Mutations in the KDM5C ARID Domain and Their Plausible Association with Syndromic Claes-Jensen-Type Disease

Domain architecture and protein-protein interactions regulate KDM5A recruitment to the chromatin

Tri-methylation of Histone 3 lysine 4 (H3K4) is an important epigenetic modification whose deposition and removal can affect the chromatin at structural and functional levels. KDM5A is one of the four known H3K4-specific demethylases. It is a part of the KDM5 family, which is characterized by a catalytic Jumonji domain capable of removing H3K4 di- and tri-methylation marks. KDM5A has been found to be involved in multiple cellular processes such as differentiation, metabolism, cell cycle, and transcription. Its link to various diseases, including cancer, makes KDM5A an important target for drug development. However, despite several studies outlining its significance in various pathways, our lack of understanding of its recruitment and function at the target sites on the chromatin presents a challenge in creating effective and targeted treatments. Therefore, it is essential to understand the recruitment mechanism of KDM5A to chromatin, and its activity therein, to comprehend how various roles of KDM5A are regulated. In this review, we discuss how KDM5A functions in a context-dependent manner on the chromatin, either directly through its structural domain, or through various interacting partners, to bring about a diverse range of functions.

Molecular and cellular events linking variants in the histone demethylase KDM5C to the intellectual disability disorder Claes-Jensen syndrome

The widespread availability of genetic testing for those with neurodevelopmental disorders has highlighted the importance of many genes necessary for the proper development and function of the nervous system. One gene found to be genetically altered in the X-linked intellectual disability disorder Claes-Jensen syndrome is KDM5C, which encodes a histone demethylase that regulates transcription by altering chromatin. While the genetic link between KDM5C and cognitive (dys)function is clear, how KDM5C functions to control transcriptional programs within neurons to impact their growth and activity remains the subject of ongoing research. Here, we review our current knowledge of Claes-Jensen syndrome and discuss important new data using model organisms that have revealed the importance of KDM5C in regulating aspects of neuronal development and function. Continued research into the molecular and cellular activities regulated by KDM5C is expected to provide critical etiological insights into Claes-Jensen syndrome and highlight potential targets for developing therapies to improve the quality of life of those affected.

Contribution of DNA methylation profiling to the reclassification of a variant of uncertain significance in the KDM5C gene

KDM5C encodes a demethylase of the histone H3 lysine 4 residue, involved in chromatin regulation and gene expression. Hemizygous KDM5C pathogenic variants cause X-linked intellectual disability of Claes-Jensen type. Because of its mode of inheritance and the low specificity of the clinical phenotype, interpretation of variants can be difficult, hence the need for functional studies and biomarkers specific to this disorder. We present the case of a male patient with intellectual disability, behavioral abnormalities and subtle dysmorphic features, in which genetic investigation identified a hemizygous novel missense KDM5C variant of uncertain significance (VUS), inherited from his asymptomatic mother and present in his paucisymptomatic sister. We assessed the global genomic DNA methylation status from a whole blood sample of the proband. Global DNA methylation profiling specifically identified the recently discovered epi-signature of Claes-Jensen syndrome. This result served as a biomarker which independently highlighted KDM5C as the cause of the disorder in this patient. Because of the X-linked mode of inheritance, variant reclassification had a high impact on genetic counseling in this family. This example highlights the value of global methylome profiling in situations of variants of uncertain significance in genes with a known specific epi-signature.

Reprogramming of the epigenome in neurodevelopmental disorders

The etiology of neurodevelopmental disorders (NDDs) remains a challenge for researchers. Human brain development is tightly regulated and sensitive to cellular alterations caused by endogenous or exogenous factors. Intriguingly, the surge of clinical sequencing studies has revealed that many of these disorders are monogenic and monoallelic. Notably, chromatin regulation has emerged as highly dysregulated in NDDs, with many syndromes demonstrating phenotypic overlap, such as intellectual disabilities, with one another. Here we discuss epigenetic writers, erasers, readers, remodelers, and even histones mutated in NDD patients, predicted to affect gene regulation. Moreover, this review focuses on disorders associated with mutations in enzymes involved in histone acetylation and methylation, and it highlights syndromes involving chromatin remodeling complexes. Finally, we explore recently discovered histone germline mutations and their pathogenic outcome on neurological function. Epigenetic regulators are mutated at every level of chromatin organization. Throughout this review, we discuss mechanistic investigations, as well as various animal and iPSC models of these disorders and their usefulness in determining pathomechanism and potential therapeutics. Understanding the mechanism of these mutations will illuminate common pathways between disorders. Ultimately, classifying these disorders based on their effects on the epigenome will not only aid in prognosis in patients but will aid in understanding the role of epigenetic machinery throughout neurodevelopment.

