Illuminating protein space with a programmable generative model.

Three billion years of evolution has produced a tremendous diversity of protein molecules1, but the full potential of proteins is likely to be much greater. Accessing this potential has been challenging for both computation and experiments because the space of possible protein molecules is much larger than the space of those likely to have functions. Here we introduce Chroma, a generative model for proteins and protein complexes that can directly sample novel protein structures and sequences, and that can be conditioned to steer the generative process towards desired properties and functions. To enable this, we introduce a diffusion process that respects the conformational statistics of polymer ensembles, an efficient neural architecture for molecular systems that enables long-range reasoning with sub-quadratic scaling, layers for efficiently synthesizing three-dimensional structures of proteins from predicted inter-residue geometries and a general low-temperature sampling algorithm for diffusion models. Chroma achieves protein design as Bayesian inference under external constraints, which can involve symmetries, substructure, shape, semantics and even natural-language prompts. The experimental characterization of 310 proteins shows that sampling from Chroma results in proteins that are highly expressed, fold and have favourable biophysical properties. The crystal structures of two designed proteins exhibit atomistic agreement with Chroma samples (a backbone root-mean-square deviation of around 1.0 Å). With this unified approach to protein design, we hope to accelerate the programming of protein matter to benefit human health, materials science and synthetic biology.

Switching an active site helix in dihydrofolate reductase reveals limits to subdomain modularity.

To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.

Evolution on the Biophysical Fitness Landscape of an RNA Virus.

Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.

Biophysical principles predict fitness landscapes of drug resistance.

Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype-phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.

Free Superoxide is an Intermediate in the Production of H2O2 by Copper(I)-Aß Peptide and O2.

Oxidative stress is considered as an important factor and an early event in the etiology of Alzheimer's disease (AD). Cu bound to the peptide amyloid-ß (Aß) is found in AD brains, and Cu-Aß could contribute to this oxidative stress, as it is able to produce in vitro H2O2 and HO˙ in the presence of oxygen and biological reducing agents such as ascorbate. The mechanism of Cu-Aß-catalyzed H2O2 production is however not known, although it was proposed that H2O2 is directly formed from O2 via a 2-electron process. Here, we implement an electrochemical setup and use the specificity of superoxide dismutase-1 (SOD1) to show, for the first time, that H2O2 production by Cu-Aß in the presence of ascorbate occurs mainly via a free O2˙(-) intermediate. This finding radically changes the view on the catalytic mechanism of H2O2 production by Cu-Aß, and opens the possibility that Cu-Aß-catalyzed O2˙(-) contributes to oxidative stress in AD, and hence may be of interest.

Simplified 2,4-dinitrophenylhydrazine spectrophotometric assay for quantification of carbonyls in oxidized proteins.

This work proposes a modification of the 2,4-dinitrophenylhydrazine (DNPH) spectrophotometric assay commonly used to evaluate the concentration of carbonyl groups in oxidized proteins. In this approach NaOH is added to the protein solution after the addition of DNPH, shifting the maximum absorbance wavelength of the derivatized protein from 370 to 450nm. This reduces the interference of DNPH and allows the direct quantification in the sample solution without the need for the precipitation, washing, and resuspension steps that are carried out in the traditional DNPH method. The two methods were compared under various conditions and are statistically equivalent.

Mutations at the flavin binding site of ETF:QO yield a MADD-like severe phenotype in Drosophila.

