Deep mutational scanning reveals a correlation between degradation and toxicity of thousands of aspartoacylase variants.

Unstable proteins are prone to form non-native interactions with other proteins and thereby may become toxic. To mitigate this, destabilized proteins are targeted by the protein quality control network. Here we present systematic studies of the cytosolic aspartoacylase, ASPA, where variants are linked to Canavan disease, a lethal neurological disorder. We determine the abundance of 6152 of the 6260 ( ~ 98%) possible single amino acid substitutions and nonsense ASPA variants in human cells. Most low abundance variants are degraded through the ubiquitin-proteasome pathway and become toxic upon prolonged expression. The data correlates with predicted changes in thermodynamic stability, evolutionary conservation, and separate disease-linked variants from benign variants. Mapping of degradation signals (degrons) shows that these are often buried and the C-terminal region functions as a degron. The data can be used to interpret Canavan disease variants and provide insight into the relationship between protein stability, degradation and cell fitness.

GMMA Can Stabilize Proteins Across Different Functional Constraints.

Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided an increase of 2-6 °C in thermal inactivation temperature and no decrease in functionality.

A mutational atlas for Parkin proteostasis.

Proteostasis can be disturbed by mutations affecting folding and stability of the encoded protein. An example is the ubiquitin ligase Parkin, where gene variants result in autosomal recessive Parkinsonism. To uncover the pathological mechanism and provide comprehensive genotype-phenotype information, variant abundance by massively parallel sequencing (VAMP-seq) is leveraged to quantify the abundance of Parkin variants in cultured human cells. The resulting mutational map, covering 9219 out of the 9300 possible single-site amino acid substitutions and nonsense Parkin variants, shows that most low abundance variants are proteasome targets and are located within the structured domains of the protein. Half of the known disease-linked variants are found at low abundance. Systematic mapping of degradation signals (degrons) reveals an exposed degron region proximal to the so-called "activation element". This work provides examples of how missense variants may cause degradation either via destabilization of the native protein, or by introducing local signals for degradation.

Conformational ensembles of the human intrinsically disordered proteome.

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.

Rapid protein stability prediction using deep learning representations.

Predicting the thermodynamic stability of proteins is a common and widely used step in protein engineering, and when elucidating the molecular mechanisms behind evolution and disease. Here, we present RaSP, a method for making rapid and accurate predictions of changes in protein stability by leveraging deep learning representations. RaSP performs on-par with biophysics-based methods and enables saturation mutagenesis stability predictions in less than a second per residue. We use RaSP to calculate ∼ 230 million stability changes for nearly all single amino acid changes in the human proteome, and examine variants observed in the human population. We find that variants that are common in the population are substantially depleted for severe destabilization, and that there are substantial differences between benign and pathogenic variants, highlighting the role of protein stability in genetic diseases. RaSP is freely available-including via a Web interface-and enables large-scale analyses of stability in experimental and predicted protein structures.

Global Analysis of Multi-Mutants to Improve Protein Function.

The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to a previously published experiment reporting on >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions (Sarkisyan et al., 2016). The GMMA method achieves a good fit to this dataset while being analytically transparent. We show experimentally that the six top-ranking substitutions progressively enhance GFP. More broadly, using only a single experiment as input our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function. In conclusion, we suggest that large libraries of multiply-substituted variants may provide a unique source of information for protein engineering.

HSP70-binding motifs function as protein quality control degrons.

Protein quality control (PQC) degrons are short protein segments that target misfolded proteins for proteasomal degradation, and thus protect cells against the accumulation of potentially toxic non-native proteins. Studies have shown that PQC degrons are hydrophobic and rarely contain negatively charged residues, features which are shared with chaperone-binding regions. Here we explore the notion that chaperone-binding regions may function as PQC degrons. When directly tested, we found that a canonical Hsp70-binding motif (the APPY peptide) functioned as a dose-dependent PQC degron both in yeast and in human cells. In yeast, Hsp70, Hsp110, Fes1, and the E3 Ubr1 target the APPY degron. Screening revealed that the sequence space within the chaperone-binding region of APPY that is compatible with degron function is vast. We find that the number of exposed Hsp70-binding sites in the yeast proteome correlates with a reduced protein abundance and half-life. Our results suggest that when protein folding fails, chaperone-binding sites may operate as PQC degrons, and that the sequence properties leading to PQC-linked degradation therefore overlap with those of chaperone binding.

Prediction of Quality-control Degradation Signals in Yeast Proteins.

