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bioRxiv2026

Accounting for social feasibility in landscape-scale scenarios for restoring nature beyond protected areas

1. Global restoration targets, including the Kunming-Montreal Global Biodiversity Framework and the European Union's Nature Restoration Regulation, call for extending restoration beyond protected area boundaries to reconnect isolated ecosystems, yet implementing these landscape-scale interventions forces trade-offs between biophysical effectiveness and social feasibility. 2. In the Grenoble region of the French Alps, we used a gradient analysis of 12 ecosystem services across protected area interfaces to design and compare two restoration scenarios. Both were built from the same set of co-selected interventions but differed only in their spatial allocation: a 'Technical' scenario targeting areas of low ecosystem service continuity around protected areas, and a 'Participatory' scenario co-designed with local stakeholders. 3. Both scenarios physically modified about 14.5% of the landscape, mostly through a forest-based adaptation strategy, yet their effects reached up to more than 60% of the territory for the most connectivity-dependent services, showing that benefits propagate well beyond the area directly modified. 4. The two scenarios diverged mainly in how they treated agricultural land. The Technical scenario reduced abrupt drops in ecosystem service provision at the protected area edge nearly twice as often as the Participatory one (46% versus 26% of the sharp declines it addressed), and at six locations removed them entirely. However, it concentrated over 99% of its non-forest effort in agricultural diversification, such as diversifying crops and adding hedgerows, the action stakeholders ranked hardest to implement, whereas the Participatory scenario favoured more feasible actions such as river restoration, which met less resistance but missed several critical discontinuities in ecosystem service supply. 5. These contrasts show that biophysical potential and social feasibility can pull restoration in different directions, and that the more effective spatial configuration is not necessarily the more implementable one. 6. Closing the implementation gap for nature-based solutions depended less on expanding the area restored than on where interventions were placed. Gradient-based diagnostics appear most useful not as fixed prescriptions but as tools to steer existing sectoral funding in agriculture, urban planning and forestry toward high-impact locations, an approach transferable to other regions working to reconnect protected areas with their surrounding landscapes as coupled social-ecological systems.

ecology↗

bioRxiv2026

The balance of local and distributed excitation shapes brain stability and reflects aging- and Alzheimer's disease-related alterations

Human brain function emerges from the interplay between recurrent local activity and distributed inter-regional interactions. However, a biologically interpretable framework for quantifying this balance between the two factors at the whole-brain level remains lacking. Here, we extended an established biophysical model to quantify inter-regional excitation and newly introduced the recurrent ratio (R-ratio), a measure of the relative balance between intra- and inter-regional excitation. Dynamical analyses showed that an optimal R-ratio supports a trade-off between network stability and flexibility. Applying this framework to healthy aging and Alzheimer's disease revealed progressively increased R-ratios with advancing age and disease severity. In healthy individuals, higher R-ratios were associated with age-related alterations in brain morphology, molecular pathology, and cognitive function, whereas Alzheimer's disease was characterized by increased R-ratios accompanied by reduced dynamical persistence. Together, these findings establish the R-ratio as a biologically interpretable marker of whole-brain excitation balance and demonstrate its utility for linking biophysical mechanisms with large-scale brain dynamics, aging, and neurodegeneration.

neuroscience↗

bioRxiv2026

Phase Separation Potential of Marsupial RSX RNA Reveals Convergent Evolution of X-Chromosome Inactivation Mechanisms

Background: X-chromosome inactivation (XCI) evolved independently in eutherian and marsupial mammals, where it is orchestrated by the unrelated long non-coding RNAs Xist and RSX, respectively. Xist organizes a repressive nuclear compartment through multivalent RNA-protein interactions, but whether RSX exploits similar biophysical principles remains unknown. A recent paper has identified bona fide RSX interacting proteins. Results: We integrated proteome-scale RNA-protein interaction prediction, experimental validation, phase-separation propensity analysis, functional annotation and comparative RNA-structure modelling to characterize the RSX interaction landscape. Using catRAPID, we ranked 1,168 RNA-binding proteins from the native Monodelphis domestica proteome. Predictions were significantly enriched for experimentally identified RSX interactors, with 4.85-fold enrichment among the top 50 candidates (P approximately 1.6 x 10-5), increasing to approximately eightfold for proteins shared by the experimental RSX and Xist interactomes (P approximately 2 x 10-6). Among 30 high-confidence RSX interactors, 13 were experimentally supported, 17 were previously unrecognized candidates and 17 exhibited high phase-separation propensity. The network was enriched in ribonucleoprotein granules and nuclear bodies and converged on m6A regulators and SR-family splicing factors. Comparative modelling detected no conserved secondary or tertiary architecture between RSX and Xist. Conclusions: RSX and Xist appear to have converged not through RNA sequence or global structure, but through recruitment of related, condensation-prone protein networks. These findings identify interaction-network and biophysical convergence as a potential principle of lncRNA-mediated chromosome regulation and provide testable candidates for determining whether RSX establishes a condensate-like compartment on the marsupial inactive X.

