Protein-protein interaction analysis of distinct molecular pathways in two subtypes of colorectal carcinoma

Complex harmonic regularization with differential evolution in a memetic framework for biomarker selection

For studying cancer and genetic diseases, the issue of identifying high correlation genes from high-dimensional data is an important problem. It is a great challenge to select relevant biomarkers from gene expression data that contains some important correlation structures, and some of the genes can be divided into different groups with a common biological function, chromosomal location or regulation. In this paper, we propose a penalized accelerated failure time model CHR-DE using a non-convex regularization (local search) with differential evolution (global search) in a wrapper-embedded memetic framework. The complex harmonic regularization (CHR) can approximate to the combination ℓp(12≤p<1) and ℓ_q (1 ≤ q < 2) for selecting biomarkers in group. And differential evolution (DE) is utilized to globally optimize the CHR’s hyperparameters, which make CHR-DE achieve strong capability of selecting groups of genes in high-dimensional biological data. We also developed an efficient path seeking algorithm to optimize this penalized model. The proposed method is evaluated on synthetic and three gene expression datasets: breast cancer, hepatocellular carcinoma and colorectal cancer. The experimental results demonstrate that CHR-DE is a more effective tool for feature selection and learning prediction.

Molecular activities and ligand-binding specificities of StAR-related lipid transfer domains: exploring integrated in silico methods and ensemble-docking approaches

In this study, cholesterol biotransformation gene-set of human steroidogenic acute regulatory protein-related lipid transfer (START) domains were evaluated from high-throughput gene screening approaches. It was shown that STARD1, STARD3 and STARD4 proteins are better effective transporters of cholesterol than STARD5 and STARD6 domains. Docking studies show a strong agreement with gene ontology enrichment data. According to both complementary strategies, it was found that only STARD1, STARD3 and STARD4 are potentially involved in cholesterol biotransformation in mitochondria through Ω1-loop of C-terminal α4-helical domain. Ensemble docking assessment for a set of selected chemicals of protein-chemical networks has shown possible binding probabilities with START domains. Among those, reproductive toxicity evoked drugs (mifepristone), insecticides (rotenone), tobacco pulmonary carcinogens (benzo(a)pyrene) and endocrine disruptor chemicals (EDCs) including perfluorooctanesulfonic acid (PFOS) and aflatoxin B₁ (AFB₁) potentially bound with novel hotspot residues of the α4-helical domain. Compound representation space and clustering approaches reveal that the START proteins show more sensitivity with these lead scaffolds, so they could provide probable barrier assets in cholesterol and steroidogenic acute regulatory (StAR) binding and leads adverse consequences in steroidogenesis. These findings indicate potential START domains and their binding levels with toxic chemicals; sorted viewpoints could be useful as a promising way to identify chemicals with related steroidogenisis impacts on human health.

Intrinsic Disorder in Proteins with Pathogenic Repeat Expansions

Intrinsically disordered proteins and proteins with intrinsically disordered regions have been shown to be highly prevalent in disease. Furthermore, disease-causing expansions of the regions containing tandem amino acid repeats often push repetitive proteins towards formation of irreversible aggregates. In fact, in disease-relevant proteins, the increased repeat length often positively correlates with the increased aggregation efficiency and the increased disease severity and penetrance, being negatively correlated with the age of disease onset. The major categories of repeat extensions involved in disease include poly-glutamine and poly-alanine homorepeats, which are often times located in the intrinsically disordered regions, as well as repeats in non-coding regions of genes typically encoding proteins with ordered structures. Repeats in such non-coding regions of genes can be expressed at the mRNA level. Although they can affect the expression levels of encoded proteins, they are not translated as parts of an affected protein and have no effect on its structure. However, in some cases, the repetitive mRNAs can be translated in a non-canonical manner, generating highly repetitive peptides of different length and amino acid composition. The repeat extension-caused aggregation of a repetitive protein may represent a pivotal step for its transformation into a proteotoxic entity that can lead to pathology. The goals of this article are to systematically analyze molecular mechanisms of the proteinopathies caused by the poly-glutamine and poly-alanine homorepeat expansion, as well as by the polypeptides generated as a result of the microsatellite expansions in non-coding gene regions and to examine the related proteins. We also present results of the analysis of the prevalence and functional roles of intrinsic disorder in proteins associated with pathological repeat expansions.

Hypothyroidism Side Effect in Patients Treated with Sunitinib or Sorafenib: Clinical and Structural Analyses

Tyrosine kinase inhibitors (TKIs) provide more effective targeted treatments for cancer, but are subject to a variety of adverse effects, such as hypothyroidism. TKI-induced hypothyroidism is a highly complicated issue, because of not only the unrealized toxicological mechanisms, but also different incidences of individual TKI drugs. While sunitinib is suspected for causing thyroid dysfunction more often than other TKIs, sorafenib is believed to be less risky. Here we integrated clinical data and in silico drug-protein interactions to examine the pharmacological distinction between sunitinib and sorafenib. Statistical analysis on the FDA Adverse Event Reporting System (FAERS) confirmed that sunitinib is more concurrent with hypothyroidism than sorafenib, which was observed in both female and male patients. Then, we used docking method and identified 3 proteins specifically binding to sunitinib but not sorafenib, i.e., retinoid X receptor alpha, retinoic acid receptors beta and gamma. As potential off-targets of sunitinib, these proteins are well known to assemble with thyroid hormone receptors, which can explain the profound impact of sunitinib on thyroid function. Taken together, we established a strategy of integrated analysis on clinical records and drug off-targets, which can be applied to explore the molecular basis of various adverse drug reactions.