Blocking protein quality control to counter hereditary cancers

PRKN-linked familial Parkinson's disease: cellular and molecular mechanisms of disease-linked variants

Parkinson's disease (PD) is a common and incurable neurodegenerative disorder that arises from the loss of dopaminergic neurons in the substantia nigra and is mainly characterized by progressive loss of motor function. Monogenic familial PD is associated with highly penetrant variants in specific genes, notably the PRKN gene, where homozygous or compound heterozygous loss-of-function variants predominate. PRKN encodes Parkin, an E3 ubiquitin-protein ligase important for protein ubiquitination and mitophagy of damaged mitochondria. Accordingly, Parkin plays a central role in mitochondrial quality control but is itself also subject to a strict protein quality control system that rapidly eliminates certain disease-linked Parkin variants. Here, we summarize the cellular and molecular functions of Parkin, highlighting the various mechanisms by which PRKN gene variants result in loss-of-function. We emphasize the importance of high-throughput assays and computational tools for the clinical classification of PRKN gene variants and how detailed insights into the pathogenic mechanisms of PRKN gene variants may impact the development of personalized therapeutics.

Cellular and molecular mechanisms of aspartoacylase and its role in Canavan disease

Canavan disease is an autosomal recessive and lethal neurological disorder, characterized by the spongy degeneration of the white matter in the brain. The disease is caused by a deficiency of the cytosolic aspartoacylase (ASPA) enzyme, which catalyzes the hydrolysis of N-acetyl-aspartate (NAA), an abundant brain metabolite, into aspartate and acetate. On the physiological level, the mechanism of pathogenicity remains somewhat obscure, with multiple, not mutually exclusive, suggested hypotheses. At the molecular level, recent studies have shown that most disease linked ASPA gene variants lead to a structural destabilization and subsequent proteasomal degradation of the ASPA protein variants, and accordingly Canavan disease should in general be considered a protein misfolding disorder. Here, we comprehensively summarize the molecular and cell biology of ASPA, with a particular focus on disease-linked gene variants and the pathophysiology of Canavan disease. We highlight the importance of high-throughput technologies and computational prediction tools for making genotype-phenotype predictions as we await the results of ongoing trials with gene therapy for Canavan disease.

Lynch syndrome, molecular mechanisms and variant classification

Patients with the heritable cancer disease, Lynch syndrome, carry germline variants in the MLH1, MSH2, MSH6 and PMS2 genes, encoding the central components of the DNA mismatch repair system. Loss-of-function variants disrupt the DNA mismatch repair system and give rise to a detrimental increase in the cellular mutational burden and cancer development. The treatment prospects for Lynch syndrome rely heavily on early diagnosis; however, accurate diagnosis is inextricably linked to correct clinical interpretation of individual variants. Protein variant classification traditionally relies on cumulative information from occurrence in patients, as well as experimental testing of the individual variants. The complexity of variant classification is due to (1) that variants of unknown significance are rare in the population and phenotypic information on the specific variants is missing, and (2) that individual variant testing is challenging, costly and slow. Here, we summarise recent developments in high-throughput technologies and computational prediction tools for the assessment of variants of unknown significance in Lynch syndrome. These approaches may vastly increase the number of interpretable variants and could also provide important mechanistic insights into the disease. These insights may in turn pave the road towards developing personalised treatment approaches for Lynch syndrome.

Interpreting the molecular mechanisms of disease variants in human transmembrane proteins

Next-generation sequencing of human genomes reveals millions of missense variants, some of which may lead to loss of protein function and ultimately disease. Here, we investigate missense variants in membrane proteins-key drivers in cell signaling and recognition. We find enrichment of pathogenic variants in the transmembrane region across 19,000 functionally classified variants in human membrane proteins. To accurately predict variant consequences, one fundamentally needs to understand the underlying molecular processes. A key mechanism underlying pathogenicity in missense variants of soluble proteins has been shown to be loss of stability. Membrane proteins, however, are widely understudied. Here, we interpret variant effects on a larger scale by performing structure-based estimations of changes in thermodynamic stability using a membrane-specific energy function and analyses of sequence conservation during evolution of 15 transmembrane proteins. We find evidence for loss of stability being the cause of pathogenicity in more than half of the pathogenic variants, indicating that this is a driving factor also in membrane-protein-associated diseases. Our findings show how computational tools aid in gaining mechanistic insights into variant consequences for membrane proteins. To enable broader analyses of disease-related and population variants, we include variant mappings for the entire human proteome.

Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation

Understanding and predicting the functional consequences of single amino acid changes is central in many areas of protein science. Here, we collect and analyze experimental measurements of effects of >150,000 variants in 29 proteins. We use biophysical calculations to predict changes in stability for each variant and assess them in light of sequence conservation. We find that the sequence analyses give more accurate prediction of variant effects than predictions of stability and that about half of the variants that show loss of function do so due to stability effects. We construct a machine learning model to predict variant effects from protein structure and sequence alignments and show how the two sources of information support one another and enable mechanistic interpretations. Together, our results show how one can leverage large-scale experimental assessments of variant effects to gain deeper and general insights into the mechanisms that cause loss of function.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

Mapping the degradation pathway of a disease-linked aspartoacylase variant

Canavan disease is a severe progressive neurodegenerative disorder that is characterized by swelling and spongy degeneration of brain white matter. The disease is genetically linked to polymorphisms in the aspartoacylase (ASPA) gene, including the substitution C152W. ASPA C152W is associated with greatly reduced protein levels in cells, yet biophysical experiments suggest a wild-type like thermal stability. Here, we use ASPA C152W as a model to investigate the degradation pathway of a disease-causing protein variant. When we expressed ASPA C152W in Saccharomyces cerevisiae, we found a decreased steady state compared to wild-type ASPA as a result of increased proteasomal degradation. However, molecular dynamics simulations of ASPA C152W did not substantially deviate from wild-type ASPA, indicating that the native state is structurally preserved. Instead, we suggest that the C152W substitution interferes with the de novo folding pathway resulting in increased proteasomal degradation before reaching its stable conformation. Systematic mapping of the protein quality control components acting on misfolded and aggregation-prone species of C152W, revealed that the degradation is highly dependent on the molecular chaperone Hsp70, its co-chaperone Hsp110 as well as several quality control E3 ubiquitin-protein ligases, including Ubr1. In addition, the disaggregase Hsp104 facilitated refolding of aggregated ASPA C152W, while Cdc48 mediated degradation of insoluble ASPA protein. In human cells, ASPA C152W displayed increased proteasomal turnover that was similarly dependent on Hsp70 and Hsp110. Our findings underscore the use of yeast to determine the protein quality control components involved in the degradation of human pathogenic variants in order to identify potential therapeutic targets.

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.

Folliculin variants linked to Birt-Hogg-Dubé syndrome are targeted for proteasomal degradation

Germline mutations in the folliculin (FLCN) tumor suppressor gene are linked to Birt-Hogg-Dubé (BHD) syndrome, a dominantly inherited genetic disease characterized by predisposition to fibrofolliculomas, lung cysts, and renal cancer. Most BHD-linked FLCN variants include large deletions and splice site aberrations predicted to cause loss of function. The mechanisms by which missense variants and short in-frame deletions in FLCN trigger disease are unknown. Here, we present an integrated computational and experimental study that reveals that the majority of such disease-causing FLCN variants cause loss of function due to proteasomal degradation of the encoded FLCN protein, rather than directly ablating FLCN function. Accordingly, several different single-site FLCN variants are present at strongly reduced levels in cells. In line with our finding that FLCN variants are protein quality control targets, several are also highly insoluble and fail to associate with the FLCN-binding partners FNIP1 and FNIP2. The lack of FLCN binding leads to rapid proteasomal degradation of FNIP1 and FNIP2. Half of the tested FLCN variants are mislocalized in cells, and one variant (ΔE510) forms perinuclear protein aggregates. A yeast-based stability screen revealed that the deubiquitylating enzyme Ubp15/USP7 and molecular chaperones regulate the turnover of the FLCN variants. Lowering the temperature led to a stabilization of two FLCN missense proteins, and for one (R362C), function was re-established at low temperature. In conclusion, we propose that most BHD-linked FLCN missense variants and small in-frame deletions operate by causing misfolding and degradation of the FLCN protein, and that stabilization and resulting restoration of function may hold therapeutic potential of certain disease-linked variants. Our computational saturation scan encompassing both missense variants and single site deletions in FLCN may allow classification of rare FLCN variants of uncertain clinical significance.

Computational analysis of androgen receptor (AR) variants to decipher the relationship between protein stability and related-diseases

Although more than 1,000 androgen receptor (AR) mutations have been identified and these mutants are pathologically important, few theoretical studies have investigated the role of AR protein folding stability in disease and its relationship with the phenotype of the patients. Here, we extracted AR variant data from four databases: ARDB, HGMD, Cosmic, and 1,000 genome. 905 androgen insensitivity syndrome (AIS)-associated loss-of-function mutants and 168 prostate cancer-associated gain-of-function mutants in AR were found. We analyzed the effect of single-residue variation on the folding stability of AR by FoldX and guanidine hydrochloride denaturation experiment, and found that genetic disease-associated mutations tend to have a significantly greater effect on protein stability than gene polymorphisms. Moreover, AR mutants in complete androgen insensitivity syndrome (CAIS) tend to have a greater effect on protein stability than in partial androgen insensitive syndrome (PAIS). This study, by linking disease phenotypes to changes in AR stability, demonstrates the importance of protein stability in the pathogenesis of hereditary disease.

Computational and cellular studies reveal structural destabilization and degradation of MLH1 variants in Lynch syndrome

Defective mismatch repair leads to increased mutation rates, and germline loss-of-function variants in the repair component MLH1 cause the hereditary cancer predisposition disorder known as Lynch syndrome. Early diagnosis is important, but complicated by many variants being of unknown significance. Here we show that a majority of the disease-linked MLH1 variants we studied are present at reduced cellular levels. We show that destabilized MLH1 variants are targeted for chaperone-assisted proteasomal degradation, resulting also in degradation of co-factors PMS1 and PMS2. In silico saturation mutagenesis and computational predictions of thermodynamic stability of MLH1 missense variants revealed a correlation between structural destabilization, reduced steady-state levels and loss-of-function. Thus, we suggest that loss of stability and cellular degradation is an important mechanism underlying many MLH1 variants in Lynch syndrome. Combined with analyses of conservation, the thermodynamic stability predictions separate disease-linked from benign MLH1 variants, and therefore hold potential for Lynch syndrome diagnostics.

