Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences

Unlocking the Gates: Therapeutic Agents for Noninvasive Drug Delivery Across the Blood-Brain Barrier

The blood-brain barrier (BBB) is a highly selective network of various cell types that acts as a filter between the blood and the brain parenchyma. Because of this, the BBB remains a major obstacle for drug delivery to the central nervous system (CNS). In recent years, there has been a focus on developing various modifiable platforms, such as monoclonal antibodies (mAbs), nanobodies (Nbs), peptides, and nanoparticles, as both therapeutic agents and carriers for targeted drug delivery to treat brain cancers and diseases. Methods for bypassing the BBB can be invasive or noninvasive. Invasive techniques, such as transient disruption of the BBB using low pulse electrical fields and intracerebroventricular infusion, lack specificity and have numerous safety concerns. In this review, we will focus on noninvasive transport mechanisms that offer high levels of biocompatibility, personalization, specificity and are regarded as generally safer than their invasive counterparts. Modifiable platforms can be designed to noninvasively traverse the BBB through one or more of the following pathways: passive diffusion through a physio-pathologically disrupted BBB, adsorptive-mediated transcytosis, receptor-mediated transcytosis, shuttle-mediated transcytosis, and somatic gene transfer. Through understanding the noninvasive pathways, new applications, including Chimeric Antigen Receptors T-cell (CAR-T) therapy, and approaches for drug delivery across the BBB are emerging.

Unleashing the Power of Evolution in Xylanase Engineering: Investigating the Role of Distal Mutation Regulation

The drive to enhance enzyme performance in industrial applications frequently clashes with the practical limitations of exhaustive experimental screening, underscoring the urgency for more refined and strategic methodologies in enzyme engineering. In this study, xylanase Xyl-1 was used as the model, coupling evolutionary insights with energy functions to obtain theoretical potential mutants, which were subsequently validated experimentally. We observed that mutations in the nonloop region primarily aimed at enhancing stability and also encountered selective pressure for activity. Notably, mutations in this region simultaneously boosted the Xyl-1 stability and activity, achieving a 65% success rate. Using a greedy strategy, mutant M4 was developed, achieving a 12 °C higher melting temperature and doubled activity. By integration of spectroscopy, crystallography, and quantum mechanics/molecular mechanics molecular dynamics, the mechanism behind the enhanced thermal stability of M4 was elucidated. It was determined that the activity differences between M4 and the wild type were primarily driven by dynamic factors influenced by distal mutations. In conclusion, the study emphasizes the pivotal role of evolution-based approaches in augmenting the stability and activity of the enzymes. It sheds light on the unique adaptive mechanisms employed by various structural regions of proteins and expands our understanding of the intricate relationship between distant mutations and enzyme dynamics.

Opportunities and challenges in design and optimization of protein function

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.

One-shot design elevates functional expression levels of a voltage-gated potassium channel

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations.

GMMA Can Stabilize Proteins Across Different Functional Constraints

Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided an increase of 2-6 °C in thermal inactivation temperature and no decrease in functionality.

Enhancing the Catalytic Efficiency of D-lactonohydrolase through the Synergy of Tunnel Engineering, Evolutionary Analysis, and Force-Field Calculations

Computational design advances enzyme evolution and their use in biocatalysis in a faster and more efficient manner. In this study, a synergistic approach integrating tunnel engineering, evolutionary analysis, and force-field calculations has been employed to enhance the catalytic activity of D-lactonohydrolase (D-Lac), which is a pivotal enzyme involved in the resolution of racemic pantolactone during the production of vitamin B5. The best mutant, N96S/A271E/F274Y/F308G (M3), was obtained and its catalytic efficiency (kcat/KM) was nearly 23-fold higher than that of the wild-type. The M3 whole-cell converted 20 % of DL-pantolactone into D-pantoic acid (D-PA, >99 % e.e.) with a conversion rate of 47 % and space-time yield of 107.1 g L-1 h-1, demonstrating its great potential for industrial-scale D-pantothenic acid production. Molecular dynamics (MD) simulations revealed that the reduction in the steric hindrance within the substrate tunnel and conformational reconstruction of the distal loop resulted in a more favourable"catalytic" conformation, making it easier for the substrate and enzyme to enter their pre-reaction state. This study illustrates the potential of the distal residue on the pivotal loop at the entrance of the D-Lac substrate tunnel as a novel modification hotspot capable of reshaping energy patterns and consequently influencing the enzymatic activity.

