Protein dynamism and evolvability

Engineering Affibody Binders to Death Receptor 5 and Tumor Necrosis Factor Receptor 1 With Improved Stability

Protein developability is an important, yet often overlooked, aspect of protein discovery campaigns that is a key driver of utility. Recent advances have improved developability screening capacity, making it an increasingly viable option in early-stage discovery. Here, we engineered one component of developability, stability, of two affibody proteins-one that targets death receptor 5 and another that targets tumor necrosis factor receptor 1-previously evolved to bind receptor and non-competitively inhibit signaling via conformational modulation. Starting from an error-prone PCR library of each affibody, variants were screened via yeast surface display binder selections, including depletion of non-specific binders, followed by developability assessment using the on-yeast protease and yeast display level assays. Multiplex deep sequencing identified variants for further evaluation. Purified variants exhibited elevated stability-8°C to 14°C increase in Tm,app-with maintained 1-2 nM affinity for the TNFR1 affibody and 30-fold improvement in the DR5 affibody affinity to 0.8 nM.

Advances in uncovering the mechanisms of macromolecular conformational entropy

During protein folding, proteins transition from a disordered polymer into a globular structure, markedly decreasing their conformational degrees of freedom, leading to a substantial reduction in entropy. Nonetheless, folded proteins retain substantial entropy as they fluctuate between the conformations that make up their native state. This residual entropy contributes to crucial functions like binding and catalysis, supported by growing evidence primarily from NMR and simulation studies. Here, we propose three major ways that macromolecules use conformational entropy to perform their functions; first, prepaying entropic cost through ordering of the ground state; second, spatially redistributing entropy, in which a decrease in entropy in one area is reciprocated by an increase in entropy elsewhere; third, populating catalytically competent ensembles, in which conformational entropy within the enzymatic scaffold aids in lowering transition state barriers. We also provide our perspective on how solving the current challenge of structurally defining the ensembles encoding conformational entropy will lead to new possibilities for controlling binding, catalysis and allostery.

Frustration in physiology and molecular medicine

Molecules provide the ultimate language in terms of which physiology and pathology must be understood. Myriads of proteins participate in elaborate networks of interactions and perform chemical activities coordinating the life of cells. To perform these often amazing tasks, proteins must move and we must think of them as dynamic ensembles of three dimensional structures formed first by folding the polypeptide chains so as to minimize the conflicts between the interactions of their constituent amino acids. It is apparent however that, even when completely folded, not all conflicting interactions have been resolved so the structure remains 'locally frustrated'. Over the last decades it has become clearer that this local frustration is not just a random accident but plays an essential part of the inner workings of protein molecules. We will review here the physical origins of the frustration concept and review evidence that local frustration is important for protein physiology, protein-protein recognition, catalysis and allostery. Also, we highlight examples showing how alterations in the local frustration patterns can be linked to distinct pathologies. Finally we explore the extensions of the impact of frustration in higher order levels of organization of systems including gene regulatory networks and the neural networks of the brain.

Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity

Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how protein systems respond to changes in their environments, such as ligand binding, stress conditions, or perturbations like mutations and post-translational modifications, influencing signal transduction and cellular phenotypes. Here, we discuss how computational approaches, ranging from molecular dynamics (MD) simulations to AI-driven methods, are instrumental in studying protein dynamics from isolated molecules to large assemblies. These techniques elucidate conformational landscapes, ligand-binding mechanisms, and protein-protein interactions and are starting to support the construction of multiscale realistic representations of highly complex systems, ranging up to whole cell models. With cryo-electron microscopy, cryo-electron tomography, and AlphaFold accelerating the structural characterization of protein networks, we suggest that integrating AI and Machine Learning with multiscale MD methods will enhance fundamental understating for systems of ever-increasing complexity, usher in exciting possibilities for predictive modeling of the behavior of cell compartments or even whole cells. These advances are indeed transforming biophysics and chemical biology, offering new opportunities to study biomolecular mechanisms at atomic resolution.

gmx_RRCS: A Precision Tool for Detecting Subtle Conformational Dynamics in Molecular Simulations

Understanding conformational changes in biomolecules is crucial for insights into their biological functions and drug design, often studied by molecular dynamics (MD) simulations. However, current measurements such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), interface area, and minimum distances fail to capture subtle conformational changes, including hydrophobic packing. Our study introduces gmx_RRCS, a precision tool developed to detect subtle conformational dynamics in MD simulations by analyzing residue-residue contact score (RRCS). This tool quantifies interaction strengths between residues, enabling systematic analysis of both major and subtle conformational changes. Its application in investigating the molecular recognition of peptide 20 by glucagon-like peptide-1 receptor (GLP-1R) quantified the interactions of specific peptide moieties with the receptor, identified crucial positions for receptor binding, and highlighted key receptor residues involved in peptide recognition throughout the MD simulation. In phosphoinositide 3-kinase alpha (PI3Kα), gmx_RRCS revealed distinct conformational states of oncogenic hotspot residues by quantifying subtle sidechain reorientations and salt bridge dynamics. Similarly, in nucleic acid systems, the tool distinguished differential binding mechanisms between ochratoxin A and norfloxacin by revealing unique interaction patterns at critical nucleobases correlating with binding affinities. The tool has been validated through the analysis of over 150 simulation trajectories, covering 40,000 ns of total simulation time and 20 systems. gmx_RRCS significantly advances structural/molecular biology studies by enhancing our understanding of protein conformational dynamics, thereby facilitating rational drug design. gmx_RRCS is freely available on GitHub (https://github.com/RuijinHospitalRCMSB/gmx_RRCS) and PyPI (https://pypi.org/project/gmx-RRCS).

Conformational Dynamics and Catalytic Backups in a Hyper-Thermostable Engineered Archaeal Protein Tyrosine Phosphatase

Protein tyrosine phosphatases (PTPs) are a family of enzymes that play important roles in regulating cellular signaling pathways. The activity of these enzymes is regulated by the motion of a catalytic loop that places a critical conserved aspartic acid side chain into the active site for acid-base catalysis upon loop closure. These enzymes also have a conserved phosphate binding loop that is typically highly rigid and forms a well-defined anion binding nest. The intimate links between loop dynamics and chemistry in these enzymes make PTPs an excellent model system for understanding the role of loop dynamics in protein function and evolution. In this context, archaeal PTPs, which have evolved in extremophilic organisms, are highly understudied, despite their unusual biophysical properties. We present here an engineered chimeric PTP (ShufPTP) generated by shuffling the amino acid sequence of five extant hyperthermophilic archaeal PTPs. Despite ShufPTP's high sequence similarity to its natural counterparts, ShufPTP presents a suite of unique properties, including high flexibility of the phosphate binding P-loop, facile oxidation of the active site cysteine, mechanistic promiscuity, and most notably, hyperthermostability, with a denaturation temperature likely >130 °C (>8°C higher than the highest recorded growth temperature of any archaeal strain). Our combined structural, biochemical, biophysical and computational analysis provides insight both into how small steps in evolutionary space can radically modulate the biophysical properties of an enzyme, and showcase the tremendous potential of archaeal enzymes for biotechnology, to generate novel enzymes capable of operating under extreme conditions.

Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis

Protein evolution has shaped enzymes that maintain stability and function across diverse thermal environments. While sequence variation, thermal stability and conformational dynamics are known to influence an enzyme's thermal adaptation, how these factors collectively govern stability and function across diverse temperatures remains unresolved. Cytosolic malate dehydrogenase (cMDH), a citric acid cycle enzyme, is an ideal model for studying these mechanisms due to its temperature-sensitive flexibility and broad presence in species from diverse thermal environments. In this study, we employ techniques inspired by deep learning and statistical mechanics to uncover how sequence variation and conformational dynamics shape patterns of cMDH's thermal adaptation. By integrating coevolutionary models with variational autoencoders (VAE), we generate a latent generative landscape (LGL) of the cMDH sequence space, enabling us to explore mutational pathways and predict fitness using direct coupling analysis (DCA). Structure predictions via AlphaFold and molecular dynamics simulations further illuminate how variations in hydrophobic interactions and conformational flexibility contribute to the thermal stability of warm- and cold-adapted cMDH orthologs. Notably, we identify the ratio of hydrophobic contacts between two regions as a predictive order parameter for thermal stability features, providing a quantitative metric for understanding cMDH dynamics across temperatures. The integrative computational framework employed in this study provides mechanistic insights into protein adaptation at both sequence and structural levels, offering unique perspectives on the evolution of thermal stability and creating avenues for the rational design of proteins with optimized thermal properties.

Phylogenetic history and temperature adaptation contribute to structural and functional stability of proteins in marine mollusks

Teasing apart the influences of phylogenetic history from thermal adaptation is a focal challenge in understanding the factors driving change in protein stability. This study conducted comprehensive comparative analyses between the phylogenetic relationships and functional/structural stabilities at protein and mRNA levels of cytosolic malate dehydrogenase (cMDH) orthologs of 41 marine mollusks living at widely different environmental temperatures. At the protein level, a significant negative correlation between adaptation temperature and heat-induced movements of the cMDH backbone was found. The movement fluctuation of individual residue varied similarly among cMDH orthologs. At the mRNA level, the free energy that occurs during the formation of the ensemble of mRNA secondary structure was significantly positively correlated with adaptation temperature. The fraction of guanine and cytosine increased with adaptation temperature. The proportion of variance in adaptation temperature that can be explained by the thermal stability (R2) was decreased after phylogenetic generalized least squares but was almost significant at both protein and mRNA levels (P < 0.05). Those analyses reveal the phylogenetic influence on the thermal adaptation of species. Our findings indicated that multi-level analysis of orthologous proteins should be considered alongside phylogenetic history to permit the development of a more comprehensive understanding of protein thermal adaptation.

Emergence of specific binding and catalysis from a designed generalist binding protein

The evolution of binding and catalysis played a central role in the emergence of life. While natural proteins have finely tuned affinities for their primary ligands, they also bind weakly and promiscuously to other molecules, which serve as starting points for stepwise, incremental evolution of entirely new specificities. Thus, modern proteins emerged from the joint exploration of sequence and structural space. The ability of natural proteins to bind promiscuously to small molecule fragments has been widely evaluated using methods including crystallographic fragment screening. However, this approach had not been applied to de novo proteins. Here, we apply this method to explore the promiscuity of a de novo small molecule-binding protein ABLE. As in Nature, we found ABLE was capable of forming weak complexes, which were found to be excellent starting points for evolving entirely new functions, including a binder of a turn-on fluorophore and a highly efficient and specific Kemp eliminase enzyme. This work shows how Nature and protein designers can take advantage of promiscuous binding interactions to evolve new proteins with specialized functions.

From duplication to fusion: Expanding Dayhoff's model of protein evolution

Dayhoff's hypothesis suggests that complex proteins emerged from simpler peptides or domains, which duplicated and fused to create more complex proteins and novel functions. These processes expanded and diversified the protein repertoire within organisms. Extensive studies and reviews over the past two decades have highlighted the impact of gene duplication on protein evolution. However, the role of fusion in this evolutionary narrative remains less understood. This perspective seeks to address this gap by emphasizing the role of fusion in evolution. Fusion is critical in determining the evolutionary fate of duplicated protomers, either preserving their ancestral function or evolving entirely new functions. It complements mutations, insertions, and deletions as evolutionary steps to enhance protein evolvability by expanding the capacity of the protein to explore new structural and functional space.

AI-enabled alkaline-resistant evolution of protein to apply in mass production

Artificial intelligence (AI) models have been used to study the compositional regularities of proteins in nature, enabling it to assist in protein design to improve the efficiency of protein engineering and reduce manufacturing cost. However, in industrial settings, proteins are often required to work in extreme environments where they are relatively scarce or even non-existent in nature. Since such proteins are almost absent in the training datasets, it is uncertain whether AI model possesses the capability of evolving the protein to adapt extreme conditions. Antibodies are crucial components of affinity chromatography, and they are hoped to remain active at the extreme environments where most proteins cannot tolerate. In this study, we applied an advanced large language model (LLM), the Pro-PRIME model, to improve the alkali resistance of a representative antibody, a VHH antibody capable of binding to growth hormone. Through two rounds of design, we ensured that the selected mutant has enhanced functionality, including higher thermal stability, extreme pH resistance, and stronger affinity, thereby validating the generalized capability of the LLM in meeting specific demands. To the best of our knowledge, this is the first LLM-designed protein product, which is successfully applied in mass production.

Evolution Enhances Kemp Eliminase Activity by Optimizing Oxyanion Stabilization and Conformational Flexibility

The base-promoted Kemp elimination reaction has been used as a model system for enzyme design. Among the multiple computationally designed and evolved Kemp eliminases generated along the years, the HG3-to-HG3.17 evolutionary trajectory is particularly interesting due to the high catalytic efficiency of HG3.17 and the debated role of glutamine 50 (Gln50) as potential oxyanion stabilizer. This study aims to elucidate the structural and dynamic changes along the evolutionary pathway from HG3 to HG3.17 that contribute to improved catalytic efficiency. In particular, we evaluate key variants along the HG3 evolutionary trajectory via molecular dynamics simulations coupled to non-covalent interactions and water analysis. Our computational study indicates that HG3.17 can adopt a catalytically competent conformation promoted by a water-mediated network of non-covalent interactions, in which aspartate 127 (Asp127) is properly positioned for proton abstraction and Gln50 and to some extent mutation cysteine 84 (Cys84) contribute to oxyanion stabilization. We find that HG3.17 exhibits a rather high flexibility of Gln50, which is regulated by the conformation adopted by the active site residue tryptophan 44 (Trp44). This interplay between Gln50 and Trp44 positioning induced by distal active site mutations affects the water-mediated network of non-covalent interactions, Gln50 preorganization, and water content of the active site pocket.

