxyectoine production. Strategies for developing more robust cell factories for highly efficient ectoine and/or 5-hydroxyectoine production are further discussed. We hope this review will provide a valuable reference for studies on the bio-based production of ectoine and 5-hydroxyectoine.

Structure-based investigation of a DNA aptamer targeting PTK7 reveals an intricate 3D fold guiding functional optimization

DNA aptamers have emerged as novel molecular tools in disease theranostics owing to their high binding affinity and specificity for protein targets, which rely on their ability to fold into distinctive three-dimensional (3D) structures. However, delicate atomic interactions that shape the 3D structures are often ignored when designing and modeling aptamers, leading to inefficient functional optimization. Challenges persist in determining high-resolution aptamer-protein complex structures. Moreover, the experimentally determined 3D structures of DNA molecules with exquisite functions remain scarce. These factors impede our comprehension and optimization of some important DNA aptamers. Here, we performed a streamlined solution NMR-based structural investigation on the 41-nt sgc8c, a prominent DNA aptamer used to target membrane protein tyrosine kinase 7, for cancer theranostics. We show that sgc8c prefolds into an intricate three-way junction (3WJ) structure stabilized by long-range tertiary interactions and extensive base-base stackings. Delineated by NMR chemical shift perturbations, site-directed mutagenesis, and 3D structural information, we identified essential nucleotides constituting the key functional elements of sgc8c that are centralized at the core of 3WJ. Leveraging the well-established structure-function relationship, we efficiently engineered two sgc8c variants by modifying the apical loop and introducing L-DNA base pairs to simultaneously enhance thermostability, biostability, and binding affinity for both protein and cell targets, a feat not previously attained despite extensive efforts. This work showcases a simplified NMR-based approach to comprehend and optimize sgc8c without acquiring the complex structure, and offers principles for the sophisticated structure-function organization of DNA molecules.

Hotspot Wizard-informed engineering of a hyperthermophilic β-glucosidase for enhanced enzyme activity at low temperatures

Hyperthermophilic enzymes serve as an important source of industrial enzymes due to their high thermostability. Unfortunately, most hyperthermophilic enzymes suffer from reduced activity at low temperatures (e.g., ambient temperature), limiting their applicability. In addition, evolving hyperthermophilic enzymes to increase low temperature activity without compromising other desired properties is generally difficult. In the current study, a variant of β-glucosidase from Pyrococcus furiosus (PfBGL) was engineered to enhance enzyme activity at low temperatures through the construction of a saturation mutagenesis library guided by the HotSpot Wizard analysis, followed by its screening for activity and thermostability. From this library construction and screening, one PfBGL mutant, PfBGL-A4 containing Q214S/A264S/F344I mutations, showed an over twofold increase in β-glucosidase activity at 25 and 50°C compared to the wild type, without compromising high-temperature activity, thermostability and substrate specificity. Our experimental and computational characterizations suggest that the findings with PfBGL-A4 may be due to the elevation of local conformational flexibility around the active site, while slightly compacting the global protein structure. This study showcases the potential of HotSpot Wizard-informed engineering of hyperthermophilic enzymes and underscores the interplays among temperature, enzyme activity, and conformational flexibility in these enzymes.

Avoiding common pitfalls in designing kinetic protocols for catalytic amyloid studies

Kinetic characterization of catalytic amyloids arguably presents a most challenging type of kinetic experiment where careful consideration of many factors is required. Here we outline common pitfalls in devising kinetic studies in such systems. Unlike the more specific protocols for various applications described in this volume, this chapter deals with general issues in setting up kinetic experiments that are incredibly important but often go without explicit mention in the specialized literature. The kinetic fundamentals described here can be also be of use to the enzymologists working with more traditional catalysts.

Simulating chemical reactions promoted by self-assembled peptides with catalytic properties

Peptides that self-assemble exhibit distinct three-dimensional structures and attributes, positioning them as promising candidates for biocatalysts. Exploring their catalytic processes enhances our comprehension of the catalytic actions inherent to self-assembling peptides, laying a theoretical foundation for creating novel biocatalysts. The investigation into the intricate reaction mechanisms of these entities is rendered challenging due to the vast variability in peptide sequences, their aggregated formations, supportive elements, structures of active sites, types of catalytic reactions, and the interplay between these variables. This complexity hampers the elucidation of the linkage between sequence, structure, and catalytic efficiency in self-assembling peptide catalysts. This chapter delves into the latest progress in understanding the mechanisms behind peptide self-assembly, serving as a catalyst in hydrolysis and oxidation reactions, and employing computational analyses. It discusses the establishment of models, selection of computational strategies, and analysis of computational procedures, emphasizing the application of modeling techniques in probing the catalytic mechanisms of peptide self-assemblies. It also looks ahead to the potential future trajectories within this research domain. Despite facing numerous obstacles, a thorough investigation into the structural and catalytic mechanisms of peptide self-assemblies, combined with the ongoing advancement in computational simulations and experimental methodologies, is set to offer valuable theoretical insights for the development of new biocatalysts, thereby significantly advancing the biocatalysis field.