Effective proteome homeostasis is key to cellular and organismal survival, and cells therefore contain efficient quality control systems to monitor and remove potentially toxic misfolded proteins. Such general protein quality control to a large extent relies on the efficient and robust delivery of misfolded or unfolded proteins to the ubiquitin-proteasome system. This is achieved via recognition of so-called degradation motifs-degrons-that are assumed to become exposed as a result of protein misfolding. Despite their importance, the nature and sequence properties of quality-control degrons remain elusive. Here, we have used data from a yeast-based screen of 23,600 17-residue peptides to build a predictor of quality-control degrons. The resulting model, QCDPred (Quality Control Degron Prediction), achieves good accuracy using only the sequence composition of the peptides as input. Our analysis reveals that strong degrons are enriched in hydrophobic amino acids and depleted in negatively charged amino acids, in line with the expectation that they are buried in natively folded proteins. We applied QCDPred to the yeast proteome, enabling us to analyse more widely the potential effects of degrons. As an example, we show a correlation between cellular abundance and degron potential in disordered regions of proteins. Together with recent results on membrane proteins, our work suggest that the recognition of exposed hydrophobic residues is a key and generic mechanism for proteome homeostasis. QCDPred is freely available as open source code and via a web interface.

14-fold increased prevalence of rare glucokinase gene variant carriers in unselected Danish patients with newly diagnosed type 2 diabetes.

AIMS: Rare variants in the glucokinase gene (GCK) cause Maturity-Onset Diabetes of the Young (MODY2/GCK-MODY). We investigated the prevalence of GCK variants, phenotypic characteristics, micro- and macrovascular disease at baseline and follow-up, and treatment among individuals with and without pathogenic GCK variants. METHODS: This is a cross-sectional study in a population-based cohort of 5,433 individuals without diabetes (Inter99 cohort) and in 2,855 patients with a new clinical diagnosis of type 2 diabetes (DD2 cohort) with sequencing of GCK. Phenotypic characteristics, presence of micro- and macrovascular disease and treatment information were available for patients in the DD2 cohort at baseline and after an average follow-up of 7.4 years. RESULTS: Twenty-two carriers of potentially deleterious GCK variants were found among patients with type 2 diabetes compared to three among 5,433 nondiabetic individuals [OR = 14.1 (95 % CI 4.2; 47.0), p = 8.9*10-6]. Patients with type 2 diabetes carrying GCK variants had significantly lower waist circumference, hip circumference and BMI, compared to non-carriers. Three GCK variant carriers with diabetes had microvascular complications during follow-up. CONCLUSIONS: Approximately 0.8% of Danish patients with newly diagnosed type 2 diabetes carry non-synonymous variants in GCK and resemble patients with GCK-MODY. Glucose-lowering treatment cessation should be considered in this subset of diabetes patients.

Understanding the Origins of Loss of Protein Function by Analyzing the Effects of Thousands of Variants on Activity and Abundance.

Understanding and predicting how amino acid substitutions affect proteins are keys to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analyzed 6,749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyze the structural and mechanistic origins of loss of function and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.

Substitutional landscape of a split fluorescent protein fragment using high-density peptide microarrays.

Split fluorescent proteins have wide applicability as biosensors for protein-protein interactions, genetically encoded tags for protein detection and localization, as well as fusion partners in super-resolution microscopy. We have here established and validated a novel platform for functional analysis of leave-one-out split fluorescent proteins (LOO-FPs) in high throughput and with rapid turnover. We have screened more than 12,000 variants of the beta-strand split fragment using high-density peptide microarrays for binding and functional complementation in Green Fluorescent Protein. We studied the effect of peptide length and the effect of different linkers to the solid support. We further mapped the effect of all possible amino acid substitutions on each position as well as in the context of some single and double amino acid substitutions. As all peptides were tested in 12 duplicates, the analysis rests on a firm statistical basis allowing for confirmation of the robustness and precision of the method. Based on experiments in solution, we conclude that under the given conditions, the signal intensity on the peptide microarray faithfully reflects the binding affinity between the split fragments. With this, we are able to identify a peptide with 9-fold higher affinity than the starting peptide.

Improving folding properties of computationally designed proteins.

While the field of computational protein design has witnessed amazing progression in recent years, folding properties still constitute a significant barrier towards designing new and larger proteins. In order to assess and improve folding properties of designed proteins, we have developed a genetics-based folding assay and selection system based on the essential enzyme, orotate phosphoribosyl transferase from Escherichia coli. This system allows for both screening of candidate designs with good folding properties and genetic selection of improved designs. Thus, we identified single amino acid substitutions in two failed designs that rescued poorly folding and unstable proteins. Furthermore, when these substitutions were transferred into a well-structured design featuring a complex folding profile, the resulting protein exhibited native-like cooperative folding with significantly improved stability. In protein design, a single amino acid can make the difference between folding and misfolding, and this approach provides a useful new platform to identify and improve candidate designs.

Structural heterogeneity and dynamics in protein evolution and design.

Recent years have witnessed substantial progress in our ability to design proteins with specific structures and to introduce new functionalities into existing protein scaffolds. Such protein design efforts test our understanding of the biophysical and functional mechanisms of naturally evolved proteins. At the same time, we also know that proteins are dynamical entities, and that many proteins rely on detailed dynamical mechanisms for regulation and function. Thus, the success of design methods, especially in relation to functional proteins, might benefit from explicit considerations of conformational heterogeneity and dynamics. In this review, we compare results from the field of protein design with laboratory protein evolution with a focus on dynamics. Recent studies show that structural dynamics is altered during evolutionary trajectories, and that allosteric effects are pronounced. Interaction networks and the resulting coupling of structure and dynamics are suggested to facilitate these effects.