A green pathway for lignin valorization: Enzymatic lignin depolymerization in biocompatible ionic liquids and deep eutectic solvents

Lignin depolymerization, which enables the breakdown of a complex and heterogeneous aromatic polymer into relatively uniform derivatives, serves as a critical process in valorization of lignin. Enzymatic lignin depolymerization has become a promising biological strategy to overcome the heterogeneity of lignin, due to its mild reaction conditions and high specificity. However, the low solubility of lignin compounds in aqueous environments prevents efficient lignin depolymerization by lignin-degrading enzymes. The employment of biocompatible ionic liquids (ILs) and deep eutectic solvents (DESs) in lignin fractionation has created a promising pathway to enzymatically depolymerize lignin within these green solvents to increase lignin solubility. In this review, recent research progress on enzymatic lignin depolymerization, particularly in a consolidated process involving ILs/DESs is summarized. In addition, the interactions between lignin-degrading enzymes and solvent systems are explored, and potential protein engineering methodology to improve the performance of lignin-degrading enzymes is discussed. Consolidation of enzymatic lignin depolymerization and biocompatible ILs/DESs paves a sustainable, efficient, and synergistic way to convert lignin into value-added products.

Enhancing Bioethanol Production from Rice Straw through Environmentally Friendly Delignification Using Versatile Peroxidase

Rice straw (RS), an agricultural residue rich in carbohydrates, has substantial potential for bioethanol production. However, the presence of lignin impedes access to these carbohydrates, hindering efficient carbohydrate-to-bioethanol conversion. Here, we expressed versatile peroxidase (VP), a lignin-degrading enzyme, in Pichia pastoris and used it to delignify RS at 30 °C using a membrane bioreactor that continuously discarded the degraded lignin. Klason lignin analysis revealed that VP-treatment led to 35% delignification of RS. We then investigated the delignified RS by SEC, FTIR, and SEM. The results revealed the changes of RS caused by VP-mediated delignification. Additionally, we compared the saccharification and fermentation yields between RSs treated with and without VP, VP-RS, and Ctrl-RS, respectively. This examination unveiled an improvement in glucose and bioethanol production, VP-RS exhibiting up to 1.5-fold and 1.4-fold production, respectively. These findings underscore the potential of VP for delignifying RS and enhancing bioethanol production through an eco-friendly approach.

Computational Characterization of the Reactivity of Compound I in Unspecific Peroxygenases

Unspecific peroxygenases (UPOs) are emerging as promising biocatalysts for selective oxyfunctionalization of unactivated C-H bonds. However, their potential in large-scale synthesis is currently constrained by suboptimal chemical selectivity. Improving the selectivity of UPOs requires a deep understanding of the molecular basis of their catalysis. Recent molecular simulations have sought to unravel UPO's selectivity and inform their design principles. However, most of these studies focused on substrate-binding poses. Few researchers have investigated how the reactivity of CpdI, the principal oxidizing intermediate in the catalytic cycle, influences selectivity in a realistic protein environment. Moreover, the influence of protein electrostatics on the reaction kinetics of CpdI has also been largely overlooked. To bridge this gap, we used multiscale simulations to interpret the regio- and enantioselective hydroxylation of the n-heptane substrate catalyzed by Agrocybe aegerita UPO (AaeUPO). We comprehensively characterized the energetics and kinetics of the hydrogen atom-transfer (HAT) step, initiated by CpdI, and the subsequent oxygen rebound step forming the product. Notably, our approach involved both free energy and potential energy evaluations in a quantum mechanics/molecular mechanics (QM/MM) setting, mitigating the dependence of results on the choice of initial conditions. These calculations illuminate the thermodynamics and kinetics of the HAT and oxygen rebound steps. Our findings highlight that both the conformational selection and the distinct chemical reactivity of different substrate hydrogen atoms together dictate the regio- and enantio-selectivity. Building on our previous study of CpdI's formation in AaeUPO, our results indicate that the HAT step is the rate-limiting step in the overall catalytic cycle. The subsequent oxygen rebound step is swift and retains the selectivity determined by the HAT step. We also pinpointed several polar and charged amino acid residues whose electrostatic potentials considerably influence the reaction barrier of the HAT step. Notably, the Glu196 residue is pivotal for both the CpdI's formation and participation in the HAT step. Our research offers in-depth insights into the catalytic cycle of AaeUPO, which will be instrumental in the rational design of UPOs with enhanced properties.

