Evolution of conformational dynamics determines the conversion of a promiscuous generalist into a specialist enzyme

Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease

Allostery is a core mechanism in biology that allows proteins to communicate and regulate activity over long structural distances. While classical models of allostery focus on conformational changes triggered by ligand binding, dynamic allostery-where protein function is modulated through alterations in thermal fluctuations without major conformational shifts-has emerged as a critical evolutionary mechanism. This review explores how evolution leverages dynamic allostery to fine-tune protein function through subtle mutations at distal sites, preserving core structural architecture while dramatically altering functional properties. Using a combination of computational approaches including Dynamic Flexibility Index (DFI), Dynamic Coupling Index (DCI), and vibrational density of states (VDOS) analysis, we demonstrate that functional adaptations in proteins often involve "hinge-shift" mechanisms, where redistribution of rigid and flexible regions modulates collective motions without changing the overall fold. This evolutionary principle is a double-edged sword: the same mechanisms that enable functional innovation also create vulnerabilities that can be exploited in disease states. Disease-associated variants frequently occur at positions highly coupled to functional sites despite being physically distant, forming Dynamic Allosteric Residue Couples (DARC sites). We demonstrate applications of these principles in understanding viral evolution, drug resistance, and capsid assembly dynamics. Understanding dynamic allostery provides critical insights into protein evolution and offers new avenues for therapeutic interventions targeting allosteric regulation.

Biosynthetic Pathways of Alaremycin and Its Derivative: Inhibitors of Porphobilinogen Synthase in Porphyrin Biosynthesis from Streptomyces sp. A012304

The antibiotic alaremycin (5-acetamido-4-oxo-5-hexenoic acid, 1), isolated from Streptomyces sp. A012304, structurally resembles 5-aminolevulinic acid (ALA), a precursor in porphyrin biosynthesis, and inhibits porphobilinogen synthase, the enzyme responsible for catalyzing the first common step of this pathway. In our previous study, the biosynthetic gene cluster responsible for alaremycin production-composed of almA (ALA synthase homologue), almB (N-acetyltransferase), almC (oxidoreductase), and almE (MFS-type transporter)-was identified, and a potential biosynthetic pathway was proposed. In this study, the biosynthetic pathway of 1 was confirmed by detecting intermediates using the liquid chromatography-mass spectrometry/MS (LC-MS/MS) analysis of extracts from Escherichia coli cells transformed with the biosynthetic genes, followed by in vitro reconstitution of the biosynthetic reactions using purified enzymes. AlmA catalyzed the condensation of l-serine and succinyl-CoA to produce 5-amino-6-hydroxy-4-oxohexanoic acid (2), AlmB catalyzed the N-acetylation of 2 to produce 5-acetamido-6-hydroxy-4-oxohexanoic acid (3), and AlmC catalyzed the dehydration of 3 to form 1. The AlmC-catalyzed reaction may involve a two-step mechanism including reduction by NADH and oxidation by Fe3+. Additionally, a novel derivative of 1 was identified in the culture broth of the producer strain, and its structure was determined as 5,6-dihydroalaremycin (5-acetamido-4-oxohexanoic acid, 4). It was revealed that 4 is synthesized via the same biosynthetic pathway but with AlmA and AlmB utilizing l-alanine as the amino acid precursor instead of l-serine.

How enzyme functions evolve: genetic, structural, and kinetic perspectives

Understanding the emergence or loss of enzyme functions comprises several approaches, such as genetic, structural, and kinetic studies. Promiscuous enzyme activities have been proposed as starting points for the emergence of novel enzyme functions, for example, through genetic models such as neofunctionalization and subfunctionalization. In both cases, neutral evolution would fix gene redundancy, critical in relaxing functional constraints and allowing specific mutations to drive innovation. The evolution of enzyme activities has a structural basis, with genetic mutations modifying the active site architecture, conformational dynamics, or interaction networks, which leads to the creation, enhancement, or restriction of enzyme functions where epistatic interactions are crucial. These structural changes impact the described kinetic mechanisms like ground-state stabilization (affinity), transition-state stabilization (catalysis), or a combination of both. Case studies across diverse enzyme families illustrate these principles, emphasizing the interplay between genetic, structural, and kinetic approaches. Finally, we discuss the importance of understanding evolutionary mechanisms and their impact on protein engineering and drug design for biomedical and industrial applications. However, these studies highlight that further experimental evolutionary data collection is necessary to enable the training of advanced machine learning models for use in biotechnological applications.

Evolutionary Dynamics of RuBisCO: Emergence of the Small Subunit and its Impact Through Time

Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is an ancient protein critical for CO2-fixation and global biogeochemistry. Form-I RuBisCO complexes uniquely harbor small subunits that form a hexadecameric complex together with their large subunits. The small subunit protein is thought to have significantly contributed to RuBisCO's response to the atmospheric rise of O2 ∼2.5 billion years ago, marking a pivotal point in the enzyme's evolutionary history. Here, we performed a comprehensive evolutionary analysis of extant and ancestral RuBisCO sequences and structures to explore the impact of the small subunit's earliest integration on the molecular dynamics of the overall complex. Our simulations suggest that the small subunit restricted the conformational flexibility of the large subunit early in its history, impacting the evolutionary trajectory of the Form-I RuBisCO complex. Molecular dynamics investigations of CO2 and O2 gas distribution around predicted ancient RuBisCO complexes suggest that a proposed "CO2-reservoir" role for the small subunit is not conserved throughout the enzyme's evolutionary history. The evolutionary and biophysical response of RuBisCO to changing atmospheric conditions on ancient Earth showcase multi-level and trackable responses of enzymes to environmental shifts over long timescales.