Following a screening on EMS-induced Drosophila mutants defective for formation and morphogenesis of epithelial cells, we have identified three lethal mutants defective for the production of embryonic cuticle. The mutants are allelic to the CG12140 gene, the fly homologue of electron transfer flavoprotein:ubiquinone oxidoreductase (ETF:QO). In humans, inherited defects in this inner membrane protein account for multiple acyl-CoA dehydrogenase deficiency (MADD), a metabolic disease of ß-oxidation, with a broad range of clinical phenotypes, varying from embryonic lethal to mild forms. The three mutant alleles carried distinct missense mutations in ETF:QO (G65E, A68V and S104F) and maternal mutant embryos for ETF:QO showed lethal morphogenetic defects and a significant induction of apoptosis following germ-band elongation. This phenotype is accompanied by an embryonic accumulation of short- and medium-chain acylcarnitines (C4, C8 and C12) as well as long-chain acylcarnitines (C14 and C16:1), whose elevation is also found in severe MADD forms in humans under intense metabolic decompensation. In agreement the ETF:QO activity in the mutant embryos is markedly decreased in relation to wild type activity. Amino acid sequence analysis and structural mapping into a molecular model of ETF:QO show that all mutations map at FAD interacting residues, two of which at the nucleotide-binding Rossmann fold. This structural domain is composed by a ß-strand connected by a short loop to an α-helix, and its perturbation results in impaired cofactor association via structural destabilisation and consequently enzymatic inactivation. This work thus pinpoints the molecular origins of a severe MADD-like phenotype in the fruit fly and establishes the proof of concept concerning the suitability of this organism as a potential model organism for MADD.

Empowering drug off-target discovery with metabolic and structural analysis.

Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of metabolomics data and growth rescue experiments. We deploy this framework to understand the intracellular molecular interactions of the multi-valent dihydrofolate reductase-targeting antibiotic compound CD15-3. We analyse global metabolomics data utilizing machine learning, metabolic modelling, and protein structural similarity to prioritize candidate drug targets. Overexpression and in vitro activity assays confirm one of the predicted candidates, HPPK (folK), as a CD15-3 off-target. This study demonstrates how established machine learning methods can be combined with mechanistic analyses to improve the resolution of drug target finding workflows for discovering off-targets of a metabolic inhibitor.

Cofactors and metabolites as potential stabilizers of mitochondrial acyl-CoA dehydrogenases.

Protein misfolding is a hallmark of a number of metabolic diseases, in which fatty acid oxidation defects are included. The latter result from genetic deficiencies in transport proteins and enzymes of the mitochondrial ß-oxidation, and milder disease conditions frequently result from conformational destabilization and decreased enzymatic function of the affected proteins. Small molecules which have the ability to raise the functional levels of the affected protein above a certain disease threshold are thus valuable tools for effective drug design. In this work we have investigated the effect of mitochondrial cofactors and metabolites as potential stabilizers in two ß-oxidation acyl-CoA dehydrogenases: short chain acyl-CoA dehydrogenase and the medium chain acyl-CoA dehydrogenase as well as glutaryl-CoA dehydrogenase, which is involved in lysine and tryptophan metabolism. We found that near physiological concentrations (low micromolar) of FAD resulted in a spectacular enhancement of the thermal stabilities of these enzymes and prevented enzymatic activity loss during a 1h incubation at 40°C. A clear effect of the respective substrate, which was additive to that of the FAD effect, was also observed for short- and medium-chain acyl-CoA dehydrogenase but not for glutaryl-CoA dehydrogenase. In conclusion, riboflavin may be beneficial during feverish crises in patients with short- and medium-chain acyl-CoA dehydrogenase as well as in glutaryl-CoA dehydrogenase deficiencies, and treatment with substrate analogs to butyryl- and octanoyl-CoAs could theoretically enhance enzyme activity for some enzyme proteins with inherited folding difficulties.

Reductive elimination of superoxide: Structure and mechanism of superoxide reductases.

Superoxide anion is among the deleterious reactive oxygen species, towards which all organisms have specialized detoxifying enzymes. For quite a long time, superoxide elimination was thought to occur through its dismutation, catalyzed by Fe, Cu, and Mn or, as more recently discovered, by Ni-containing enzymes. However, during the last decade, a novel type of enzyme was established that eliminates superoxide through its reduction: the superoxide reductases, which are spread among anaerobic and facultative microorganisms, from the three life kingdoms. These enzymes share the same unique catalytic site, an iron ion bound to four histidines and a cysteine that, in its reduced form, reacts with superoxide anion with a diffusion-limited second order rate constant of approximately 10(9) M(-1) s(-1). In this review, the properties of these enzymes will be thoroughly discussed.

