Computational methods for prediction and classification of G protein-coupled receptors

G protein-coupled receptors (GPCRs) constitute the largest group of membrane receptor proteins in eukaryotes. Due to their significant roles in many physiological processes such as vision, smell, and inflammation, GPCRs are the targets of many prescribed drugs. However, the functional and structural diversity of GPCRs has kept their prediction and classification based on amino acid sequence data as a challenging bioinformatics problem. As existing computational methods to predict and classify GPCRs are focused on mammalian (mostly human) data, the ultimate goal of our project is to establish an ensemble approach and implement a web-based software that can be used reliably on a wider range of organisms. As a first step, we have constructed a searchable MySQL database with experimentally confirmed GPCRs and non-GPCRs along with protein features for distinguishing them. This database currently contains 2887 GPCR and 1614 non-GPCR sequences collected from the UniProtKB/Swiss-Prot protein database, covering over 300 species including arthropods, fungi, nematode, etc. Each protein in the database is assigned a unique identification number and linked to information about its source organism, sequence lengths, and other features including amino acid and dipeptide composition. For the GPCRs, family classifications according to the popular GRAFS and IUPHAR systems are also included. This database will provide the training and testing data for subsequent steps in our ongoing work to evaluate existing computational tools, incorporate them into our ensemble, and apply them to identify potential GPCRs in several fly, mosquito, and tick species that are of biomedical or agricultural importance

GPCR-PEnDB: A Database Of Protein Sequences And Derived Features To Facilitate Prediction And Classification Of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) constitute the largest group of membrane receptor proteins in eukaryotes. Due to their significant roles in various physiological processes such as vision, smell, and inflammation, GPCRs are the targets of many prescription drugs. However, the functional and sequence diversity of GPCRs has kept their prediction and classification based on amino acid sequence data as a challenging bioinformatics problem. There are existing computational approaches, mainly using machine learning and statistical methods, to predict and classify GPCRs based on amino acid sequence and sequence derived features. In this project, we have constructed a searchable MySQL database, named GPCR-PEnDB (GPCR Prediction Ensemble Database), of confirmed GPCRs and non-GPCRs with the goal of allowing users to conveniently access useful information of GPCRs in a wide range of organisms and to compile reliable training and testing datasets for different combinations of computational tools. GPCR-PEnDB currently contains 3129 confirmed GPCR and 3575 non-GPCR sequences collected from the UniProtKB/Swiss-Prot protein database, encompassing over 1200 species. The non-GPCR entries include transmembrane proteins for evaluating various prediction programs\u27 abilities to distinguish GPCRs from other transmembrane proteins. Each protein is linked to information about its source organism, classification, sequence lengths and composition, and other derived sequence features. Compared to GPCRdb, which is considered the most comprehensive GPCR resource available, our database contains much fewer GPCR sequences because of our requirement for every GPCR to be confirmed. Nevertheless, our database contains 1094 GPCRs not found in GPCRdb. In particular, all of the class D and E GPCRs and many of Class A sensory receptors are missing from GPCRdb. I will present several examples of using this GPCR-PEnDB along with its graphical user interface to query for GPCRs with specific sequence properties and to compare the prediction accuracies of GPCR prediction tools. This initial version of GPCR-PEnDB will provide a framework for future extensions to include additional sequence features, three-dimensional structural data, and ligand binding information to facilitate the design and assessment of GPCR prediction and classification tools as well as experimental studies to help understand the functional roles of various types of GPCRs

What Makes GPCRs from Different Families Bind to the Same Ligand?

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs

Phytomedicines of traditional health-care professionals in the vicinity of Lawachara Forest Reserve, Moulvibazar district, Bangladesh

An ethnomedicinal survey was carried out among traditional health-care professionals practicing in the vicinity of Lawachara Forest Reserve in Sreemangal sub-district of Moulvibazar district, Bangladesh. Interviews were carried out with two practitioners who dispensed various medicinal plants to various tribal group and mainstream community members residing in the area. The two practitioners were observed to use a total of 43 plants distributed into 32 families for treatment of various diseases. The diseases treated included respiratory tract disorders, pain, gastrointestinal disorders, skin diseases, hair loss, hypertension, diabetes, rheumatic fever, dengue fever, jaundice, cuts and wounds, snake bite, urinary troubles, heart disorders, anemia, sexual disorders, and liver disorders. The formulations used were simple; plants or plant parts were orally taken or topically applied in the form of juice, direct chewing, and cooking followed by oral partaking of the cooked plants. The plants used for treatment of diabetes, rheumatic fever, dengue fever, heart and liver disorders merit special attention from scientists for they can form the basis of new drugs towards treatment of these diseases. Since gastrointestinal disorders and various types of pain are common disorders, scientific validation of plants used to treat these diseases can prove to be beneficial to the rural folks who lack access or cannot afford allopathic medicines

Differential Expression of Non-Coding RNA Signatures in Thyroid Cancer between Two Ethnic Groups

Filipino Americans show higher thyroid cancer recurrence rates compared to European Americans. Although they are likely to die of this malignancy, the molecular mechanism has not yet been determined. Recent studies demonstrated that small non-coding RNAs could be utilized to assess thyroid cancer prognosis in tumor models. The goal of this study is to determine whether microRNA (miRNA) signatures are differentially expressed in thyroid cancer in two different ethnic groups. We also determined whether these miRNA signatures are related to cancer staging. This is a retrospective study of archival samples from patients with thyroid cancer (both sexes) in the pathology division from the last ten years at Loma Linda University School of Medicine, California. Deidentified patient demographics were extracted from the patient chart. Discarded formalin-fixed paraffin-embedded tissues were collected post-surgeries. We determined the differential expressions of microRNA in archival samples from Filipino Americans compared to European Americans using the state-of-the-art technique, HiSeq4000. By ingenuity pathway analysis, we determined miRNA targets and the pathways that those targets are involved in. We validated their expressions by real-time quantitative PCR and correlated them with the clinicopathological status in a larger cohort of miRNA samples from both ethnicities. We identified the differentially upregulated/downregulated miRNA clusters in Filipino Americans compared to European Americans. Some of these miRNA clusters are known to target genes that are linked to cancer invasion and metastasis. In univariate analysis, ethnicity and tumor staging were significant factors predicting miR-4633-5p upregulation. When including these factors in a multivariate logistic regression model, ethnicity and tumor staging remained significant independent predictors of miRNA upregulation, whereas the interaction of ethnicity and tumor staging was not significant. In contrast, ethnicity remained an independent predictor of significantly downregulated miR-491-5p and let-7 family. We provide evidence that Filipino Americans showed differentially expressed tumor-tissue-derived microRNA clusters. The functional implications of these miRNAs are under investigation

Treatment with benznidazole and pentoxifylline regulates microRNA transcriptomic profile in a murine model of Chagas chronic cardiomyopathy.

Chronic Chagas cardiomyopathy (CCC) is one of the leading causes of morbidity and mortality due to cardiovascular disorders in endemic areas of Chagas disease (CD), a neglected tropical illness caused by the protozoan parasite Trypanosoma cruzi. CCC is characterized by parasite persistence and inflammatory response in the heart tissue, which occur parallel to microRNA (miRNA) alterations. Here, we investigated the miRNA transcriptome profiling in the cardiac tissue of chronically T. cruzi-infected mice treated with a suboptimal dose of benznidazole (Bz), the immunomodulator pentoxifylline alone (PTX), or the combination of both (Bz+PTX), following the CCC onset. At 150 days post-infection, Bz, PTX, and Bz+PTX treatment regimens improved electrocardiographic alterations, reducing the percentage of mice afflicted by sinus arrhythmia and second-degree atrioventricular block (AVB2) when compared with the vehicle-treated animals. miRNA Transcriptome profiling revealed considerable changes in the differential expression of miRNAs in the Bz and Bz+PTX treatment groups compared with the control (infected, vehicle-treated) group. The latter showed pathways related to organismal abnormalities, cellular development, skeletal muscle development, cardiac enlargement, and fibrosis, likely associated with CCC. Bz-Treated mice exhibited 68 differentially expressed miRNAs related to signaling pathways like cell cycle, cell death and survival, tissue morphology, and connective tissue function. Finally, the Bz+PTX-treated group revealed 58 differentially expressed miRNAs associated with key signaling pathways related to cellular growth and proliferation, tissue development, cardiac fibrosis, damage, and necrosis/cell death. The T. cruzi-induced upregulation of miR-146b-5p, previously shown in acutely infected mice and in vitro T. cruzi-infected cardiomyocytes, was reversed upon Bz and Bz+PTX treatment regimens when further experimentally validated. Our results further our understanding of molecular pathways related to CCC progression and evaluation of treatment response. Moreover, the differentially expressed miRNAs may serve as drug targets, associated molecular therapy, or biomarkers of treatment outcomes