Allostery and Evolution: A Molecular Journey Through the Structural and Dynamical Landscape of an Enzyme Super Family

Allosteric regulation is a powerful mechanism for controlling the efficiency of enzymes. Deciphering the evolutionary mechanisms by which allosteric properties have been acquired in enzymes is of fundamental importance. We used the malate (MalDH) and lactate deydrogenases (LDHs) superfamily as model to elucidate this phenomenon. By introducing a few of mutations associated to the emergence of allosteric LDHs into the non-allosteric MalDH from Methanopyrus kandleri, we have gradually shifted its enzymatic profile toward that typical of allosteric LDHs. We first investigated the process triggering homotropic activation. The structures of the resulting mutants show the typical compact organization of the R-active state of LDHs, but a distorted (T-like) catalytic site demonstrating that they corresponds to hybrid states. Molecular dynamics simulations and free energy calculations confirmed the capability of these mutants to sample the T-inactive state. By adding a final single mutation to fine-tune the flexibility of the catalytic site, we obtained an enzyme with both sigmoid (homotropic) and hyperbolic (heterotropic) substrate activation profiles. Its structure shows a typical extended T-state as in LDHs, whereas its catalytic state has as a restored configuration favorable for catalysis. Free energy calculations indicate that the T and R catalytic site configurations are in an equilibrium that depends on solvent conditions. We observed long-range communication between monomers as required for allosteric activation. Our work links the evolution of allosteric regulation in the LDH/MDH superfamily to the ensemble model of allostery at molecular level, and highlights the important role of the underlying protein dynamics.

Engineering the native ensemble to tune protein function: Diverse mutational strategies and interlinked molecular mechanisms

Natural proteins are fragile entities, intrinsically sensitive to perturbations both at the level of sequence and their immediate environment. Here, we highlight the diverse strategies available for engineering function through mutations influencing backbone conformational entropy, charge-charge interactions, and in the loops and hinge regions, many of which are located far from the active site. It thus appears that there are potentially numerous ways to microscopically vary the identity of residues and the constituent interactions to tune function. Functional modulation could occur via changes in native-state stability, altered thermodynamic coupling extents within the folded structure, redistributed dynamics, or through modulation of the population of conformational substates. As these mechanisms are intrinsically linked and given the pervasive long-range effects of mutations, it is crucial to consider the interaction network as a whole and fully map the native conformational landscape to place mutational effects in the context of allostery and protein evolution.

Transition Path Sampling Based Free Energy Calculations of Evolution's Effect on Rates in β-Lactamase: The Contributions of Rapid Protein Dynamics to Rate

β-Lactamases are one of the primary enzymes responsible for antibiotic resistance and have existed for billions of years. The structural differences between a modern class A TEM-1 β-lactamase compared to a sequentially reconstructed Gram-negative bacteria β-lactamase are minor. Despite the similar structures and mechanisms, there are different functions between the two enzymes. We recently identified differences in dynamics effects that result from evolutionary changes that could potentially account for the increase in substrate specificity and catalytic rate. In this study, we used transition path sampling-based calculations of free energies to identify how evolutionary changes found between an ancestral β-lactamase, and its extant counterpart TEM-1 β-lactamase affect rate.

Physiological cost of antibiotic resistance: Insights from a ribosome variant in bacteria

Antibiotic-resistant ribosome variants arise spontaneously in bacterial populations; however, their impact on the overall bacterial physiology remains unclear. We studied the naturally arising antibiotic-resistant L22* ribosome variant of Bacillus subtilis and identified a Mg2+-dependent physiological cost. Coculture competition experiments show that Mg2+ limitation hinders the growth of the L22* variant more than the wild type (WT), even under antibiotic pressure. This growth disadvantage of L22* cells is not due to lower ribosome abundance but rather due to reduced intracellular Mg2+ levels. Coarse-grained elastic-network modeling of ribosome conformational dynamics suggests that L22* ribosomes associate more tightly with Mg2+ when compared to WT. We combined the structural modeling and experimental measurements in a steady-state model to predict cellular adenosine 5'-triphosphate (ATP) levels, which also depend on Mg2+. Experiments confirmed a predicted ATP drop in L22* cells under Mg2+ limitation, while WT cells were less affected. Intracellular competition for a finite Mg2+ pool can thus suppress the establishment of an antibiotic-resistant ribosome variant.

Ancestral Sequence Reconstruction to Enable Biocatalytic Synthesis of Azaphilones

Biocatalysis can be powerful in organic synthesis but is often limited by enzymes' substrate scope and selectivity. Developing a biocatalytic step involves identifying an initial enzyme for the target reaction followed by optimization through rational design, directed evolution, or both. These steps are time consuming, resource-intensive, and require expertise beyond typical organic chemistry. Thus, an effective strategy for streamlining the process from enzyme identification to implementation is essential to expanding biocatalysis. Here, we present a strategy combining bioinformatics-guided enzyme mining and ancestral sequence reconstruction (ASR) to resurrect enzymes for biocatalytic synthesis. Specifically, we achieve an enantioselective synthesis of azaphilone natural products using two ancestral enzymes: a flavin-dependent monooxygenase (FDMO) for stereodivergent oxidative dearomatization and a substrate-selective acyltransferase (AT) for the acylation of the enzymatically installed hydroxyl group. This cascade, stereocomplementary to established chemoenzymatic routes, expands access to enantiomeric linear tricyclic azaphilones. By leveraging the co-occurrence and coevolution of FDMO and AT in azaphilone biosynthetic pathways, we identified an AT candidate, CazE, and addressed its low solubility and stability through ASR, obtaining a more soluble, stable, promiscuous, and reactive ancestral AT (AncAT). Sequence analysis revealed AncAT as a chimeric composition of its descendants with enhanced reactivity likely due to ancestral promiscuity. Flexible receptor docking and molecular dynamics simulations showed that the most reactive AncAT promotes a reactive geometry between substrates. We anticipate that our bioinformatics-guided, ASR-based approach can be broadly applied in target-oriented synthesis, reducing the time required to develop biocatalytic steps and efficiently access superior biocatalysts.