Two-way reaction of versatile peroxidase with artificial lignin enhances low-molecular weight fractions

In recent years, versatile peroxidase (VP) has emerged as a promising enzyme for biotechnological applications, as it can oxidize lignin without the external mediators. To gain insights into the breakdown process of artificial lignin by VP, reaction between the two was studied. Degradation products were fractionated using ultrafiltration and analyzed by RP- high performance liquid chromatography with mass detection (HPLC-MS) chromatography. Four fractions were obtained based on their molecular sizes: >10, 3-10, 1-3, and <1 kDa. Interestingly, while VP did not significantly alter the yields of these fractions, the chromatograms revealed the presence of oligomers with different molecular weights (MWs) resulting from the enzymatic activity. The VP exhibits a dual role in its enzymatic activity: both degrading and synthesizing these oligomers. This was confirmed by principal component analysis (PCA). The positive correlations were found between certain oligomers (D1 and D2, D5 and D6, as well as between D7, D10, T2, and T4), suggesting their simultaneous degradation. On the other hand, a negative correlation was found between the monomer and some oligomers (D7, D10, T2, and T4), indicating the decomposition of these oligomers into monomers. These findings shed light on the intricate interplay between VP and artificial lignin, offering valuable insights for potential applications in lignin valorization.

Active site determination of novel plant versatile peroxidase extracted from Citrus sinensis and bioconversion of β-naphthol

A ligninolytic peroxidase called versatile peroxidase, VP, (EC 1.11.1.16) is an iron-containing metalloenzyme. The most distinctive feature of this enzyme is its composite molecular framework, which combines lignin peroxidase's capacity to oxidize compounds with high-redox potential with manganese peroxidase's capacity to oxidize Mn2+ to Mn3+. In this study, we have extracted amino acid sequences from the Citrus sinensis source and subjected them to various computation tools to visualize the insight secondary and 3D structure, physicochemical properties, and validation of the structure which have not been studied so far to further investigate the catalytic efficiency and effectiveness of VP. The binding energies of HEME and HEME C (HEC) ligands with produced PDB (6rqf.1. A) have been also assessed, analyzed, and confirmed utilizing AutoDock. Binding energies were calculated using the AutoDock and validated by MD simulation using SCHRODINGER DESMOND. Most stable confirmation was achieved through a protein-ligand interaction study. Bio-technological use of VP in the biotransformation of β-naphthol has also been studied. The findings in the current study will have a substantial impact on proteomics, biochemistry, biotechnology, and possible uses of versatile peroxidase in the bio-remediation of different toxic organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03758-x.

Elucidating the role of media nitrogen in augmenting the production of lignin-depolymerizing enzymes by white-rot fungi

Indigenous white-rot fungal isolates Schizophyllum commune, Phanerochaete chrysosporium, Ganoderma racenaceum, and Lentinus squarrosulus, demonstrating the ability to depolymerize lignin of the crop residues, were studied for their potential to produce ligninolytic enzymes using modified production media under conditions of limiting and excess nitrogen for higher enzymatic expressions. Secretome-rich media on the investigation confirmed the successful production of lignin-depolymerizing enzymes, viz. laccase, lignin peroxidase, manganese peroxidase, and versatile peroxidase. Production of laccases and peroxidases was statistically significant in nitrogen-limiting media with and without the substrate, across all white-rot fungal cultures at 95% confidence interval. Nitrogen-limiting media with the substrate on analysis extracellularly expressed 99.27 U of laccase and 68.48 U of manganese peroxidase in Schizophyllum commune, while 195.14 U of lignin peroxidase was produced by Phanerochaete chrysosporium. Lentinus squarrosulus expressed 455.34 U of laccase and 357.13 U of versatile peroxidase with 250.09 U of laccase and 206.95 U of manganese peroxidase produced by Ganoderma racenaceum for every milliliter of the media used. Nitrogen-limiting media triggered the production of laccase during the initial stages of growth while the expression of peroxidases was predominant at a later stage. Also, this media evinced increased enzymatic yields with low biomass content compared to nitrogen-excess conditions. The extant study confirmed the positive influence of nitrogen-limiting media in the efficient production of ligninolytic enzymes and their suggestive degradation potential for environmental pollutants, making these enzymes a safe, clean alternative to the use of chemicals and the media to be effective for large-scale production of ligninolytic enzymes. IMPORTANCE Lignin on account of its high abundance, complex polymeric structure, and biochemical properties is identified as a promising candidate in renewable energy and bioproduct manufacturing. However, depolymerization of lignin remains a major challenge in lignin utilization, entailing the employment of harsh treatments representing not only an environmental concern but also a waste of economic potential. Developing an alternative green technology to minimize this impact is imperative. Methods using enzymes to depolymerize lignin are the focus of recent studies. Current research work emphasized the efficient expression of the major lignin-depolymerizing enzymes: laccases, lignin peroxidases, manganese peroxidases, and versatile peroxidases from native isolates of white-rot fungus for several biotechnological applications as well as treatment of crop residues for use as ruminant feed in improving productivity. The importance of nitrogen in augmenting the expression of lignin-depolymerizing enzymes and providing a media recipe for the cost-effective production of ligninolytic enzymes is highlighted.

