Molecular basis of R133C Rett syndrome

Rett syndrome is a debilitating autistic spectrum disorder affecting one in ten thousand girls. Patients develop normally for up to eighteen months before a period of regression involving stagnation in head growth, loss of speech, hand use and mobility. It is almost exclusively caused by mutation in Methyl CpG binding Protein 2 (MeCP2). MeCP2 has traditionally been thought of as a transcriptional repressor, although its exact function remains unknown and it has recently been shown that the protein can also bind to hydroxymethylation and non-CpG methylation, which occurs predominantly at CAC sites in the mature nervous system. Genotype-phenotype studies of the most common Rett-causing mutations in affected patients revealed that a missense mutation, R133C results in a milder form of Rett syndrome. The reasons for this are unclear, as the mutation lies right in the heart of the methylated DNA binding domain. Previous in vitro studies of R133C showed a severe deficit in binding to methylated cytosine. A subsequent study found that R133C binding to hydroxymethylated cytosine was specifically impaired, whereas binding to methylated cytosine was indistinguishable from wildtype. Defining the DNA binding impairment of MeCP2R133C would yield important insights into Rett disease pathophysiology and provide an explanation for the phenotypic spectrum seen in patients. To shed light on these matters, a novel mouse model of the R133C mutation was created. The R133C mouse had a phenotype that was less severe than other missense mutant mice, in terms of survival, growth, Rett-like phenotypic score and some behavioural paradigms thus recapitulating the patient data. At the molecular level in adult mouse brain, MeCP2R133C protein abundance was reduced. Immunohistochemistry showed that MeCP2R133C had an abnormal pattern of localisation in the nucleus of neurons. In vitro electrophoretic mobility shift assays suggested that MeCP2R133C binding to (hydroxy)methyl-CAC may be reduced to a greater extent than binding to mCpG. Chromatin immunoprecipitation experiments confirmed the deficit in binding to methylated sites and supported a disproportionate reduction in binding to methylation in a CAC sequence context. Analysis of adult mouse cerebellar gene expression revealed a subtle upregulation of long genes and downregulation of short genes. Based on these data, it is proposed that Rett syndrome caused by the R133C mutation results from a combination of protein instability and defective binding to methylated DNA. Methyl-CAC binding is potentially abolished. The downstream biological consequence of this is a length-dependent deregulation of gene expression in the brain

Modelling the Effects of Disease-Associated Single Amino Acid Variants and Rescuing the Effects by Small Molecules

Single nucleotide polymorphism (SNP) is a variation of a single nucleotide in the genome. Some of these variations can cause a change of single amino acid in the corresponding protein, resulting in single amino acid variation (SAV). SAVs can lead to profound alterations of the corresponding biological processes and thus can be associated with many human diseases. This dissertation focuses on integration of existing and development of new computational approaches to model the effects of SAVs with the goal to reveal molecular mechanism of human diseases. Since proton transfer and pKa shifts are frequently attributed to disease causality, the proton transfers in the protein-nucleic acid interactions are investigated and along with development of a new computational approach to predict the SAV’s effect on the protein-DNA binding affinity. The SAVs in four proteins: Lysine-specific demethylase 5C (KDM5C), Spermine Synthase (SpmSyn), 7-Dehydrocholesterol reductase (DHCR7) and methyl CpG binding protein 2 (MeCP2) are extensively studied using numerous computational approaches to reveal molecular details of disease-associated effects. In case of MeCP2 protein, the effects of the most commonly occurring disease-causing mutation, R133C, was targeted by structure-based virtual screening to identify the small molecules potentially to rescue the malfunctioning R133C mutant

Modeling Electrostatics in Molecular Biology and Its Relevance With Molecular Mechanisms of Diseases

Electrostatics plays an essential role in molecular biology. Modeling electrostatics in molecular biology is complicated due to the water phase, mobile ions, and irregularly shaped inhomogeneous biological macromolecules. This dissertation presents the popular DelPhi package that solves PBE and delivers the electrostatic potential distribution of biomolecules. We used the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase and demonstrated that the first-principles method could also model the binding. This dissertation also reflects the use of existing computational approaches to model the effects of Single Amino Acid Variations (SAVs) to reveal molecular mechanisms related to human diseases. We used our supervised in-house combinatory in-silico predictor method to investigate the impact of unclassified missense mutations in the MEN1 gene found in breast cancer tissue. We also examined the biophysical and biochemical properties to predict the effects of these missense variants on the menin protein stability and interactions. The results are compared with the impact of known pathogenic mutations in menin causing neoplasia. In the end, we showed the role of intravesicular pH in melanosome maturation and formation. The computational investigation was done to understand the pH-dependent stability of several membrane proteins and compared them to the pH dependence of the strength of TYR. We confirmed that the pH optimum of TYR is neutral. Our findings are consistent with previous work that demonstrated a correlation between the pH optima of stability and activity

Structural, Dynamical, and Energetical Consequences of Rett Syndrome Mutation R133C in MeCP2

Rett Syndrome (RTT) is a progressive neurodevelopmental disease affecting females. RTT is caused by mutations in the MECP2 gene and various amino acid substitutions have been identified clinically in different domains of the multifunctional MeCP2 protein encoded by this gene. The R133C variant in the methylated-CpG-binding domain (MBD) of MeCP2 is the second most common disease-causing mutation in the MBD. Comparative molecular dynamics simulations of R133C mutant and wild-type MBD have been performed to understand the impact of the mutation on structure, dynamics, and interactions of the protein and subsequently understand the disease mechanism. Two salt bridges within the protein and two critical hydrogen bonds between the protein and DNA are lost upon the R133C mutation. The mutation was found to weaken the interaction with DNA and also cause loss of helicity within the 141-144 region. The structural, dynamical, and energetical consequences of R133C mutation were investigated in detail at the atomic resolution. Several important implications of this have been shown regarding protein stability and hydration dynamics as well as its interaction with DNA. The results are in agreement with previous experimental studies and further provide atomic level understanding of the molecular origin of RTT associated with R133C variant