Insights into AlphaFold's breakthrough in neurodegenerative diseases.

Neurodegenerative diseases (ND) are disorders of the central nervous system (CNS) characterized by impairment in neurons' functions, and complete loss, leading to memory loss, and difficulty in learning, language, and movement processes. The most common among these NDs are Alzheimer's disease (AD) and Parkinson's disease (PD), although several other disorders also exist. These are frontotemporal dementia (FTD), amyotrophic lateral syndrome (ALS), Huntington's disease (HD), and others; the major pathological hallmark of NDs is the proteinopathies, either of amyloid-ß (Aß), tauopathies, or synucleinopathies. Aggregation of proteins that do not undergo normal configuration, either due to mutations or through some disturbance in cellular pathway contributes to the diseases. Artificial Intelligence (AI) and deep learning (DL) have proven to be successful in the diagnosis and treatment of various congenital diseases. DL approaches like AlphaFold (AF) are a major leap towards success in CNS disorders. This 3D protein geometry modeling algorithm developed by DeepMind has the potential to revolutionize biology. AF has the potential to predict 3D-protein confirmation at an accuracy level comparable to experimentally predicted one, with the additional advantage of precisely estimating protein interactions. This breakthrough will be beneficial to identify diseases' advancement and the disturbance of signaling pathways stimulating impaired functions of proteins. Though AlphaFold has solved a major problem in structural biology, it cannot predict membrane proteins-a beneficial approach for drug designing.

Multi-omic analysis of dysregulated pathways in triple negative breast cancer.

The aggressive characteristics of triple-negative breast cancer (TNBC) and the absence of targeted medicines make TNBC a challenging clinical case. The molecular landscape of TNBC has been well-understood thanks to recent developments in multi-omic analysis, which have also revealed dysregulated pathways and possible treatment targets. This review summarizes the utilization of multi-omic approaches in elucidating TNBC's complex biology and therapeutic avenues. Dysregulated pathways including cell cycle progression, immunological modulation, and DNA damage response have been uncovered in TNBC by multi-omic investigations that integrate genomes, transcriptomics, proteomics, and metabolomics data. Methods like this pave the door for the discovery of new therapeutic targets, such as the EGFR, PARP, and mTOR pathways, which in turn direct the creation of more precise treatments. Recent developments in TNBC treatment strategies, including immunotherapy, PARP inhibitors, and antibody-drug conjugates, show promise in clinical trials. Emerging biomarkers like MUC1, YB-1, and immune-related markers offer insights into personalized treatment approaches and prognosis prediction. Despite the strengths of multi-omic analysis in offering a more comprehensive view and personalized treatment strategies, challenges exist. Large sample sizes and ensuring high-quality data remain crucial for reliable findings. Multi-omic analysis has revolutionized TNBC research, shedding light on dysregulated pathways, potential targets, and emerging biomarkers. Continued research efforts are imperative to translate these insights into improved outcomes for TNBC patients.

Gene expression and transcriptional regulation driven by transcription factors involved in congenital heart defects.

BACKGROUND: Congenital heart disease (CHD) is one of the most important birth defects caused by more than one mutated gene. Mutations in the genes could cause different types of congenital heart defects including atrial septal defect (ASD), tetralogy of Fallot (TOF), and ventricular septal defect (VSD). OBJECTIVES: Cardiac transcription factors are key players for heart development and are actively involved in controlling stress regulation of the heart. Transcription factors are sequence-specific DNA binding proteins that control the process of transcription and work in a synergistic manner. We aim to characterize core cardiac transcription factors including NKX2-5, TBX, SRF, GATA4, and MEF2, which encode homeobox and MADS domain and play a crucial role in heart development. METHODS: In this study, we have explored the important transcription factors involved in cardiac development and genes controlling the expression and regulation process by using the bioinformatics approach. RESULTS: We have predicted the orthologs and homologs based on their evolutionary history, conserved protein domains, functional sites, and 3D structures for better understanding and presentation of factors responsible for causing CHD. Results showed the importance of these transcription factors for normal heart functioning and development. CONCLUSION: Understanding the molecular pathways and genetic basis of CHD will help to open a new door for the treatment of patients with cardiac defects.

Computational insights into missense mutations in HTT gene causing Huntington's disease and its interactome networks.