The Evolution of the Acylation Mechanism in β-Lactamase and Rapid Protein Dynamics

β-Lactamases are a class of well-studied enzymes that are known to have existed since billions of years ago, starting as a defense mechanism to stave off competitors and are now enzymes responsible for antibiotic resistance. Using ancestral sequence reconstruction, it is possible to study the crystal structure of a laboratory resurrected 2-3 billion year-old β-lactamase. Comparing the ancestral enzyme to its modern counterpart, a TEM-1 β-lactamase, the structural changes are minor, and it is probable that dynamic effects play an important role in the evolution of function. We used molecular dynamics simulations and employed transition path sampling methods to identify the presence of rate-enhancing dynamics at the femtosecond level in both systems, found that these fast motions are more efficiently coordinated in the modern enzyme, and examined how specific dynamics can pinpoint evolutionary effects that are essential for improving enzymatic catalysis.

Friends and relatives: insight into conformational regulation from orthologues and evolutionary lineages using KIF and KIN

Noncovalent interaction networks provide a powerful means to represent and analyze protein structure. Such networks can represent both static structures and dynamic conformational ensembles. We have recently developed two tools for analyzing such interaction networks and generating hypotheses for protein engineering. Here, we apply these tools to the conformational regulation of substrate specificity in class A β-lactamases, particularly the evolutionary development from generalist to specialist catalytic function and how that can be recapitulated or reversed by protein engineering. These tools, KIF and KIN, generate a set of prioritized residues and interactions as targets for experimental protein engineering.

Mechanistic conformational and substrate selectivity profiles emerging in the evolution of enzymes via parallel trajectories

Laboratory evolution studies have demonstrated that parallel evolutionary trajectories can lead to genetically distinct enzymes with high activity towards a non-preferred substrate. However, it is unknown whether such enzymes have convergent conformational dynamics and mechanistic features. To address this question, we use as a model the wild-type Homo sapiens kynureninase (HsKYNase), which is of great interest for cancer immunotherapy. Earlier, we isolated HsKYNase_66 through an unusual evolutionary trajectory, having a 410-fold increase in the kcat/KM for kynurenine (KYN) and reverse substrate selectivity relative to HsKYNase. Here, by following a different evolutionary trajectory we generate a genetically distinct variant, HsKYNase_93D9, that exhibits KYN catalytic activity comparable to that of HsKYNase_66, but instead it is a "generalist" that accepts 3'-hydroxykynurenine (OH-KYN) with the same proficiency. Pre-steady-state kinetic analysis reveals that while the evolution of HsKYNase_66 is accompanied by a change in the rate-determining step of the reactions, HsKYNase_93D9 retains the same catalytic mechanism as HsKYNase. HDX-MS shows that the conformational dynamics of the two enzymes are markedly different and distinct from ortholog prokaryotic enzymes with high KYN activity. Our work provides a mechanistic framework for understanding the relationship between evolutionary mechanisms and phenotypic traits of evolved generalist and specialist enzyme species.

Evidence that the cold- and menthol-sensing functions of the human TRPM8 channel evolved separately

Transient receptor potential melastatin 8 (TRPM8) is a temperature- and menthol-sensitive ion channel that contributes to diverse physiological roles, including cold sensing and pain perception. Clinical trials targeting TRPM8 have faced repeated setbacks predominantly due to the knowledge gap in unraveling the molecular underpinnings governing polymodal activation. A better understanding of the molecular foundations between the TRPM8 activation modes may aid the development of mode-specific, thermal-neutral therapies. Ancestral sequence reconstruction was used to explore the origins of TRPM8 activation modes. By resurrecting key TRPM8 nodes along the human evolutionary trajectory, we gained valuable insights into the trafficking, stability, and function of these ancestral forms. Notably, this approach unveiled the differential emergence of cold and menthol sensitivity over evolutionary time, providing a fresh perspective on complex polymodal behavior. These studies provide a paradigm for understanding polymodal behavior in TRPM8 and other proteins with the potential to enhance our understanding of sensory receptor biology and pave the way for innovative therapeutic interventions.

Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.

Recent advances in structure-based enzyme engineering for functional reconstruction

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

Conformational Tuning Shapes the Balance between Functional Promiscuity and Specialization in Paralogous Plasmodium Acyl-CoA Binding Proteins

Paralogous proteins confer enhanced fitness to organisms via complex sequence-conformation codes that shape functional divergence, specialization, or promiscuity. Here, we dissect the underlying mechanism of promiscuous binding versus partial subfunctionalization in paralogues by studying structurally identical acyl-CoA binding proteins (ACBPs) from Plasmodium falciparum that serve as promising drug targets due to their high expression during the protozoan proliferative phase. Combining spectroscopic measurements, solution NMR, SPR, and simulations on two of the paralogues, A16 and A749, we show that minor sequence differences shape nearly every local and global conformational feature. A749 displays a broader and heterogeneous native ensemble, weaker thermodynamic coupling and cooperativity, enhanced fluctuations, and a larger binding pocket volume compared to A16. Site-specific tryptophan probes signal a graded reduction in the sampling of substates in the holo form, which is particularly apparent in A749. The paralogues exhibit a spectrum of binding affinities to different acyl-CoAs with A749, the more promiscuous and hence the likely ancestor, binding 1000-fold stronger to lauroyl-CoA under physiological conditions. We thus demonstrate how minor sequence changes modulate the extent of long-range interactions and dynamics, effectively contributing to the molecular evolution of contrasting functional repertoires in paralogues.

