Computational approaches for identifying disease-causing mutations in proteins

Advancements in genome sequencing have expanded the scope of investigating mutations in proteins across different diseases. Amino acid mutations in a protein alter its structure, stability and function and some of them lead to diseases. Identification of disease-causing mutations is a challenging task and it will be helpful for designing therapeutic strategies. Hence, mutation data available in the literature have been curated and stored in several databases, which have been effectively utilized for developing computational methods to identify deleterious mutations (drivers), using sequence and structure-based properties of proteins. In this chapter, we describe the contents of specific databases that have information on disease-causing and neutral mutations followed by sequence and structure-based properties. Further, characteristic features of disease-causing mutations will be discussed along with computational methods for identifying cancer hotspot residues and disease-causing mutations in proteins.

Structural basis for inhibition of a GH116 β-glucosidase and its missense mutants by GBA2 inhibitors: Crystallographic and quantum chemical study

The crystal structure of the Thermoanaerobacterium xylanolyticum in glycoside hydrolase family 116 (TxGH116) β-glucosidase provides a structural model for human GBA2 glucosylceramidase, an enzyme defective in hereditary spastic paraplegia and a potential therapeutic target for treating Gaucher disease. To assess the therapeutic potential of known inhibitors, the X-ray structure of TxGH116 in complex with isofagomine (IFG) was determined at 2.0 Å resolution and showed the IFG bound in a relaxed chair conformation. The binding of IFG and 7 other iminosugar inhibitors to wild-type and mutant enzymes (Asp508His and Arg786His) mimicking GBA2 pathogenic variants was then evaluated computationally by two-layered ONIOM calculations (at the B3LYP:PM7 level). Calculations showed that six charged residues, Glu441, Asp452, His507, Asp593, Glu777, and Arg786 influence inhibitor binding most. His507, Glu777 and Arg786, form strong hydrogen bonds with the inhibitors (∼1.4-1.6 Å). Thus, the missense mutation of one of these residues in Arg786His has a greater effect on the interaction energies for all inhibitors compared to Asp508His. In line with the experimental data for the inhibitors that have been tested, the favorable interaction energy between the inhibitors and the TxGH116 protein followed the trend: isofagomine > 1-deoxynojirimycin > glucoimidazole > N-butyl-deoxynojirimycin ≈ N-nonyl-deoxynojirimycin > conduritol B epoxide ≈ azepane 1 > azepane 2. The obtained structural and energetic properties and comparison to the GBA2 model can lead to understanding of structural requirement for inhibitor binding in GH116 to aid the design of high potency GBA2 inhibitors.

Functional and structural impact of 10 ACADM missense mutations on human medium chain acyl-Coa dehydrogenase

Medium chain acyl-CoA dehydrogenase (MCAD) deficiency (MCADD) is associated with ACADM gene mutations, leading to an impaired function and/or structure of MCAD. Importantly, after import into the mitochondria, MCAD must incorporate a molecule of flavin adenine dinucleotide (FAD) per subunit and assemble into tetramers. However, the effect of MCAD amino acid substitutions on FAD incorporation has not been investigated. Herein, the commonest MCAD variant (p.K304E) and 11 additional rare variants (p.Y48C, p.R55G, p.A88P, p.Y133C, p.A140T, p.D143V, p.G224R, p.L238F, p.V264I, p.Y372N, and p.G377V) were functionally and structurally characterized. Half of the studied variants presented a FAD content <65 % compared to the wild-type. Most of them were recovered as tetramers, except the p.Y372N (mainly as dimers). No correlation was found between the levels of tetramers and FAD content. However, a correlation between FAD content and the cofactor's affinity, proteolytic stability, thermostability, and thermal inactivation was established. We showed that the studied amino acid changes in MCAD may alter the substrate chain-length dependence and the interaction with electron-transferring-flavoprotein (ETF) necessary for a proper functioning electron transfer thus adding additional layers of complexity to the pathological effect of ACADM missense mutations. Although the majority of the variant MCADs presented an impaired capacity to retain FAD during their synthesis, some of them were structurally rescued by cofactor supplementation, suggesting that in the mitochondrial environment the levels and activity of those variants may be dependent of FAD's availability thus contributing for the heterogeneity of the MCADD phenotype found in patients presenting the same genotype.

