Resources and tools for rare disease variant interpretation

: Collectively, rare genetic disorders affect a substantial portion of the world's population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis

Studio delle relazioni tra alimentazione e stati fisiopatologici mediante un approccio di biologia dei sistemi

2014-2015Lifestyle and food choices have an important role in the onset and in the prevention of some diseases. The assumption of some food-related molecules can have different effects on human health; for example, the antioxidants can lower the risk of some diseases, while the mycotoxins, contaminants of cereals and milk, could be involved in the rise of Autism Spectrum Disorders in genetically predisposed patients. The aim of this project was to identify possible protein targets for both mycotoxins and antioxidants, and to understand the mechanisms of actions underlying their effects. Protein targets were searched through a reverse docking approach using idTarget web-server. Subsequently, molecular docking using AutoDock 4.2 between the ligands (mycotoxins and antioxidants) and each of the selected protein targets was performed, in order to identify their binding sites. The interactions between mycotoxins and possible protein targets with good predicted energies were selected in order to validate them experimentally by means of techniques such as fluorescence techniques and MST. The interactions between antioxidants and possible protein targets with good predicted energies were selected to perform functional analysis via bioinformatics tools. The fluorescence techniques confirm that some mycotoxins bind the Acetylcholinesterase and Neuroligin-4, X linked, which is involved in Autism disease. The functional analysis results about the protein targets of the antioxidants suggests that chemopreventive effects of antioxidants in human pathologies, in particular for colon cancer, may be related to the possible interference of these molecules with the activity of nucleotide metabolism and methylation enzymes, similarly to some classes of anticancer drugs.[edited by Autor]XIV n.s

Predicting the stability of mutant proteins by computational approaches: an overview

A very large number of computational methods to predict the change in thermodynamic stability of proteins due to mutations have been developed during the last 30 years, and many different web servers are currently available. Nevertheless, most of them suffer from severe drawbacks that decrease their general reliability and, consequently, their applicability to different goals such as protein engineering or the predictions of the effects of mutations in genetic diseases. In this review, we have summarized all the main approaches used to develop these tools, with a survey of the web servers currently available. Moreover, we have also reviewed the different assessments made during the years, in order to allow the reader to check directly the different performances of these tools, to select the one that best fits his/her needs, and to help naïve users in finding the best option for their needs

Computational methods to assist in the discovery of pharmacological chaperones for rare diseases

Pharmacological chaperones are chemical compounds able to bind proteins and stabilize them against denaturation and following degradation. Some pharmacological chaperones have been approved, or are under investigation, for the treatment of rare inborn errors of metabolism, caused by genetic mutations that often can destabilize the structure of the wild-type proteins expressed by that gene. Given that, for rare diseases, there is a general lack of pharmacological treatments, many expectations are poured out on this type of compounds. However, their discovery is not straightforward. In this review, we would like to focus on the computational methods that can assist and accelerate the search for these compounds, showing also examples in which these methods were successfully applied for the discovery of promising molecules belonging to this new category of pharmacologically active compounds

Performance of Web tools for predicting changes in protein stability caused by mutations

Background Despite decades on developing dedicated Web tools, it is still difficult to predict correctly the changes of the thermodynamic stability of proteins caused by mutations. Here, we assessed the reliability of five recently developed Web tools, in order to evaluate the progresses in the field. Results The results show that, although there are improvements in the field, the assessed predictors are still far from ideal. Prevailing problems include the bias towards destabilizing mutations, and, in general, the results are unreliable when the mutation causes a Delta Delta G within the interval +/- 0.5 kcal/mol. We found that using several predictors and combining their results into a consensus is a rough, but effective way to increase reliability of the predictions. Conclusions We suggest all developers to consider in their future tools the usage of balanced data sets for training of predictors, and all users to combine the results of multiple tools to increase the chances of having correct predictions about the effect of mutations on the thermodynamic stability of a protein

The evolution of a Web resource: The Galactosemia Proteins Database 2.0

Galactosemia Proteins Database 2.0 is a Web-accessible resource collecting information about the structural and functional effects of the known variations associated to the three different enzymes of the Leloir pathway encoded by the genes GALT, GALE, and GALK1 and involved in the different forms of the genetic disease globally called â\u80\u9cgalactosemia.â\u80\u9d It represents an evolution of two available online resources we previously developed, with new data deriving from new structures, new analysis tools, and new interfaces and filters in order to improve the quality and quantity of information available for different categories of users. We propose this new resource both as a landmark for the entire world community of galactosemia and as a model for the development of similar tools for other proteins object of variations and involved in human diseases

Standardizing macromolecular structure files: further efforts are needed

: Investigating large datasets of biological information by automatic procedures may offer chances of progress in knowledge. Recently, tremendous improvements in structural biology have allowed the number of structures in the Protein Data Bank (PDB) archive to increase rapidly, in particular those for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated proteins. However, their automatic analysis can be hampered by the nonuniform descriptors used by authors in some records of the PDB and PDBx/mmCIF files. In this opinion article we highlight the difficulties encountered in automating the analysis of hundreds of structures, suggesting that further standardization of the description of these molecular entities and of their attributes, generalized to the macromolecular structures contained in the PDB, might generate files more suitable for automatized analyses of a large number of structures

Analysis of the Structure-Function-Dynamics Relationships of GALT Enzyme and of Its Pathogenic Mutant p.Q188R: A Molecular Dynamics Simulation Study in Different Experimental Conditions

The third step of the catabolism of galactose in mammals is catalyzed by the enzyme galactose-1-phosphate uridylyltransferase (GALT), a homodimeric enzyme with two active sites located in the proximity of the intersubunit interface. Mutations of this enzyme are associated to the rare inborn error of metabolism known as classic galactosemia; in particular, the most common mutation, associated with the most severe phenotype, is the one that replaces Gln188 in the active site of the enzyme with Arg (p.Gln188Arg). In the past, and more recently, the structural effects of this mutation were deduced on the static structure of the wild-type human enzyme; however, we feel that a dynamic view of the proteins is necessary to deeply understand their behavior and obtain tips for possible therapeutic interventions. Thus, we performed molecular dynamics simulations of both wild-type and p.Gln188Arg GALT proteins in the absence or in the presence of the substrates in different conditions of temperature. Our results suggest the importance of the intersubunit interactions for a correct activity of this enzyme and can be used as a starting point for the search of drugs able to rescue the activity of this enzyme in galactosemic patients