bioinformatics↗

bioRxiv2026

Phosphorylation of the Kv7.4 B helix reorganizes calmodulin interactions and reduces PIP2 binding

Voltage-gated Kv7 (KCNQ, M-type) potassium channels regulate cellular excitability through interactions with phosphatidylinositol 4,5-bisphosphate (PIP2;) and calmodulin (CaM). The distal B helix of Kv7.2-5 channels contains a conserved protein kinase C (PKC) phosphorylation site, suggesting that phosphorylation may regulate channel activity by altering CaM- and PIP2;-dependent mechanisms. Here, we investigated the effects of phosphorylation of Thr552 within the Kv7.4 B helix using electrophysiology, biophysical assays, NMR spectroscopy, and molecular dynamics simulations. Phosphomimetic substitution of Thr552 produced a loss-of-function phenotype characterized by reduced current density and a depolarizing shift in voltage-dependent activation without altering channel surface expression. Biophysical studies demonstrated that phosphorylation produced only modest effects on overall CaM association. However, NMR spectroscopy revealed phosphorylation-dependent changes in apoCaM interactions, and molecular dynamics simulations identified remodeling of the local interaction network surrounding the distal B-helix polybasic (KRK motif) region. In contrast, phosphorylation markedly reduced PIP2; binding to both the isolated B helix and CaM-associated Kv7.4 regulatory complexes. Mutation of the distal B-helix KRK motif similarly impaired PIP2; binding, identifying this region as an important determinant of lipid recognition. Together, these findings support a model in which phosphorylation of Thr552 suppresses Kv7.4 activity primarily by reducing PIP2; interactions while reorganizing, rather than disrupting, CaM binding. These results identify Thr552 as a critical regulatory site linking phosphorylation-dependent signaling to Kv7.4 channel gating.

biochemistry↗

bioRxiv2026

Optimization of a Human Anti-polio Monoclonal Antibody as a Potential Therapeutic Modality

Background. Vaccines have been an essential tool in bringing the world close to polio eradication, with over 99.9 percent of the global population free of poliovirus. No antiviral drugs or monoclonal antibody products, however, are currently licensed for treatment of polio. We previously isolated a human monoclonal antibody (9H2) with potent neutralizing activity against all three poliovirus serotypes. To advance 9H2 as a therapeutic candidate, we optimized its sequence to extend serum half-life and improve manufacturability. Methods. A Multi-Attribute Method under stress conditions identified post-translational modification sites, and Abacus (Trademark) ranked sequence liabilities. Six amino acid substitutions were introduced into the variable regions, generating 23 combinatorial variants. Codon-optimized genes were synthesized and engineered into a human immunoglobulin G1 backbone containing crystallizable fragment (Fc) mutations (M428L/N434S) to extend serum half-life. Constructs were transfected into CHO K1 cells to generate stable pools in 24 well plates. Protein A purified antibodies were characterized using biophysical assays and an in vitro poliovirus neutralization assay. Results. All variants retained high in vitro neutralizing activity against poliovirus. A lead candidate was selected based on integrated assessment of biophysical properties across eight assays and expression yield. Conclusions. Structure-guided engineering and experimental evaluation enabled optimization of the 9H2 antibody sequence and identification of a lead candidate suitable for clinical manufacturing as a potential anti-poliovirus immunotherapeutic agent.

biochemistry↗

bioRxiv2026

Quantitative machine learning of protein interactions reveals the multiscale organization and molecular syntax of signaling networks