Mutations to transcription factor MAX allosterically increase DNA selectivity by altering folding and binding pathways

Understanding how proteins discriminate between preferred and non-preferred ligands ('selectivity') is essential for predicting biological function and a central goal of protein engineering efforts, yet the biophysical mechanisms underpinning selectivity remain poorly understood. Towards this end, we study how variants of the promiscuous transcription factor (TF) MAX (H. sapiens) alter DNA specificity and selectivity, yielding >1700 Kds and >500 rate constants in complex with multiple DNA sequences. Twenty-two of the 240 assayed MAX point mutations enhance selectivity, yet none of these mutations occur at residues that contact nucleotides in published structures. By applying thermodynamic and kinetic models to these results and previous observations for the highly similar yet far more selective TF Pho4 (S. cerevisiae), we find that these mutations enhance selectivity by altering partitioning between or affinity within conformations with different intrinsic selectivity, providing a mechanistic basis for allosteric modulation of ligand selectivity. These results highlight the importance of conformational heterogeneity in determining sequence selectivity and can guide future efforts to engineer selective proteins.

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.

Enzyme-Regulated Non-Thermal Fluctuations Enhance Ligand Diffusion and Receptor-Mediated Endocytosis

Active enzymes during catalyzing chemical reactions, have been found to generate significant mechanical fluctuations, which can influence the dynamics of their surroundings. These phenomena open new avenues for controlling mass transport in complex and dynamically inhomogeneous environments through localized chemical reactions. To explore this potential, we studied the uptake of transferrin molecules in retinal pigment epithelium (RPE) cells via clathrin-mediated endocytosis. In the presence of enzyme catalysis in the extracellular matrix, we observed a significant enhancement in the transport of fluorophore-tagged transferrin inside the cells. Fluorescence correlation spectroscopy measurements showed substantial increase in transferrin diffusion in the presence of active fluctuations. This study sheds light on the possibility that enzyme-substrate reactions within the extracellular matrix may induce long-range mechanical influences, facilitating targeted material delivery within intracellular milieu more efficiently than passive diffusion. These insights are expected to contribute to the development of better therapeutic strategies by overcoming limitations imposed by slow molecular diffusion under complex environments.

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.

A general temperature-guided language model to design proteins of enhanced stability and activity

Designing protein mutants with both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can suggest protein mutants with improved stability and activity without any prior experimental mutagenesis data for the specified protein. Leveraging temperature-aware language modeling, PRIME demonstrated superior predictive ability compared to current state-of-the-art models on the public mutagenesis dataset across 283 protein assays. Furthermore, we validated PRIME's predictions on five proteins, examining the impact of the top 30 to 45 single-site mutations on various protein properties, including thermal stability, antigen-antibody binding affinity, and the ability to polymerize nonnatural nucleic acid or resilience to extreme alkaline conditions. More than 30% of PRIME-recommended mutants exhibited superior performance compared to their premutation counterparts across all proteins and desired properties. We developed an efficient and effective method based on PRIME to rapidly obtain multisite mutants with enhanced activity and stability. Hence, PRIME demonstrates broad applicability in protein engineering.

Engineering inhibitory repeat domains of Pin-II type proteinase inhibitors indicate their high structural-functional tolerance to mutagenesis

Plant proteinase inhibitors (PIs) are critical in defending against biotic stress. Most PIs contain an inhibitory repeat domain (IRD), which serves as the functional component, displaying a high degree of sequence and structural conservation. In this study, we examined the structural and functional resilience of IRDs using a combination of computational modeling and experimental validation. We have taken an evolution-based approach to enhance the PIs effectiveness of two previously identified Capsicum annuum IRDs, IRD4 and IRD10. Through in silico site-saturation mutagenesis of IRD4 and IRD10, we identified key sites associated with enhanced PI activity for targeted mutagenesis. Binding energy predictions for a mutant IRD library, tested against target proteases, suggested that positions R11 and N32 in IRD4 and N32 and H33 in IRD10 were promising candidates for further modification to improve inhibitory potential. Subsequent experimental validation revealed that the mutant proteins IRD4_R11K and IRD4_N32S exhibited stronger chymotrypsin inhibition than the wild-type (WT) IRD4. Similarly, the mutants IRD10_N32S and IRD10_H33 N demonstrated improved trypsin inhibition relative to the WT IRD10. These findings indicate that engineered IRD variants can tolerate structural changes while maintaining or enhancing their inhibitory activity against target proteases. Overall, this study demonstrates the potential of engineering PIs to increase their structural and functional resilience, offering new opportunities for biotechnological applications.

Building, Maintaining, and (re-)Deploying Genetic Toolkits during Convergent Evolution

A surprising insight from the advent of genomic sequencing was that many genes are deeply conserved during evolution. With a particular focus on genes that interact with light in animals, I explore the metaphor of genetic toolkits, which can be operationalized as lists of genes involved in a trait of interest. A fascinating observation is that genes of a toolkit are often used again and again during convergent evolution, sometimes across vast phylogenetic distances. Such a pattern in the evolution of toolkits requires three different stages: (i) origin, (ii) maintenance, and (iii) redeployment of the genes. The functional origins of toolkit genes might often be rooted in interactions with external environments. The origins of light interacting genes in particular may be tied to ancient responses to photo-oxidative stress, inspiring questions about the extent to which the evolution of other toolkits was also impacted by stress. Maintenance of genetic toolkits over long evolutionary timescales requires gene multifunctionality to prevent gene loss when a trait of interest is absent. Finally, the deployment of toolkit genes in convergently evolved traits like eyes sometimes involves the repeated use of similar, ancient genes yet other times involves different genes, specific to each convergent origin. How often a particular gene family is used time and again for the same function may depend on how many possible biological solutions are available. When few solutions exist and the genes are maintained, evolution may be constrained to use the same genes over and over. However, when many different solutions are possible, convergent evolution often takes multiple different paths. Therefore, a focus on genetic toolkits highlights the combination of legacy-plus-innovation that drives the evolution of biological diversity.

The origin of mutational epistasis

The interconnected processes of protein folding, mutations, epistasis, and evolution have all been the subject of extensive analysis throughout the years due to their significance for structural and evolutionary biology. The origin (molecular basis) of epistasis-the non-additive interactions between mutations-is still, nonetheless, unknown. The existence of a new perspective on protein folding, a problem that needs to be conceived as an 'analytic whole', will enable us to shed light on the origin of mutational epistasis at the simplest level-within proteins-while also uncovering the reasons why the genetic background in which they occur, a key component of molecular evolution, could foster changes in epistasis effects. Additionally, because mutations are the source of epistasis, more research is needed to determine the impact of post-translational modifications, which can potentially increase the proteome's diversity by several orders of magnitude, on mutational epistasis and protein evolvability. Finally, a protein evolution thermodynamic-based analysis that does not consider specific mutational steps or epistasis effects will be briefly discussed. Our study explores the complex processes behind the evolution of proteins upon mutations, clearing up some previously unresolved issues, and providing direction for further research.

Structural Plasticity within 3-Hydroxy-3-Methylglutaryl Synthases Catalyzing the First Step of β-Branching in Polyketide Biosynthesis Underpins a Dynamic Mechanism of Substrate Accommodation

Understanding how enzymes have been repurposed by evolution to carry out new functions is a key goal of mechanistic enzymology. In this study we aimed to identify the adaptations required to allow the 3-hydroxy-3-methylglutaryl (HMG)-CoA synthase (HMGCS) enzymes of primary isoprenoid assembly to function in specialized polyketide biosynthetic pathways, where they initiate β-branching. This role notably necessitates that the HMG synthases (HMGSs) act on substrates tethered to noncatalytic acyl carrier protein (ACP) domains instead of coenzyme A, and accommodation of substantially larger chains within the active sites. Here, we show using a combination of X-ray crystallography and small-angle X-ray scattering, that a model HMGS from the virginiamycin system exhibits markedly increased flexibility relative to its characterized HMGCS counterparts. This mobility encompasses multiple secondary structural elements that define the dimensions and chemical nature of the active site, as well the catalytic residues themselves. This result was unexpected given the well-ordered character of the HMGS within the context of an HMGS/ACP complex, but analysis by synchrotron radiation circular dichroism demonstrates that this interaction leads to increased HMGS folding. This flexible to more rigid transition is notably not accounted for by AlphaFold2, which yielded a structural model incompatible with binding of the native substrates. Taken together, these results illustrate the continued necessity of an integrative structural biology approach combining crystallographic and solution-phase data for elucidating the mechanisms underlying enzyme remodeling, information which can inform strategies to replicate such evolution effectively in the laboratory.

Effects of selection stringency on the outcomes of directed evolution

Directed evolution makes mutant lineages compete in climbing complicated sequence-function landscapes. Given this underlying complexity it is unclear how selection stringency, a ubiquitous parameter of directed evolution, impacts the outcome. Here we approach this question in terms of the fitnesses of the candidate variants at each round and the heterogeneity of their distributions of fitness effects. We show that even if the fittest mutant is most likely to yield the fittest mutants in the next round of selection, diversification can improve outcomes by sampling a larger variety of fitness effects. We find that heterogeneity in fitness effects between variants, larger population sizes, and evolution over a greater number of rounds all encourage diversification.

Structural basis for FN3K-mediated protein deglycation

Protein glycation is a universal, non-enzymatic modification that occurs when a sugar covalently attaches to a primary amine. These spontaneous modifications may have deleterious or regulatory effects on protein function, and their removal is mediated by the conserved metabolic kinase fructosamine-3-kinase (FN3K). Despite its crucial role in protein repair, we currently have a poor understanding of how FN3K engages or phosphorylates its substrates. By integrating structural biology and biochemistry, we elucidated the catalytic mechanism for FN3K-mediated protein deglycation. Our work identifies key amino acids required for binding and phosphorylating glycated substrates and reveals the molecular basis of an evolutionarily conserved protein repair pathway. Additional structural-functional studies revealed unique structural features of human FN3K as well as differences in the dimerization behavior and regulation of FN3K family members. Our findings improve our understanding of the structure of FN3K and its catalytic mechanism, which opens new avenues for therapeutically targeting FN3K.

Determinants of Unfolding Cooperativity and Binding Are Decoupled in a DNA Binding Domain

The relative magnitudes of noncovalent stabilization energies or the coupling free energies in folded proteins are anisotropically distributed, uniquely influencing folding and functional behaviors. In this regard, the fructose repressor (FruR) DBD belonging to the LacR repressor family harbors a three-residue insertion─KQY─between the canonical second and third helices. This sequence insertion promotes a strong Tyr-Tyr stacking interaction that is not observed in related homologues. Combining experiments with simulations, we show that the Tyr-Tyr stacking contributes to a decoupled unfolding due to the localization of a large part of the stabilization energy in this specific structural region. This leads to melting temperatures from different probes spanning nearly 10 K, while concomitantly stabilizing a partially structured intermediate state. Disruption of the aromatic stacking interaction via an alanine mutation promotes a molten-globular state whose native ensemble is replete with non-native interactions while displaying enhanced thermodynamic fluctuations and minimal calorimetric cooperativity. Surprisingly, the molten-globular variant of FruR DBD binds to the operator site on DNA with an affinity similar to that of the wild-type but with altered secondary-structure characteristics in the bound state, underscoring the chaperone-like role of DNA through its large negative electrostatic potential. FruR DBD thus appears to be at the verge of disorder as expected of an entropically destabilizing three-residue insertion but is rescued by the aromatic stacking interaction that distinctly dictates the finer details of stability, cooperativity, and binding.

Evolutionary origins and innovations sculpting the mammalian PRPS enzyme complex

The phosphoribosyl pyrophosphate synthetase (PRPS) enzyme conducts a chokepoint reaction connecting central carbon metabolism and nucleotide production pathways, making it essential for life1,2. Here, we show that the presence of multiple PRPS-encoding genes is a hallmark trait of eukaryotes, and we trace the evolutionary origins and define the individual functions of each of the five mammalian PRPS homologs - three isozymes (one testis-restricted)3,4 and two non-enzymatic associated proteins (APs)5,6 - which we demonstrate operate together as a large molecular weight complex capable of attaining a heterogeneous array of functional multimeric configurations. Employing a repertoire of isogenic fibroblast clones in all viable individual or combinatorial assembly states, we define preferential interactions between subunits, and we show that cells lacking PRPS2, PRPSAP1, and PRPSAP2 render PRPS1 into aberrant homo-oligomeric assemblies with diminished metabolic flux and impaired proliferative capacity. We demonstrate how numerous evolutionary innovations in the duplicated genes have created specialized roles for individual complex members and identify translational control mechanisms that enable fine-tuned regulation of PRPS assembly and activity, which provide clues into the positive and negative selective pressures that facilitate metabolic flexibility and tissue specialization in advanced lifeforms. Collectively, our study demonstrates how evolution has transformed a single PRPS gene into a multimeric complex endowed with functional and regulatory features that govern cellular biochemistry.

Catalytic Redundancies and Conformational Plasticity Drives Selectivity and Promiscuity in Quorum Quenching Lactonases

Several enzymes from the metallo-β-lactamase-like family of lactonases (MLLs) degrade N-acyl L-homoserine lactones (AHLs). They play a role in a microbial communication system known as quorum sensing, which contributes to pathogenicity and biofilm formation. Designing quorum quenching (QQ) enzymes that can interfere with this communication allows them to be used in a range of industrial and biomedical applications. However, tailoring these enzymes for specific communication signals requires a thorough understanding of their mechanisms and the physicochemical properties that determine their substrate specificities. We present here a detailed biochemical, computational, and structural study of GcL, which is a highly proficient and thermostable MLL with broad substrate specificity. We show that GcL not only accepts a broad range of substrates but also hydrolyzes these substrates through at least two different mechanisms. Further, the preferred mechanism appears to depend on both the substrate structure and/or the nature of the residues lining the active site. We demonstrate that other lactonases, such as AiiA and AaL, show similar mechanistic promiscuity, suggesting that this is a shared feature among MLLs. Mechanistic promiscuity has been seen previously in the lactonase/paraoxonase PON1, as well as with protein tyrosine phosphatases that operate via a dual general acid mechanism. The apparent prevalence of this phenomenon is significant from both a biochemical and protein engineering perspective: in addition to optimizing for specific substrates, it may be possible to optimize for specific mechanisms, opening new doors not just for the design of novel quorum quenching enzymes but also of other mechanistically promiscuous enzymes.

Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign

Enzymes exhibit diverse conformations, as represented in the free energy landscape (FEL). Such conformational diversity provides enzymes with the ability to evolve towards novel functions. The challenge lies in identifying mutations that enhance specific conformational changes, especially if located in distal sites from the active site cavity. The shortest path map (SPM) method, which we developed to address this challenge, constructs a graph based on the distances and correlated motions of residues observed in nanosecond timescale molecular dynamics (MD) simulations. We recently introduced a template based AlphaFold2 (tAF2) approach coupled with 10 nanosecond MD simulations to quickly estimate the conformational landscape of enzymes and assess how the FEL is shifted after mutation. In this study, we evaluate the potential of SPM when coupled with tAF2-MD in estimating conformational heterogeneity and identifying key conformationally-relevant positions. The selected model system is the beta subunit of tryptophan synthase (TrpB). We compare how the SPM pathways differ when integrating tAF2 with different MD simulation lengths from as short as 10 ns until 50 ns and considering two distinct Amber forcefield and water models (ff14SB/TIP3P versus ff19SB/OPC). The new methodology can more effectively capture the distal mutations found in laboratory evolution, thus showcasing the efficacy of tAF2-MD-SPM in rapidly estimating enzyme dynamics and identifying the key conformationally relevant hotspots for computational enzyme engineering.

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

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

Peptides En Route from Prebiotic to Biotic Catalysis

In the quest to understand prebiotic catalysis, different molecular entities, mainly minerals, metal ions, organic cofactors, and ribozymes, have been implied as key players. Of these, inorganic and organic cofactors have gained attention for their ability to catalyze a wide array of reactions central to modern metabolism and frequently participate in these reactions within modern enzymes. Nevertheless, bridging the gap between prebiotic and modern metabolism remains a fundamental question in the origins of life. In this Account, peptides are investigated as a potential bridge linking prebiotic catalysis by minerals/cofactors to enzymes that dominate modern life's chemical reactions. Before ribosomal synthesis emerged, peptides of random sequences were plausible on early Earth. This was made possible by different sources of amino acid delivery and synthesis, as well as their condensation under a variety of conditions. Early peptides and proteins probably exhibited distinct compositions, enriched in small aliphatic and acidic residues. An increase in abundance of amino acids with larger side chains and canonical basic groups was most likely dependent on the emergence of their more challenging (bio)synthesis. Pressing questions thus arise: how did this composition influence the early peptide properties, and to what extent could they contribute to early metabolism? Recent research from our group and colleagues shows that highly acidic peptides/proteins comprising only the presumably "early" amino acids are in fact competent at secondary structure formation and even possess adaptive folding characteristics such as spontaneous refoldability and chaperone independence to achieve soluble structures. Moreover, we showed that highly acidic proteins of presumably "early" composition can still bind RNA by utilizing metal ions as cofactors to bridge carboxylate and phosphoester functional groups. And finally, ancient organic cofactors were shown to be capable of binding to sequences from amino acids considered prebiotically plausible, supporting their folding properties and providing functional groups, which would nominate them as catalytic hubs of great prebiotic relevance. These findings underscore the biochemical plausibility of an early peptide/protein world devoid of more complex amino acids yet collaborating with other catalytic species. Drawing from the mechanistic properties of protein-cofactor catalysis, it is speculated here that the early peptide/protein-cofactor ensemble could facilitate a similar range of chemical reactions, albeit with lower catalytic rates. This hypothesis invites a systematic experimental test. Nonetheless, this Account does not exclude other scenarios of prebiotic-to-biotic catalysis or prioritize any specific pathways of prebiotic syntheses. The objective is to examine peptide availability, composition, and functional potential among the various factors involved in the emergence of early life.

Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence

Artificial Intelligence (AI) is having a revolutionary impact on our societies. It is helping humans in facing the global challenges of this century. Traditionally, AI is developed in software or through neuromorphic engineering in hardware. More recently, a brand-new strategy has been proposed. It is the so-called Chemical AI (CAI), which exploits molecular, supramolecular, and systems chemistry in wetware to mimic human intelligence. In this work, two promising approaches for boosting CAI are described. One regards designing and implementing neural surrogates that can communicate through optical or chemical signals and give rise to networks for computational purposes and to develop micro/nanorobotics. The other approach concerns "bottom-up synthetic cells" that can be exploited for applications in various scenarios, including future nano-medicine. Both topics are presented at a basic level, mainly to inform the broader audience of non-specialists, and so favour the rise of interest in these frontier subjects.

Phylogenetic variations in a novel family of hyperstable apple snail egg proteins: insights into structural stability and functional trends

The relationship between protein stability and functional evolution is little explored in proteins purified from natural sources. Here, we investigated a novel family of egg proteins (Perivitellin-1, PV1) from Pomacea snails. Their remarkable stability and clade-related functions in most derived clades (Canaliculata and Bridgesii) make them excellent candidates for exploring this issue. To that aim, we studied PV1 (PpaPV1) from the most basal lineage, Flagellata. PpaPV1 displays unparalleled structural and kinetic stability, surpassing PV1s from derived clades, ranking among the most hyperstable proteins documented in nature. Its spectral features contribute to a pale egg coloration, exhibiting a milder glycan binding lectin activity with a narrower specificity than PV1s from the closely related Bridgesii clade. These findings provide evidence for substantial structural and functional changes throughout the genus' PV1 evolution. We observed that structural and kinetic stability decreased in a clade-related fashion and was associated with large variations in defensive traits. For instance, pale PpaPV1 lectin turns potent in the Bridgesii clade, adversely affecting gut morphology, while giving rise to brightly colored PV1s providing eggs with a conspicuous, probably warning signal in the Canaliculata clade. This work provides a comprehensive comparative analysis of PV1s from various apple snail species within a phylogenetic framework, offering insights into the interplay among their structural features, stability profiles and functional roles. More broadly, our work provides one of the first examples from natural evolution showing the crucial link among protein structure, stability and evolution of new functions.

Conformational Dynamics, Energetics, and the Divergent Evolution of Allosteric Regulation: The Case of the Yeast MAPK Family

Allosteric mechanisms provide finely-tuned control over signalling proteins. Proteins of the same family may share high sequence identity and structural similarity but show distinct traits of allosteric control and evolutionary divergent regulation. Revealing the determinants of such properties may be important to understand the molecular bases of different regulatory pathways. Herein, we investigate whether and how evolutionarily-divergent traits of allosteric regulation in homologous proteins can be decoded in terms of internal dynamics and interaction networks that support functionally oriented conformations. In this framework, we start from the comparative analysis of the dynamics and energetics of the yeast MAP Kinases (MAPKs) Fus3 and Kss1 in their native basins. Importantly, distinctive dynamic and energetic stabilization features emerge, which can be related to the two proteins' differential ability to be phosphorylated and engage with the allosteric activator Ste5. We then expanded our study to other evolutionarily-related MAPKs. We show that the dynamical and energetical traits defining the distinct regulatory profiles of Fus3 and Kss1 can be traced along their evolutionary tree. Overall, our approach is able to reconnect (latent) allostery with the principal elements of protein structural stabilization and dynamics, showing how allosteric regulation was encrypted in MAPKs structure well before Ste5 appearance.

Enhancing predictions of protein stability changes induced by single mutations using MSA-based Language Models

MOTIVATION

Protein Language Models offer a new perspective for addressing challenges in structural biology, while relying solely on sequence information. Recent studies have investigated their effectiveness in forecasting shifts in thermodynamic stability caused by single amino acid mutations, a task known for its complexity due to the sparse availability of data, constrained by experimental limitations. To tackle this problem, we introduce two key novelties: leveraging a Protein Language Model that incorporates Multiple Sequence Alignments to capture evolutionary information, and using a recently released mega-scale dataset with rigorous data pre-processing to mitigate overfitting.

RESULTS

We ensure comprehensive comparisons by fine-tuning various pre-trained models, taking advantage of analyses such as ablation studies and baselines evaluation. Our methodology introduces a stringent policy to reduce the widespread issue of data leakage, rigorously removing sequences from the training set when they exhibit significant similarity with the test set. The MSA Transformer emerges as the most accurate among the models under investigation, given its capability to leverage co-evolution signals encoded in aligned homologous sequences. Moreover, the optimized MSA Transformer outperforms existing methods and exhibits enhanced generalization power, leading to a notable improvement in predicting changes in protein stability resulting from point mutations.

AVAILABILITY AND IMPLEMENTATION

Code and data at https://github.com/RitAreaSciencePark/PLM4Muts.

SUPPLEMENTARY INFORMATION

Supplementary Information is available at Bioinformatics online.

Bacteriophage Φ21's receptor-binding protein evolves new functions through destabilizing mutations that generate non-genetic phenotypic heterogeneity

How viruses evolve to expand their host range is a major question with implications for predicting the next pandemic. Gain-of-function experiments have revealed that host-range expansions can occur through relatively few mutations in viral receptor-binding proteins, and the search for molecular mechanisms that explain such expansions is underway. Previous research on expansions of receptor use in bacteriophage λ has shown that mutations that destabilize λ's receptor-binding protein cause it to fold into new conformations that can utilize novel receptors but have weakened thermostability. These observations led us to hypothesize that other viruses may take similar paths to expand their host range. Here, we find support for our hypothesis by studying another virus, bacteriophage 21 (Φ21), which evolves to use two new host receptors within 2 weeks of laboratory evolution. By measuring the thermodynamic stability of Φ21 and its descendants, we show that as Φ21 evolves to use new receptors and expands its host range, it becomes less stable and produces viral particles that are genetically identical but vary in their thermostabilities. Next, we show that this non-genetic heterogeneity between particles is directly associated with receptor use innovation, as phage particles with more derived receptor-use capabilities are more unstable and decay faster. Lastly, by manipulating the expression of protein chaperones during Φ21 infection, we demonstrate that heterogeneity in receptor use of phage particles arises during protein folding. Altogether, our results provide support for the hypothesis that viruses can evolve new receptor-use tropisms through mutations that destabilize the receptor-binding protein and produce multiple protein conformers.

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Four Parallel Pathways in T4 Ligase-Catalyzed Repair of Nicked DNA with Diverse Bending Angles

The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase-AMP complex and the ligase-AMP-DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase-AMP complex that persist in the ligase-AMP-DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Effects of selection stringency on the outcomes of directed evolution

Directed evolution makes mutant lineages compete in climbing complicated sequence-function landscapes. Given this underlying complexity it is unclear how selection stringency, a ubiquitous parameter of directed evolution, impacts the outcome. Here we approach this question in terms of the fitnesses of the candidate variants at each round and the heterogeneity of their distributions of fitness effects. We show that even if the fittest mutant is most likely to yield the fittest mutants in the next round of selection, diversification can improve outcomes by sampling a larger variety of fitness effects. We find that heterogeneity in fitness effects between variants, larger population sizes, and evolution over a greater number of rounds all encourage diversification.

Rational Design of Loop Dynamics for a Barrel-Shaped Enzyme by Introducing Disulfide Bonds

Loop dynamics redesign is an important strategy to manipulate protein function. Cellobiose 2-epimerase (CE) and other members of its superfamily are widely used for diverse industrial applications. The structural feature of the loops connecting barrel helices contributes greatly to the differences in their functional characteristics. Inspired by the in-silico mutation with molecular dynamics (MD) simulation analysis, we propose a strategy for identifying disulfide bond mutation candidates based on the prediction of protein flexibility and residue-residue interaction. The most beneficial mutant with the newly introduced disulfide bond would simultaneously improve both its thermostability and its reaction propensity to the targeting isomerization product. The ratio of the isomerization/epimerization catalytic rate was improved from 4:103 to 9:22. MD simulation and binding free energy calculations were applied to provide insights into molecular recognition upon mutations. The comparative analysis of enzyme/substrate binding modes indicates that the altered catalytic reaction pathway is due to less efficient binding of the native product. The key residue responsible for the observed phenotype was identified by energy decomposition and was further confirmed by the mutation experiment. The rational design of the key loop region might be a promising strategy to alter the catalytic behavior of all (α/α)6-barrel-like proteins.