Emerging of lysine demethylases (KDMs): From pathophysiological insights to novel therapeutic opportunities

In recent years, there have been remarkable scientific advancements in the understanding of lysine demethylases (KDMs) because of their demethylation of diverse substrates, including nucleic acids and proteins. Novel structural architectures, physiological roles in the gene expression regulation, and ability to modify protein functions made KDMs the topic of interest in biomedical research. These structural diversities allow them to exert their function either alone or in complex with numerous other bio-macromolecules. Impressive number of studies have demonstrated that KDMs are localized dynamically across the cellular and tissue microenvironment. Their dysregulation is often associated with human diseases, such as cancer, immune disorders, neurological disorders, and developmental abnormalities. Advancements in the knowledge of the underlying biochemistry and disease associations have led to the development of a series of modulators and technical compounds. Given the distinct biophysical and biochemical properties of KDMs, in this review we have focused on advances related to the structure, function, disease association, and therapeutic targeting of KDMs highlighting improvements in both the specificity and efficacy of KDM modulation.

CoevDB: a database of intramolecular coevolution among protein-coding genes of the bony vertebrates

The study of molecular coevolution, due to its potential to identify gene regions under functional or structural constraints, has recently been subject to numerous scientific inquiries. Particular efforts have been conducted to develop methods predicting the presence of coevolution in molecular sequences. Among these methods, a few aim to model the underlying evolutionary process of coevolution, which enable to differentiate the shared history of genes to coevolution and thus improve their accuracy. However, the usage of such methods remains sparse due to their expensive computational cost and the lack of resources alleviating this issue. Here we present CoevDB (http://phylodb.unil.ch/CoevDB), a database containing the result of a large-scale analysis of intramolecular coevolution of 8201 protein-coding genes of bony vertebrates. The web interface of CoevDB gives access to the results to 800 millions of statistical tests corresponding to all the pairs of sites analyzed. Several type of queries enable users to explore the database by either targeting specific genes or by discovering genes having promising estimations of coevolution.

Computational chemistry methods to investigate the effects caused by DNA variants linked with disease

Computational chemistry offers variety of tools to study properties of biological macromolecules. These tools vary in terms of levels of details from quantum mechanical treatment to numerous macroscopic approaches. Here, we provide a review of computational chemistry algorithms and tools for modeling the effects of genetic variations and their association with diseases. Particular emphasis is given on modeling the effects of missense mutations on stability, conformational dynamics, binding, hydrogen bond network, salt bridges, and pH-dependent properties of the corresponding macromolecules. It is outlined that the disease may be caused by alteration of one or several of above-mentioned biophysical characteristics, and a successful prediction of pathogenicity requires detailed analysis of how the alterations affect the function of involved macromolecules. The review provides a short list of most commonly used algorithms to predict the molecular effects of mutations as well.

Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases

Structural information of biological macromolecules is crucial and necessary to deliver predictions about the effects of mutations-whether polymorphic or deleterious (i.e., disease causing), wherein, thermodynamic parameters, namely, folding and binding free energies potentially serve as effective biomarkers. It may be emphasized that the effect of a mutation depends on various factors, including the type of protein (globular, membrane or intrinsically disordered protein) and the structural context in which it occurs. Such information may positively aid drug-design. Furthermore, due to the intrinsic plasticity of proteins, even mutations involving radical change of the structural and physico⁻chemical properties of the amino acids (native vs. mutant) can still have minimal effects on protein thermodynamics. However, if a mutation causes significant perturbation by either folding or binding free energies, it is quite likely to be deleterious. Mitigating such effects is a promising alternative to the traditional approaches of designing inhibitors. This can be done by structure-based in silico screening of small molecules for which binding to the dysfunctional protein restores its wild type thermodynamics. In this review we emphasize the effects of mutations on two important biophysical properties, stability and binding affinity, and how structures can be used for structure-based drug design to mitigate the effects of disease-causing variants on the above biophysical properties.

Sex Chromosome Effects on Male-Female Differences in Mammals

Fundamental differences exist between males and females, encompassing anatomy, physiology, behaviour, and genetics. Such differences undoubtedly play a part in the well documented, yet poorly understood, disparity in disease susceptibility between the sexes. Although traditionally attributed to gonadal sex hormone effects, recent work has begun to shed more light on the contribution of genetics - and in particular the sex chromosomes - to these sexual dimorphisms. Here, we explore the accumulating evidence for a significant genetic component to mammalian sexual dimorphism through the paradigm of sex chromosome evolution. The differences between the extant X and Y chromosomes, at both a sequence and regulatory level, arose across 166 million years. A functional result of these differences is cell autonomous sexual dimorphism. By understanding the process that changed a pair of homologous ancestral autosomes into the extant mammalian X and Y, we believe it easier to consider the mechanisms that may contribute to hormone-independent male-female differences. We highlight key roles for genes with homologues present on both sex chromosomes, where the X-linked copy escapes X chromosome inactivation. Finally, we summarise current experimental paradigms and suggest areas for developments to further increase our understanding of cell autonomous sexual dimorphism in the context of health and disease.

Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver

Motivation

Protein-DNA interactions are essential for regulating many cellular processes, such as transcription, replication, recombination and translation. Amino acid mutations occurring in DNA-binding proteins have profound effects on protein-DNA binding and are linked with many diseases. Hence, accurate and fast predictions of the effects of mutations on protein-DNA binding affinity are essential for understanding disease-causing mechanisms and guiding plausible treatments.

Results

Here we report a new method Single Amino acid Mutation binding free energy change of Protein-DNA Interaction (SAMPDI). The method utilizes modified Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) approach along with an additional set of knowledge-based terms delivered from investigations of the physicochemical properties of protein-DNA complexes. The method is benchmarked against experimentally determined binding free energy changes caused by 105 mutations in 13 proteins (compiled ProNIT database and data from recent references), and results in correlation coefficient of 0.72.

Availability and implementation

http://compbio.clemson.edu/SAMPDI.

Contact

ealexov@clemson.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Histone Demethylase KDM5 Is Essential for Larval Growth in Drosophila

Regulated gene expression is necessary for developmental and homeostatic processes. The KDM5 family of transcriptional regulators are histone H3 lysine 4 demethylases that can function through both demethylase-dependent and -independent mechanisms. While loss and overexpression of KDM5 proteins are linked to intellectual disability and cancer, respectively, their normal developmental functions remain less characterized. Drosophila melanogaster provides an ideal system to investigate KDM5 function, as it encodes a single ortholog in contrast to the four paralogs found in mammalian cells. To examine the consequences of complete loss of KDM5, we generated a null allele of Drosophila kdm5, also known as little imaginal discs (lid), and show that it is essential for viability. Animals lacking KDM5 show a dramatically delayed larval development that coincides with decreased proliferation and increased cell death in wing imaginal discs. Interestingly, this developmental delay is independent of the well-characterized Jumonji C (JmjC) domain-encoded histone demethylase activity of KDM5, suggesting key functions for less characterized domains. Consistent with the phenotypes observed, transcriptome analyses of kdm5 null mutant wing imaginal discs revealed the dysregulation of genes involved in several cellular processes, including cell cycle progression and DNA repair. Together, our analyses reveal KDM5 as a key regulator of larval growth and offer an invaluable tool for defining the biological activities of KDM5 family proteins.

Computational Investigation of the Missense Mutations in DHCR7 Gene Associated with Smith-Lemli-Opitz Syndrome

Smith-Lemli-Opitz syndrome (SLOS) is a cholesterol synthesis disorder characterized by physical, mental, and behavioral symptoms. It is caused by mutations in 7-dehydroxycholesterolreductase gene (DHCR7) encoding DHCR7 protein, which is the rate-limiting enzyme in the cholesterol synthesis pathway. Here we demonstrate that pathogenic mutations in DHCR7 protein are located either within the transmembrane region or are near the ligand-binding site, and are highly conserved among species. In contrast, non-pathogenic mutations observed in the general population are located outside the transmembrane region and have different effects on the conformational dynamics of DHCR7. All together, these observations suggest that the non-classified mutation R228Q is pathogenic. Our analyses indicate that pathogenic effects may affect protein stability and dynamics and alter the binding affinity and flexibility of the binding site.

Cofactors-loaded quaternary structure of lysine-specific demethylase 5C (KDM5C) protein: Computational model

The KDM5C gene (also known as JARID1C and SMCX) is located on the X chromosome and encodes a ubiquitously expressed 1560-aa protein, which plays an important role in lysine methylation (specifically reverses tri- and di-methylation of Lys4 of histone H3). Currently, 13 missense mutations in KDM5C have been linked to X-linked mental retardation. However, the molecular mechanism of disease is currently unknown due to the experimental difficulties in expressing such large protein and the lack of experimental 3D structure. In this work, we utilize homology modeling, docking, and experimental data to predict 3D structures of KDM5C domains and their mutual arrangement. The resulting quaternary structure includes KDM5C JmjN, ARID, PHD1, JmjC, ZF domains, substrate histone peptide, enzymatic cofactors, and DNA. The predicted quaternary structure was investigated with molecular dynamic simulation for its stability, and further analysis was carried out to identify features measured experimentally. The predicted structure of KDM5C was used to investigate the effects of disease-causing mutations and it was shown that the mutations alter domain stability and inter-domain interactions. The structural model reported in this work could prompt experimental investigations of KDM5C domain-domain interaction and exploration of undiscovered functionalities. Proteins 2016; 84:1797-1809. © 2016 Wiley Periodicals, Inc.

SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations

Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach

Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. Availability: the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.