The p53 Pathway: Origins, Inactivation in Cancer, and Emerging Therapeutic Approaches.

Inactivation of the transcription factor p53, through either direct mutation or aberrations in one of its many regulatory pathways, is a hallmark of virtually every tumor. In recent years, screening for p53 activators and a better understanding of the molecular mechanisms of oncogenic perturbations of p53 function have opened up a host of novel avenues for therapeutic intervention in cancer: from the structure-guided design of chemical chaperones to restore the function of conformationally unstable p53 cancer mutants, to the development of potent antagonists of the negative regulators MDM2 and MDMX and other modulators of the p53 pathway for the treatment of cancers with wild-type p53. Some of these compounds have now moved from proof-of-concept studies into clinical trials, with prospects for further, personalized anticancer medicines. We trace the structural evolution of the p53 pathway, from germ-line surveillance in simple multicellular organisms to its pluripotential role in humans.

Evolutionary origins and interactomes of human, young microproteins and small peptides translated from short open reading frames.

All species continuously evolve short open reading frames (sORFs) that can be templated for protein synthesis and may provide raw materials for evolutionary adaptation. We analyzed the evolutionary origins of 7,264 recently cataloged human sORFs and found that most were evolutionarily young and had emerged de novo. We additionally identified 221 previously missed sORFs potentially translated into peptides of up to 15 amino acids-all of which are smaller than the smallest human microprotein annotated to date. To investigate the bioactivity of sORF-encoded small peptides and young microproteins, we subjected 266 candidates to a mass-spectrometry-based interactome screen with motif resolution. Based on these interactomes and additional cellular assays, we can associate several candidates with mRNA splicing, translational regulation, and endocytosis. Our work provides insights into the evolutionary origins and interaction potential of young and small proteins, thereby helping to elucidate this underexplored territory of the human proteome.

Regulatory Themes and Variations by the Stress-Signaling Nucleotide Alarmones (p)ppGpp in Bacteria.

Bacterial stress-signaling alarmones are important components of a protective network against diverse stresses such as nutrient starvation and antibiotic assault. pppGpp and ppGpp, collectively (p)ppGpp, have well-documented regulatory roles in gene expression and protein translation. Recent work has highlighted another key function of (p)ppGpp: inducing rapid and coordinated changes in cellular metabolism by regulating enzymatic activities, especially those involved in purine nucleotide synthesis. Failure of metabolic regulation by (p)ppGpp results in the loss of coordination between metabolic and macromolecular processes, leading to cellular toxicity. In this review, we document how (p)ppGpp and newly characterized nucleotides pGpp and (p)ppApp directly regulate these enzymatic targets for metabolic remodeling. We examine targets' common determinants for alarmone interaction as well as their evolutionary diversification. We highlight classical and emerging themes in nucleotide signaling, including oligomerization and allostery along with metabolic interconversion and crosstalk, illustrating how they allow optimized bacterial adaptation to their environmental niches.

Orange carotenoid proteins: structural understanding of evolution and function.

Cyanobacteria uniquely contain a primitive water-soluble carotenoprotein, the orange carotenoid protein (OCP). Nearly all extant cyanobacterial genomes contain genes for the OCP or its homologs, implying an evolutionary constraint for cyanobacteria to conserve its function. Genes encoding the OCP and its two constituent structural domains, the N-terminal domain, helical carotenoid proteins (HCPs), and its C-terminal domain, are found in the most basal lineages of extant cyanobacteria. These three carotenoproteins exemplify the importance of the protein for carotenoid properties, including protein dynamics, in response to environmental changes in facilitating a photoresponse and energy quenching. Here, we review new structural insights for these carotenoproteins and situate the role of the protein in what is currently understood about their functions.

Ancestral ribonucleases back in motion for evolutionary-dynamics guided protein design.

The dynamics behavior of a protein is essential for its functionality. Here, Doucet et al. demonstrate how the evolutionary analysis of conformational pathways within a protein family serves to identify common core scaffolds that accommodate branch-specific functional regions controlled by flexibility switches, offering a model for evolutionary-dynamics based protein design.

A six-amino-acid motif is a major determinant in functional evolution of HOX1 proteins.

