What makes a protein fold amenable to functional innovation? Fold polarity and stability trade-offs

Addressing epistasis in the design of protein function

Mutations in protein active sites can dramatically improve function. The active site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated in combination with others in a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants and dramatically slows natural and lab evolutionary processes. Research has shed light on the molecular origins of epistasis and its role in shaping evolutionary trajectories and outcomes. In addition, sequence- and AI-based strategies that infer epistatic relationships from mutational patterns in natural or experimental evolution data have been used to design functional protein variants. In recent years, combinations of such approaches and atomistic design calculations have successfully predicted highly functional combinatorial mutations in active sites. These were used to design thousands of functional active-site variants, demonstrating that, while our understanding of epistasis remains incomplete, some of the determinants that are critical for accurate design are now sufficiently understood. We conclude that the space of active-site variants that has been explored by evolution may be expanded dramatically to enhance natural activities or discover new ones. Furthermore, design opens the way to systematically exploring sequence and structure space and mutational impacts on function, deepening our understanding and control over protein activity.

Automated Flow Peptide Synthesis Enables Engineering of Proteins with Stabilized Transient Binding Pockets

Engineering at the amino acid level is key to enhancing the properties of existing proteins in a desired manner. So far, protein engineering has been dominated by genetic approaches, which have been extremely powerful but only allow for minimal variations beyond the canonical amino acids. Chemical peptide synthesis allows the unrestricted incorporation of a vast set of unnatural amino acids with much broader functionalities, including the incorporation of post-translational modifications or labels. Here we demonstrate the potential of chemical synthesis to generate proteins in a specific conformation, which would have been unattainable by recombinant protein expression. We use recently established rapid automated flow peptide synthesis combined with solid-phase late-stage modifications to rapidly generate a set of FK506-binding protein 51 constructs bearing defined intramolecular lactam bridges. This trapped an otherwise rarely populated transient pocket-as confirmed by crystal structures-which led to an up to 39-fold improved binding affinity for conformation-selective ligands and represents a unique system for the development of ligands for this rare conformation. Overall, our results show how rapid automated flow peptide synthesis can be applied to precision protein engineering.

Adaptive Capacity of a DNA Polymerase Clamp-loader ATPase Complex

The ability of mutations to facilitate adaptation is central to evolution. To understand how mutations can lead to functional adaptation in a complex molecular machine, we created a defective version of the T4 clamp-loader complex, which is essential for DNA replication. This variant, which is ∼5,000-fold less active than the wild type, was made by replacing the catalytic domains with those from another phage. A directed-evolution experiment revealed that multiple substitutions to a single negatively charged residue in the chimeric clamp loader-Asp 86-restore fitness to within ∼20-fold of wild type. These mutations remove an adventitious electrostatic repulsive interaction between Asp 86 and the sliding clamp. Thus, the fitness decrease of the chimeric clamp loader is caused by a reduction in affinity between the clamp loader and the clamp. Deep mutagenesis shows that the reduced fitness of the chimeric clamp loader is also compensated for by lysine and arginine substitutions of several DNA-proximal residues in the clamp loader or the sliding clamp. Our results demonstrate that there is a latent capacity for increasing the affinity of the clamp loader for DNA and the sliding clamp, such that even single-point mutations can readily compensate for the loss of function due to suboptimal interactions elsewhere.

Hyperstable Synthetic Mini-Proteins as Effective Ligand Scaffolds

Small, single-domain protein scaffolds are compelling sources of molecular binding ligands with the potential for efficient physiological transport, modularity, and manufacturing. Yet, mini-proteins require a balance between biophysical robustness and diversity to enable new functions. We tested the developability and evolvability of millions of variants of 43 designed libraries of synthetic 40-amino acid βαββ proteins with diversified sheet, loop, or helix paratopes. We discovered a scaffold library that yielded hundreds of binders to seven targets while exhibiting high stability and soluble expression. Binder discovery yielded 6-122 nM affinities without affinity maturation and Tms averaging ≥78 °C. Broader βαββ libraries exhibited varied developability and evolvability. Sheet paratopes were the most consistently developable, and framework 1 was the most evolvable. Paratope evolvability was dependent on target, though several libraries were evolvable across many targets while exhibiting high stability and soluble expression. Select βαββ proteins are strong starting points for engineering performant binders.

Determinants of Developability and Evolvability of Synthetic Miniproteins as Ligand Scaffolds

Binding ligands empower molecular therapeutics and diagnostics. Despite an array of protein scaffolds engineered for binding, the biophysical elements that drive developability and evolvability are not fully understood. In particular, engineering novel function while maintaining biophysical integrity within the context of small, single-domain proteins is challenged by integration of the structural framework and the evolved binding site. Miniproteins present a challenge to our limits of protein engineering capability and provide advantages in physiological targeting, modularity for multi-functional constructs, and unique binding modes. Herein, we evaluate the ability of hyperstable synthetic miniproteins, originally designed for foldedness, to function as binding scaffolds. We synthesized 45 combinatorial libraries, with 109 variants, systematically varied across two topologies, each with five starting frameworks and four or five diverse, structurally distinct paratopes, to elucidate their impact on evolvability and developability. We evaluated evolvability with yeast display binding selections against four targets. High-throughput assays -stability via yeast display and soluble expression via split-GFP in E. coli - measured developability. The comprehensive, robust dataset demonstrates how protein topology, parental framework, and paratope structure and location all impact scaffold performance. A hyperstable framework and localized diversity are not sufficient for an effective scaffold, but several designs of these elements within synthetic miniproteins designed solely for stability result in scaffold libraries with effective evolvability and developability. Engineered variants were well-folded, thermally stable, and bound target with single-digit nanomolar affinity. Thus, hyperstable synthetic miniproteins can serve as precursors to developable, evolvable mini-scaffolds with unique potential for physiological transport, modularity, and binding modes.

