Onset of coupled atmosphere-ocean oxygenation 2.3 billion years ago.

The initial rise of molecular oxygen (O2) shortly after the Archaean-Proterozoic transition 2.5 billion years ago was more complex than the single step-change once envisioned. Sulfur mass-independent fractionation records suggest that the rise of atmospheric O2 was oscillatory, with multiple returns to an anoxic state until perhaps 2.2 billion years ago1-3. Yet few constraints exist for contemporaneous marine oxygenation dynamics, precluding a holistic understanding of planetary oxygenation. Here we report thallium (Tl) isotope ratio and redox-sensitive element data for marine shales from the Transvaal Supergroup, South Africa. Synchronous with sulfur isotope evidence of atmospheric oxygenation in the same shales3, we found lower authigenic 205Tl/203Tl ratios indicative of widespread manganese oxide burial on an oxygenated seafloor and higher redox-sensitive element abundances consistent with expanded oxygenated waters. Both signatures disappear when the sulfur isotope data indicate a brief return to an anoxic atmospheric state. Our data connect recently identified atmospheric O2 dynamics on early Earth with the marine realm, marking an important turning point in Earth's redox history away from heterogeneous and highly localized 'oasis'-style oxygenation.

Phylogenomics and the rise of the angiosperms.

Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins5-7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes8. This 15-fold increase in genus-level sampling relative to comparable nuclear studies9 provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade.

Complementing model species with model clades.

Model species continue to underpin groundbreaking plant science research. At the same time, the phylogenetic resolution of the land plant Tree of Life continues to improve. The intersection of these two research paths creates a unique opportunity to further extend the usefulness of model species across larger taxonomic groups. Here we promote the utility of the Arabidopsis thaliana model species, especially the ability to connect its genetic and functional resources, to species across the entire Brassicales order. We focus on the utility of using genomics and phylogenomics to bridge the evolution and diversification of several traits across the Brassicales to the resources in Arabidopsis, thereby extending scope from a model species by establishing a "model clade". These Brassicales-wide traits are discussed in the context of both the model species Arabidopsis thaliana and the family Brassicaceae. We promote the utility of such a "model clade" and make suggestions for building global networks to support future studies in the model order Brassicales.

The amyloid cascade hypothesis: an updated critical review.

Results from recent clinical trials of antibodies that target amyloid-ß (Aß) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aß may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aß playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Excess mortality in Denmark, Finland, Norway and Sweden during the COVID-19 pandemic 2020-2022.

BACKGROUND: The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022. METHODS: Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses. RESULTS: While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022. CONCLUSION: Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Stability and expression of SARS-CoV-2 spike-protein mutations.

Protein fold stability likely plays a role in SARS-CoV-2 S-protein evolution, together with ACE2 binding and antibody evasion. While few thermodynamic stability data are available for S-protein mutants, many systematic experimental data exist for their expression. In this paper, we explore whether such expression levels relate to the thermodynamic stability of the mutants. We studied mutation-induced SARS-CoV-2 S-protein fold stability, as computed by three very distinct methods and eight different protein structures to account for method- and structure-dependencies. For all methods and structures used (24 comparisons), computed stability changes correlate significantly (99% confidence level) with experimental yeast expression from the literature, such that higher expression is associated with relatively higher fold stability. Also significant, albeit weaker, correlations were seen between stability and ACE2 binding effects. The effect of thermodynamic fold stability may be direct or a correlate of amino acid or site properties, notably the solvent exposure of the site. Correlation between computed stability and experimental expression and ACE2 binding suggests that functional properties of the SARS-CoV-2 S-protein mutant space are largely determined by a few simple features, due to underlying correlations. Our study lends promise to the development of computational tools that may ideally aid in understanding and predicting SARS-CoV-2 S-protein evolution.

A Hyb-Seq phylogeny of Boechera and related genera using a combination of Angiosperms353 and Brassicaceae-specific bait sets.