N-terminal truncation (N-) and directional proton transfer in an old yellow enzyme enables tunable efficient producing (R)- or (S)-citronellal

(R)-Citronellal is a valuable molecule as the precursor for the industrial synthesis of (-)-menthol, one of the worldwide best-selling compounds in the flavors and fragrances field. However, its biocatalytic production, even from the optically pure substrate (E)-citral, is inherently limited by the activity of Old Yellow Enzyme (OYE). Herein, we rationally designed a different approach to increase the activity of OYE in biocatalytic production. The activity of OYE from Corynebacterium glutamicum (CgOYE) is increased, as well as superior thermal stability and pH tolerance via truncating the different lengths of regions at N-terminal of CgOYE. Next, we converted the truncation mutant N31-CgOYE, a protein involved in proton transfer for the asymmetric hydrogenation of CC bonds, into highly (R)- and (S)-stereoselective enzymes using only three mutations. The mixture of racemic (E/Z)-citral is reduced into the (R)-citronellal with ee and conversion up to 99 % by the mutant of CgOYE, overcoming the problem of the reduction for the mixtures of (E/Z)-citral in biocatalytic reaction. The present work provides a general and effective strategy for improving the activity of OYE, in which the partially conserved histidine residues provide "tunable gating" for the enantioselectivity for both the (R)- and (S)-isomerases.

Creating new-to-nature carbon fixation: A guide

Synthetic biology aims at designing new biological functions from first principles. These new designs allow to expand the natural solution space and overcome the limitations of naturally evolved systems. One example is synthetic CO2-fixation pathways that promise to provide more efficient ways for the capture and conversion of CO2 than natural pathways, such as the Calvin Benson Bassham (CBB) cycle of photosynthesis. In this review, we provide a practical guideline for the design and realization of such new-to-nature CO2-fixation pathways. We introduce the concept of "synthetic CO2-fixation", and give a general overview over the enzymology and topology of synthetic pathways, before we derive general principles for their design from their eight naturally evolved analogs. We provide a comprehensive summary of synthetic carbon-assimilation pathways and derive a step-by-step, practical guide from the theoretical design to their practical implementation, before ending with an outlook on new developments in the field.

Biomolecular NMR in the AI-assisted structural biology era: Old tricks and new opportunities

Over the last 40 years nuclear magnetic resonance (NMR) spectroscopy has established itself as one of the most versatile techniques for the characterization of biomolecules, especially proteins. Given the molecular size limitations of NMR together with recent advances in cryo-electron microscopy and artificial intelligence-assisted protein structure prediction, the bright future of NMR in structural biology has been put into question. In this mini review we argue the contrary. We discuss the unique opportunities solution NMR offers to the protein chemist that distinguish it from all other experimental or computational methods, and how it can benefit from machine learning.

Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.

Fishing for Catalysis: Experimental Approaches to Narrowing Search Space in Directed Evolution of Enzymes

Directed evolution has transformed protein engineering offering a path to rapid improvement of protein properties. Yet, in practice it is limited by the hyper-astronomic protein sequence search space, and approaches to identify mutagenic hot spots, i.e., locations where mutations are most likely to have a productive impact, are needed. In this perspective, we categorize and discuss recent progress in the experimental approaches (broadly defined as structural, bioinformatic, and dynamic) to hot spot identification. Recent successes in harnessing protein dynamics and machine learning approaches provide new opportunities for the field and will undoubtedly help directed evolution reach its full potential.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

O2 Carrier Myoglobin Also Exhibits β-Lactamase Activity That Is Regulated by the Heme Coordination State

Heme proteins perform a variety of biological functions and also play significant roles in the field of bio-catalysis. The β-lactamase activity of heme proteins has rarely been reported. Herein, we found, for the first time, that myoglobin (Mb), an O₂ carrier, also exhibits novel β-lactamase activity by catalyzing the hydrolysis of ampicillin. The catalytic proficiency ((k_cat/K_M)/k_uncat) was determined to be 6.25 × 10¹⁰, which is much higher than the proficiency reported for designed metalloenzymes, although it is lower than that of natural β-lactamases. Moreover, we found that this activity could be regulated by an engineered disulfide bond, such as Cys46-Cys61 in F46C/L61C Mb or by the addition of imidazole to directly coordinate to the heme center. These results indicate that the heme active site is responsible for the β-lactamase activity of Mb. Therefore, the study suggests the potential of heme proteins acting as β-lactamases, which broadens the diversity of their catalytic functions.