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.

Conformational Behavior of SARS-Cov-2 Spike Protein Variants: Evolutionary Jumps in Sequence Reverberate in Structural Dynamic Differences

SARS-CoV-2 has evolved rapidly in the first 3 years of pandemic diffusion. The initial evolution of the virus appeared to proceed through big jumps in sequence changes rather than through the stepwise accumulation of point mutations on already established variants. Here, we examine whether this nonlinear mutational process reverberates in variations of the conformational dynamics of the SARS-CoV-2 Spike protein (S-protein), the first point of contact between the virus and the human host. We run extensive microsecond-scale molecular dynamics simulations of seven distinct variants of the protein in their fully glycosylated state and set out to elucidate possible links between the mutational spectrum of the S-protein and the structural dynamics of the respective variant, at global and local levels. The results reveal that mutation-dependent structural and dynamic modulations mostly consist of increased coordinated motions in variants that acquire stability and in an increased internal flexibility in variants that are less stable. Importantly, a limited number of functionally important substructures (the receptor binding domain, in particular) share the same time of movements in all variants, indicating efficient preorganization for functional regions dedicated to host interactions. Our results support a model in which the internal dynamics of the S-proteins from different strains varies in a way that reflects the observed random and non-stepwise jumps in sequence evolution, while conserving the functionally oriented traits of conformational dynamics necessary to support productive interactions with host receptors.

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.

Combinatorial assembly and design of enzymes

The design of structurally diverse enzymes is constrained by long-range interactions that are necessary for accurate folding. We introduce an atomistic and machine learning strategy for the combinatorial assembly and design of enzymes (CADENZ) to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a 10-fold improved hit rate and more than 10,000 recovered enzymes. This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.

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.

Experimental and In Silico Analysis of TEM β-Lactamase Adaptive Evolution

Multiple mutations often have non-additive (epistatic) phenotypic effects. Epistasis is of fundamental biological relevance but is not well understood mechanistically. Adaptive evolution, i.e., the evolution of new biochemical activities, is rich in epistatic interactions. To better understand the principles underlying epistasis during genetic adaptation, we studied the evolution of TEM-1 β-lactamase variants exhibiting cefotaxime resistance. We report the collection of a library of 487 observed evolutionary trajectories for TEM-1 and determine the epistasis status based on cefotaxime resistance phenotype for 206 combinations of 2-3 TEM-1 mutations involving 17 positions under adaptive selective pressure. Gain-of-function (GOF) mutations are gatekeepers for adaptation. To see if GOF phenotypes can be inferred based solely on sequence data, we calculated the enrichment of GOF mutations in the different categories of epistatic pairs. Our results suggest that this is possible because GOF mutations are particularly enriched in sign and reciprocal sign epistasis, which leave a major imprint on the sequence space accessible to evolution. We also used FoldX to explore the relationship between thermodynamic stability and epistasis. We found that mutations in observed evolutionary trajectories tend to destabilize the folded structure of the protein, albeit their cumulative effects are consistently below the protein's free energy of folding. The destabilizing effect is stronger for epistatic pairs, suggesting that modest or local alterations in folding stability can modulate catalysis. Finally, we report a significant relationship between epistasis and the degree to which two protein positions are structurally and dynamically coupled, even in the absence of ligand.

Design and optimization of enzymatic activity in a de novo β-barrel scaffold

While native scaffolds offer a large diversity of shapes and topologies for enzyme engineering, their often unpredictable behavior in response to sequence modification makes de novo generated scaffolds an exciting alternative. Here we explore the customization of the backbone and sequence of a de novo designed eight stranded β-barrel protein to create catalysts for a retro-aldolase model reaction. We show that active and specific catalysts can be designed in this fold and use directed evolution to further optimize activity and stereoselectivity. Our results support previous suggestions that different folds have different inherent amenability to evolution and this property could account, in part, for the distribution of natural enzymes among different folds.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Natural Evolution Provides Strong Hints about Laboratory Evolution of Designer Enzymes

Laboratory evolution combined with computational enzyme design provides the opportunity to generate novel biocatalysts. Nevertheless, it has been challenging to understand how laboratory evolution optimizes designer enzymes by introducing seemingly random mutations. A typical enzyme optimized with laboratory evolution is the abiological Kemp eliminase, initially designed by grafting active site residues into a natural protein scaffold. Here, we relate the catalytic power of laboratory-evolved Kemp eliminases to the statistical energy ([Formula: see text]) inferred from their natural homologous sequences using the maximum entropy model. The [Formula: see text] of designs generated by directed evolution is correlated with enhanced activity and reduced stability, thus displaying a stability-activity trade-off. In contrast, the [Formula: see text] for mutants in catalytic-active remote regions (in which remote residues are important for catalysis) is strongly anticorrelated with the activity. These findings provide an insight into the role of protein scaffolds in the adaption to new enzymatic functions. It also indicates that the valley in the [Formula: see text] landscape can guide enzyme design for abiological catalysis. Overall, the connection between laboratory and natural evolution contributes to understanding what is optimized in the laboratory and how new enzymatic function emerges in nature, and provides guidance for computational enzyme design.