Molecular Ratchets and Kinetic Asymmetry: Giving Chemistry Direction

Over the last two decades ratchet mechanisms have transformed the understanding and design of stochastic molecular systems-biological, chemical and physical-in a move away from the mechanical macroscopic analogies that dominated thinking regarding molecular dynamics in the 1990s and early 2000s (e.g. pistons, springs, etc), to the more scale-relevant concepts that underpin out-of-equilibrium research in the molecular sciences today. Ratcheting has established molecular nanotechnology as a research frontier for energy transduction and metabolism, and has enabled the reverse engineering of biomolecular machinery, delivering insights into how molecules 'walk' and track-based synthesisers operate, how the acceleration of chemical reactions enables energy to be transduced by catalysts (both motor proteins and synthetic catalysts), and how dynamic systems can be driven away from equilibrium through catalysis. The recognition of molecular ratchet mechanisms in biology, and their invention in synthetic systems, is proving significant in areas as diverse as supramolecular chemistry, systems chemistry, dynamic covalent chemistry, DNA nanotechnology, polymer and materials science, molecular biology, heterogeneous catalysis, endergonic synthesis, the origin of life, and many other branches of chemical science. Put simply, ratchet mechanisms give chemistry direction. Kinetic asymmetry, the key feature of ratcheting, is the dynamic counterpart of structural asymmetry (i.e. chirality). Given the ubiquity of ratchet mechanisms in endergonic chemical processes in biology, and their significance for behaviour and function from systems to synthesis, it is surely just as fundamentally important. This Review charts the recognition, invention and development of molecular ratchets, focussing particularly on the role for which they were originally envisaged in chemistry, as design elements for molecular machinery. Different kinetically asymmetric systems are compared, and the consequences of their dynamic behaviour discussed. These archetypal examples demonstrate how chemical systems can be driven inexorably away from equilibrium, rather than relax towards it.

Innovative communication of molecular evolution through sound: a biological sonification concert

Background

A major challenge of evolutionary biology is making underlying concepts accessible to wide audiences. One method for doing so is to utilise multi-media formats that have potential to engage and inform through entertainment. This pilot study outlines and discusses a sonification concert that integrated musical performance with a range of evolutionary concepts and ideas fundamental to an understanding of evolution, such as protein sequences. We aimed to showcase sound-art objects and live-coding performances created using sonification as a mechanism for presenting complex biological processes to both researcher and non-researchers. We sought to evaluate the effectiveness of this art-adjacent practice for public engagement with evolutionary biology research, and also to gather feedback to guide future events. Toward this end, we held a live concert showcasing biologically-based algorithmic music exploring links between evolutionary biology research, sound art, and musical performance. The event had three main acts: a generative audio-visual piece giving an artistic representation of SARS coronavirus based on a parameter-mapping sonification of protein sequence of the replicase polyprotein; a pre-recorded string ensemble demonstrating the effects of codon selection on translation speed using parameter-mapping sonification; and a live-coded music piece interactively sonifying protein structures.

Results

Our event attracted 90 attendees. We evaluated success using direct observation and written feedback forms with a 58% response rate: 95% of respondents stated they had enjoyed the event and 63% indicated they were inspired by it.

Conclusions

Presenting the sonic outputs of sonification research in a concert format showed good potential for the pursuit of public engagement with evolutionary biology research, demonstrating the ability to engage curiosity and inspire an audience while also conveying scientific content alongside the nuanced and complex world of modern evolutionary biology.

A finely balanced order-disorder equilibrium sculpts the folding-binding landscape of an antibiotic sequestering protein

TipA, a MerR family transcription factor from Streptomyces lividans, promotes antibiotic resistance by sequestering broad-spectrum thiopeptide-based antibiotics, thus counteracting their inhibitory effect on ribosomes. TipAS, a minimal binding motif which is expressed as an isoform of TipA, harbors a partially disordered N-terminal subdomain that folds upon binding multiple antibiotics. The extent and nature of the underlying molecular heterogeneity in TipAS that shapes its promiscuous folding-function landscape is an open question and is critical for understanding antibiotic-sequestration mechanisms. Here, combining equilibrium and time-resolved experiments, statistical modeling, and simulations, we show that the TipAS native ensemble exhibits a pre-equilibrium between binding-incompetent and binding-competent substates, with the fully folded state appearing only as an excited state under physiological conditions. The binding-competent state characterized by a partially structured N-terminal subdomain loses structure progressively in the physiological range of temperatures, swells on temperature increase, and displays slow conformational exchange across multiple conformations. Binding to the bactericidal antibiotic thiostrepton follows a combination of induced-fit and conformational-selection-like mechanisms, via partial binding and concomitant stabilization of the binding-competent substate. These ensemble features are evolutionarily conserved across orthologs from select bacteria that infect humans, underscoring the functional role of partial disorder in the native ensemble of antibiotic-sequestering proteins belonging to the MerR family.

Catalytic Redundancies and Conformational Plasticity Drives Selectivity and Promiscuity in Quorum Quenching Lactonases

Several enzymes from the metallo-β-lactamase-like family of lactonases (MLLs) degrade N- acyl-L-homoserine lactones (AHLs). In doing so, they play a role in a microbial communication system, quorum sensing, which contributes to pathogenicity and biofilm formation. There is currently great interest in designing quorum quenching ( QQ ) enzymes that can interfere with this communication and be used in a range of industrial and biomedical applications. However, tailoring these enzymes for specific targets requires a thorough understanding of their mechanisms and the physicochemical properties that determine their substrate specificities. We present here a detailed biochemical, computational, and structural study of the MLL GcL, which is highly proficient, thermostable, and has broad substrate specificity. Strikingly, we show that GcL does not only accept a broad range of substrates but is also capable of utilizing different reaction mechanisms that are differentially used in function of the substrate structure or the remodeling of the active site via mutations. Comparison of GcL to other lactonases such as AiiA and AaL demonstrates similar mechanistic promiscuity, suggesting this is a shared feature across lactonases in this enzyme family. Mechanistic promiscuity has previously been observed in the lactonase/paraoxonase PON1, as well as with protein tyrosine phosphatases that operate via a dual general-acid mechanism. The apparent prevalence of this phenomenon is significant from both a biochemical and an engineering perspective: in addition to optimizing for specific substrates, it is possible to optimize for specific mechanisms, opening new doors not just for the design of novel quorum quenching enzymes, but also of other mechanistically promiscuous enzymes.