Protein stability in an ionic liquid milieu: on the use of differential scanning fluorimetry.

Protein stability is a major bottleneck in the biotechnological application of ionic liquid-containing solvents, either in the frame of biocatalysis or protein storage. Herein, differential scanning fluorimetry was successfully implemented as a high throughput method to fast scan the impact of a number of cholinium-based ionic liquids on the stability of proteins.

Development of antibacterial compounds that constrain evolutionary pathways to resistance.

Antibiotic resistance is a worldwide challenge. A potential approach to block resistance is to simultaneously inhibit WT and known escape variants of the target bacterial protein. Here, we applied an integrated computational and experimental approach to discover compounds that inhibit both WT and trimethoprim (TMP) resistant mutants of E. coli dihydrofolate reductase (DHFR). We identified a novel compound (CD15-3) that inhibits WT DHFR and its TMP resistant variants L28R, P21L and A26T with IC50 50-75 µM against WT and TMP-resistant strains. Resistance to CD15-3 was dramatically delayed compared to TMP in in vitro evolution. Whole genome sequencing of CD15-3-resistant strains showed no mutations in the target folA locus. Rather, gene duplication of several efflux pumps gave rise to weak (about twofold increase in IC50) resistance against CD15-3. Altogether, our results demonstrate the promise of strategy to develop evolution drugs - compounds which constrain evolutionary escape routes in pathogens.

Purification, crystallization and X-ray crystallographic analysis of Archaeoglobus fulgidus neelaredoxin.

Neelaredoxins are a type of superoxide reductase (SOR), which are blue 14 kDa metalloproteins with a catalytic nonhaem iron centre coordinated by four histidines and one cysteine in the ferrous form. Anaerobic organisms such as Archaeoglobus fulgidus, a hyperthermophilic sulfate-reducing archaeon, have developed defence mechanisms against toxic oxygen species in which superoxide reductases play a key role. SOR is responsible for scavenging toxic superoxide anion radicals (O(2)(*-)), catalysing the one-electron reduction of superoxide to hydrogen peroxide. Crystals of recombinant A. fulgidus neelaredoxin in the oxidized form (13.7 kDa, 125 residues) were obtained using polyethylene glycol and ammonium sulfate. These crystals diffracted to 1.9 A resolution and belonged to the tetragonal space group P4(1)2(1)2, with unit-cell parameters a = b = 75.72, c = 185.44 A. Cell-content analysis indicated the presence of a tetramer in the asymmetric unit, with a Matthews coefficient (V(M)) of 2.36 A(3) Da(-1) and an estimated solvent content of 48%. The three-dimensional structure was determined by the MAD method and is currently under refinement.

Adaptation to mutational inactivation of an essential gene converges to an accessible suboptimal fitness peak.

The mechanisms of adaptation to inactivation of essential genes remain unknown. Here we inactivate E. coli dihydrofolate reductase (DHFR) by introducing D27G,N,F chromosomal mutations in a key catalytic residue with subsequent adaptation by an automated serial transfer protocol. The partial reversal G27- > C occurred in three evolutionary trajectories. Conversely, in one trajectory for D27G and in all trajectories for D27F,N strains adapted to grow at very low metabolic supplement (folAmix) concentrations but did not escape entirely from supplement auxotrophy. Major global shifts in metabolome and proteome occurred upon DHFR inactivation, which were partially reversed in adapted strains. Loss-of-function mutations in two genes, thyA and deoB, ensured adaptation to low folAmix by rerouting the 2-Deoxy-D-ribose-phosphate metabolism from glycolysis towards synthesis of dTMP. Multiple evolutionary pathways of adaptation converged to a suboptimal solution due to the high accessibility to loss-of-function mutations that block the path to the highest, yet least accessible, fitness peak.

Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.