Enabling Role of Ligand-Driven Conformational Changes in Enzyme Evolution

Many enzymes that show a large specificity in binding the enzymatic transition state with a higher affinity than the substrate utilize substrate binding energy to drive protein conformational changes to form caged substrate complexes. These protein cages provide strong stabilization of enzymatic transition states. Using part of the substrate binding energy to drive the protein conformational change avoids a similar strong stabilization of the Michaelis complex and irreversible ligand binding. A seminal step in the development of modern enzyme catalysts was the evolution of enzymes that couple substrate binding to a conformational change. These include enzymes that function in glycolysis (triosephosphate isomerase), the biosynthesis of lipids (glycerol phosphate dehydrogenase), the hexose monophosphate shunt (6-phosphogluconate dehydrogenase), and the mevalonate pathway (isopentenyl diphosphate isomerase), catalyze the final step in the biosynthesis of pyrimidine nucleotides (orotidine monophosphate decarboxylase), and regulate the cellular levels of adenine nucleotides (adenylate kinase). The evolution of enzymes that undergo ligand-driven conformational changes to form active protein-substrate cages is proposed to proceed by selection of variants, in which the selected side chain substitutions destabilize a second protein conformer that shows compensating enhanced binding interactions with the substrate. The advantages inherent to enzymes that incorporate a conformational change into the catalytic cycle provide a strong driving force for the evolution of flexible protein folds such as the TIM barrel. The appearance of these folds represented a watershed event in enzyme evolution that enabled the rapid propagation of enzyme activities within enzyme superfamilies.

Dan Tawfik's Lessons for Protein Engineers about Enzymes Adapting to New Substrates

Natural evolution has been creating new complex systems for billions of years. The process is spontaneous and requires neither intelligence nor moral purpose but is nevertheless difficult to understand. The late Dan Tawfik spent years studying enzymes as they adapted to recognize new substrates. Much of his work focused on gaining fundamental insights, so the practical utility of his experiments may not be obvious even to accomplished protein engineers. Here we focus on two questions fundamental to any directed evolution experiment. Which proteins are the best starting points for such experiments? Which trait(s) of the chosen parental protein should be evolved to achieve the desired outcome? We summarize Tawfik's contributions to our understanding of these problems, to honor his memory and encourage those unfamiliar with his ideas to read his publications.

Mechanisms of protein evolution

How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

Fate of carotenoids in yeasts: synthesis and cleavage

Carotenoids and their cleavage products (norisoprenoids) have excellent functional properties with diverse applications in foods, medicaments, cosmetics, etc. Carotenoids can be oxidatively cleaved through nonspecific reactions or by carotenoid cleavage oxygenases (CCOs), the product of which could further modify food flavor. This review provides comprehensive information on both carotenoid synthesis and cleavage processes with emphasis on enzyme characterization and biosynthetic pathway optimization. The use of interdisciplinary approaches of bioengineering and computer-aided experimental technology for key enzyme modification and systematic pathway design is beneficial to monitor metabolic pathways and assess pathway bottlenecks, which could efficiently lead to accumulation of carotenoids in microorganisms. The identification of CCOs spatial structures isolated from different species has made a significant contribution to the current state of knowledge. Current trends in carotenoid-related flavor modification are also discussed. In particular, we propose the carotenoid-synthesizing yeast Rhodotorula spp. for the production of food bioactive compounds. Understanding the behavior underlying the formation of norisoprenoids from carotenoids using interdisciplinary approaches may point toward other areas of investigation that could lead to better exploiting the potential use of autochthonous yeast in flavor enhancement.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Switching an active site helix in dihydrofolate reductase reveals limits to subdomain modularity

To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.

SARS-CoV-2 Spike Protein Mutations and Escape from Antibodies: A Computational Model of Epitope Loss in Variants of Concern

The SARS-CoV-2 spike (S) protein is exposed on the viral surface and is the first point of contact between the virus and the host. For these reasons it represents the prime target for Covid-19 vaccines. In recent months, variants of this protein have started to emerge. Their ability to reduce or evade recognition by S-targeting antibodies poses a threat to immunological treatments and raises concerns for their consequences on vaccine efficacy. To develop a model able to predict the potential impact of S-protein mutations on antibody binding sites, we performed unbiased multi-microsecond molecular dynamics of several glycosylated S-protein variants and applied a straightforward structure-dynamics-energy based strategy to predict potential changes in immunogenic regions on each variant. We recover known epitopes on the reference D614G sequence. By comparing our results, obtained on isolated S-proteins in solution, to recently published data on antibody binding and reactivity in new S variants, we directly show that modifications in the S-protein consistently translate into the loss of potentially immunoreactive regions. Our findings can thus be qualitatively reconnected to the experimentally characterized decreased ability of some of the Abs elicited against the dominant S-sequence to recognize variants. While based on the study of SARS-CoV-2 spike variants, our computational epitope-prediction strategy is portable and could be applied to study immunoreactivity in mutants of proteins of interest whose structures have been characterized, helping the development/selection of vaccines and antibodies able to control emerging variants.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution

Darwinian evolution preferentially follows mutational pathways whose individual steps increase fitness. Alternative pathways with mutational steps that do not increase fitness are less accessible. Here, we show that mistranslation, the erroneous incorporation of amino acids into nascent proteins, can increase the accessibility of such alternative pathways and, ultimately, of high fitness genotypes. We subject populations of the beta‐lactamase TEM‐1 to directed evolution in Escherichia coli under both low‐ and high‐mistranslation rates, selecting for high activity on the antibiotic cefotaxime. Under low mistranslation rates, different evolving TEM‐1 populations ascend the same high cefotaxime‐resistance peak, which requires three canonical DNA mutations. In contrast, under high mistranslation rates they ascend three different high cefotaxime‐resistance genotypes, which leads to higher genotypic diversity among populations. We experimentally reconstruct the adaptive DNA mutations and the potential evolutionary paths to these high cefotaxime‐resistance genotypes. This reconstruction shows that some of the DNA mutations do not change fitness under low mistranslation, but cause a significant increase in fitness under high‐mistranslation, which helps increase the accessibility of different high cefotaxime‐resistance genotypes. In addition, these mutations form a network of pairwise epistatic interactions that leads to mutually exclusive evolutionary trajectories towards different high cefotaxime‐resistance genotypes. Our observations demonstrate that protein mistranslation and the phenotypic mutations it causes can alter the evolutionary exploration of fitness landscapes and reduce the predictability of evolution.

Local interactions with the Glu166 base and the conformation of an active site loop play key roles in carbapenem hydrolysis by the KPC-2 β-lactamase

The Klebsiella pneumoniae carbapenemase-2 (KPC-2) is a common source of antibiotic resistance in Gram-negative bacterial infections. KPC-2 is a class A β-lactamase that exhibits a broad substrate profile and hydrolyzes most β-lactam antibiotics including carbapenems owing to rapid deacylation of the covalent acyl-enzyme intermediate. However, the features that allow KPC-2 to deacylate substrates more rapidly than non-carbapenemase enzymes are not clear. The active-site residues in KPC-2 are largely conserved in sequence and structure compared with non-carbapenemases, suggesting that subtle alterations may collectively facilitate hydrolysis of carbapenems. We utilized a nonbiased genetic approach to identify mutants deficient in carbapenem hydrolysis but competent for ampicillin hydrolysis. Subsequent pre–steady-state enzyme kinetics analyses showed that the substitutions slow the rate of deacylation of carbapenems. Structure determination via X-ray diffraction indicated that a F72Y mutant forms a hydrogen bond between the tyrosine hydroxyl group and Glu166, which may lower basicity and impair the activation of the catalytic water for deacylation, whereas several mutants impact the structure of the Q214-R220 active site loop. A T215P substitution lowers the deacylation rate and drastically alters the conformation of the loop, thereby disrupting interactions between the enzyme and the carbapenem acyl-enzyme intermediate. Thus, the environment of the Glu166 general base and the precise placement and conformational stability of the Q214-R220 loop are critical for efficient deacylation of carbapenems by the KPC-2 enzyme. Therefore, the design of carbapenem antibiotics that interact with Glu166 or alter the Q214-R220 loop conformation may disrupt enzyme function and overcome resistance.

Inhibition of the Clostridioides difficile Class D β-Lactamase CDD-1 by Avibactam

Avibactam is a potent diazobicyclooctane inhibitor of class A and C β-lactamases. The inhibitor also exhibits variable activity against some class D enzymes from Gram-negative bacteria; however, its interaction with recently discovered class D β-lactamases from Gram-positive bacteria has not been studied. Here, we describe microbiological, kinetic, and mass spectrometry studies of the interaction of avibactam with CDD-1, a class D β-lactamase from the clinically important pathogen Clostridioides difficile, and show that avibactam is a potent irreversible mechanism-based inhibitor of the enzyme. X-ray crystallographic studies at three time-points demonstrate the rapid formation of a stable CDD-1-avibactam acyl-enzyme complex and highlight differences in the anchoring of the inhibitor by class D enzymes from Gram-positive and Gram-negative bacteria.

A novel framework for engineering protein loops exploring length and compositional variation

Insertions and deletions (indels) are known to affect function, biophysical properties and substrate specificity of enzymes, and they play a central role in evolution. Despite such clear significance, this class of mutation remains an underexploited tool in protein engineering with few available platforms capable of systematically generating and analysing libraries of varying sequence composition and length. We present a novel DNA assembly platform (InDel assembly), based on cycles of endonuclease restriction digestion and ligation of standardised dsDNA building blocks, that can generate libraries exploring both composition and sequence length variation. In addition, we developed a framework to analyse the output of selection from InDel-generated libraries, combining next generation sequencing and alignment-free strategies for sequence analysis. We demonstrate the approach by engineering the well-characterized TEM-1 β-lactamase Ω-loop, involved in substrate specificity, identifying multiple novel extended spectrum β-lactamases with loops of modified length and composition-areas of the sequence space not previously explored. Together, the InDel assembly and analysis platforms provide an efficient route to engineer protein loops or linkers where sequence length and composition are both essential functional parameters.