BACKGROUND: Huntington's disease is a rare neurodegenerative illness of the central nervous system that is inherited in an autosomal dominant pattern. Mutant huntingtin protein is produced as a result of enlargement of CAG repeat in the N-terminal of the polyglutamine tract. AIM OF THE STUDY: Herein, we aim to investigate the mutations and their effects on the HTT gene and its genetic variants. Additionally, the protein-protein interaction of HTT with other proteins and receptor-ligand interaction with the three-dimensional structure of huntingtin protein were identified. METHODS: A comprehensive analysis of the HTT interactome and protein-ligand interaction has been carried out to provide a global picture of structure-function analysis of huntingtin protein. Mutations were analyzed and mutation verification tools were used to check the effect of mutation on protein function. RESULTS: The results showed, mutations in a single gene are not only responsible for causing a particular disease but may also cause other hereditary disorders as well. Moreover, the modification at the nucleotide level also cause the change in the specific amino acid which may disrupt the function of HTT and its interacting proteins contributing in disease pathogenesis. Furthermore, the interaction between MECP2 and BDNF lowers the rate of transcriptional activity. Molecular docking further confirmed the strong interaction between MECP2 and BDNF with highest affinity. Amino acid residues of the HTT protein, involved in the interaction with tetrabenazine were N912, Y890, G2385, and V2320. These findings proved, tetrabenazine as one of the potential therapeutic agent for treatment of Huntington's disease. CONCLUSION: These results give further insights into the genetics of Huntington's disease for a better understanding of disease models which will be beneficial for the future therapeutic studies.

Heterologous expression, molecular studies and biochemical characterization of a novel alkaline esterase gene from Bacillus thuringiensis for detergent industry.

Present study was aimed to clone and express the esterase encoding gene from Bacillus thuringiensis in E. coli BL21. Purification of recombinant esterase enzyme was achieved up to 48.6 purification folds by ion exchange chromatography with specific activity of 126.36 U mg-1. Molecular weight of esterase enzyme was 29 kDa as measured by SDS-PAGE. Purified esterase enzyme showed stability up to 90% at 90 °C and remained stable in a wide pH range (8-11). Molecular docking strengthens the experimental results by showing the higher binding energy with p-NP-butyrate. Enzyme activity was found to be reduced by EDTA but enhanced in the presence of other metal ions. Enzyme activity was reduced with 1% SDS, PMSF, and urea but organic solvents did not show considerable impact on it even at higher concentrations. Purified recombinant esterase was also found to be compatible with commercial laundry detergents and showed very good stability (up to 90%). All these properties proved the esterase enzyme from B. thuringensis a significant addition in detergent industry.

Insilico study of genes involved in Congenital Hypothyroidism.

OBJECTIVE: To study the orthologs of the five genes of congenital hypothyroidism NIS, PAX8, DUOX2, FOXE1, NKX2-1 that are involved in the development of the thyroid gland. METHODS: The study was conducted at INMOL Cancer Hospital, Lahore in September 2017 and comprised of finding gene orthologs, phylogenetic tree and domains of NIS, PAX8, DUOX2, FOXE1, NKX2-1 which were studied using different bioinformatics tools, including FASTA, BLAST, ENSEMBL, UniProt, MultiAlin, to find out the important domains involved in the mutations of these genes. RESULTS: Genes showed consensus sequence / motifs involved in congenital hypothyroidism. Phylogenetic results showed that these genes shared some common motifs. Phylogenetic trees revealed sub-clusters with high protein homology. CONCLUSIONS: Genes involved in congenital hypothyroidism were found to have a consensus sequence motifs.

The PTI to ETI Continuum in Phytophthora-Plant Interactions.

Phytophthora species are notorious pathogens of several economically important crop plants. Several general elicitors, commonly referred to as Pathogen-Associated Molecular Patterns (PAMPs), from Phytophthora spp. have been identified that are recognized by the plant receptors to trigger induced defense responses in a process termed PAMP-triggered Immunity (PTI). Adapted Phytophthora pathogens have evolved multiple strategies to evade PTI. They can either modify or suppress their elicitors to avoid recognition by host and modulate host defense responses by deploying hundreds of effectors, which suppress host defense and physiological processes by modulating components involved in calcium and MAPK signaling, alternative splicing, RNA interference, vesicle trafficking, cell-to-cell trafficking, proteolysis and phytohormone signaling pathways. In incompatible interactions, resistant host plants perceive effector-induced modulations through resistance proteins and activate downstream components of defense responses in a quicker and more robust manner called effector-triggered-immunity (ETI). When pathogens overcome PTI-usually through effectors in the absence of R proteins-effectors-triggered susceptibility (ETS) ensues. Qualitatively, many of the downstream defense responses overlap between PTI and ETI. In general, these multiple phases of Phytophthora-plant interactions follow the PTI-ETS-ETI paradigm, initially proposed in the zigzag model of plant immunity. However, based on several examples, in Phytophthora-plant interactions, boundaries between these phases are not distinct but are rather blended pointing to a PTI-ETI continuum.