Cells employ dense networks of transient protein-protein interactions mediated by modular peptide-binding domains and unstructured peptidic motifs for high-fidelity information processing. How these networks physically execute computations through protein interactions governed by complex intra- and intermolecular mechanisms remains indiscernible from current, sparse and non-quantitative, maps of the human interactome. Here, we introduce a quantitative statistical mechanical modeling (QSM) approach for machine learning domain-peptide affinities with experimental-level accuracy. Leveraging a new, principled algorithm for data harmonization and a biophysically informed neural network architecture, QSM learns to predict dissociation constants directly from amino acid sequences with calibrated confidence. We use QSM to construct the first quantitative drafts of human signaling networks and study these networks across three physical scales--recognition mechanisms of modular binding domains, combinatorial logic of multi-dentate proteins, and pathways inferred from de novo inference of protein interaction networks. We find that (i) modular domains, based on their binding preferences, selectivities, and strengths, fall into a limited number of biophysical equivalence groups, (ii) those domains, along with peptidic motifs, are "syntactically" combined within proteins to yield multivalent recognition mechanisms, and (iii) the organization of cellular function can be traced back to algorithmically detectable modules induced by domain-mediated interactions. In aggregate, these analyses instantiate a tractable roadmap towards a comprehensive, mechanistic, and simulatable articulation of the systems biology of signaling.

systems biology↗

bioRxiv2026

Remodeling of cholesterol metabolism in melanoma progression regulates nuclear membrane mechanics.

Metastatic cancer cells migrate through physically restrictive environments where nuclear deformation ruptures the nuclear envelope (NE) resulting in genomic instability. Although structural proteins of the NE are established regulators of nuclear mechanics, how nuclear membrane (NM) lipid composition contributes to its biophysical response to mechanical stress remains poorly understood. Here, we show that melanoma progression is associated with broad transcriptional remodeling of cholesterol homeostasis that is established early in disease progression, with altered expression of cholesterol biosynthesis genes associated with reduced patient survival. Building on our previous identification of the inner NM sterol reductase lamin B receptor (LBR) as a regulator of NE fragility, we find that LBR-dependent cholesterol biosynthesis promotes cholesterol enrichment within the NM and alters its spatial organization during cellular confinement. Quantitative fluorescence and lifetime imaging of biosensors of cholesterol distribution, lipid order, and tension reveals that cholesterol remodeling alters NM lipid organization and results in high NM tension in melanoma cells that is selectively reduced by cholesterol depletion. Cellular confinement generates nuclear blebs where cholesterol becomes preferentially enriched at highly curved, rupture-prone regions of the NM. Together, our results establish cholesterol-dependent NM remodeling as a regulator of nuclear mechanics and link metabolic changes acquired during cancer progression to the biophysical response of the NM to mechanical stress.

cell biology↗

bioRxiv2014

Too packed to change: site-specific substitution rates and side-chain packing in protein evolution

In protein evolution, due to functional and biophysical constraints, the rates of amino acid substitution differ from site to site. Among the best predictors of site-specific rates is packing density. The packing density measure that best correlates with rates is the weighted contact number (WCN), the sum of inverse square distances between the sites C and the other C. According to a mechanistic stress model proposed recently, rates are determined by packing because mutating packed sites stresses and destabilizes the proteins active conformation. While WCN is a measure of C packing, mutations replace side chains, which prompted us to consider whether a sites evolutionary divergence is constrained by main-chain packing or side-chain packing. To address this issue, we extended the stress theory to model side chains explicitly. The theory predicts that rates should depend solely on side-chain packing. We tested these predictions on a data set of structurally and functionally diverse monomeric enzymes. We found that, on average, side-chain contact density (WCN{rho}) explains 39.1% of among-sites rate variation, larger than main-chain contact density (WCN) which explains 32.1%. More importantly, the independent contribution of WCN is only 0.7%. Thus, as predicted by the stress theory, site-specific evolutionary rates are determined by side-chain packing.