Diversification of Ubiquinone Biosynthesis via Gene Duplications, Transfers, Losses, and Parallel Evolution

The availability of an ever-increasing diversity of prokaryotic genomes and metagenomes represents a major opportunity to understand and decipher the mechanisms behind the functional diversification of microbial biosynthetic pathways. However, it remains unclear to what extent a pathway producing a specific molecule from a specific precursor can diversify. In this study, we focus on the biosynthesis of ubiquinone (UQ), a crucial coenzyme that is central to the bioenergetics and to the functioning of a wide variety of enzymes in Eukarya and Pseudomonadota (a subgroup of the formerly named Proteobacteria). UQ biosynthesis involves three hydroxylation reactions on contiguous carbon atoms. We and others have previously shown that these reactions are catalyzed by different sets of UQ-hydroxylases that belong either to the iron-dependent Coq7 family or to the more widespread flavin monooxygenase (FMO) family. Here, we combine an experimental approach with comparative genomics and phylogenetics to reveal how UQ-hydroxylases evolved different selectivities within the constrained framework of the UQ pathway. It is shown that the UQ-FMOs diversified via at least three duplication events associated with two cases of neofunctionalization and one case of subfunctionalization, leading to six subfamilies with distinct hydroxylation selectivity. We also demonstrate multiple transfers of the UbiM enzyme and the convergent evolution of UQ-FMOs toward the same function, which resulted in two independent losses of the Coq7 ancestral enzyme. Diversification of this crucial biosynthetic pathway has therefore occurred via a combination of parallel evolution, gene duplications, transfers, and losses.

Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis

Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

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

Loop dynamics and the evolution of enzyme activity

In the early 2000s, Tawfik presented his 'New View' on enzyme evolution, highlighting the role of conformational plasticity in expanding the functional diversity of limited repertoires of sequences. This view is gaining increasing traction with increasing evidence of the importance of conformational dynamics in both natural and laboratory evolution of enzymes. The past years have seen several elegant examples of harnessing conformational (particularly loop) dynamics to successfully manipulate protein function. This Review revisits flexible loops as critical participants in regulating enzyme activity. We showcase several systems of particular interest: triosephosphate isomerase barrel proteins, protein tyrosine phosphatases and β-lactamases, while briefly discussing other systems in which loop dynamics are important for selectivity and turnover. We then discuss the implications for engineering, presenting examples of successful loop manipulation in either improving catalytic efficiency, or changing selectivity completely. Overall, it is becoming clearer that mimicking nature by manipulating the conformational dynamics of key protein loops is a powerful method of tailoring enzyme activity, without needing to target active-site residues.

Protein dynamics provide mechanistic insights about epistasis among common missense polymorphisms

Sequencing of the protein coding genome has revealed many different missense mutations of human proteins and different population frequencies of corresponding haplotypes, which consist of different sets of those mutations. Here, we present evidence for pairwise intramolecular epistasis (i.e., nonadditive interactions) between many such mutations through an analysis of protein dynamics. We suggest that functional compensation for conserving protein dynamics is a likely evolutionary mechanism that maintains high-frequency mutations that are individually nonneutral but epistatically compensating within proteins. This analysis is the first of its type to look at human proteins with specific high population frequency mutations and examine the relationship between mutations that make up that observed high-frequency protein haplotype. Importantly, protein dynamics revealed a separation between high and low frequency haplotypes within a target protein cytochrome P450 2A7, with the high-frequency haplotypes showing behavior closer to the wild-type protein. Common protein haplotypes containing two mutations display dynamic compensation in which one mutation can correct for the dynamic effects of the other. We also utilize a dynamics-based metric, EpiScore, that evaluates the epistatic interactions and allows us to see dynamic compensation within many other proteins.

Critical Assessment of Self-Consistency Checks in the All-Atom Molecular Dynamics Simulation of Intrinsically Disordered Proteins

All atom simulations can be used to quantify conformational properties of Intrinsically Disordered Proteins (IDP). However, simulations must satisfy convergence checks to ensure observables computed from simulation are reliable and reproducible. While absolute convergence is purely a theoretical concept requiring infinitely long simulation, a more practical, yet rigorous, approach is to impose Self Consistency Checks (SCCs) to gain confidence in the simulated data. Currently there is no study of SCCs in IDPs, unlike their folded counterparts. In this paper, we introduce different criteria for self-consistency checks for IDPs. Next, we impose these SCCs to critically assess the performance of different simulation protocols using the N terminal domain of HIV Integrase and the linker region of SARS-CoV-2 Nucleoprotein as two model IDPs. All simulation protocols begin with all-atom implicit solvent Monte Carlo (MC) simulation and subsequent clustering of MC generated conformations to create the representative structures of the IDPs. These representative structures serve as the initial structure for subsequent molecular dynamics (MD) runs with explicit solvent. We conclude that generating multiple short (∼3 μs) MD simulation trajectories─all starting from the most representative MC generated conformation─and merging them is the protocol of choice due to (i) its ability to satisfy multiple SCCs, (ii) consistently reproducing experimental data, and (iii) the efficiency of running independent trajectories in parallel by harnessing multiple cores available in modern GPU clusters. Running one long trajectory (greater than 20 μs) can also satisfy the first two criteria but is less desirable due to prohibitive computation time. These findings help resolve the challenge of identifying a usable starting configuration, provide an objective measure of SCC, and establish rigorous criteria to determine the minimum length (for one long simulation) or number of trajectories needed in all-atom simulation of IDPs.

Moonlighting enzymes: when cellular context defines specificity

It is not often realized that the absolute protein specificity is an exception rather than a rule. Two major kinds of protein multi-specificities are promiscuity and moonlighting. This review discusses the idea of enzyme specificity and then focusses on moonlighting. Some important examples of protein moonlighting, such as crystallins, ceruloplasmin, metallothioniens, macrophage migration inhibitory factor, and enzymes of carbohydrate metabolism are discussed. How protein plasticity and intrinsic disorder enable the removing the distinction between enzymes and other biologically active proteins are outlined. Finally, information on important roles of moonlighting in human diseases is updated.

