PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update

In silico analysis of PFN1 related to amyotrophic lateral sclerosis

Profilin 1 (PFN1) protein plays key roles in neuronal growth and differentiation, membrane trafficking, and regulation of the actin cytoskeleton. Four natural variants of PFN1 were described as related to ALS, the most common adult-onset motor neuron disorder. However, the pathological mechanism of PFN1 in ALS is not yet completely understood. The goal of this work is to thoroughly analyze the effects of the ALS-related mutations on PFN1 structure and function using computational simulations. Here, PhD-SNP, PMUT, PolyPhen-2, SIFT, SNAP, SNPS&GO, SAAP, nsSNPAnalyzer, SNPeffect4.0 and I-Mutant2.0 were used to predict the functional and stability effects of PFN1 mutations. ConSurf was used for the evolutionary conservation analysis, and GROMACS was used to perform the MD simulations. The mutations C71G, M114T, and G118V, but not E117G, were predicted as deleterious by most of the functional prediction algorithms that were used. The stability prediction indicated that the ALS-related mutations could destabilize PFN1. The ConSurf analysis indicated that the mutation C71G, M114T, E117G, and G118V occur in highly conserved positions. The MD results indicated that the studied mutations could affect the PFN1 flexibility at the actin and PLP-binding domains, and consequently, their intermolecular interactions. It may be therefore related to the functional impairment of PFN1 upon C71G, M114T, E117G and G118V mutations, and their involvement in ALS development. We also developed a database, SNPMOL (http://www.snpmol.org/), containing the results presented on this paper for biologists and clinicians to exploit PFN1 and its natural variants.

Fitness of unregulated human Ras mutants modeled by implementing computational mutagenesis and machine learning techniques

Ras proteins play a pivotal role as oncogenes by participating in diverse signaling events, including those linked to cell growth, differentiation, and proliferation. Using experimental fitness data and implementing artificial intelligence and a computational mutagenesis technique, we developed models that reliably predict fitness for all single residue mutants of H-ras proto-oncogene protein p21. The computational mutagenesis generated a feature vector of protein structural changes for each variant, and these data correlated well with fitness. Random forest classification and tree regression machine learning algorithms were implemented for training predictive models. Cross-validations were used to evaluate model performance, and control experiments were performed to assess statistical significance. Classification models revealed a balanced accuracy rate as high as 82%, with a Matthew's correlation of 0.63, and an area under ROC curve of 0.90. Similarly, regression models displayed Pearson's correlation reaching 0.79. On the other hand, control data sets led to performance values consistent with random guessing. Comparisons with several related state-of-the-art methods reflected favorably on our trained models. This H-Ras proof-of-principle study suggests a complementary approach for understanding mechanisms with which other proteins are involved in oncogenesis, including related Ras isoforms, and for providing useful insights into designing future diagnostic and treatment modalities.

In silico analysis of the V66M variant of human BDNF in psychiatric disorders: An approach to precision medicine

Brain-derived neurotrophic factor (BDNF) plays an important role in neurogenesis and synapse formation. The V66M is the most prevalent BDNF mutation in humans and impairs the function and distribution of BDNF. This mutation is related to several psychiatric disorders. The pro-region of BDNF, particularly position 66 and its adjacent residues, are determinant for the intracellular sorting and activity-dependent secretion of BDNF. However, it has not yet been fully elucidated. The present study aims to analyze the effects of the V66M mutation on BDNF structure and function. Here, we applied nine algorithms, including SIFT and PolyPhen-2, for functional and stability prediction of the V66M mutation. The complete theoretical model of BNDF was generated by Rosetta and validated by PROCHECK, RAMPAGE, ProSa, QMEAN and Verify-3D algorithms. Structural alignment was performed using TM-align. Phylogenetic analysis was performed using the ConSurf server. Molecular dynamics (MD) simulations were performed and analyzed using the GROMACS 2018.2 package. The V66M mutation was predicted as deleterious by PolyPhen-2 and SIFT in addition to being predicted as destabilizing by I-Mutant. According to SNPeffect, the V66M mutation does not affect protein aggregation, amyloid propensity, and chaperone binding. The complete theoretical structure of BDNF proved to be a reliable model. Phylogenetic analysis indicated that the V66M mutation of BDNF occurs at a non-conserved position of the protein. MD analyses indicated that the V66M mutation does not affect the BDNF flexibility and surface-to-volume ratio, but affects the BDNF essential motions, hydrogen-bonding and secondary structure particularly at its pre and pro-domain, which are crucial for its activity and distribution. Thus, considering that these parameters are determinant for protein interactions and, consequently, protein function; the alterations observed throughout the MD analyses may be related to the functional impairment of BDNF upon V66M mutation, as well as its involvement in psychiatric disorders.