Parameters and determinants of responses to selection in antibody libraries

The sequences of antibodies from a given repertoire are highly diverse at few sites located on the surface of a genome-encoded larger scaffold. The scaffold is often considered to play a lesser role than highly diverse, non-genome-encoded sites in controlling binding affinity and specificity. To gauge the impact of the scaffold, we carried out quantitative phage display experiments where we compare the response to selection for binding to four different targets of three different antibody libraries based on distinct scaffolds but harboring the same diversity at randomized sites. We first show that the response to selection of an antibody library may be captured by two measurable parameters. Second, we provide evidence that one of these parameters is determined by the degree of affinity maturation of the scaffold, affinity maturation being the process by which antibodies accumulate somatic mutations to evolve towards higher affinities during the natural immune response. In all cases, we find that libraries of antibodies built around maturated scaffolds have a lower response to selection to other arbitrary targets than libraries built around germline-based scaffolds. We thus propose that germline-encoded scaffolds have a higher selective potential than maturated ones as a consequence of a selection for this potential over the long-term evolution of germline antibody genes. Our results are a first step towards quantifying the evolutionary potential of biomolecules.

Antibodies in the immune system consist of a genetically encoded scaffold that exposes a few highly diverse, non-genetically encoded sites. This focused diversity is sufficient to produce antibodies that bind to any target molecule. To understand the role of the scaffold, which acquires hypermutations during the immune response, over the selective response, we analyze quantitative in vitro experiments where large antibody populations based on different scaffolds are selected against different targets. We show that selective responses are described statistically by two parameters, one of which depends on prior evolution of the scaffold as part of a previous response. Our work provides methods to assay whether naïve antibody scaffolds are endowed with a distinctively high selective potential.

Linking molecular evolution to molecular grafting

Molecular grafting is a strategy for the engineering of molecular scaffolds into new functional agents, such as next-generation therapeutics. Despite its wide use, studies so far have focused almost exclusively on demonstrating its utility rather than understanding the factors that lead to either poor or successful grafting outcomes. Here, we examine protein evolution and identify parallels between the natural process of protein functional diversification and the artificial process of molecular grafting. We discuss features of natural proteins that are correlated to innovability-the capacity to acquire new functions-and describe their implications to molecular grafting scaffolds. Disulfide-rich peptides are used as exemplars because they are particularly promising scaffolds onto which new functions can be grafted. This article provides a perspective on why some scaffolds are more suitable for grafting than others, identifying opportunities on how molecular grafting might be improved.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion

De novo protein design has succeeded in generating a large variety of globular proteins, but the construction of protein scaffolds with cavities that could accommodate large signaling molecules, cofactors, and substrates remains an outstanding challenge. The long, often flexible loops that form such cavities in many natural proteins are difficult to precisely program and thus challenging for computational protein design. Here we describe an alternative approach to this problem. We fused two stable proteins with C2 symmetry-a de novo designed dimeric ferredoxin fold and a de novo designed TIM barrel-such that their symmetry axes are aligned to create scaffolds with large cavities that can serve as binding pockets or enzymatic reaction chambers. The crystal structures of two such designs confirm the presence of a 420 cubic Ångström chamber defined by the top of the designed TIM barrel and the bottom of the ferredoxin dimer. We functionalized the scaffold by installing a metal-binding site consisting of four glutamate residues close to the symmetry axis. The protein binds lanthanide ions with very high affinity as demonstrated by tryptophan-enhanced terbium luminescence. This approach can be extended to other metals and cofactors, making this scaffold a modular platform for the design of binding proteins and biocatalysts.

Comprehensive exploration of the translocation, stability and substrate recognition requirements in VIM-2 lactamase

Metallo-β-lactamases (MBLs) degrade a broad spectrum of β-lactam antibiotics, and are a major disseminating source for multidrug resistant bacteria. Despite many biochemical studies in diverse MBLs, molecular understanding of the roles of residues in the enzyme's stability and function, and especially substrate specificity, is lacking. Here, we employ deep mutational scanning (DMS) to generate comprehensive single amino acid variant data on a major clinical MBL, VIM-2, by measuring the effect of thousands of VIM-2 mutants on the degradation of three representative classes of β-lactams (ampicillin, cefotaxime, and meropenem) and at two different temperatures (25°C and 37°C). We revealed residues responsible for expression and translocation, and mutations that increase resistance and/or alter substrate specificity. The distribution of specificity-altering mutations unveiled distinct molecular recognition of the three substrates. Moreover, these function-altering mutations are frequently observed among naturally occurring variants, suggesting that the enzymes have continuously evolved to become more potent resistance genes.