PREMISE: Although Boechera (Boechereae, Brassicaceae) has become a plant model system for both ecological genomics and evolutionary biology, all previous phylogenetic studies have had limited success in resolving species relationships within the genus. The recent effective application of sequence data from target enrichment approaches to resolve the evolutionary relationships of several other challenging plant groups prompted us to investigate their usefulness in Boechera and Boechereae. METHODS: To resolve the phylogeny of Boechera and closely related genera, we utilized the Hybpiper pipeline to analyze two combined bait sets: Angiosperms353, with broad applicability across flowering plants; and a Brassicaceae-specific bait set designed for use in the mustard family. Relationships for 101 samples representing 81 currently recognized species were inferred from a total of 1114 low-copy nuclear genes using both supermatrix and species coalescence methods. RESULTS: Our analyses resulted in a well-resolved and highly supported phylogeny of the tribe Boechereae. Boechereae is divided into two major clades, one comprising all western North American species of Boechera, the other encompassing the eight other genera of the tribe. Our understanding of relationships within Boechera is enhanced by the recognition of three core clades that are further subdivided into robust regional species complexes. CONCLUSIONS: This study presents the first broadly sampled, well-resolved phylogeny for most known sexual diploid Boechera. This effort provides the foundation for a new phylogenetically informed taxonomy of Boechera that is crucial for its continued use as a model system.

Survival of the cheapest: how proteome cost minimization drives evolution.

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models.

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias BM . The models were externally validated on three test data sets probing different pathologies and for internal consistency (symmetry and neutrality). Model structure and performance substantially depended on training data and even fitting method. We developed two final models: SimBa-IB for typical natural mutations and SimBa-SYM for situations where stabilizing and destabilizing mutations occur to a similar extent. SimBa-SYM, despite is simplicity, is essentially non-biased (vs. the Ssym data set) while still performing well for all data sets (R ~ 0.46-0.54, MAE = 1.16-1.24 kcal/mol). The simple models provide advantage in terms of interpretability, use and future improvement, and are freely available on GitHub.

Structural heterogeneity and precision of implications drawn from cryo-electron microscopy structures: SARS-CoV-2 spike-protein mutations as a test case.

Protein structures may be used to draw functional implications at the residue level, but how sensitive are these implications to the exact structure used? Calculation of the effects of SARS-CoV-2 S-protein mutations based on experimental cryo-electron microscopy structures have been abundant during the pandemic. To understand the precision of such estimates, we studied three distinct methods to estimate stability changes for all possible mutations in 23 different S-protein structures (3.69 million ΔΔG values in total) and explored how random and systematic errors can be remedied by structure-averaged mutation group comparisons. We show that computational estimates have low precision, due to method and structure heterogeneity making results for single mutations uninformative. However, structure-averaged differences in mean effects for groups of substitutions can yield significant results. Illustrating this protocol, functionally important natural mutations, despite individual variations, average to a smaller stability impact compared to other possible mutations, independent of conformational state (open, closed). In summary, we document substantial issues with precision in structure-based protein modeling and recommend sensitivity tests to quantify these effects, but also suggest partial solutions to the problem in the form of structure-averaged "ensemble" estimates for groups of residues when multiple structures are available.

Assessment of AlphaFold2 for Human Proteins via Residue Solvent Exposure.

As only 35% of human proteins feature (often partial) PDB structures, the protein structure prediction tool AlphaFold2 (AF2) could have massive impact on human biology and medicine fields, making independent benchmarks of interest. We studied AF2's ability to describe the backbone solvent exposure as a functionally important and easily interpretable "natural coordinate" of protein conformation, using human proteins as test case. After screening for appropriate comparative sets, we matched 1818 human proteins predicted by AF2 against 7585 unique experimental PDBs, and after curation for sequence overlap, we assessed 1264 comparative pairs comprising 115 unique AF2 structures and 652 unique experimental structures. AF2 performed markedly worse for multimers, whereas ligands, cofactors, and experimental resolution were interestingly not very important for performance. AF2 performed excellently for monomer proteins. Challenges relating to specific groups of residues and multimers were analyzed. We identified larger deviations for lower-confidence scores (pLDDT), and exposed residues and polar residues (e.g., Asp, Glu, Asn) being less accurately described than hydrophobic residues. Proline conformations were the hardest to predict, probably due to a common location in dynamic solvent-accessible parts. In summary, using solvent exposure as a metric, we quantified the performance of AF2 for human proteins and provided estimates of the expected agreement as a function of ligand presence, multimer/monomer status, local residue solvent exposure, pLDDT, and amino acid type. Overall performance was found to be excellent.