Characterization of the Hydrodynamics in a Miniaturized Dissolution Apparatus.

The hydrodynamics of a miniaturized dissolution apparatus was characterized using computational fluid dynamics simulations and analyzed in relation to the biorelevance and robustness of measurements of drug dissolution and precipitation kinetics from supersaturated drug solutions. The effect of using 3 different agitator geometries operated at 50, 100, 150, and 200 rpm as well as different positioning of an UV probe in the vessel was systematically evaluated. The computational fluid dynamics simulations were validated using a particle streak velocimetry experiment. The results show that the choice of agitator geometry influences the hydrodynamics of the system and indicates that an off-center probe position may result in more robust measurements. Furthermore, the study shows that the agitator geometry has a significant effect on supersaturation studies due to differences in the hydrodynamic shear produced by the agitator.

Computational Dehydration of Crystalline Hydrates Using Molecular Dynamics Simulations.

Molecular dynamics (MD) simulations have evolved to an increasingly reliable and accessible technique and are today implemented in many areas of biomedical sciences. We present a generally applicable method to study dehydration of hydrates based on MD simulations and apply this approach to the dehydration of ampicillin trihydrate. The crystallographic unit cell of the trihydrate is used to construct the simulation cell containing 216 ampicillin and 648 water molecules. This system is dehydrated by removing water molecules during a 2200 ps simulation, and depending on the computational dehydration rate, different dehydrated structures were observed. Removing all water molecules immediately and removing water relatively fast (10 water molecules/10 ps) resulted in an amorphous system, whereas relatively slow computational dehydration (3 water molecules/10 ps) resulted in a crystalline anhydrate. The structural changes could be followed in real time, and in addition, an intermediate amorphous phase was identified. The computationally identified dehydrated structure (anhydrate) was slightly different from the experimentally known anhydrate structure suggesting that the simulated computational structure could represent a kinetically trapped dehydration intermediate.

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template.

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations.

Local structure in the disordered solid solution of cis- and trans-perinones.

The cis- and trans-isomers of the polycyclic aromatic compound perinone, C26H12N4O2, form a solid solution (Vat Red 14). This solid solution is isotypic to the crystal structures of cis-perinone (Pigment Red 194) and trans-perinone (Pigment Orange 34) and exhibits a combined positional and orientational disorder: In the crystal, each molecular position is occupied by either a cis- or trans-perinone molecule, both of which have two possible molecular orientations. The structure of cis-perinone exhibits a twofold orientational disorder, whereas the structure of trans-perinone is ordered. The crystal structure of the solid solution was determined by single-crystal X-ray analysis. Extensive lattice-energy minimizations with force-field and DFT-D methods were carried out on combinatorially complete sets of ordered models. For the disordered systems, local structures were calculated, including preferred local arrangements, ordering lengths, and probabilities for the arrangement of neighbouring molecules. The superposition of the atomic positions of all energetically favourable calculated models corresponds well with the experimentally determined crystal structures, explaining not only the atomic positions, but also the site occupancies and anisotropic displacement parameters.

Distinguishing tautomerism in the crystal structure of (Z)-N-(5-ethyl-2,3-dihydro-1,3,4-thiadiazol-2-ylidene)-4-methylbenzenesulfonamide using DFT-D calculations and (13)C solid-state NMR.

The crystal structure of the title compound, C11H13N3O2S2, has been determined previously on the basis of refinement against laboratory powder X-ray diffraction (PXRD) data, supported by comparison of measured and calculated (13)C solid-state NMR spectra [Hangan et al. (2010). Acta Cryst. B66, 615-621]. The molecule is tautomeric, and was reported as an amine tautomer [systematic name: N-(5-ethyl-1,3,4-thiadiazol-2-yl)-p-toluenesulfonamide], rather than the correct imine tautomer. The protonation site on the molecule's 1,3,4-thiadiazole ring is indicated by the intermolecular contacts in the crystal structure: N-H...O hydrogen bonds are established at the correct site, while the alternative protonation site does not establish any notable intermolecular interactions. The two tautomers provide essentially identical Rietveld fits to laboratory PXRD data, and therefore they cannot be directly distinguished in this way. However, the correct tautomer can be distinguished from the incorrect one by previously reported quantitative criteria based on the extent of structural distortion on optimization of the crystal structure using dispersion-corrected density functional theory (DFT-D) calculations. Calculation of the (13)C SS-NMR spectrum based on the correct imine tautomer also provides considerably better agreement with the measured (13)C SS-NMR spectrum.

PHAISTOS: a framework for Markov chain Monte Carlo simulation and inference of protein structure.

We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area solvent model. A flexible command-line and configuration-file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms.