Exploring the impact of circular RNA on ALS progression: A systematic review.

Amyotrophic lateral sclerosis is a neurodegenerative disease that damages motor neurons and causes gradual muscular weakening and paralysis. Although studies have linked a number of genetic and environmental factors to ALS, the specific causes and mechanisms of the disease are still unclear. The pivotal role of circular RNA in the pathogenesis of ALS is a newly emerging area of research. The term "circular RNA" describes a particular class of RNA molecule that, in contrast to most RNA molecules, has a closed-loop structure. According to recent research, circular RNA might be essential for the development and progression of ALS. It has been discovered that these circular RNAs support important cellular functions related to ALS, including protein turnover, mitochondrial function, RNA processing, and cellular transport. Gaining knowledge about the precise roles and processes of circular RNA in the development of ALS could assist in understanding the pathophysiology of the disease and possibly pave the way for the development of targeted therapies. However, the understanding of circular RNA in ALS is still limited, and more research is needed to fully elucidate its role. In order to gain a comprehensive understanding of the role of circRNAs in ALS, it is imperative to delve into the various mechanisms through which circRNAs may contribute to the development and progression of the disease. Examining the current status of circRNA research in ALS and offering insights into their potential as therapeutic targets and diagnostic markers are the primary objectives of this review.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions.

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Computational identification and molecular dynamics simulation of potential circularRNA derived peptide from gene expression profile of Rheumatoid arthritis, Alzheimer's disease, and Atrial fibrillation.

The two most serious global health challenges confronting human society today are autoimmune disorders (AIDs) and neurological diseases (NDs), both of which shorten people's lives and worsen the situation. Despite their extensive impact, statistics show that AIDs is associated with a higher risk of ND. Circular RNAs (circRNAs) are critical in several illnesses and disorders, especially AID and ND. Therefore, the present study focused on understanding the underlying causes of the pathophysiology of diseases such as AID and ND through in silico-based research. In order to determine how circRNAs are related to various disease pathways, this study examined the gene expression data sets for Rheumatoid arthritis (RA), Alzheimer's disease (AD), and atrial fibrillation (AF). Our study identified and analyzed two circRNAs, their respective host genes (DHTKD1 and RAN) and their related miRNAs, which could serve as potential markers for treating disorders like myotonic dystrophy type 1, spinocerebellar ataxia and fragile X syndrome. Further, the circRNA-derived peptide was identified and analysed with the molecular dynamics simulation (MDS) followed by a principal component (PC) based free energy landscape (FEL) profile. The computational results obtained here provide a basis for the development of therapeutics against AD, RA and AF. Moreover, further functional studies are needed to validate their role in disease aetiology and to provide a detailed understanding of their association with AID and ND.Communicated by Ramaswamy H. Sarma.

HighlightsSignificant circular RNAs associated with autoimmune disorders and neurological diseases are identifiedIdentified circular RNAs and their host genes (DHTKD1 and RAN) impacted multiple disease pathwaysThe stability of circularRNA-derived peptide was checked with MD simulation followed by PCA-based FEL analysisThe potential of circular RNAs as biomarkers or therapeutic targets for human diseases was highlighted.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB.

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.