Association between missense variants of uncertain significance in the CHEK2 gene and hereditary breast cancer: a cosegregation and bioinformatics analysis.

Inherited mutations in the CHEK2 gene have been associated with an increased lifetime risk of developing breast cancer (BC). We aim to identify in the study population the prevalence of mutations in the CHEK2 gene in diagnosed BC patients, evaluate the phenotypic characteristics of the tumor and family history, and predict the deleteriousness of the variants of uncertain significance (VUS). A genetic study was performed, from May 2016 to April 2020, in 396 patients diagnosed with BC at the University Hospital Lozano Blesa of Zaragoza, Spain. Patients with a genetic variant in the CHEK2 gene were selected for the study. We performed a descriptive analysis of the clinical variables, a bibliographic review of the variants, and a cosegregation study when possible. Moreover, an in-depth bioinformatics analysis of CHEK2 VUS was carried out. We identified nine genetic variants in the CHEK2 gene in 10 patients (two pathogenic variants and seven VUS). This supposes a prevalence of 0.75% and 1.77%, respectively. In all cases, there was a family history of BC in first- and/or second-degree relatives. We carried out a cosegregation study in two families, being positive in one of them. The bioinformatics analyses predicted the pathogenicity of six of the VUS. In conclusion, CHEK2 mutations have been associated with an increased risk for BC. This risk is well-established for foundation variants. However, the risk assessment for other variants is unclear. The incorporation of bioinformatics analysis provided supporting evidence of the pathogenicity of VUS.

A look at the face of the molten globule: Structural model of the Helicobacter pylori apoflavodoxin ensemble at acidic pH.

Molten globule (MG) is the name given to a compact, non-native conformation of proteins that has stimulated the imagination and work in the protein folding field for more than 40 years. The MG has been proposed to play a central role in the folding reaction and in important cell functions, and to be related to the onset of misfolding diseases. Due to its inherent intractability to high-resolution studies, atomistic structural models have not yet been obtained. We present here an integrative atomistic model of the MG formed at acidic pH by the apoflavodoxin from the human pathogen Helicobacter pylori. This MG has been previously shown to exhibit the archetypical expansion, spectroscopic and thermodynamic features of a molten conformation. To obtain the model, we have analyzed the stability of wild-type and 55 apoflavodoxin mutants to derive experimental equilibrium Φ values that have been used in biased molecular dynamics simulations to convert the native conformation into an MG ensemble. The ensemble has been refined to reproduce the experimental hydrodynamic radius and circular dichroism (CD) spectrum. The refined ensemble, deposited in PDB-Dev, successfully explains the characteristic 1 H-nuclear magnetic resonance (NMR) and near-UV CD spectral features of the MG as well as its solvent-accessible surface area (SASA) change upon unfolding. This integrative model of an MG will help to understand the energetics and roles of these elusive conformations in protein folding and misfolding. Interestingly, the apoflavodoxin MG is structurally unrelated to previously described partly unfolded conformations of this protein, exemplifying that equilibrium MGs need not to reflect the properties of kinetic intermediates.

Protposer: The web server that readily proposes protein stabilizing mutations with high PPV.

Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer , a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer.

PirePred: An Accurate Online Consensus Tool to Interpret Newborn Screening-Related Genetic Variants in Structural Context.

PirePred is a genetic interpretation tool used for a variety of medical conditions investigated in newborn screening programs. The PirePred server retrieves, analyzes, and displays in real time genetic and structural data on 58 genes/proteins associated with medical conditions frequently investigated in the newborn. PirePred analyzes the predictions generated by 15 pathogenicity predictors and applies an optimized majority vote algorithm to classify any possible nonsynonymous single-nucleotide variant as pathogenic, benign, or of uncertain significance. PirePred predictions for variants of clear clinical significance are better than those of any of the individual predictors considered (based on accuracy, sensitivity, and negative predictive value) or are among the best ones (for positive predictive value and Matthews correlation coefficient). PirePred predictions also outperform the comparable in silico predictions offered as supporting evidence, according to American College of Medical Genetics and Genomics guidelines, by VarSome and Franklin. Also, PirePred has very high prediction coverage. To facilitate the molecular interpretation of the missense, nonsense, and frameshift variants in ClinVar, the changing amino acid residue is displayed in its structural context, which is analyzed to provide functional clues. PirePred is an accurate, robust, and easy-to-use tool for clinicians involved in neonatal screening programs and for researchers of related diseases. The server is freely accessible and provides a user-friendly gateway into the structural/functional consequences of genetic variants at the protein level.

Protein haploinsufficiency drivers identify MYBPC3 variants that cause hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease. Variants in MYBPC3, the gene encoding cardiac myosin-binding protein C (cMyBP-C), are the leading cause of HCM. However, the pathogenicity status of hundreds of MYBPC3 variants found in patients remains unknown, as a consequence of our incomplete understanding of the pathomechanisms triggered by HCM-causing variants. Here, we examined 44 nontruncating MYBPC3 variants that we classified as HCM-linked or nonpathogenic according to cosegregation and population genetics criteria. We found that around half of the HCM-linked variants showed alterations in RNA splicing or protein stability, both of which can lead to cMyBP-C haploinsufficiency. These protein haploinsufficiency drivers associated with HCM pathogenicity with 100% and 94% specificity, respectively. Furthermore, we uncovered that 11% of nontruncating MYBPC3 variants currently classified as of uncertain significance in ClinVar induced one of these molecular phenotypes. Our strategy, which can be applied to other conditions induced by protein loss of function, supports the idea that cMyBP-C haploinsufficiency is a fundamental pathomechanism in HCM.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when.

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.