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Saba Shahzadi

Publications and source records attributed to Saba Shahzadi.

3 recordsLinked to original sources

EWS-RNA Binding Protein 1: Structural Insights into Ewing Sarcoma by Conformational Dynamics Investigations.

BACKGROUND: Prior research has demonstrated that proteins play a significant role in the prognosis and treatments of various sarcomas, including Ewing sarcoma through the interplay of downstream signaling cascades. However, there is limited understanding about the strcucture conformation of EWSR1 and its structural implication in the prognosis of Ewsing Sarcoma by interaction with RNA molecules. AIMS: The primary goal of ongoing research is to determine how EWSR1 contributes to Ewing sarcoma. OBJECTIVE: The current study explores the complexity of EWSR1 structure and its conformational interactions with RNA in relation to Ewing sarcoma. METHODS: Here, we employed a comparative modeling approach to predict EWSR1 domains separately and assembled them into one structural unit using a DEMO server. Additionally, the RNA motifs interacting with EWSR1 were predicted, and the 3D model was built using RNAComposer. Protein-RNA docking and MD simulation studies were carried out to check the intermolecular interactions and stability behavior of docked EWSR1-RNA complexes. RESULTS: The overall results explore the structural insights into EWSR1 and their interactions with RNA, which may play a momentous role in co- and post-transcriptional regulation to control gene expression. CONCLUSION: Taken togather, our findings suggest that EWSR1 may be a useful therapeutic target for the diagnosis and management of Ewing sarcoma.

Sarcoma, Ewing

Prediction and Evaluation of Protein Aggregation with Computational Methods.

Protein and peptide aggregation has recently become one of the most studied biomedical problems due to its central role in several neurodegenerative disorders and of biotechnological importance. Multiple in silico methods, databases, tools, and algorithms have been developed to predict aggregation of proteins and peptides to better understand fundamental mechanisms of various aggregation diseases. Here, we attempt to provide a brief overview of bioinformatic methods and tools to better understand molecular mechanisms of aggregation disorders. Furthermore, through a better understanding of protein aggregation mechanisms, it might be possible to design novel therapeutic agents to treat and hopefully prevent protein aggregation diseases.

Computational Biology

A Glimpse of Noncoding RNAs: Secondary Structure, Emerging Trends, and Potential Applications in Human Diseases.

An appealing strategy for the treatment of several diseases is the therapeutic targeting of noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). Many antisense oligonucleotides and small interfering RNAs have been tested in clinical studies over the past 10 years, and several of these have received FDA approval. However, trial results have thus far been mixed, with some studies reporting strong effects and others showing low effectiveness or side effects, including toxicity. Clinical trials for alternative entities like antimiRNAs are underway, and interest in lncRNA-based therapies is constantly growing. From this perspective, we discuss the basic overview of ncRNAs, their significant role as therapeutic biomarkers against different diseases, and the role of secondary structure in noncoding RNAs.

Humans