Deciphering the evolution of flavin-dependent monooxygenase stereoselectivity using ancestral sequence reconstruction

Controlling the selectivity of a reaction is critical for target-oriented synthesis. Accessing complementary selectivity profiles enables divergent synthetic strategies, but is challenging to achieve in biocatalytic reactions given enzymes' innate preferences of a single selectivity. Thus, it is critical to understand the structural features that control selectivity in biocatalytic reactions to achieve tunable selectivity. Here, we investigate the structural features that control the stereoselectivity in an oxidative dearomatization reaction that is key to making azaphilone natural products. Crystal structures of enantiocomplementary biocatalysts guided the development of multiple hypotheses centered on the structural features that control the stereochemical outcome of the reaction; however, in many cases, direct substitutions of active site residues in natural proteins led to inactive enzymes. Ancestral sequence reconstruction (ASR) and resurrection were employed as an alternative strategy to probe the impact of each residue on the stereochemical outcome of the dearomatization reaction. These studies suggest that two mechanisms are active in controlling the stereochemical outcome of the oxidative dearomatization reaction: one involving multiple active site residues in AzaH and the other dominated by a single Phe to Tyr switch in TropB and AfoD. Moreover, this study suggests that the flavin-dependent monooxygenases (FDMOs) adopt simple and flexible strategies to control stereoselectivity, which has led to stereocomplementary azaphilone natural products produced by fungi. This paradigm of combining ASR and resurrection with mutational and computational studies showcases sets of tools for understanding enzyme mechanisms and provides a solid foundation for future protein engineering efforts.

A conserved SH3-like fold in diverse putative proteins tetramerizes into an oxidoreductase providing an antimicrobial resistance phenotype

We present a potential mechanism for emergence of catalytic activity that is essential for survival, from a non-catalytic protein fold. The type B dihydrofolate reductase (DfrB) family of enzymes were first identified in pathogenic bacteria because their dihydrofolate reductase activity is sufficient to provide trimethoprim (TMP) resistance. DfrB enzymes are described as poorly evolved as a result of their unusual structural and kinetic features. No characterized protein shares sequence homology with DfrB enzymes; how they evolved to emerge in the modern resistome is unknown. In this work, we identify DfrB homologues from a database of putative and uncharacterized proteins. These proteins include an SH3-like fold homologous to the DfrB enzymes, embedded in a variety of additional structural domains. By means of functional, structural and biophysical characterization, we demonstrate that these distant homologues and their extracted SH3-like fold can display dihydrofolate reductase activity and confer TMP resistance. We provide evidence of tetrameric assembly and catalytic mechanism analogous to that of DfrB enzymes. These results contribute, to our knowledge, the first insights into a potential evolutionary path taken by this SH3-like fold to emerge in the modern resistome following introduction of TMP. This article is part of the theme issue 'Reactivity and mechanism in chemical and synthetic biology'.

Structural and biochemical characterization of Leptospira interrogans Lsa45 reveals a penicillin-binding protein with esterase activity

Leptospirosis is a bacterial disease that affects humans and animals and is caused by Leptospira. The recommended treatment for leptospirosis is antibiotic therapy, which should be given early in the course of the disease. Despite the use of these antibiotics, their role during the course of the disease is still not completely clear because of the lack of effective clinical trials, particularly for severe cases of the disease. Here, we present the characterization of L. interrogans Lsa45 protein by gel filtration, protein crystallography, SAXS, fluorescence and enzymatic assays. The oligomeric studies revealed that Lsa45 is monomeric in solution. The crystal structure of Lsa45 revealed the presence of two subdomains: a large α/β subdomain and a small α-helical subdomain. The large subdomain contains the amino acids Ser122, Lys125, and Tyr217, which correspond to the catalytic triad that is essential for β-lactamase or serine hydrolase activity in similar enzymes. Additionally, we also confirmed the bifunctional promiscuity of Lsa45, in hydrolyzing both the 4-nitrophenyl acetate (p-NPA) and nitrocefin β-lactam antibiotic. Therefore, this study provides novel insights into the structure and function of enzymes from L. interrogans, which furthers our understanding of this bacterium and the development of new therapies for the prevention and treatment of leptospirosis.

Correlated Evolution of Low-Frequency Vibrations and Function in Enzymes

Previous studies of the flexibility of ancestral proteins suggest that proteins evolve their function by altering their native state ensemble. Here, we propose a more direct method to analyze such changes during protein evolution by comparing thermally activated vibrations at frequencies below 6 THz, which report on the dynamics of collective protein modes. We analyzed the backbone vibrational density of states of ancestral and extant β-lactamases and thioredoxins and observed marked changes in the vibrational spectrum in response to evolution. Coupled with previously observed changes in protein flexibility, the observed shifts of vibrational mode densities suggest that protein dynamics and dynamical allostery are critical factors for the evolution of enzymes with specialized catalytic and biophysical properties.

Computational and data mining studies to understand the distribution and dynamics of Temoneria (TEM) β-lactamase and their interaction with β-lactam and β-lactamase inhibitors

β-lactams are large group of antibiotics widely used to suppress the bacterial growth by inhibiting cell wall synthesis. Bacterial resistance against β-lactam antibiotics is primarily mediated through the production of Temoneria (TEM) β-lactamase (BLs), with almost 474 variants identified in Lactamase Engineering Database (LacED). The present study aims to develop a model to track the evolution of TEM BLs and their interactions with β-lactam and BLs inhibitors through data mining and computational approaches. Further, the model will be used to predict the effective combinations of β-lactam and BLs inhibitors to treat the bacterial infection harbouring emerging variants of β-lactamase. The molecular docking study results demonstrated that most TEM mutants recorded the least binding energy to penicillin and cephalosporin (I/II/III/IV/V generations) class of antibiotics. On the contrary, the same mutants recorded higher binding energy to carbapenem and Monobactam class of antibiotics. Among the BLs inhibitors, tazobactam recorded the least binding energy against most of the TEM mutants, indicating that it can lower the catalytic activity of TEM BLs, thereby potentiating antibiotic action. Similarly, data mining work has assisted us in creating a database of TEM mutants that has comprehensive data on mutations, bacterial diversity, Km, MIC, and IRT types. It has been noted that earlier released antibiotics like amoxicillin and ampicillin had lower Km and higher MIC values, which indicates the prevalence of bacterial resistance. By analysing the differential binding energy (ΔBE) of the selected TEM mutants against β-lactam and BLs inhibitors, the most effective combination of β-lactam (carbapenem and monobactam class of antibiotics) and BLs inhibitors (tazobactam) was identified, to cure bacterial diseases/infections and to prevent similar antibiotic resistance outbreaks. Therefore, our study opens a new avenue in developing strategies to manage antibiotic resistance in bacteria.