Antagonism between substitutions in β-lactamase explains a path not taken in the evolution of bacterial drug resistance

CTX-M β-lactamases are widespread in Gram-negative bacterial pathogens and provide resistance to the cephalosporin cefotaxime but not to the related antibiotic ceftazidime. Nevertheless, variants have emerged that confer resistance to ceftazidime. Two natural mutations, causing P167S and D240G substitutions in the CTX-M enzyme, result in 10-fold increased hydrolysis of ceftazidime. Although the combination of these mutations would be predicted to increase ceftazidime hydrolysis further, the P167S/D240G combination has not been observed in a naturally occurring CTX-M variant. Here, using recombinantly expressed enzymes, minimum inhibitory concentration measurements, steady-state enzyme kinetics, and X-ray crystallography, we show that the P167S/D240G double mutant enzyme exhibits decreased ceftazidime hydrolysis, lower thermostability, and decreased protein expression levels compared with each of the single mutants, indicating negative epistasis. X-ray structures of mutant enzymes with covalently trapped ceftazidime suggested that a change of an active-site Ω-loop to an open conformation accommodates ceftazidime leading to enhanced catalysis. 10-μs molecular dynamics simulations further correlated Ω-loop opening with catalytic activity. We observed that the WT and P167S/D240G variant with acylated ceftazidime both favor a closed conformation not conducive for catalysis. In contrast, the single substitutions dramatically increased the probability of open conformations. We conclude that the antagonism is due to restricting the conformation of the Ω-loop. These results reveal the importance of conformational heterogeneity of active-site loops in controlling catalytic activity and directing evolutionary trajectories.

Active Site-Induced Evolutionary Constraints Follow Fold Polarity Principles in Soluble Globular Enzymes

A recent analysis of evolutionary rates in >500 globular soluble enzymes revealed pervasive conservation gradients toward catalytic residues. By looking at amino acid preference profiles rather than evolutionary rates in the same data set, we quantified the effects of active sites on site-specific constraints for physicochemical traits. We found that conservation gradients respond to constraints for polarity, hydrophobicity, flexibility, rigidity and structure in ways consistent with fold polarity principles; while sites far from active sites seem to experience no physicochemical constraint, rather being highly variable and favoring amino acids of low metabolic cost. Globally, our results highlight that amino acid variation contains finer information about protein structure than usually regarded in evolutionary models, and that this information is retrievable automatically with simple fits. We propose that analyses of the kind presented here incorporated into models of protein evolution should allow for better description of the physical chemistry that underlies molecular evolution.

Structural and mechanistic aspects of carotenoid cleavage dioxygenases (CCDs)

Carotenoid cleavage dioxygenases (CCDs) comprise a superfamily of mononuclear non-heme iron proteins that catalyze the oxygenolytic fission of alkene bonds in carotenoids to generate apocarotenoid products. Some of these enzymes exhibit additional activities such as carbon skeleton rearrangement and trans-cis isomerization. The group also includes a subfamily of enzymes that split the interphenyl alkene bond in molecules such as resveratrol and lignostilbene. CCDs are involved in numerous biological processes ranging from production of light-sensing chromophores to degradation of lignin derivatives in pulping waste sludge. These enzymes exhibit unique features that distinguish them from other families of non-heme iron enzymes. The distinctive properties and biological importance of CCDs have stimulated interest in their modes of catalysis. Recent structural, spectroscopic, and computational studies have helped clarify mechanistic aspects of CCD catalysis. Here, we review these findings emphasizing common and unique properties of CCDs that enable their variable substrate specificity and regioselectivity. This article is part of a Special Issue entitled Carotenoids recent advances in cell and molecular biology edited by Johannes von Lintig and Loredana Quadro.

Structure-Based Analysis of Cryptic-Site Opening

Many proteins in their unbound structures have cryptic sites that are not appropriately sized for drug binding. We consider here 32 proteins from the recently published CryptoSite set with validated cryptic sites, and study whether the sites remain cryptic in all available X-ray structures of the proteins solved without any ligand bound near the sites. It was shown that only few of these proteins have binding pockets that never form without ligand binding. Sites that are cryptic in some structures but spontaneously form in others are also rare. In most proteins the forming of pockets is affected by mutations or ligand binding at locations far from the cryptic site. To further explore these mechanisms, we applied adiabatic biased molecular dynamics simulations to guide the proteins from their ligand-free structures to ligand-bound conformations, and studied the distribution of druggability scores of the pockets located at the cryptic sites.

The modular structure of α/β-hydrolases

The α/β-hydrolase fold family is highly diverse in sequence, structure and biochemical function. To investigate the sequence-structure-function relationships, the Lipase Engineering Database (https://led.biocatnet.de) was updated. Overall, 280 638 protein sequences and 1557 protein structures were analysed. All α/β-hydrolases consist of the catalytically active core domain, but they might also contain additional structural modules, resulting in 12 different architectures: core domain only, additional lids at three different positions, three different caps, additional N- or C-terminal domains and combinations of N- and C-terminal domains with caps and lids respectively. In addition, the α/β-hydrolases were distinguished by their oxyanion hole signature (GX-, GGGX- and Y-types). The N-terminal domains show two different folds, the Rossmann fold or the β-propeller fold. The C-terminal domains show a β-sandwich fold. The N-terminal β-propeller domain and the C-terminal β-sandwich domain are structurally similar to carbohydrate-binding proteins such as lectins. The classification was applied to the newly discovered polyethylene terephthalate (PET)-degrading PETases and MHETases, which are core domain α/β-hydrolases of the GX- and the GGGX-type respectively. To investigate evolutionary relationships, sequence networks were analysed. The degree distribution followed a power law with a scaling exponent γ = 1.4, indicating a highly inhomogeneous network which consists of a few hubs and a large number of less connected sequences. The hub sequences have many functional neighbours and therefore are expected to be robust toward possible deleterious effects of mutations. The cluster size distribution followed a power law with an extrapolated scaling exponent τ = 2.6, which strongly supports the connectedness of the sequence space of α/β-hydrolases. DATABASE: Supporting data about domains from other proteins with structural similarity to the N- or C-terminal domains of α/β-hydrolases are available in Data Repository of the University of Stuttgart (DaRUS) under doi: https://doi.org/10.18419/darus-458.