Gene duplication and divergence is a major driver in the emergence of evolutionary novelties. How variations in amino acid sequences lead to loss of ancestral activity and functional diversification of proteins is poorly understood. We used cross-species functional analysis of Drosophila Labial and its mouse HOX1 orthologs (HOXA1, HOXB1, and HOXD1) as a paradigm to address this issue. Mouse HOX1 proteins display low (30%) sequence similarity with Drosophila Labial. However, substituting endogenous Labial with the mouse proteins revealed that HOXA1 has retained essential ancestral functions of Labial, while HOXB1 and HOXD1 have diverged. Genome-wide analysis demonstrated similar DNA-binding patterns of HOXA1 and Labial in mouse cells, while HOXB1 binds to distinct targets. Compared with HOXB1, HOXA1 shows an enrichment in co-occupancy with PBX proteins on target sites and exists in the same complex with PBX on chromatin. Functional analysis of HOXA1-HOXB1 chimeric proteins uncovered a novel six-amino-acid C-terminal motif (CTM) flanking the homeodomain that serves as a major determinant of ancestral activity. In vitro DNA-binding experiments and structural prediction show that CTM provides an important domain for interaction of HOXA1 proteins with PBX. Our findings show that small changes outside of highly conserved DNA-binding regions can lead to profound changes in protein function.

Molecular determinants of protein evolvability.

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip.

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 104 variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 105 molecular variants of full-length human O6-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Halofilins as emerging bactofilin families of archaeal cell shape plasticity orchestrators.

Bactofilins are rigid, nonpolar bacterial cytoskeletal filaments that link cellular processes to specific curvatures of the cytoplasmic membrane. Although homologs of bactofilins have been identified in archaea and eukaryotes, functional studies have remained confined to bacterial systems. Here, we characterize representatives of two families of archaeal bactofilins from the pleomorphic archaeon Haloferax volcanii, halofilin A (HalA) and halofilin B (HalB). HalA and HalB polymerize in vitro, assembling into straight bundles. HalA polymers are highly dynamic and accumulate at positive membrane curvatures in vivo, whereas HalB forms more static foci that localize in areas of local negative curvatures on the outer cell surface. Gene deletions and live-cell imaging show that halofilins are critical in maintaining morphological integrity during shape transition from disk (sessile) to rod (motile). Morphological defects in ΔhalA result in accumulation of highly positive curvatures in rods but not in disks. Conversely, disk-shaped cells are exclusively affected by halB deletion, resulting in flatter cells. Furthermore, while ΔhalA and ΔhalB cells imprecisely determine the future division plane, defects arise predominantly during the disk-to-rod shape remodeling. The deletion of halA in the haloarchaeon Halobacterium salinarum, whose cells are consistently rod-shaped, impacted morphogenesis but not cell division. Increased levels of halofilins enforced drastic deformations in cells devoid of the S-layer, suggesting that HalB polymers are more stable at defective S-layer lattice regions. Our results suggest that halofilins might play a significant mechanical scaffolding role in addition to possibly directing envelope synthesis.

Emergent time scales of epistasis in protein evolution.

We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic model for protein families. We show that the proposed framework accurately reproduces the sequence statistics of both short-time (experimental) and long-time (natural) protein evolution, suggesting applicability also to relatively data-poor intermediate evolutionary time scales, which are currently inaccessible to evolution experiments. Our model uncovers a highly collective nature of epistasis, gradually changing the fitness effect of mutations in a diverging sequence context, rather than acting via strong interactions between individual mutations. This collective nature triggers the emergence of a long evolutionary time scale, separating fast mutational processes inside a given sequence context, from the slow evolution of the context itself. The model quantitatively reproduces epistatic phenomena such as contingency and entrenchment, as well as the loss of predictability in protein evolution observed in deep mutational scanning experiments of distant homologs. It thereby deepens our understanding of the interplay between mutation and selection in shaping protein diversity and functions, allows one to statistically forecast evolution, and challenges the prevailing independent-site models of protein evolution, which are unable to capture the fundamental importance of epistasis.

Addressing epistasis in the design of protein function.

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

Machine learning in biological physics: From biomolecular prediction to design.

Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics. However, in this perspective, we argue that a more successful approach is a proper combination of these two methodologies. We discuss how ideas coming from physical modeling neuronal processing led to early formulations of computational neural networks, e.g., Hopfield networks. We then show how modern learning approaches like Potts models, Boltzmann machines, and the transformer architecture are related to each other, specifically, through a shared energy representation. We summarize recent efforts to establish these connections and provide examples on how each of these formulations integrating physical modeling and machine learning have been successful in tackling recent problems in biomolecular structure, dynamics, function, evolution, and design. Instances include protein structure prediction; improvement in computational complexity and accuracy of molecular dynamics simulations; better inference of the effects of mutations in proteins leading to improved evolutionary modeling and finally how machine learning is revolutionizing protein engineering and design. Going beyond naturally existing protein sequences, a connection to protein design is discussed where synthetic sequences are able to fold to naturally occurring motifs driven by a model rooted in physical principles. We show that this model is "learnable" and propose its future use in the generation of unique sequences that can fold into a target structure.

The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes.

Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.

Oligomeric interactions maintain active-site structure in a noncooperative enzyme family.

The evolutionary benefit accounting for widespread conservation of oligomeric structures in proteins lacking evidence of intersubunit cooperativity remains unclear. Here, crystal and cryo-EM structures, and enzymological data, demonstrate that a conserved tetramer interface maintains the active-site structure in one such class of proteins, the short-chain dehydrogenase/reductase (SDR) superfamily. Phylogenetic comparisons support a significantly longer polypeptide being required to maintain an equivalent active-site structure in the context of a single subunit. Oligomerization therefore enhances evolutionary fitness by reducing the metabolic cost of enzyme biosynthesis. The large surface area of the structure-stabilizing oligomeric interface yields a synergistic gain in fitness by increasing tolerance to activity-enhancing yet destabilizing mutations. We demonstrate that two paralogous SDR superfamily enzymes with different specificities can form mixed heterotetramers that combine their individual enzymological properties. This suggests that oligomerization can also diversify the functions generated by a given metabolic investment, enhancing the fitness advantage provided by this architectural strategy.

Marginal specificity in protein interactions constrains evolution of a paralogous family.

The evolution of novel functions in biology relies heavily on gene duplication and divergence, creating large paralogous protein families. Selective pressure to avoid detrimental cross-talk often results in paralogs that exhibit exquisite specificity for their interaction partners. But how robust or sensitive is this specificity to mutation? Here, using deep mutational scanning, we demonstrate that a paralogous family of bacterial signaling proteins exhibits marginal specificity, such that many individual substitutions give rise to substantial cross-talk between normally insulated pathways. Our results indicate that sequence space is locally crowded despite overall sparseness, and we provide evidence that this crowding has constrained the evolution of bacterial signaling proteins. These findings underscore how evolution selects for "good enough" rather than optimized phenotypes, leading to restrictions on the subsequent evolution of paralogs.

Patterns of selection across gene regulatory networks.

Gene regulatory networks (GRNs) are the core engine of organismal development. If we would like to understand the origin and diversification of phenotypes, it is necessary to consider the structure of GRNs in order to reconstruct the links between genetic mutations and phenotypic change. Much of the progress in evolutionary developmental biology, however, has occurred without a nuanced consideration of the evolution of functional relationships between genes, especially in the context of their broader network interactions. Characterizing and comparing GRNs across traits and species in a more detailed way will allow us to determine how network position influences what genes drive adaptive evolution. In this perspective paper, we consider the architecture of developmental GRNs and how positive selection strength may vary across a GRN. We then propose several testable models for these patterns of selection and experimental approaches to test these models.

Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function.

Advances in personalized medicine and protein engineering require accurately predicting outcomes of amino acid substitutions. Many algorithms correctly predict that evolutionarily-conserved positions show "toggle" substitution phenotypes, which is defined when a few substitutions at that position retain function. In contrast, predictions often fail for substitutions at the less-studied "rheostat" positions, which are defined when different amino acid substitutions at a position sample at least half of the possible functional range. This review describes efforts to understand the impact and significance of rheostat positions: (1) They have been observed in globular soluble, integral membrane, and intrinsically disordered proteins; within single proteins, their prevalence can be up to 40%. (2) Substitutions at rheostat positions can have biological consequences and ∼10% of substitutions gain function. (3) Although both rheostat and "neutral" (defined when all substitutions exhibit wild-type function) positions are nonconserved, the two classes have different evolutionary signatures. (4) Some rheostat positions have pleiotropic effects on function, simultaneously modulating multiple parameters (e.g., altering both affinity and allosteric coupling). (5) In structural studies, substitutions at rheostat positions appear to cause only local perturbations; the overall conformations appear unchanged. (6) Measured functional changes show promising correlations with predicted changes in protein dynamics; the emergent properties of predicted, dynamically coupled amino acid networks might explain some of the complex functional outcomes observed when substituting rheostat positions. Overall, rheostat positions provide unique opportunities for using single substitutions to tune protein function. Future studies of these positions will yield important insights into the protein sequence/function relationship.