Probing the origin of prion protein misfolding via reconstruction of ancestral proteins

Prion diseases are fatal neurodegenerative diseases caused by pathogenic misfolding of the prion protein, PrP. They are transmissible between hosts, and sometimes between different species, as with transmission of bovine spongiform encephalopathy to humans. Although PrP is found in a wide range of vertebrates, prion diseases are seen only in certain mammals, suggesting that infectious misfolding was a recent evolutionary development. To explore when PrP acquired the ability to misfold infectiously, we reconstructed the sequences of ancestral versions of PrP from the last common primate, primate-rodent, artiodactyl, placental, bird, and amniote. Recombinant ancestral PrPs were then tested for their ability to form β-sheet aggregates, either spontaneously or when seeded with infectious prion strains from human, cervid, or rodent species. The ability to aggregate developed after the oldest ancestor (last common amniote), and aggregation capabilities diverged along evolutionary pathways consistent with modern-day susceptibilities. Ancestral bird PrP could not be seeded with modern-day prions, just as modern-day birds are resistant to prion disease. Computational modeling of structures suggested that differences in helix 2 could account for the resistance of ancestral bird PrP to seeding. Interestingly, ancestral primate PrP could be converted by all prion seeds, including both human and cervid prions, raising the possibility that species descended from an ancestral primate have retained the susceptibility to conversion by cervid prions. More generally, the results suggest that susceptibility to prion disease emerged prior to ~100 million years ago, with placental mammals possibly being generally susceptible to disease.

Slow Protein Dynamics Elicits New Enzymatic Functions by Means of Epistatic Interactions

Protein evolution depends on the adaptation of these molecules to different functional challenges. This occurs by tuning their biochemical, biophysical, and structural traits through the accumulation of mutations. While the role of protein dynamics in biochemistry is well recognized, there are limited examples providing experimental evidence of the optimization of protein dynamics during evolution. Here we report an NMR study of four variants of the CTX-M β-lactamases, in which the interplay of two mutations outside the active site enhances the activity against a cephalosporin substrate, ceftazidime. The crystal structures of these enzymes do not account for this activity enhancement. By using NMR, here we show that the combination of these two mutations increases the backbone dynamics in a slow timescale and the exposure to the solvent of an otherwise buried β-sheet. The two mutations located in this β-sheet trigger conformational changes in loops located at the opposite side of the active site. We postulate that the most active variant explores alternative conformations that enable binding of the more challenging substrate ceftazidime. The impact of the mutations in the dynamics is context-dependent, in line with the epistatic effect observed in the catalytic activity of the different variants. These results reveal the existence of a dynamic network in CTX-M β-lactamases that has been exploited in evolution to provide a net gain-of-function, highlighting the role of alternative conformations in protein evolution.

Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an "Allosterized" Enzyme using Evolution Guided Punctual Mutations

We unveil the intimate relationship between protein dynamics and allostery by following the trajectories of model proteins in their conformational and sequence spaces. Starting from a nonallosteric hyperthermophilic malate dehydrogenase, we have tracked the role of protein dynamics in the evolution of the allosteric capacity. Based on a large phylogenetic analysis of the malate (MalDH) and lactate dehydrogenase (LDH) superfamily, we identified two amino acid positions that could have had a major role for the emergence of allostery in LDHs, which we targeted for investigation by site-directed mutagenesis. Wild-type MalDH and the single and double mutants were tested with respect to their substrate recognition profiles. The double mutant displayed a sigmoid-shaped profile typical of homotropic activation in LDH. By using molecular dynamics simulations, we showed that the mutations induce a drastic change in the protein sampling of its conformational landscape, making transiently T-like (inactive) conformers, typical of allosteric LDHs, accessible. Our data fit well with the seminal key concept linking protein dynamics and evolvability. We showed that the selection of a new phenotype can be achieved by a few key dynamics-enhancing mutations causing the enrichment of low-populated conformational substates.

Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme

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

OBI: A computational tool for the analysis and systematization of the positive selection in proteins

There are multiple tools for positive selection analysis, including vaccine design and detection of variants of circulating drug-resistant pathogens in population selection. However, applying these tools to analyze a large number of protein families or as part of a comprehensive phylogenomics pipeline could be challenging. Since many standard bioinformatics tools are only available as executables, integrating them into complex Bioinformatics pipelines may not be possible.

We have developed OBI, an open-source tool aimed to facilitate positive selection analysis on a large scale. It can be used as a stand-alone command-line app that can be easily installed and used as a Conda package.

Some advantages of using OBI are:•

It speeds up the analysis by automating the entire process

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It allows multiple starting points and customization for the analysis

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It allows the retrieval and linkage of structural and evolutive data for a protein through

We hope to provide with OBI a solution for reliably speeding up large-scale protein evolutionary and structural analysis.

In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins

The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it.

Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants

Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor fall in any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for pathogenesis. In this study, we present an analysis of 591 pathogenic missense variants in 144 human enzymes that suggests that allosteric dynamic coupling of mutated positions with known active sites is a plausible biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of β-Glucocerebrosidase (GCase) in which a vast majority of 94 sites harboring Gaucher disease-associated missense variants are located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling caused by missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease.