Biophysical and Mechanistic Models for Disease-Causing Protein Variants

The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

NQO1: A target for the treatment of cancer and neurological diseases, and a model to understand loss of function disease mechanisms

NAD(P)H quinone oxidoreductase 1 (NQO1) is a multi-functional protein that catalyses the reduction of quinones (and other molecules), thus playing roles in xenobiotic detoxification and redox balance, and also has roles in stabilising apoptosis regulators such as p53. The structure and enzymology of NQO1 is well-characterised, showing a substituted enzyme mechanism in which NAD(P)H binds first and reduces an FAD cofactor in the active site, assisted by a charge relay system involving Tyr-155 and His-161. Protein dynamics play important role in physio-pathological aspects of this protein. NQO1 is a good target to treat cancer due to its overexpression in cancer cells. A polymorphic form of NQO1 (p.P187S) is associated with increased cancer risk and certain neurological disorders (such as multiple sclerosis and Alzheimer´s disease), possibly due to its roles in the antioxidant defence. p.P187S has greatly reduced FAD affinity and stability, due to destabilization of the flavin binding site and the C-terminal domain, which leading to reduced activity and enhanced degradation. Suppressor mutations partially restore the activity of p.P187S by local stabilization of these regions, and showing long-range allosteric communication within the protein. Consequently, the correction of NQO1 misfolding by pharmacological chaperones is a viable strategy, which may be useful to treat cancer and some neurological conditions, targeting structural spots linked to specific disease-mechanisms. Thus, NQO1 emerges as a good model to investigate loss of function mechanisms in genetic diseases as well as to improve strategies to discriminate between neutral and pathogenic variants in genome-wide sequencing studies.

Toward mechanistic models for genotype-phenotype correlations in phenylketonuria using protein stability calculations

Phenylketonuria (PKU) is a genetic disorder caused by variants in the gene encoding phenylalanine hydroxylase (PAH), resulting in accumulation of phenylalanine to neurotoxic levels. Here, we analyzed the cellular stability, localization, and interaction with wild-type PAH of 20 selected PKU-linked PAH protein missense variants. Several were present at reduced levels in human cells, and the levels increased in the presence of a proteasome inhibitor, indicating that proteins are proteasome targets. We found that all the tested PAH variants retained their ability to associate with wild-type PAH, and none formed aggregates, suggesting that they are only mildly destabilized in structure. In all cases, PAH variants were stabilized by the cofactor tetrahydrobiopterin (BH₄ ), a molecule known to alleviate symptoms in certain PKU patients. Biophysical calculations on all possible single-site missense variants using the full-length structure of PAH revealed a strong correlation between the predicted protein stability and the observed stability in cells. This observation rationalizes previously observed correlations between predicted loss of protein destabilization and disease severity, a correlation that we also observed using new calculations. We thus propose that many disease-linked PAH variants are structurally destabilized, which in turn leads to proteasomal degradation and insufficient amounts of cellular PAH protein.

Protein stability and degradation in health and disease

The cellular proteome performs highly varied functions to sustain life. Since most of these functions require proteins to fold properly, they can be impaired by mutations that affect protein structure, leading to diseases such as Alzheimer's disease, cystic fibrosis, and Lynch syndrome. The cell has evolved an intricate protein quality control (PQC) system that includes degradation pathways and a multitude of molecular chaperones and co-chaperones, all working together to catalyze the refolding or removal of aberrant proteins. Thus, the PQC system limits the harmful consequences of dysfunctional proteins, including those arising from disease-causing mutations. This complex system is still not fully understood. In particular the structural and sequence motifs that, when exposed, trigger degradation of misfolded proteins are currently under investigation. Moreover, several attempts are being made to activate or inhibit parts of the PQC system as a treatment for diseases. Here, we briefly review the present knowledge on the PQC system and list current strategies that are employed to exploit the system in disease treatment.

Endoplasmic reticulum stress in the development of multiple myeloma and drug resistance

Multiple myeloma (MM) is a haematological malignancy of mature antibody‐secreting plasma cells. Currently, MM is incurable, but advances in drug treatments have increased patient lifespan. One of the characteristics of MM is the excessive production of monoclonal immunoglobulin (also referred to as paraprotein). This high level of protein production induces endoplasmic reticulum (ER) stress, and proteasomal degradation of the paraprotein is required to avoid ER stress‐induced cell death. Consequently, proteasomal inhibitors such as bortezomib have been particularly effective therapies. Unfortunately development of resistance to bortezomib is common. In this review, we address how control of endoplasmic reticulum stress is important in the development of MM and how the unfolded protein response and its associated stress response pathways are involved in the development of bortezomib resistance.