Utility of protein-protein binding surfaces composed of anti-parallel alpha-helices and beta-sheets selected by phage display.

Over the past 3 decades, a diverse collection of small protein domains have been used as scaffolds to generate general purpose protein-binding reagents using a variety of protein display and enrichment technologies. To expand the repertoire of scaffolds and protein surfaces that might serve this purpose, we have explored the utility of (i) a pair of anti-parallel alpha-helices in a small highly disulfide-bonded 4-helix bundle, the CC4 domain from reversion-inducing Cysteine-rich Protein with Kazal Motifs and (ii) a concave beta-sheet surface and two adjacent loops in the human FN3 domain, the scaffold for the widely used monobody platform. Using M13 phage display and next generation sequencing, we observe that, in both systems, libraries of ∼30 million variants contain binding proteins with affinities in the low µM range for baits corresponding to the extracellular domains of multiple mammalian proteins. CC4- and FN3-based binding proteins were fused to the N- and/or C-termini of Fc domains and used for immunostaining of transfected cells. Additionally, FN3-based binding proteins were inserted into VP1 of AAV to direct AAV infection to cells expressing a defined surface receptor. Finally, FN3-based binding proteins were inserted into the Pvc13 tail fiber protein of an extracellular contractile injection system particle to direct protein cargo delivery to cells expressing a defined surface receptor. These experiments support the utility of CC4 helices B and C and of FN3 beta-strands C, D, and F together with adjacent loops CD and FG as surfaces for engineering general purpose protein-binding reagents.

Ancestral sequence reconstruction dissects structural and functional differences among eosinophil ribonucleases.

Evolutionarily conserved structural folds can give rise to diverse biological functions, yet predicting atomic-scale interactions that contribute to the emergence of novel activities within such folds remains challenging. Pancreatic-type ribonucleases illustrate this complexity, sharing a core structure that has evolved to accommodate varied functions. In this study, we used ancestral sequence reconstruction to probe evolutionary and molecular determinants that distinguish biological activities within eosinophil members of the RNase 2/3 subfamily. Our investigation unveils functional, structural, and dynamical behaviors that differentiate the evolved ancestral ribonuclease (AncRNase) from its contemporary eosinophil RNase orthologs. Leveraging the potential of ancestral reconstruction for protein engineering, we used AncRNase predictions to design a minimal 4-residue variant that transforms human RNase 2 into a chimeric enzyme endowed with the antimicrobial and cytotoxic activities of RNase 3 members. This work provides unique insights into mutational and evolutionary pathways governing structure, function, and conformational states within the eosinophil RNase subfamily, offering potential for targeted modulation of RNase-associated functions.

Adaptive Evolution of Nearctic Deepwater Fish Vision: Implications for Assessing Functional Variation for Conservation.

Intraspecific functional variation is critical for adaptation to rapidly changing environments. For visual opsins, functional variation can be characterized in vitro and often reflects a species' ecological niche but is rarely considered in the context of intraspecific variation or the impact of recent environmental changes on species of cultural or commercial significance. Investigation of adaptation in postglacial lakes can provide key insight into how rapid environmental changes impact functional evolution. Here, we report evidence for molecular adaptation in vision in 2 lineages of Nearctic fishes that are deep lake specialists: ciscoes and deepwater sculpin. We found depth-related variation in the dim-light visual pigment rhodopsin that evolved convergently in these 2 lineages. In vitro characterization of spectral sensitivity of the convergent deepwater rhodopsin alleles revealed blue-shifts compared with other more widely distributed alleles. These blue-shifted rhodopsin alleles were only observed in deep clear postglacial lakes with underwater visual environments enriched in blue light. This provides evidence of remarkably rapid and convergent visual adaptation and intraspecific functional variation in rhodopsin. Intraspecific functional variation has important implications for conservation, and these fishes are of conservation concern and great cultural, commercial, and nutritional importance to Indigenous communities. We collaborated with the Saugeen Ojibway Nation to develop and test a metabarcoding approach that we show is efficient and accurate in recovering the ecological distribution of functionally relevant variation in rhodopsin. Our approach bridges experimental analyses of protein function and genetics-based tools used in large-scale surveys to better understand the ecological extent of adaptive functional variation.