Biophysics↗

bioRxiv2015

Photon-HDF5: an open file format for single-molecule fluorescence experiments using photon-counting detectors

We introduce Photon-HDF5, an open and efficient file format to simplify exchange and long term accessibility of data from single-molecule fluorescence experiments based on photon-counting detectors such as single-photon avalanche diode (SPAD), photomultiplier tube (PMT) or arrays of such detectors. The format is based on HDF5, a widely used platform- and language-independent hierarchical file format for which user-friendly viewers are available. Photon-HDF5 can store raw photon data (timestamp, channel number, etc...) from any acquisition hardware, but also setup and sample description, information on provenance, authorship and other metadata, and is flexible enough to include any kind of custom data.\n\nThe format specifications are hosted on a public website, which is open to contributions by the biophysics community. As an initial resource, the website provides code examples to read Photon-HDF5 files in several programming languages and a reference Python library (phconvert), to create new Photon-HDF5 files and convert several existing file formats into Photon-HDF5. To encourage adoption by the academic and commercial communities, all software is released under the MIT open source license.

Biophysics↗

bioRxiv2015

Extracellular Forces Cause the Nucleus to Deform in a Highly Controlled Anisotropic Manner

Physical forces arising in the extra-cellular environment have a profound impact on cell fate and gene regulation; however the underlying biophysical mechanisms that control this sensitivity remain elusive. It is hypothesized that gene expression may be influenced by the physical deformation of the nucleus in response to force. Here, using 3T3s as a model, we demonstrate that extra-cellular forces cause cell nuclei to rapidly deform (< 1 s) preferentially along their shorter nuclear axis, in an anisotropic manner. Nuclear anisotropy is shown to be regulated by the cytoskeleton within intact cells, with actin and microtubules resistant to orthonormal strains. Importantly, nuclear anisotropy is intrinsic, and observed in isolated nuclei. The sensitivity of this behaviour is influenced by chromatin organization and lamin-A expression. An anisotropic response to force was also highly conserved amongst an array of examined nuclei from differentiated and undifferentiated cell types. Although the functional purpose of this conserved material property remains elusive, it may provide a mechanism through which mechanical cues in the microenvironment are rapidly transmitted to the genome.

Biophysics↗

bioRxiv2015

Measuring and modeling diffuse scattering in protein X-ray crystallography

X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations must be measured. Until now measurement of diffuse scattering from protein crystals has been scarce, due to the extra effort of collecting diffuse data. Here, we present three-dimensional measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested Translation-Libration-Screw (TLS), Liquid-Like Motions (LLM), and coarse-grained Normal Modes (NM) models of protein motions. The LLM model provides a global picture of motions and were refined against the diffuse data, while the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that NM-based refinement can generate dynamics-inspired structural models that simultaneously agree with both Bragg and diffuse scattering.\n\nSignificanceThe structural details of protein motions are critical to understanding many biological processes, but they are often hidden to conventional biophysical techniques. Diffuse X-ray scattering can reveal details of the correlated movements between atoms; however, the data collection historically has required extra effort and dedicated experimental protocols. We have measured three-dimensional diffuse intensities in X-ray diffraction from CypA and trypsin crystals using standard crystallographic data collection techniques. Analysis of the resulting data is consistent with the protein motions resembling diffusion in a liquid or vibrations of a soft solid. Our results show that using diffuse scattering to model protein motions can become a component of routine crystallographic analysis through the extension of commonplace methods.

Biophysics↗

bioRxiv2016

Predictive multi-scale computational environment for studying epithelial dynamics