While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function-such as growth in the presence or absence of an antibiotic-are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral α-helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.

Proteostasis Environment Shapes Higher-Order Epistasis Operating on Antibiotic Resistance.

Recent studies have affirmed that higher-order epistasis is ubiquitous and can have large effects on complex traits. Yet, we lack frameworks for understanding how epistatic interactions are influenced by central features of cell physiology. In this study, we assess how protein quality control machinery-a critical component of cell physiology-affects epistasis for different traits related to bacterial resistance to antibiotics. Specifically, we disentangle the interactions between different protein quality control genetic backgrounds and two sets of mutations: (i) SNPs associated with resistance to antibiotics in an essential bacterial enzyme (dihydrofolate reductase, or DHFR) and (ii) differing DHFR bacterial species-specific amino acid background sequences (Escherichia coli, Listeria grayi, and Chlamydia muridarum). In doing so, we improve on generic observations that epistasis is widespread by discussing how patterns of epistasis can be partly explained by specific interactions between mutations in an essential enzyme and genes associated with the proteostasis environment. These findings speak to the role of environmental and genotypic context in modulating higher-order epistasis, with direct implications for evolutionary theory, genetic modification technology, and efforts to manage antimicrobial resistance.

Stability of the Influenza Virus Hemagglutinin Protein Correlates with Evolutionary Dynamics.

Protein thermodynamics are an integral determinant of viral fitness and one of the major drivers of protein evolution. Mutations in the influenza A virus (IAV) hemagglutinin (HA) protein can eliminate neutralizing antibody binding to mediate escape from preexisting antiviral immunity. Prior research on the IAV nucleoprotein suggests that protein stability may constrain seasonal IAV evolution; however, the role of stability in shaping the evolutionary dynamics of the HA protein has not been explored. We used the full coding sequence of 9,797 H1N1pdm09 HA sequences and 16,716 human seasonal H3N2 HA sequences to computationally estimate relative changes in the thermal stability of the HA protein between 2009 and 2016. Phylogenetic methods were used to characterize how stability differences impacted the evolutionary dynamics of the virus. We found that pandemic H1N1 IAV strains split into two lineages that had different relative HA protein stabilities and that later variants were descended from the higher-stability lineage. Analysis of the mutations associated with the selective sweep of the higher-stability lineage found that they were characterized by the early appearance of highly stabilizing mutations, the earliest of which was not located in a known antigenic site. Experimental evidence further suggested that H1N1 HA stability may be correlated with in vitro virus production and infection. A similar analysis of H3N2 strains found that surviving lineages were also largely descended from viruses predicted to encode more-stable HA proteins. Our results suggest that HA protein stability likely plays a significant role in the persistence of different IAV lineages. IMPORTANCE One of the constraints on fast-evolving viruses, such as influenza virus, is protein stability, or how strongly the folded protein holds together. Despite the importance of this protein property, there has been limited investigation of the impact of the stability of the influenza virus hemagglutinin protein-the primary antibody target of the immune system-on its evolution. Using a combination of computational estimates of stability and experiments, our analysis found that viruses with more-stable hemagglutinin proteins were associated with long-term persistence in the population. There are two potential reasons for the observed persistence. One is that more-stable proteins tolerate destabilizing mutations that less-stable proteins could not, thus increasing opportunities for immune escape. The second is that greater stability increases the fitness of the virus through increased production of infectious particles. Further research on the relative importance of these mechanisms could help inform the annual influenza vaccine composition decision process.

Differential Enzyme Flexibility Probed Using Solid-State Nanopores.

Enzymes and motor proteins are dynamic macromolecules that coexist in a number of conformations of similar energies. Protein function is usually accompanied by a change in structure and flexibility, often induced upon binding to ligands. However, while measuring protein flexibility changes between active and resting states is of therapeutic significance, it remains a challenge. Recently, our group has demonstrated that breadth of signal amplitudes in measured electrical signatures as an ensemble of individual protein molecules is driven through solid-state nanopores and correlates with protein conformational dynamics. Here, we extend our study to resolve subtle flexibility variation in dihydrofolate reductase mutants from unlabeled single molecules in solution. We first demonstrate using a canonical protein system, adenylate kinase, that both size and flexibility changes can be observed upon binding to a substrate that locks the protein in a closed conformation. Next, we investigate the influence of voltage bias and pore geometry on the measured electrical pulse statistics during protein transport. Finally, using the optimal experimental conditions, we systematically study a series of wild-type and mutant dihydrofolate reductase proteins, finding a good correlation between nanopore-measured protein conformational dynamics and equilibrium bulk fluorescence probe measurements. Our results unequivocally demonstrate that nanopore-based measurements reliably probe conformational diversity in native protein ensembles.

Kinetics of electron transfer from NADH to the Escherichia coli nitric oxide reductase flavorubredoxin.

Escherichia coli flavorubredoxin (FlRd) belongs to the family of flavodiiron proteins (FDPs), microbial enzymes that are expressed to scavenge nitric oxide (NO) under anaerobic conditions. To degrade NO, FlRd has to be reduced by NADH via the FAD-binding protein flavorubredoxin reductase, thus the kinetics of electron transfer along this pathway was investigated by stopped-flow absorption spectroscopy. We found that NADH, but not NADPH, quickly reduces the FlRd-reductase (k = 5.5 +/- 2.2 x 10(6) M(-1).s(-1) at 5 degrees C), with a limiting rate of 255 +/- 17 s(-1). The reductase in turn quickly reduces the rubredoxin (Rd) center of FlRd, as assessed at 5 degrees C working with the native FlRd enzyme (k = 2.4 +/- 0.1 x 10(6) m(-1).s(-1)) and with its isolated Rd-domain (k approximately 1 x 10(7) M(-1).s(-1)); in both cases the reaction was found to be dependent on pH and ionic strength. In FlRd the fast reduction of the Rd center occurs synchronously with the formation of flavin mononucleotide semiquinone. Our data provide evidence that (a) FlRd-reductase rapidly shuttles electrons between NADH and FlRd, a prerequisite for NO reduction in this detoxification pathway, and (b) the electron accepting site in FlRd, the Rd center, is in very fast redox equilibrium with the flavin mononucleotide.

Rational Design of Novel Allosteric Dihydrofolate Reductase Inhibitors Showing Antibacterial Effects on Drug-Resistant Escherichia coli Escape Variants.

In drug discovery, systematic variations of substituents on a common scaffold and bioisosteric replacements are often used to generate diversity and obtain molecules with better biological effects. However, this could saturate the small-molecule diversity pool resulting in drug resistance. On the other hand, conventional drug discovery relies on targeting known pockets on protein surfaces leading to drug resistance by mutations of critical pocket residues. Here, we present a two-pronged strategy of designing novel drugs that target unique pockets on a protein's surface to overcome the above problems. Dihydrofolate reductase, DHFR, is a critical enzyme involved in thymidine and purine nucleotide biosynthesis. Several classes of compounds that are structural analogues of the substrate dihydrofolate have been explored for their antifolate activity. Here, we describe 10 novel small-molecule inhibitors of Escherichia coli DHFR, EcDHFR, belonging to the stilbenoid, deoxybenzoin, and chalcone family of compounds discovered by a combination of pocket-based virtual ligand screening and systematic scaffold hopping. These inhibitors show a unique uncompetitive or noncompetitive inhibition mechanism, distinct from those reported for all known inhibitors of DHFR, indicative of binding to a unique pocket distinct from either substrate or cofactor-binding pockets. Furthermore, we demonstrate that rescue mutants of EcDHFR, with reduced affinity to all known classes of DHFR inhibitors, are inhibited at the same concentration as the wild-type. These compounds also exhibit antibacterial activity against E. coli harboring the drug-resistant variant of DHFR. This discovery is the first report on a novel class of inhibitors targeting a unique pocket on EcDHFR.