A Concise Total Synthesis of the Fungal Isoquinoline Alkaloid TMC-120B.

Recent reports of antiepileptic activity of the fungal alkaloid TMC-120B have renewed the interest in this natural product. Previous total syntheses of TMC-120B comprise many steps and have low overall yields (11-17 steps, 1.5-2.9% yield). Thus, to access this compound more efficiently, we herein present a concise and significantly improved total synthesis of the natural product. Our short synthesis relies on two key cyclization steps to assemble the central scaffold: isoquinoline formation via an ethynyl-imino cyclization and an intramolecular Friedel-Crafts reaction to form the furanone.

A base measure of precision for protein stability predictors: structural sensitivity.

BACKGROUND: Prediction of the change in fold stability (ΔΔG) of a protein upon mutation is of major importance to protein engineering and screening of disease-causing variants. Many prediction methods can use 3D structural information to predict ΔΔG. While the performance of these methods has been extensively studied, a new problem has arisen due to the abundance of crystal structures: How precise are these methods in terms of structure input used, which structure should be used, and how much does it matter? Thus, there is a need to quantify the structural sensitivity of protein stability prediction methods. RESULTS: We computed the structural sensitivity of six widely-used prediction methods by use of saturated computational mutagenesis on a diverse set of 87 structures of 25 proteins. Our results show that structural sensitivity varies massively and surprisingly falls into two very distinct groups, with methods that take detailed account of the local environment showing a sensitivity of ~ 0.6 to 0.8 kcal/mol, whereas machine-learning methods display much lower sensitivity (~ 0.1 kcal/mol). We also observe that the precision correlates with the accuracy for mutation-type-balanced data sets but not generally reported accuracy of the methods, indicating the importance of mutation-type balance in both contexts. CONCLUSIONS: The structural sensitivity of stability prediction methods varies greatly and is caused mainly by the models and less by the actual protein structural differences. As a new recommended standard, we therefore suggest that ΔΔG values are evaluated on three protein structures when available and the associated standard deviation reported, to emphasize not just the accuracy but also the precision of the method in a specific study. Our observation that machine-learning methods deemphasize structure may indicate that folded wild-type structures alone, without the folded mutant and unfolded structures, only add modest value for assessing protein stability effects, and that side-chain-sensitive methods overstate the significance of the folded wild-type structure.

Membrane dynamics of γ-secretase with the anterior pharynx-defective 1B subunit.

The four-subunit protease complex γ-secretase cleaves many single-pass transmembrane (TM) substrates, including Notch and ß-amyloid precursor protein to generate amyloid-ß (Aß), central to Alzheimer's disease. Two of the subunits anterior pharynx-defective 1 (APH-1) and presenilin (PS) exist in two homologous forms APH1-A and APH1-B, and PS1 and PS2. The consequences of these variations are poorly understood and could affect Aß production and γ-secretase medicine. Here, we developed the first complete structural model of the APH-1B subunit using the published cryo-electron microscopy (cryo-EM) structures of APH1-A (Protein Data Bank: 5FN2, 5A63, and 6IYC). We then performed all-atom molecular dynamics simulations at 303 K in a realistic bilayer system to understand both APH-1B alone and in γ-secretase without and with substrate C83-bound. We show that APH-1B adopts a 7TM topology with a water channel topology similar to APH-1A. We demonstrate direct transport of water through this channel, mainly via Glu84, Arg87, His170, and His196. The apo and holo states closely resemble the experimental cryo-EM structures with APH-1A, however with subtle differences: The substrate-bound APH-1B γ-secretase was quite stable, but some TM helices of PS1 and APH-1B rearranged in the membrane consistent with the disorder seen in the cryo-EM data. This produces different accessibility of water molecules for the catalytic aspartates of PS1, critical for Aß production. In particular, we find that the typical distance between the catalytic aspartates of PS1 and the C83 cleavage sites are shorter in APH-1B, that is, it represents a more closed state, due to interactions with the C-terminal fragment of PS1. Our structural-dynamic model of APH-1B alone and in γ-secretase suggests generally similar topology but some notable differences in water accessibility which may be relevant to the protein's existence in two forms and their specific function and location.