Sequence-dependent and -independent information in a combined random energy model for protein folding and coding

Random energy models (REMs) provide a simple description of the energy landscapes that guide protein folding and evolution. The requirement of a large energy gap between the native structure and unfolded conformations, considered necessary for cooperative, protein-like, folding behavior, indicates that proteins differ markedly from random heteropolymers. It has been suggested, therefore, that natural selection might have acted to choose nonrandom amino acid sequences satisfying this particular condition, implying that a large fraction of possible, unselected random sequences, would not fold to any structure. From an informational perspective, however, this scenario could indicate that protein structures, regarded as messages to be transmitted through a communication channel, would not be efficiently encoded in amino acid sequences, regarded as the communication channel for this transmission, since a large fraction of possible channel states would not be used. Here, we use a combined REM for conformations and sequences, with previously estimated parameters for natural proteins, to explore an alternative possibility in which the appropriate shape of the landscape results mainly from the deviation from randomness of possible native structures instead of sequences. We observe that this situation emerges naturally if the distribution of conformational energies happens to arise from two independent contributions corresponding to sequence-dependent and -independent terms. This construction is consistent with the hypothesis of a protein burial folding code, with native structures being determined by a modest amount of sequence-dependent atomic burial information with sequence-independent constraints imposed by unspecific hydrogen bond formation. More generally, an appropriate combination of sequence-dependent and -independent information accommodates the possibility of an efficient structural encoding with the main physical requirement for folding, providing possible insight not only on the folding process but also on several aspects sequence evolution such as neutral networks, conformational coverage, and de novo gene emergence.

Viral Receptor-Binding Protein Evolves New Function through Mutations That Cause Trimer Instability and Functional Heterogeneity

When proteins evolve new activity, a concomitant decrease in stability is often observed because the mutations that confer new activity can destabilize the native fold. In the conventional model of protein evolution, reduced stability is considered a purely deleterious cost of molecular innovation because unstable proteins are prone to aggregation and are sensitive to environmental stressors. However, recent work has revealed that nonnative, often unstable protein conformations play an important role in mediating evolutionary transitions, raising the question of whether instability can itself potentiate the evolution of new activity. We explored this question in a bacteriophage receptor-binding protein during host-range evolution. We studied the properties of the receptor-binding protein of bacteriophage λ before and after host-range evolution and demonstrated that the evolved protein is relatively unstable and may exist in multiple conformations with unique receptor preferences. Through a combination of structural modeling and in vitro oligomeric state analysis, we found that the instability arises from mutations that interfere with trimer formation. This study raises the intriguing possibility that protein instability might play a previously unrecognized role in mediating host-range expansions in viruses.

Modulation of Biophysical Properties of Nucleocapsid Protein in the Mutant Spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also exhibiting functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

The evolutionary origin of naturally occurring intermolecular Diels-Alderases from Morus alba

Biosynthetic enzymes evolutionarily gain novel functions, thereby expanding the structural diversity of natural products to the benefit of host organisms. Diels-Alderases (DAs), functionally unique enzymes catalysing [4 + 2] cycloaddition reactions, have received considerable research interest. However, their evolutionary mechanisms remain obscure. Here, we investigate the evolutionary origins of the intermolecular DAs in the biosynthesis of Moraceae plant-derived Diels-Alder-type secondary metabolites. Our findings suggest that these DAs have evolved from an ancestor functioning as a flavin adenine dinucleotide (FAD)-dependent oxidocyclase (OC), which catalyses the oxidative cyclisation reactions of isoprenoid-substituted phenolic compounds. Through crystal structure determination, computational calculations, and site-directed mutagenesis experiments, we identified several critical substitutions, including S348L, A357L, D389E and H418R that alter the substrate-binding mode and enable the OCs to gain intermolecular DA activity during evolution. This work provides mechanistic insights into the evolutionary rationale of DAs and paves the way for mining and engineering new DAs from other protein families.

Similar enzymatic functions in distinct bioluminescence systems: Evolutionary recruitment of sulfotransferases in ostracod light organs

Genes from ancient families are sometimes involved in the convergent evolutionary origins of similar traits, even across vast phylogenetic distances. Sulfotransferases are an ancient family of enzymes that transfer sulfate from a donor to a wide variety of substrates, including probable roles in some bioluminescence systems. Here we demonstrate multiple sulfotransferases, highly expressed in light organs of the bioluminescent ostracod Vargula tsujii , transfer sulfate in vivo to the luciferin substrate, vargulin. We find luciferin sulfotransferases of ostracods are not orthologous to known luciferin sulfotransferases of fireflies or sea pansies; animals with distinct and convergently evolved bioluminescence systems compared to ostracods. Therefore, distantly related sulfotransferases were independently recruited at least three times, leading to parallel evolution of luciferin metabolism in three highly diverged organisms. Re-use of homologous genes is surprising in these bioluminescence systems because the other components, including luciferins and luciferases, are completely distinct. Whether convergently evolved traits incorporate ancient genes with similar functions or instead use distinct, often newer, genes may be constrained by how many genetic solutions exist for a particular function. When fewer solutions exist, as in genetic sulfation of small molecules, evolution may be more constrained to use the same genes time and again.

MD simulations indicate Omicron P132H of SARS-CoV-2 Mpro is a potential allosteric mutant involved in modulating the dynamics of catalytic site entry loop

The SARS-CoV-2 main protease Mpro, essential for viral replication is an important drug target. It plays a critical role in processing viral polyproteins necessary for viral replication assembly. One of the predominant SARS-CoV-2 Mpro mutations of Omicron variant is Pro132His. Structurally, this mutation site is located ∼22 Å away from the catalytic site. The solved crystal structure of this mutant in complex with inhibitors as well as its reported catalytic efficiency did not show any difference with respect to the wild type. Thus, the mutation was concluded to be non-allosteric. Based on microsecond long MD simulation of the Pro132His mutant and wild type, we show that Pro132His mutation affects the conformational equilibrium with more population of conformational substates having open catalytic site, modulated by the dynamics of the catalytic site entry loop, implying the allosteric nature of this mutation. The structural analysis indicates that rearrangement of hydrogen bonds between His132 and adjacent residues enhances the dynamics of the linker, which in turn is augmented by the inherent dynamic flexibility of the catalytic pocket entry site due to the presence of charged residues. The altered dynamics leading to loss of secondary structures corroborate well with the reported compromised thermal stability.