Evaluation of performance of leading algorithms for variant pathogenicity predictions and designing a combinatory predictor method: application to Rett syndrome variants

Background

Genomics diagnostic tests are done for a wide spectrum of complex genetics conditions such as autism and cancer. The growth of technology has not only aided in successfully decoding the genetic variants that causes or trigger these disorders. However, interpretation of these variants is not a trivial task even at a level of distinguish pathogenic vs benign variants.

Methods

We used the clinically significant variants from ClinVar database to evaluate the performance of 14 most popular in-silico predictors using supervised learning methods. We implemented a feature selection and random forest classification algorithm to identify the best combination of predictors to evaluate the pathogenicity of a variant. Finally, we have also utilized this combination of predictors to reclassify the variants of unknown significance in MeCP2 gene that are associated with the Rett syndrome.

Results

The results from analysis shows an optimized selection of prediction algorithm and developed a combinatory predictor method. Our combinatory approach of using both best performing independent and ensemble predictors reduces any algorithm biases in variant characterization. The reclassification of variants (such as VUS) in MECP2 gene associated with RETT syndrome suggest that the combinatory in-silico predictor approach had a higher success rate in categorizing their pathogenicity.

Modeling three-dimensional genomic organization in evolution and pathogenesis

The regulation of gene expression is mediated via the complex three-dimensional (3D) conformation of the genetic material and its interactions with various intracellular factors. Various experimental and computational approaches have been developed in recent years for understating the relation between the 3D conformation of the genome and the phenotypes of cells in normal condition and diseases. In this review, we will discuss novel approaches for analyzing and modeling the 3D genomic conformation, focusing on deciphering disease-causing mutations that affect gene expression. We conclude that as this is a very challenging mission, an important direction should involve the comparative analysis of various 3D models from various organisms or cells.

The six metal binding domains in human copper transporter, ATP7B: molecular biophysics and disease-causing mutations

Wilson Disease (WD) is a hereditary genetic disorder, which coincides with a dysfunctional copper (Cu) metabolism caused by mutations in ATP7B, a membrane-bound P1B-type ATPase responsible for Cu export from hepatic cells. The N-terminal part (~ 600 residues) of the multi-domain 1400-residue ATP7B constitutes six metal binding domains (MBDs), each of which can bind a copper ion, interact with other ATP7B domains as well as with different proteins. Although the ATP7B's MBDs have been investigated in vitro and in vivo intensively, it remains unclear how these domains modulate overall structure, dynamics, stability and function of ATP7B. The presence of six MBDs is unique to mammalian ATP7B homologs, and many WD causing missense mutations are found in these domains. Here, we have summarized previously reported in vitro biophysical data on the MBDs of ATP7B and WD point mutations located in these domains. Besides the demonstration of where the research field stands today, this review showcasts the need for further biophysical investigation about the roles of MBDs in ATP7B function. Molecular mechanisms of ATP7B are important not only in the development of new WD treatment but also for other aspects of human physiology where Cu transport plays a role.

Structural and functional analyses of Barth syndrome-causing mutations and alternative splicing in the tafazzin acyltransferase domain

Tafazzin is a mitochondrial phospholipid transacylase, and its mutations cause Barth syndrome (BTHS). Human tafazzin gene produces four distinct alternatively spliced transcripts. To understand the molecular mechanisms of tafazzin deficiency, we performed an atomic resolution analysis of the influence of the BTHS mutations and of alternative splicing on the structure and function of tafazzin. From the three-dimensional (3D) homology modeling of tafazzin, we identified candidate amino acid residues that contribute to cardiolipin binding and to mitochondrial membrane associations that facilitate acyl-transfer reactions. Primate specific exon 5, which is alternatively spliced, is predicted to correspond to an intrinsically unstructured region in the protein. We proposed that this region should change the substrate-binding affinity and/or contribute to primate-specific molecular interactions. Exon 7, another alternatively spliced exon, encodes a region forming a part of the putative substrate-binding cleft, suggesting that the gene products lacking exon 7 will lose their substrate-binding ability. We demonstrate a clear localization of the BTHS mutations at residues responsible for membrane association, substrate binding, and the conformational stability of tafazzin. These findings provide new insights into the function of defective tafazzin and the pathogenesis of BTHS at the level of protein 3D structure and the evolution of alternatively spliced exons in primates.