Crystal Engineering of Supramolecular 1,4-Benzene Bisamides by Side-Chain Modification - Towards Tuneable Anisotropic Morphologies and Surfaces.

Benzene bisamides are promising building blocks for supramolecular nano-objects. Their functionality depends on morphology and surface properties. However, a direct link between surface properties and molecular structure itself is missing for this material class. Here, we investigate this interplay for two series of 1,4-benzene bisamides with symmetric and asymmetric peripheral substitution. We elucidated the crystal structures, determined the nano-object morphologies and derived the wetting behaviour of the preferentially exposed surfaces. The crystal structures were solved by combining single-crystal and powder X-ray diffraction, solid-state NMR spectroscopy and computational modelling. Bulky side groups, here t-butyl groups, serve as a structure-directing motif into a packing pattern, which favours the formation of thin platelets. The use of slim peripheral groups on both sides, in our case linear perfluorinated, alkyl chains, self-assemble the benzene bisamides into a second packing pattern which leads to ribbon-like nano-objects. For both packing types, the preferentially exposed surfaces consist of the ends of the peripheral groups. Asymmetric substitution with bulky and slim groups leads to an ordered alternating arrangement of the groups exposed to the surface. This allows the hydrophobicity of the surfaces to be gradually altered. We thus identified two leitmotifs for molecular packings of benzene bisamides providing the missing link between the molecular structure, the anisotropic morphologies and adjustable surface properties of the supramolecular nano-objects.

Three Simple Properties Explain Protein Stability Change upon Mutation.

Accurate prediction of protein stability upon mutation enables rational engineering of new proteins and insights into protein evolution and monogenetic diseases caused by single-point amino acid substitutions. Many tools have been developed to this aim, ranging from energy-based models to machine-learning methods that use large amounts of experimental data. However, as the methods become more complex, the interpretation of the chemistry underlying the protein stability effects becomes obscure. It is thus of interest to identify the simplest prediction model that retains complete amino acid specific interpretation; for a given number of input descriptors, we expect such a model to be almost universal. In this study, we identify such a limiting model, SimBa, a simple multilinear regression model trained on a substitution-type-balanced experimental data set. The model accounts only for the solvent accessibility of the site, volume difference, and polarity difference caused by mutation. Our results show that this very simple and directly applicable model performs comparably to other much more complex, widely used protein stability prediction methods. This suggests that a hard limit of ∼1 kcal/mol numerical accuracy and an R ∼ 0.5 trend accuracy exists and that new features, such as account of unfolded states, water colocalization, and amino acid correlations, are required to improve accuracy to, e.g., 1/2 kcal/mol.

Precision Biotransformation of Emerging Pollutants by Human Cytochrome P450 Using Computational-Experimental Synergy: A Case Study of Tris(1,3-dichloro-2-propyl) Phosphate.

Precision biotransformation is an envisioned strategy offering detailed insights into biotransformation pathways in real environmental settings using experimentally guided high-accuracy quantum chemistry. Emerging pollutants, whose metabolites are easily overlooked but may cause idiosyncratic toxicity, are important targets of such a strategy. We demonstrate here that complex metabolic reactions of tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) catalyzed by human CYP450 enzymes can be mapped via a three-step synergy strategy: (i) screening the possible metabolites via high-throughout (moderate-accuracy) computations; (ii) analyzing the proposed metabolites in vitro by human liver microsomes and recombinant human CYP450 enzymes; and (iii) rationalizing the experimental data via precise mechanisms using high-level targeted computations. Through the bilateral dialogues from qualitative to semi-quantitative to quantitative levels, we show how TDCIPP metabolism especially by CYP3A4 generates bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) as an O-dealkylation metabolite and bis(1,3-dichloro-2-propyl) 3-chloro-1-hydroxy-2-propyl phosphate (alcoholß-dehalogen) as a dehalogenation/reduction metabolite via the initial rate-determining H-abstraction from αC- and ßC-positions. The relative yield ratio [dehalogenation/reduction]/[O-dealkylation] is derived from the relative barriers of H-abstraction at the ßC- and αC-positions by CYP3A4, estimated as 0.002 to 0.23, viz., an in vitro measured ratio of 0.04. Importantly, alcoholß-dehalogen formation points to a new mechanism involving successive oxidation and reduction functions of CYP450, with its precursor aldehydeß-dehalogen being a key intermediate detected by trapping assays and rationalized by computations. We conclude that the proposed three-step synergy strategy may meet the increasing challenge of elucidating biotransformation mechanisms of substantial synthesized organic compounds in the future.

