High-resolution melt curve analysis: An approach for variant detection in the TPO gene of congenital hypothyroid patients in Bangladesh

TPO (Thyroid Peroxidase) is known to be one of the major genes involved in congenital hypothyroid patients with thyroid dyshormonogenesis. The present study aims to validate high-resolution melting (HRM) curve analysis as a substitute method for Sanger sequencing, focusing on the frequently observed non-synonymous mutations c.1117G>T, c.1193G>C, and c.2173A>C in the TPO gene in patients from Bangladesh. We enrolled 36 confirmed cases of congenital hypothyroid patients with dyshormonogenesis to establish the HRM method. Blood specimens were collected, and DNA was extracted followed by PCR and Sanger sequencing. Among the 36 specimens, 20 were pre-sequenced, and variants were characterized through Sanger sequencing. Following pre-sequencing, the 20 pre-sequenced specimens underwent real-time PCR-HRM curve analysis to determine the proper HRM condition for separating the three variations from the wild-type state into heterozygous and homozygous states. Furthermore, 16 unknown specimens were subjected to HRM analysis to validate the method. This method demonstrated a sensitivity and specificity of 100 percent in accurately discerning wild-type alleles from both homozygous and heterozygous states of c.1117G>T (23/36; 63.8%), c.1193G>C (30/36; 83.3%), and c.2173A>C (23/36; 63.8%) variants frequently encountered among 36 Bangladeshi patients. The HRM data was found to be similar to the sequencing result, thus confirming the validity of the HRM approach for TPO gene variant detection. In conclusion, HRM-based molecular technique targeting variants c.1117G>T, c.1193G>C, and c.2173A>C could be used as a high throughput, rapid, reliable, and cost-effective screening approach for the detection of all common mutations in TPO gene in Bangladeshi patients with dyshormonogenesis.

Biological and clinical significance of the glypican-3 gene in human lung adenocarcinoma: An in silico analysis

Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan, has long been found to be dysregulated in human lung adenocarcinomas (LUADs). Nevertheless, the function, mutational profile, epigenetic regulation, co-expression profile, and clinicopathological significance of the GPC3 gene in LUAD progression are not well understood. In this study, we analyzed cancer microarray datasets from publicly available databases using bioinformatics tools to elucidate the above parameters. We observed significant downregulation of GPC3 in LUAD tissues compared to their normal counterparts, and this downregulation was associated with shorter overall survival (OS) and relapse-free survival (RFS). Nevertheless, no significant differences in the methylation pattern of GPC3 were observed between LUAD and normal tissues, although lower promoter methylation was observed in male patients. GPC3 expression was also found to correlate significantly with infiltration of B cells, CD8+, CD4+, macrophages, neutrophils, and dendritic cells in LUAD. In addition, a total of 11 missense mutations were identified in LUAD patients, and ~1.4% to 2.2% of LUAD patients had copy number amplifications in GPC3. Seventeen genes, mainly involved in dopamine receptor-mediated signaling pathways, were frequently co-expressed with GPC3. We also found 11 TFs and 7 miRNAs interacting with GPC3 and contributing to disease progression. Finally, we identified 3 potential inhibitors of GPC3 in human LUAD, namely heparitin, gemcitabine and arbutin. In conclusion, GPC3 may play an important role in the development of LUAD and could serve as a promising biomarker in LUAD.

Investigation of the impact of nonsynonymous mutations on thyroid peroxidase dimer

Congenital hypothyroidism is one of the most common preventable endocrine disorders associated with thyroid dysgenesis or dyshormonogenesis. Thyroid peroxidase (TPO) gene defect is mainly responsible for dyshormonogenesis; a defect in the thyroid hormone biosynthesis pathway. In Bangladesh, there is limited data regarding the genetic etiology of Congenital Hypothyroidism (CH). The present study investigates the impact of the detected mutations (p.Ala373Ser, and p.Thr725Pro) on the TPO dimer protein. We have performed sequential molecular docking of H2O2 and I- ligands with both monomers of TPO dimer to understand the iodination process in thyroid hormone biosynthesis. Understanding homodimer interactions at the atomic level is a critical challenge to elucidate their biological mechanisms of action. The docking results reveal that mutations in the dimer severely disrupt its catalytic interaction with essential ligands. Molecular dynamics simulation has been performed to validate the docking results, thus realizing the consequence of the mutation in the biological system's mimic. The dynamics results expose that mutations destabilize the TPO dimer protein. Finally, principal component analysis exhibits structural and energy profile discrepancies in wild-type and mutant dimers. The findings of this study highlight that the mutations in TPO protein can critically affect the dimer structure and loss of enzymatic activity is persistent. Other factors also might influence the hormone synthesis pathway, which is under investigation.