Mitotic rounding (MR) during cell division is critical for the robust segregation of chromosomes into daughter cells and is frequently perturbed in cancerous cells. MR has been studied extensively in individual cultured cells, but the physical mechanisms regulating MR in intact tissues are still poorly understood. A cell undergoes mitotic rounding by simultaneously reducing adhesion with its neighbors, increasing actomyosin contraction around the cortex, and increasing the osmotic pressure of the cytoplasm. Whether these changes are purely additive, synergistic or impact separate aspects of MR is not clear. Specific modulation of these processes in dividing cells within a tissue is experimentally challenging, because of off-target effects and the difficulty of targeting only dividing cells. In this study, we analyze MR in epithelial cells by using a newly developed multi-scale, cell-based computational model that is calibrated using experimental observations from a model system of epithelial tissue growth, the Drosophila wing imaginal disc. The model simulations predict that increase in apical surface area of mitotic cells is solely driven by increasing cytoplasmic pressure. MR however is not achieved within biological constraints unless all three properties (cell-cell adhesion, cortical stiffness and pressure) are simultaneously regulated by the cell. The new multi-scale model is computationally implemented using a parallelization algorithm on a cluster of graphic processing units (GPUs) to make simulations of tissues with a large number of cells feasible. The model is extensible to investigate a wide range of cellular phenomena at the tissue scale.\n\nAuthor SummaryMitotic rounding (MR) during cell division is critical for the robust segregation of chromosomes into daughter cells and is frequently perturbed in cancerous cells. MR has been studied extensively in individual cultured cells, but the physical mechanisms regulating MR in intact tissues are still poorly understood. The newly developed computational model Epi-scale enables one to produce new hypotheses about the underlying biophysical mechanisms governing MR of epithelial cells within the developing tissue micro-environment. In particular, our simulations results predict that robust mitotic rounding requires co-current changes in cell-cell adhesion, cortical stiffness and cytoplasmic pressure, and explains how regulation of each property impacts the shapes of dividing cells in tissues.

Biophysics↗

bioRxiv2016

Compaction and segregation of sister chromatids via active loop extrusion

The mechanism by which chromatids and chromosomes are segregated during mitosis and meiosis is a major puzzle of biology and biophysics. Using polymer simulations of chromosome dynamics, we show that a single mechanism of loop extrusion by condensins can robustly compact, segregate and disentangle chromosomes, arriving at individualized chromatids with morphology observed in vivo. Our model resolves the paradox of topological simplification concomitant with chromosome \"condensation\", and explains how enzymes a few nanometers in size are able to control chromosome geometry and topology at micron length scales. We suggest that loop extrusion is a universal mechanism of genome folding that mediates functional interactions during interphase and compacts chromosomes during mitosis.

Biophysics↗

bioRxiv2016

Active Microrheology of Intestinal Mucus in the Larval Zebrafish

Mucus is a complex biological fluid that plays a variety of functional roles in many physiological systems. Intestinal mucus in particular serves as a physical barrier to pathogens, a medium for the diffusion of nutrients and metabolites, and an environmental home for colonizing microbes. Its rheological properties have therefore been the subject of many investigations, thus far limited, however, to in vitro studies due to the difficulty of measurement in the natural context of the gut. This limitation especially hinders our understanding of how the gut microbiota interact with the intestinal environment, since examination of this calls not only for in vivo measurement techniques, but for techniques that can be applied to model organisms in which the microbial state of the gut can be controlled. We address this challenge by developing a method that combines magnetic microrheology, light sheet fluorescence microscopy, and microgavage of particles, applying this to the larval zebrafish, a model vertebrate. We present measurements of the viscosity of mucus within the intestinal bulb of both germ-free (devoid of intestinal microbes) and conventionally reared larval zebrafish. At the length scale probed ({approx} 10m), we find that mucus behaves as a Newtonian fluid, with no discernable elastic component. Surprisingly, despite known differences in the the number of secretory cells in germ-free zebrafish and their conventional counterparts, the fluid viscosity for these two groups was very similar. Our measurements provide the first in vivo measurements of intestinal mucus rheology at micron length scales in living animals, quantifying of an important biomaterial environment and highlighting the utility of active magnetic microrheology for biophysical studies.

Biophysics↗

bioRxiv2016

Measuring Mechanodynamics using an Unsupported Epithelial Monolayer Grown at an Air-Water Interface

Actomyosin contraction and relaxation in a monolayer is a fundamental biophysical process in development and homeostasis. Current methods used to characterize the mechanodynamics of monolayers often involve cells grown on solid supports such as glass or gels. The results of these studies are fundamentally influenced by these supporting structures. Here, we describe a new methodology for measuring the mechanodynamics of epithelial monolayers by culturing cells at an air-liquid interface. These model monolayers are grown in the absence of any supporting structures allowing us to remove cell-substrate effects. This methods potential was evaluated by observing and quantifying the generation and release of internal stresses upon actomyosin contraction (320{+/-}50Pa) and relaxation (190{+/-}40Pa) in response to chemical treatments. This is in contrast to the results observed in monolayers grown on solid substrates (glass and gels) where movement was drastically muted. Tracking the displacement of cell nuclei, cell edges and cluster perimeter allowed us to quantify the strain dynamics in the monolayer indicating the reliability of this method. New insights were also revealed with this approach. Although unsupported monolayers exhibited clear major and minor strain axes, they were not correlated to the general alignment of cell nuclei. The situation was dramatically different when the monolayers were grown on soft gels and hard glass substrates. It was observed that both gels and glass substrates led to the promotion of long-range alignment of cell nuclei. In addition, the strain orientation was correlated to nuclear alignment on the soft deformable gels. This new approach provides us with a picture of basal actomyosin mechanodynamics in a simplified system allowing us to infer how the presence of a substrate impacts actomyosin contractility and long-range multi-cellular organization and dynamics. This new methodology will also enable many new questions to be asked about the molecular regulation of the mechanodynamics of unsupported monolayers.