Stable Mammalian Serum Albumins Designed for Bacterial Expression

Albumin is the most abundant protein in the blood serum of mammals and has essential carrier and physiological roles. Albumins are also used in a wide variety of molecular and cellular experiments and in the cultivated meat industry. Despite their importance, however, albumins are challenging for heterologous expression in microbial hosts, likely due to 17 conserved intramolecular disulfide bonds. Therefore, albumins used in research and biotechnological applications either derive from animal serum, despite severe ethical and reproducibility concerns, or from recombinant expression in yeast or rice. We use the PROSS algorithm to stabilize human and bovine serum albumins, finding that all are highly expressed in E. coli. Design accuracy is verified by crystallographic analysis of a human albumin variant with 16 mutations. This albumin variant exhibits ligand binding properties similar to those of the wild type. Remarkably, a design with 73 mutations relative to human albumin exhibits over 40 °C improved stability and is stable beyond the boiling point of water. Our results suggest that proteins with many disulfide bridges have the potential to exhibit extreme stability when subjected to design. The designed albumins may be used to make economical, reproducible, and animal-free reagents for molecular and cell biology. They also open the way to high-throughput screening to study and enhance albumin carrier properties.

Dye Decolorization by a Miniaturized Peroxidase Fe-MimochromeVI*a

Oxidases and peroxidases have found application in the field of chlorine-free organic dye degradation in the paper, toothpaste, and detergent industries. Nevertheless, their widespread use is somehow hindered because of their cost, availability, and batch-to-batch reproducibility. Here, we report the catalytic proficiency of a miniaturized synthetic peroxidase, Fe-Mimochrome VI*a, in the decolorization of four organic dyes, as representatives of either the heterocyclic or triarylmethane class of dyes. Fe-Mimochrome VI*a performed over 130 turnovers in less than five minutes in an aqueous buffer at a neutral pH under mild conditions.

Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology-A review

Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization of lignin, oxidative cleavage of xenobiotics and phenolics. LMEs implementation in the biotechnological and industrial sectors has sparked significant attention, although its potential future applications remain underexploited. To understand the mechanism of LMEs in sustainable pollution mitigation, several studies have been undertaken to assess the feasibility of LMEs in correlating to diverse pollutants for binding and intermolecular interactions at the molecular level. However, further investigation is required to fully comprehend the underlying mechanism. In this review we presented the key structural and functional features of LMEs, including the computational aspects, as well as the advanced applications in biotechnology and industrial research. Furthermore, concluding remarks and a look ahead, the use of LMEs coupled with computational frameworks, built upon artificial intelligence (AI) and machine learning (ML), has been emphasized as a recent milestone in environmental research.

Computational design and molecular dynamics simulations suggest the mode of substrate binding in ceramide synthases

Until now, membrane-protein stabilization has relied on iterations of mutations and screening. We now validate a one-step algorithm, mPROSS, for stabilizing membrane proteins directly from an AlphaFold2 model structure. Applied to the lipid-generating enzyme, ceramide synthase, 37 designed mutations lead to a more stable form of human CerS2. Together with molecular dynamics simulations, we propose a pathway by which substrates might be delivered to the ceramide synthases.

Data-driven strategies for the computational design of enzyme thermal stability: trends, perspectives, and prospects

Thermal stability is one of the most important properties of enzymes, which sustains life and determines the potential for the industrial application of biocatalysts. Although traditional methods such as directed evolution and classical rational design contribute greatly to this field, the enormous sequence space of proteins implies costly and arduous experiments. The development of enzyme engineering focuses on automated and efficient strategies because of the breakthrough of high-throughput DNA sequencing and machine learning models. In this review, we propose a data-driven architecture for enzyme thermostability engineering and summarize some widely adopted datasets, as well as machine learning-driven approaches for designing the thermal stability of enzymes. In addition, we present a series of existing challenges while applying machine learning in enzyme thermostability design, such as the data dilemma, model training, and use of the proposed models. Additionally, a few promising directions for enhancing the performance of the models are discussed. We anticipate that the efficient incorporation of machine learning can provide more insights and solutions for the design of enzyme thermostability in the coming years.