Genotype-phenotype relations of the von Hippel-Lindau tumor suppressor inferred from a large-scale analysis of disease mutations and interactors

Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease.

Structural and Computational Characterization of Disease-Related Mutations Involved in Protein-Protein Interfaces

One of the known potential effects of disease-causing amino acid substitutions in proteins is to modulate protein-protein interactions (PPIs). To interpret such variants at the molecular level and to obtain useful information for prediction purposes, it is important to determine whether they are located at protein-protein interfaces, which are composed of two main regions, core and rim, with different evolutionary conservation and physicochemical properties. Here we have performed a structural, energetics and computational analysis of interactions between proteins hosting mutations related to diseases detected in newborn screening. Interface residues were classified as core or rim, showing that the core residues contribute the most to the binding free energy of the PPI. Disease-causing variants are more likely to occur at the interface core region rather than at the interface rim (p < 0.0001). In contrast, neutral variants are more often found at the interface rim or at the non-interacting surface rather than at the interface core region. We also found that arginine, tryptophan, and tyrosine are over-represented among mutated residues leading to disease. These results can enhance our understanding of disease at molecular level and thus contribute towards personalized medicine by helping clinicians to provide adequate diagnosis and treatments.

Loss of tubulin deglutamylase CCP1 causes infantile-onset neurodegeneration

A set of glutamylases and deglutamylases controls levels of tubulin polyglutamylation, a prominent post-translational modification of neuronal microtubules. Defective tubulin polyglutamylation was first linked to neurodegeneration in the Purkinje cell degeneration (pcd) mouse, which lacks deglutamylase CCP1, displays massive cerebellar atrophy, and accumulates abnormally glutamylated tubulin in degenerating neurons. We found biallelic rare and damaging variants in the gene encoding CCP1 in 13 individuals with infantile-onset neurodegeneration and confirmed the absence of functional CCP1 along with dysregulated tubulin polyglutamylation. The human disease mainly affected the cerebellum, spinal motor neurons, and peripheral nerves. We also demonstrate previously unrecognized peripheral nerve and spinal motor neuron degeneration in pcd mice, which thus recapitulated key features of the human disease. Our findings link human neurodegeneration to tubulin polyglutamylation, entailing this post-translational modification as a potential target for drug development for neurodegenerative disorders.

Molecular characterization of Axenfeld-Rieger spectrum and other anterior segment dysgeneses in a sample of Mexican patients

BACKGROUND

Anterior segment dysgenesis (ASD) and Axenfeld-Rieger spectrum (ARS) are mainly due to PITX2 and FOXC1 defects, but it is difficult in some patients to differentiate among PITX2-, FOXC1-, PAX6- and CYP1B1-related disorders. Here, we set out to characterize the pathogenic variants (PV) in PITX2, FOXC1, CYP1B1 and PAX6 in nine unrelated Mexican ARS/ASD patients and in their available affected/unaffected relatives.

MATERIALS AND METHODS

Automated Sanger sequencing of PITX2, FOXC1, PAX6 and CYP1B1 was performed; those patients without a PV were subsequently analyzed by Multiplex Ligation-dependent Probe Amplification (MLPA) for PITX2, FOXC1 and PAX6. Missense variants were evaluated with the MutPred, Provean, PMUT, SIFT, PolyPhen-2, CUPSAT and HOPE programs.

RESULTS

We identified three novel PV in PITX2 (NM_153427.2:c.217G>A, c.233T>C and c.279del) and two in FOXC1 [NM_001453.2:c.274C>T (novel) and c.454T>A] in five ARS patients. The previously reported FOXC1 c.367C>T or p.(Gln123*) variant was identified in a patient with ASD. The ocular phenotype related to FOXC1 included aniridia, corneal opacity and early onset glaucoma, while an asymmetric ocular phenotype and aniridia were associated with PITX2. No gene rearrangements were documented by MLPA analysis, nor were any PV identified in PAX6 or CYP1B1.

CONCLUSIONS

Heterozygous PV in the PITX2 and FOXC1 genes accounted for 66% (6/9) of the ARS/ASD cases. The absence of PAX6 or CYP1B1 abnormalities could reflect our small sample size, although their analysis could be justified in ARS/ASD patients that present with congenital glaucoma or aniridia.