Biophysics↗

bioRxiv2016

Large scale chromosome folding is stable against local changes in chromatin structure

Characterizing the link between small-scale chromatin structure and large-scale chromosome folding during interphase is a prerequisite for understanding transcription. Yet, this link remains poorly investigated. Here, we introduce a simple biophysical model where interphase chromosomes are described in terms of the folding of chromatin sequences composed of alternating blocks of fibers with different thicknesses and flexibilities, and we use it to study the influence of sequence disorder on chromosome behaviors in space and time. By employing extensive computer simulations,we thus demonstrate that chromosomes undergo noticeable conformational changes only on length-scales smaller than 105 basepairs and time-scales shorter than a few seconds, and we suggest there might exist effective upper bounds to the detection of chromosome reorganization in eukaryotes. We prove the relevance of our framework by modeling recent experimental FISH data on murine chromosomes.\n\nAuthor SummaryA key determining factor in many important cellular processes as DNA transcription, for instance, the specific composition of the chromatin fiber sequence has a major influence on chromosome folding during interphase. Yet, how this is achieved in detail remains largely elusive. In this work, we explore this link by means of a novel quantitative computational polymer model for interphase chromosomes where the associated chromatin filaments are composed of mixtures of fibers with heterogeneous physical properties. Our work suggests a scenario where chromosomes undergo only limited reorganization, namely on length-scales below 105 basepairs and time-scales shorter than a few seconds. Our conclusions are supported by recent FISH data on murine chromosomes.

Biophysics↗

bioRxiv2016

Physical basis of large microtubule aster growth

Microtubule asters - radial arrays of microtubules organized by centrosomes - play a fundamental role in the spatial coordination of animal cells. The standard model of aster growth assumes a fixed number of microtubules originating from the centrosomes. However, aster morphology in this model does not scale with cell size, and we recently found evidence for non-centrosomal microtubule nucleation. Here, we combine autocatalytic nucleation and polymerization dynamics to develop a biophysical model of aster growth. Our model predicts that asters expand as traveling waves and recapitulates all major aspects of aster growth. As the nucleation rate increases, the model predicts an explosive transition from stationary to growing asters with a discontinuous jump of the growth velocity to a nonzero value. Experiments in frog egg extract confirm the main theoretical predictions. Our results suggest that asters observed in large frog and amphibian eggs are a meshwork of short, unstable microtubules maintained by autocatalytic nucleation and provide a paradigm for the assembly of robust and evolvable polymer networks.

Biophysics↗

bioRxiv2016

The role of evolutionary selection in the dynamics of protein structure evolution

Homology modeling is a powerful tool for predicting a proteins structure. This approach is successful because proteins whose sequences are only 30% identical still adopt the same structure, while structure similarity rapidly deteriorates beyond the 30% threshold. By studying the divergence of protein structure as sequence evolves in real proteins and in evolutionary simulations, we show that this non-linear sequence-structure relationship emerges as a result of selection for protein folding stability in divergent evolution. Fitness constraints prevent the emergence of unstable protein evolutionary intermediates thereby enforcing evolutionary paths that preserve protein structure despite broad sequence divergence. However on longer time scales, evolution is punctuated by rare events where the fitness barriers obstructing structure evolution are overcome and discovery of new structures occurs. We outline biophysical and evolutionary rationale for broad variation in protein family sizes, prevalence of compact structures among ancient proteins and more rapid structure evolution of proteins with lower packing density.

Biophysics↗