Molecular investigation of TSHR gene in Bangladeshi congenital hypothyroid patients

The disorder of thyroid gland development or thyroid dysgenesis accounts for 80-85% of congenital hypothyroidism (CH) cases. Mutations in the TSHR gene are mostly associated with thyroid dysgenesis, and prevent or disrupt normal development of the gland. There is limited data available on the genetic spectrum of congenital hypothyroid children in Bangladesh. Thus, an understanding of the molecular aetiology of thyroid dysgenesis is a prerequisite. The aim of the study was to investigate the effect of mutations in the TSHR gene on the small molecule thyrogenic drug-binding site of the protein. We identified two nonsynonymous mutations (p.Ser508Leu, p.Glu727Asp) in the exon 10 of the TSHR gene in 21 patients with dysgenesis by sequencing-based analysis. Later, the TSHR368-764 protein was modeled by the I-TASSER server for wild-type and mutant structures. The model proteins were targeted by thyrogenic drugs, MS437 and MS438 to perceive the effect of mutations. The damaging effect in drug-protein complexes of mutants was explored by molecular docking and molecular dynamics simulations. The binding affinity of wild-type protein was much higher than the mutant cases for both of the drug ligands (MS437 and MS438). Molecular dynamics simulates the dynamic behavior of wild-type and mutant complexes. MS437-TSHR368-764MT2 and MS438-TSHR368-764MT1 showed stable conformations in biological environments. Finally, Principle Component Analysis revealed structural and energy profile discrepancies. TSHR368-764MT1 exhibited much more variations than TSHR368-764WT and TSHR368-764MT2, emphasizing a more damaging pattern in TSHR368-764MT1. This genetic study might be helpful to explore the mutational impact on drug binding sites of TSHR protein which is important for future drug design and selection for the treatment of congenital hypothyroid children with dysgenesis.

Remdesivir analogs against SARS-CoV-2 RNA-dependent RNA polymerase

The COVID-19 pandemic has already taken many lives but is still continuing its spread and exerting jeopardizing effects. This study is aimed to find the most potent ligands from 703 analogs of remdesivir against RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus . RdRp is a major part of a multi-subunit transcription complex of the virus, which is essential for viral replication. In clinical trials, it has been found that remdesivir is effective to inhibit viral replication in Ebola and in primary human lung cell cultures; it effectively impedes replication of a broad-spectrum pre-pandemic bat coronaviruses and epidemic human coronaviruses. After virtual screening, 30 most potent ligands and remdesivir were modified with triphosphate. Quantum mechanics-based quantitative structure-activity relationship envisages the binding energy for ligands applying partial least square (PLS) regression. PLS regression remarkably predicts the binding energy of the effective ligands with an accuracy of 80% compared to the value attained from molecular docking. Two ligands (L4:58059550 and L28:126719083), which have more interactions with the target protein than the other ligands including standard remdesivir triphosphate, were selected for further analysis. Molecular dynamics simulation is done to assess the stability and dynamic nature of the drug-protein complex. Binding-free energy results via PRODIGY server and molecular mechanics/Poisson-Boltzmann surface area method depict that the potential and solvation energies play a crucial role. Considering all computational analysis, we recommend the best remdesivir analogs can be utilized for efficacy test through in vitro and in vivo trials against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Structure and dynamics of membrane protein in SARS-CoV-2

SARS-CoV-2 membrane (M) protein performs a variety of critical functions in virus infection cycle. However, the expression and purification of membrane protein structure is difficult despite tremendous progress. In this study, the 3 D structure is modeled followed by intensive validation and molecular dynamics simulation. The lack of suitable homologous templates (>30% sequence identities) leads us to construct the membrane protein models using template-free modeling (de novo or ab initio) approach with Robetta and trRosetta servers. Comparing with other model structures, it is evident that trRosetta (TM-score: 0.64; TM region RMSD: 2 Å) can provide the best model than Robetta (TM-score: 0.61; TM region RMSD: 3.3 Å) and I-TASSER (TM-score: 0.45; TM region RMSD: 6.5 Å). 100 ns molecular dynamics simulations are performed on the model structures by incorporating membrane environment. Moreover, secondary structure elements and principal component analysis (PCA) have also been performed on MD simulation data. Finally, trRosetta model is utilized for interpretation and visualization of interacting residues during protein-protein interactions. The common interacting residues including Phe103, Arg107, Met109, Trp110, Arg131, and Glu135 in the C-terminal domain of M protein are identified in membrane-spike and membrane-nucleocapsid protein complexes. The active site residues are also predicted for potential drug and peptide binding. Overall, this study might be helpful to design drugs and peptides against the modeled membrane protein of SARS-CoV-2 to accelerate further investigation. Communicated by Ramaswamy H. Sarma.

Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2

SARS-CoV-2 virus outbreak poses a major threat to humans worldwide due to its highly contagious nature. In this study, molecular docking, molecular dynamics, and structure-activity relationship are employed to assess the binding affinity and interaction of 76 prescription drugs against RNA dependent RNA polymerase (RdRp) and Main Protease (Mpro) of SARS-CoV-2. The RNA-dependent RNA polymerase is a vital enzyme of coronavirus replication/transcription complex whereas the main protease acts on the proteolysis of replicase polyproteins. Among 76 prescription antiviral drugs, four drugs (Raltegravir, Simeprevir, Cobicistat, and Daclatasvir) that are previously used for human immunodeficiency virus (HIV), hepatitis C virus (HCV), Ebola, and Marburg virus show higher binding energy and strong interaction with active sites of the receptor proteins. To explore the dynamic nature of the interaction, 100 ns molecular dynamics (MD) simulation is performed on the selected protein-drug complexes and apo-protein. Binding free energy of the selected drugs is performed by MM/PBSA. Besides docking and dynamics, partial least square (PLS) regression method is applied for the quantitative structure activity relationship to generate and predict the binding energy for drugs. PLS regression satisfactorily predicts the binding energy of the effective antiviral drugs compared to binding energy achieved from molecular docking with a precision of 85%. This study highly recommends researchers to screen these potential drugs in vitro and in vivo against SARS-CoV-2 for further validation of utility.