Sequence Determinants of Substrate Ambiguity in a HAD Phosphosugar Phosphatase of Arabidopsis Thaliana

The Arabidopsis thaliana broad-range sugar phosphate phosphatase AtSgpp (NP_565895.1, locus AT2G38740) and the specific DL-glycerol-3-phosphatase AtGpp (NP_568858.1, locus AT5G57440) are members of the wide family of magnesium-dependent acid phosphatases subfamily I with the C1-type cap domain haloacid dehalogenase-like hydrolase proteins (HAD). Although both AtSgpp and AtGpp have a superimporsable α/β Rossmann core active site, they differ with respect to the loop-5 of the cap domain, accounting for the differences in substrate specificity. Recent functional studies have demonstrated the essential but not sufficient role of the signature sequence within the motif-5 in substrate discrimination. To better understand the mechanism underlying the control of specificity, we explored additional sequence determinants underpinning the divergent evolutionary selection exerted on the substrate affinity of both enzymes. The most evident difference was found in the loop preceding the loop-5 of the cap domain, which is extended in three additional residues in AtSgpp. To determine if the shortening of this loop would constrain the substrate ambiguity of AtSgpp, we deleted these three aminoacids. The kinetic analyses of the resulting mutant protein AtSgpp3Δ (ΔF53, ΔN54, ΔN55) indicate that promiscuity is compromised. AtSgpp3Δ displays highest level of discrimination for D-ribose-5-phosphate compared to the rest of phosphate ester metabolites tested, which may suggest a proper orientation of D-ribose-5-phosphate in the AtSgpp3Δ active site.

Limits to Compensatory Mutations: Insights from Temperature-Sensitive Alleles

Previous experiments with temperature-sensitive mutants of the yeast enzyme orotidine 5'-phosphate decarboxylase (encoded in gene URA3) yielded the unexpected result that reversion occurs only through exact reversal of the original mutation (Jakubowska A, Korona R. 2009. Lack of evolutionary conservation at positions important for thermal stability in the yeast ODCase protein. Mol Biol Evol. 26(7):1431-1434.). We recreated a set of these mutations in which the codon had two nucleotide substitutions, making exact reversion much less likely. We screened these double mutants for reversion and obtained a number of compensatory mutations occurring at alternative sites in the molecule. None of these compensatory mutations fully restored protein performance. The mechanism of partial compensation is consistent with a model in which protein stabilization is additive, as the same secondary mutations can compensate different primary alternations. The distance between primary and compensatory residues precludes direct interaction between the sites. Instead, most of the compensatory mutants were clustered in proximity to the catalytic center. All of the second-site compensatory substitutions occurred at relatively conserved sites, and the amino acid replacements were to residues found at these sites in a multispecies alignment of the protein. Based on the estimated distribution of changes in Gibbs free energy among a large number of amino acid replacements, we estimate that, for most proteins, the probability that a second-site mutation would have a sufficiently large stabilizing effect to offset a temperature-sensitive mutation in the order of 10-4 or less. Hence compensation is likely to take place only for slightly destabilizing mutations because highly stabilizing mutations are exceeding rare.

Impact of Mutations on NPAC Structural Dynamics: Mechanistic Insights from MD Simulations

NPAC is a cytokine-like nuclear factor involved in chromatin modification and regulation of gene expression. In humans, the C-terminal domain of NPAC has the conserved structure of the β-hydroxyacid dehydrogenases (β-HAD) protein superfamily, which forms a stable tetrameric core scaffold for demethylase enzymes and organizes multiple sites for chromatin interactions. In spite of the close structural resemblance to other β-HAD family members, the human NPAC dehydrogenase domain lacks a highly conserved catalytic lysine, substituted by a methionine. The reintroduction of the catalytic lysine by M437 K mutation results in a significant decrease of stability of the tetramer. Here, we have computationally investigated the molecular determinants of the functional differences between methionine and lysine-containing NPAC proteins. We find that the single mutation can determine strong consequences in terms of dynamics, stability, and ultimately ability to assemble in supramolecular complexes: the higher stability and lower flexibility of the methionine variant structurally preorganizes the monomer for tetramerization, whereas lysine increases flexibility and favors conformations that, while catalytically active, are not optimal for tetrameric assembly. We combine structure-dynamics analysis to an evolutionary study of NPAC sequences, showing that the methionine mutation occurs in a specifically flexible region of the lysine-containing protein, flanked by two domains that concentrate most of the stabilizing interactions. In our model, such separation of stability nuclei and flexible regions appears to favor the functional innovability of the protein.