Evolution of endemism on a young tropical mountain.

Tropical mountains are hot spots of biodiversity and endemism, but the evolutionary origins of their unique biotas are poorly understood. In varying degrees, local and regional extinction, long-distance colonization, and local recruitment may all contribute to the exceptional character of these communities. Also, it is debated whether mountain endemics mostly originate from local lowland taxa, or from lineages that reach the mountain by long-range dispersal from cool localities elsewhere. Here we investigate the evolutionary routes to endemism by sampling an entire tropical mountain biota on the 4,095-metre-high Mount Kinabalu in Sabah, East Malaysia. We discover that most of its unique biodiversity is younger than the mountain itself (6 million years), and comprises a mix of immigrant pre-adapted lineages and descendants from local lowland ancestors, although substantial shifts from lower to higher vegetation zones in this latter group were rare. These insights could improve forecasts of the likelihood of extinction and 'evolutionary rescue' in montane biodiversity hot spots under climate change scenarios.

A computer-simulated mechanism of familial Alzheimer's disease: Mutations enhance thermal dynamics and favor looser substrate-binding to γ-secretase.

The 4-subunit intramembrane protease complex γ-secretase cleaves many substrates including fragments of the ß-amyloid precursor protein (APP), leading to formation of Aß peptides, and Notch. Mutations in APP and the catalytic subunit of γ-secretase, presenilin, cause familial Alzheimer's disease (fAD). Mutations are assumed to change the substrate-binding and cleavage and thereby the Aß formed. Whereas a wild-type structure of substrate-bound γ-secretase became recently available from cryogenic electron microscopy (6IYC), the structure and dynamics of mutant proteins remain obscure. Here, we studied five prominent mutants of substrate-bound γ-secretase by explicit all-atom molecular dynamics in a phospholipid membrane model at physiological temperature using the experimental structure as template: The presenilin 1 mutants E280A, G384A, A434C, and L435F and the V717I mutant of APP. Our structures and dynamics provide the first atomic detail into how fAD-causing mutations affect substrate binding to γ-secretase. The pathogenic mutations tend to increase the space and variability in the substrate binding site, as seen e.g. from the distance from catalytic aspartate to substrate cleavage sites. We suggest that we have identified the molecular cause of the "imprecise cleavage" that leads to two trimming pathways in γ-secretase, consistent with the FIST model, which may rationalize the experimental Aß42/Aß40 ratios as a molecular basis for fAD.

Common mechanism of thermostability in small α- and ß-proteins studied by molecular dynamics.

Protein thermostability is important to evolution, diseases, and industrial applications. Proteins use diverse molecular strategies to achieve stability at high temperature, yet reducing the entropy of unfolding seems required. We investigated five small α-proteins and five ß-proteins with known, distinct structures and thermostability (Tm ) using multi-seed molecular dynamics simulations at 300, 350, and 400 K. The proteins displayed diverse changes in hydrogen bonding, solvent exposure, and secondary structure with no simple relationship to Tm . Our dynamics were in good agreement with experimental B-factors at 300 K and insensitive to force-field choice. Despite the very distinct structures, the native-state (300 + 350 K) free-energy landscapes (FELs) were significantly broader for the two most thermostable proteins and smallest for the three least stable proteins in both the α- and ß-group and with both force fields studied independently (tailed t-test, 95% confidence level). Our results suggest that entropic ensembles stabilize proteins at high temperature due to reduced entropy of unfolding, viz., ΔG = ΔH - TΔS. Supporting this mechanism, the most thermostable proteins were also the least kinetically stable, consistent with broader FELs, typified by villin headpiece and confirmed by specific comparison to a mesophilic ortholog of Thermus thermophilus apo-pyrophosphate phosphohydrolase. We propose that molecular strategies of protein thermostabilization, although diverse, tend to converge toward highest possible entropy in the native state consistent with the functional requirements. We speculate that this tendency may explain why many proteins are not optimally structured and why molten-globule states resemble native proteins so much.