Dynamic Allostery Highlights the Evolutionary Differences between the CoV-1 and CoV-2 Main Proteases

The SARS-CoV-2 coronavirus has become one of the most immediate and widely-studied systems since its identification and subsequent global outbreak from 2019-2021. In an effort to understand the biophysical changes as a result of mutations, the mechanistic details of multiple different proteins within the SARS-CoV-2 virus have been studied and compared with SARS-CoV-1. Focusing on the main protease (mPro), we first explored the long-range dynamics using the Dynamic Coupling Index (DCI) to investigate the dynamic coupling between the catalytic site residues and the rest of the protein, both inter and intra chain, for the CoV-1 and CoV-2 mPro. We found that there is significant cross-chain coupling between these active sites and specific distal residues in the CoV-2 mPro not present in CoV-1. The enhanced long distance interactions, particularly between the two chains, suggest subsequently enhanced cooperativity for CoV-2. A further comparative analysis of the dynamic flexibility using the Dynamic Flexibility Index (DFI) between the CoV-1 and CoV-2 mPros shows that the inhibitor binding near active sites induces change in flexibility to a distal region of the protein, opposite in behavior between the two systems; this region becomes more flexible upon inhibitor binding in CoV-1 while it becomes less flexible in the CoV-2 mPro. Upon inspection, we show that, on average, the dynamic flexibility of the sites substituted from CoV-1 to CoV-2 changes significantly less than the average calculated across all residues within the structure, indicating that the differences in behaviors between the two systems is likely the result of allosteric influence, where the new substitutions in CoV-2 induce flexibility and dynamical changes elsewhere in the structure.

The stability and dynamics of computationally designed proteins

Protein stability, dynamics and function are intricately linked. Accordingly, protein designers leverage dynamics in their designs and gain insight to their successes and failures by analyzing their proteins' dynamics. Molecular dynamics (MD) simulations are a powerful computational tool for quantifying both local and global protein dynamics. This review highlights studies where MD simulations were applied to characterize the stability and dynamics of designed proteins and where dynamics were incorporated into computational protein design. First, we discuss the structural basis underlying the extreme stability and thermostability frequently observed in computationally designed proteins. Next, we discuss examples of designed proteins, where dynamics were not explicitly accounted for in the design process, whose coordinated motions or active site dynamics, as observed by MD simulation, enhanced or detracted from their function. Many protein functions depend on sizeable or subtle conformational changes, so we finally discuss the computational design of proteins to perform a specific function that requires consideration of motion by multi-state design.

Transferability of tigecycline resistance: Characterization of the expanding Tet(X) family

Tetracycline and its derivative tigecycline are clinical options against Gram-negative bacterial infections. The emergence of mobile Tet(X) enzymes that destruct tetracycline-type antibiotics is posing a big challenge to antibacterial therapy and food/environmental securities. Here, we present an update on a growing number of Tet(X) variants. We describe structure and action of Tet(X) enzyme, and discuss the evolutional origin. In addition, potential Tet(X) inhibitors are given. This mini-review might benefit better understanding of Tet(X)-mediated tigecycline resistance. This article is categorized under: Infectious Diseases > Genetics/Genomics/Epigenetics Infectious Diseases > Environmental Factors Infectious Diseases > Molecular and Cellular Physiology.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

Structural dynamics in the evolution of a bilobed protein scaffold

Proteins conduct numerous complex biological functions by use of tailored structural dynamics. The molecular details of how these emerged from ancestral peptides remains mysterious. How does nature utilize the same repertoire of folds to diversify function? To shed light on this, we analyzed bilobed proteins with a common structural core, which is spread throughout the tree of life and is involved in diverse biological functions such as transcription, enzymatic catalysis, membrane transport, and signaling. We show here that the structural dynamics of the structural core differentiate predominantly via terminal additions during a long-period evolution. This diversifies substrate specificity and, ultimately, biological function.

Novel biophysical tools allow the structural dynamics of proteins and the regulation of such dynamics by binding partners to be explored in unprecedented detail. Although this has provided critical insights into protein function, the means by which structural dynamics direct protein evolution remain poorly understood. Here, we investigated how proteins with a bilobed structure, composed of two related domains from the periplasmic-binding protein–like II domain family, have undergone divergent evolution, leading to adaptation of their structural dynamics. We performed a structural analysis on ∼600 bilobed proteins with a common primordial structural core, which we complemented with biophysical studies to explore the structural dynamics of selected examples by single-molecule Förster resonance energy transfer and Hydrogen–Deuterium exchange mass spectrometry. We show that evolutionary modifications of the structural core, largely at its termini, enable distinct structural dynamics, allowing the diversification of these proteins into transcription factors, enzymes, and extracytoplasmic transport-related proteins. Structural embellishments of the core created interdomain interactions that stabilized structural states, reshaping the active site geometry, and ultimately altered substrate specificity. Our findings reveal an as-yet-unrecognized mechanism for the emergence of functional promiscuity during long periods of evolution and are applicable to a large number of domain architectures.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

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Evolution of protein structures occurs at the level of global interaction network.

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More than 70% of the protein residues are weakly or marginally coupled.

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Functional ‘sector’ regions are a manifestation of marginal coupling.

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Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

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The proposed methodology can be used to understand allostery and epistasis.