The Structural Dynamics of Engineered β-Lactamases Vary Broadly on Three Timescales yet Sustain Native Function

Understanding the principles of protein dynamics will help guide engineering of protein function: altering protein motions may be a barrier to success or may be an enabling tool for protein engineering. The impact of dynamics on protein function is typically reported over a fraction of the full scope of motional timescales. If motional patterns vary significantly at different timescales, then only by monitoring motions broadly will we understand the impact of protein dynamics on engineering functional proteins. Using an integrative approach combining experimental and in silico methodologies, we elucidate protein dynamics over the entire span of fast to slow timescales (ps to ms) for a laboratory-engineered system composed of five interrelated β-lactamases: two natural homologs and three laboratory-recombined variants. Fast (ps-ns) and intermediate (ns-µs) dynamics were mostly conserved. However, slow motions (µs-ms) were few and conserved in the natural homologs yet were numerous and widely dispersed in their recombinants. Nonetheless, modified slow dynamics were functionally tolerated. Crystallographic B-factors from high-resolution X-ray structures were partly predictive of the conserved motions but not of the new slow motions captured in our solution studies. Our inspection of protein dynamics over a continuous range of timescales vividly illustrates the complexity of dynamic impacts of protein engineering as well as the functional tolerance of an engineered enzyme system to new slow motions.

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure.

Local frustration around enzyme active sites

Conflicting biological goals often meet in the specification of protein sequences for structure and function. Overall, strong energetic conflicts are minimized in folded native states according to the principle of minimal frustration, so that a sequence can spontaneously fold, but local violations of this principle open up the possibility to encode the complex energy landscapes that are required for active biological functions. We survey the local energetic frustration patterns of all protein enzymes with known structures and experimentally annotated catalytic residues. In agreement with previous hypotheses, the catalytic sites themselves are often highly frustrated regardless of the protein oligomeric state, overall topology, and enzymatic class. At the same time a secondary shell of more weakly frustrated interactions surrounds the catalytic site itself. We evaluate the conservation of these energetic signatures in various family members of major enzyme classes, showing that local frustration is evolutionarily more conserved than the primary structure itself.

Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes

Genetic variation among orthologous proteins can cause cryptic phenotypic properties that only manifest in changing environments. Such variation may impact the evolvability of proteins, but the underlying molecular basis remains unclear. Here, we performed comparative directed evolution of four orthologous metallo-β-lactamases toward a new function and found that different starting genotypes evolved to distinct evolutionary outcomes. Despite a low initial fitness, one ortholog reached a significantly higher fitness plateau than its counterparts, via increasing catalytic activity. By contrast, the ortholog with the highest initial activity evolved to a less-optimal and phenotypically distinct outcome through changes in expression, oligomerization and activity. We show how cryptic molecular properties and conformational variation of active site residues in the initial genotypes cause epistasis, that could lead to distinct evolutionary outcomes. Our work highlights the importance of understanding the molecular details that connect genetic variation to protein function to improve the prediction of protein evolution.

Protein engineers turned evolutionists-the quest for the optimal starting point

The advent of laboratory directed evolution yielded a fruitful crosstalk between the disciplines of molecular evolution and bio-engineering. Here, we outline recent developments in both disciplines with respect to how one can identify the best starting points for directed evolution, such that highly efficient and robust tailor-made enzymes can be obtained with minimal optimization. Directed evolution studies have highlighted essential features of engineer-able enzymes: highly stable, mutationally robust enzymes with the capacity to accept a broad range of substrates. Robust, evolvable enzymes can be inferred from the natural sequence record. Broad substrate spectrum relates to conformational plasticity and can also be predicted by phylogenetic analyses and/or by computational design. Overall, an increasingly powerful toolkit is becoming available for identifying optimal starting points including network analyses of enzyme superfamilies and other bioinformatics methods.

The scale-free nature of protein sequence space

The sequence space of five protein superfamilies was investigated by constructing sequence networks. The nodes represent individual sequences, and two nodes are connected by an edge if the global sequence identity of two sequences exceeds a threshold. The networks were characterized by their degree distribution (number of nodes with a given number of neighbors) and by their fractal network dimension. Although the five protein families differed in sequence length, fold, and domain arrangement, their network properties were similar. The fractal network dimension Df was distance-dependent: a high dimension for single and double mutants (Df = 4.0), which dropped to Df = 0.7-1.0 at 90% sequence identity, and increased to Df = 3.5-4.5 below 70% sequence identity. The distance dependency of the network dimension is consistent with evolutionary constraints for functional proteins. While random single and double mutations often result in a functional protein, the accumulation of more than ten mutations is dominated by epistasis. The networks of the five protein families were highly inhomogeneous with few highly connected communities ("hub sequences") and a large number of smaller and less connected communities. The degree distributions followed a power-law distribution with similar scaling exponents close to 1. Because the hub sequences have a large number of functional neighbors, they are expected to be robust toward possible deleterious effects of mutations. Because of their robustness, hub sequences have the potential of high innovability, with additional mutations readily inducing new functions. Therefore, they form hotspots of evolution and are promising candidates as starting points for directed evolution experiments in biotechnology.