Identification of a Potent Cytotoxic Pyrazole with Anti-Breast Cancer Activity That Alters Multiple Pathways

In this study, we identified a novel pyrazole-based derivative (P3C) that displayed potent cytotoxicity against 27 human cancer cell lines derived from different tissue origins with 50% cytotoxic concentrations (CC50) in the low micromolar and nanomolar range, particularly in two triple-negative breast cancer (TNBC) cell lines (from 0.25 to 0.49 µM). In vitro assays revealed that P3C induces reactive oxygen species (ROS) accumulation leading to mitochondrial depolarization and caspase-3/7 and -8 activation, suggesting the participation of both the intrinsic and extrinsic apoptotic pathways. P3C caused microtubule disruption, phosphatidylserine externalization, PARP cleavage, DNA fragmentation, and cell cycle arrest on TNBC cells. In addition, P3C triggered dephosphorylation of CREB, p38, ERK, STAT3, and Fyn, and hyperphosphorylation of JNK and NF-kB in TNBC cells, indicating the inactivation of both p38MAPK/STAT3 and ERK1/2/CREB signaling pathways. In support of our in vitro assays, transcriptome analyses of two distinct TNBC cell lines (MDA-MB-231 and MDA-MB-468 cells) treated with P3C revealed 28 genes similarly affected by the treatment implicated in apoptosis, oxidative stress, protein kinase modulation, and microtubule stability

Genomic characterisation of breast fibroepithelial lesions in an international cohort

Fibroepithelial lesions (FELs) are a heterogeneous group of tumours comprising fibroadenomas (FAs) and phyllodes tumours (PTs). Here we used a 16-gene panel that was previously discovered to be implicated in pathogenesis and progression, to characterise a large international cohort of FELs via targeted sequencing. The study comprised 303 (38%) FAs and 493 (62%) PTs which were contributed by the International Fibroepithelial Consortium. There were 659 (83%) Asian and 109 (14%) non-Asian FELs, while the ethnicity of the rest was unknown. Genetic aberrations were significantly associated with increasing grade of PTs, and were detected more in PTs than FAs for MED12, TERT promoter, RARA, FLNA, SETD2, TP53, RB1, EGFR, and IGF1R. Most borderline and malignant PTs possessed ≥ 2 mutations, while there were more cases of FAs with ≤ 1 mutation compared to PTs. FELs with MED12 mutations had significantly higher rates of TERT promoter, RARA, SETD2, EGFR, ERBB4, MAP3K1, and IGF1R aberrations. However, FELs with wild-type MED12 were more likely to express TP53 and PIK3CA mutations. There were no significant differences observed between the mutational profiles of recurrent FAs, FAs with a history of subsequent ipsilateral recurrence or contralateral occurrence, and FAs without a history of subsequent events. We identified recurrent mutations which were more frequent in PTs than FAs, with borderline and malignant PTs harbouring cancer driver gene and multiple mutations. This study affirms the role of a set of genes in FELs, including its potential utility in classification based on mutational profiles