Repertoire of Computationally Designed Peroxygenases for Enantiodivergent C-H Oxyfunctionalization Reactions

The generation of enantiodivergent biocatalysts for C-H oxyfunctionalizations is ever more important in modern synthetic chemistry. Here, we have applied the FuncLib algorithm based on phylogenetic and Rosetta calculations to design a diverse repertoire of active, stable, and enantiodivergent fungal peroxygenases. 24 designs, each carrying 4-5 mutations in the catalytic core, were expressed functionally in yeast and benchmarked against characteristic model compounds. Several designs were active and stable in a range of temperature and pH, displaying unprecedented enantiodivergence, changing regioselectivity from alkyl to aromatic hydroxylation, and increasing catalytic efficiencies up to 10-fold, with 15-fold improvements in total turnover numbers over the parental enzyme. We find that this dramatic functional divergence stems from beneficial epistasis among the mutations and an extensive reorganization of the heme channel. Our work demonstrates that FuncLib can rapidly design highly functional libraries enriched in enantioselective peroxygenases not seen in nature for a range of biotechnological applications.

Creative biological lignin conversion routes toward lignin valorization

Lignin, the largest renewable aromatic resource, is a promising alternative feedstock for the sustainable production of various chemicals, fuels, and materials. Despite this potential, lignin is characterized by heterogeneous and macromolecular structures that must be addressed. In this review, we present biological lignin conversion routes (BLCRs) that offer opportunities for overcoming these challenges, making lignin valorization feasible. Funneling heterogeneous aromatics via a 'biological funnel' offers a high-specificity bioconversion route for aromatic platform chemicals. The inherent aromaticity of lignin drives atom-economic functionalization routes toward aromatic natural product generation. By harnessing the ligninolytic capacities of specific microbial systems, powerful aromatic ring-opening routes can be developed to generate various value-added products. Thus, BLCRs hold the promise to make lignin valorization feasible and enable a lignocellulose-based bioeconomy.

Designed High-Redox Potential Laccases Exhibit High Functional Diversity

White-rot fungi secrete an impressive repertoire of high-redox potential laccases (HRPLs) and peroxidases for efficient oxidation and utilization of lignin. Laccases are attractive enzymes for the chemical industry due to their broad substrate range and low environmental impact. Since expression of functional recombinant HRPLs is challenging, however, iterative-directed evolution protocols have been applied to improve their expression, activity, and stability. We implement a rational, stabilize-and-diversify strategy to two HRPLs that we could not functionally express. First, we use the PROSS stability-design algorithm to allow functional expression in yeast. Second, we use the stabilized enzymes as starting points for FuncLib active-site design to improve their activity and substrate diversity. Four of the FuncLib-designed HRPLs and their PROSS progenitor exhibit substantial diversity in reactivity profiles against high-redox potential substrates, including lignin monomers. Combinations of 3-4 subtle mutations that change the polarity, solvation, and sterics of the substrate-oxidation site result in orders of magnitude changes in reactivity profiles. These stable and versatile HRPLs are a step toward generating an effective lignin-degrading consortium of enzymes that can be secreted from yeast. The stabilize-and-diversify strategy can be applied to other challenging enzyme families to study and expand the utility of natural enzymes.

Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations

Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.

What Have We Learned from Design of Function in Large Proteins?

The overarching goal of computational protein design is to gain complete control over protein structure and function. The majority of sophisticated binders and enzymes, however, are large and exhibit diverse and complex folds that defy atomistic design calculations. Encouragingly, recent strategies that combine evolutionary constraints from natural homologs with atomistic calculations have significantly improved design accuracy. In these approaches, evolutionary constraints mitigate the risk from misfolding and aggregation, focusing atomistic design calculations on a small but highly enriched sequence subspace. Such methods have dramatically optimized diverse proteins, including vaccine immunogens, enzymes for sustainable chemistry, and proteins with therapeutic potential. The new generation of deep learning-based ab initio structure predictors can be combined with these methods to extend the scope of protein design, in principle, to any natural protein of known sequence. We envision that protein engineering will come to rely on completely computational methods to efficiently discover and optimize biomolecular activities.