Controlling the Substrate Specificity of an Enzyme through Structural Flexibility by Varying the Salt-Bridge Density

Many enzymes, particularly in one single family, with highly conserved structures and folds exhibit rather distinct substrate specificities. The underlying mechanism remains elusive, the resolution of which is of great importance for biochemistry, biophysics, and bioengineering. Here, we performed a neutron scattering experiment and molecular dynamics (MD) simulations on two structurally similar CYP450 proteins; CYP101 primarily catalyzes one type of ligands, then CYP2C9 can catalyze a large range of substrates. We demonstrated that it is the high density of salt bridges in CYP101 that reduces its structural flexibility, which controls the ligand access channel and the fluctuation of the catalytic pocket, thus restricting its selection on substrates. Moreover, we performed MD simulations on 146 different kinds of CYP450 proteins, spanning distinct biological categories including Fungi, Archaea, Bacteria, Protista, Animalia, and Plantae, and found the above mechanism generally valid. We demonstrated that, by fine changes of chemistry (salt-bridge density), the CYP450 superfamily can vary the structural flexibility of its member proteins among different biological categories, and thus differentiate their substrate specificities to meet the specific biological needs. As this mechanism is well-controllable and easy to be implemented, we expect it to be generally applicable in future enzymatic engineering to develop proteins of desired substrate specificities.

Exploiting enzyme evolution for computational protein design

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies.

Toho-1 β-lactamase: backbone chemical shift assignments and changes in dynamics upon binding with avibactam

Backbone chemical shift assignments for the Toho-1 β-lactamase (263 amino acids, 28.9 kDa) are reported based on triple resonance solution-state NMR experiments performed on a uniformly 2H,13C,15N-labeled sample. These assignments allow for subsequent site-specific characterization at the chemical, structural, and dynamical levels. At the chemical level, titration with the non-β-lactam β-lactamase inhibitor avibactam is found to give chemical shift perturbations indicative of tight covalent binding that allow for mapping of the inhibitor binding site. At the structural level, protein secondary structure is predicted based on the backbone chemical shifts and protein residue sequence using TALOS-N and found to agree well with structural characterization from X-ray crystallography. At the dynamical level, model-free analysis of 15N relaxation data at a single field of 16.4 T reveals well-ordered structures for the ligand-free and avibactam-bound enzymes with generalized order parameters of ~ 0.85. Complementary relaxation dispersion experiments indicate that there is an escalation in motions on the millisecond timescale in the vicinity of the active site upon substrate binding. The combination of high rigidity on short timescales and active site flexibility on longer timescales is consistent with hypotheses for achieving both high catalytic efficiency and broad substrate specificity: the induced active site dynamics allows variously sized substrates to be accommodated and increases the probability that the optimal conformation for catalysis will be sampled.

Were Ancestral Proteins Less Specific?

Some have hypothesized that ancestral proteins were, on average, less specific than their descendants. If true, this would provide a universal axis along which to organize protein evolution and suggests that reconstructed ancestral proteins may be uniquely powerful tools for protein engineering. Ancestral sequence reconstruction studies are one line of evidence used to support this hypothesis. Previously, we performed such a study, investigating the evolution of peptide-binding specificity for the paralogs S100A5 and S100A6. The modern proteins appeared more specific than their last common ancestor (ancA5/A6), as each paralog bound a subset of the peptides bound by ancA5/A6. In this study, we revisit this transition, using quantitative phage display to measure the interactions of 30,533 random peptides with human S100A5, S100A6, and ancA5/A6. This unbiased screen reveals a different picture. While S100A5 and S100A6 do indeed bind to a subset of the peptides recognized by ancA5/A6, they also acquired new peptide partners outside of the set recognized by ancA5/A6. Our previous work showed that ancA5/A6 had lower specificity than its descendants when measured against biological targets; our new work shows that ancA5/A6 has similar specificity to the modern proteins when measured against a random set of peptide targets. This demonstrates that altered biological specificity does not necessarily indicate altered intrinsic specificity, and sounds a cautionary note for using ancestral reconstruction studies with biological targets as a means to infer global evolutionary trends in specificity.

Correlated Motions in Structural Biology

Correlated motions in proteins arising from the collective movements of residues have long been proposed to be fundamentally important to key properties of proteins, from allostery and catalysis to evolvability. Recent breakthroughs in structural biology have made it possible to capture proteins undergoing complex conformational changes, yet intrinsic correlated motions within a conformation remain one of the least understood facets of protein structure. For many decades, the analysis of total X-ray scattering held the promise of animating crystal structures with correlated motions. With recent advances in both X-ray detectors and data interpretation methods, this long-held promise can now be met. In this Perspective, we will introduce how correlated motions are captured in total scattering and provide guidelines for the collection, interpretation, and validation of data. As structural biology continues to push the boundaries, we see an opportunity to gain atomistic insight into correlated motions using total scattering as a bridge between theory and experiment.

Two β-Lactamase Variants with Reduced Clavulanic Acid Inhibition Display Different Millisecond Dynamics

The β-lactamase of Mycobacterium tuberculosis, BlaC, is susceptible to inhibition by clavulanic acid. The ability of this enzyme to escape inhibition through mutation was probed using error-prone PCR combined with functional screening in Escherichia coli. The variant that was found to confer the most inhibitor resistance, K234R, as well as variant G132N that was found previously were characterized using X-ray crystallography and nuclear magnetic resonance (NMR) relaxation experiments to probe structural and dynamic properties. The G132N mutant exists in solution in two almost equally populated conformations that exchange with a rate of ca. 88 s-1. The conformational change affects a broad region of the enzyme. The crystal structure reveals that the Asn132 side chain forces the peptide bond between Ser104 and Ile105 in a cis-conformation. The crystal structure suggests multiple conformations for several side chains (e.g., Ser104 and Ser130) and a short loop (positions 214 to 216). In the K234R mutant, the active-site dynamics are significantly diminished with respect to the wild-type enzyme. These results show that multiple evolutionary routes are available to increase inhibitor resistance in BlaC and that active-site dynamics on the millisecond time scale are not required for catalytic function.

Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have noncanonical and "long-distance" outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions ("toggle"), ten nonconserved positions showed progressive changes from a range of substitutions ("rheostat"), and three nonconserved positions tolerated almost all substitutions ("neutral"). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.