Deciphering the miRNA-mRNA Interaction Landscape between Breast Cancer and Triple-Negative Breast Cancer: An Integrated Bioinformatics Approach.

Breast cancer (BC) is globally recognized as the second most prevalent form of cancer. It predominantly affects women and can be categorized into distinct types based on the overexpression of specific cancer receptors.The key receptors implicated in this context are the human epidermal growth factor receptor-2 (HER2), estrogen receptor (ER), and progesterone receptor (PR), alongside a particularly intricate subclass known as triple-negative breast cancer (TNBC). This subclassification is critical for the stratification of breast cancer and informs therapeutic decision-making processes. Due to a lack of therapeutic targets, such as growth factor receptors, TNBC is the most aggressive type. Hence, identifying targetable regulators such as miRNAs could pave the way for potential therapeutic interventions. To identify common differentially expressed mRNAs (DE-mRNAs) in BC, including TNBC, we leveraged two data sets from the GEO collection and The Cancer Genome Atlas (TCGA). Significant DE-mRNAs were identified through PPI, MCODE, CytoNCA, and CytoHubba analyses. Following this, miRNAs were predicted using mirDIP. We utilized GSE42568, GSE185645, and TCGA and identified 159 common DE-mRNAs. Using Cytoscape plug-ins, we identified the 10 most significant DE-mRNAs in BC. Using mirDIP, target miRNAs for 10 DE-mRNAs were identified. We conducted an advanced analysis on the TNBC GEO data set (GSE45498) to corroborate the significance of shared DE-mRNAs and DE-miRNAs in TNBC. We identified four downregulated DE-miRNAs, including hsa-miR-802, hsa-miR-1258, hsa-miR-548a-3p, and hsa-miR-2053, significantly associated with TNBC. Our study revealed significant miRNA-mRNA interactions, specifically hsa-miR-802/MELK, hsa-miR-1258/NCAPG, miR-548a-3p/CCNA2, and hsa-miR-2053/NUSAP1, in both BC and TNBC. The observed downregulation of hsa-miR-548a-3p is associated with diminished survival rates in BC patients, emphasizing their potential utility as prognostic indicators. Furthermore, the differential expression of mRNAs, including CCNB2, UBE2C, MELK, and KIF2C, correlates with reduced survival outcomes, signifying their critical role as potential targets for therapeutic intervention in both BC and TNBC. These findings highlight specific regulatory mechanisms that are potentially crucial for understanding and treating these cancer types.

A new horizon in the phosphorylated sites of AGA: the structural impact of C163S mutation in aspartylglucosaminuria through molecular dynamics simulation.

Aspartylglucosaminuria (AGU) is a lysosomal storage disorder caused by insufficient aspartylglucosaminidase (AGA) activity leading to chronic neurodegeneration. We utilized the PhosphoSitePlus tool to identify the AGA protein's phosphorylation sites. The phosphorylation was induced on the specific residue of the three-dimensional AGA protein, and the structural changes upon phosphorylation were studied via molecular dynamics simulation. Furthermore, the structural behaviour of C163S mutation and C163S mutation with adjacent phosphorylation was investigated. We have examined the structural impact of phosphorylated forms and C163S mutation in AGA. Molecular dynamics simulations (200 ns) exposed patterns of deviation, fluctuation, and change in compactness of Y178 phosphorylated AGA protein (Y178-p), T215 phosphorylated AGA protein (T215-p), T324 phosphorylated AGA protein (T324-p), C163S mutant AGA protein (C163S), and C163S mutation with Y178 phosphorylated AGA protein (C163S-Y178-p). Y178-p, T215-p, and C163S mutation demonstrated an increase in intramolecular hydrogen bonds, leading to greater compactness of the AGA forms. Principle component analysis (PCA) and Gibbs free energy of the phosphorylated/C163S mutation structures exhibit transition in motion/orientation than Wild type (WT). T215-p may be more dominant among these than the other studied phosphorylated forms. It might contribute to hydrolyzing L-asparagine functioning as an asparaginase, thereby regulating neurotransmitter activity. This study revealed structural insights into the phosphorylation of Y178, T215, and T324 in AGA protein. Additionally, it exposed the structural changes of the C163S mutation and C163S-Y178-p of AGA protein. This research will shed light on a better understanding of AGA's phosphorylated mechanism.Communicated by Ramaswamy H. Sarma.

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease.

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP + + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

Identification of potential inhibitor targeting KRAS mutation in Papillary Thyroid Carcinoma through molecular docking and dynamic simulation analysis.

Thyroid cancer is a predominant form of endocrine malignancy, which destabilizes the metabolic rate of the body. The rapid increase in the incidence rate of thyroid cancer in recent years has aroused great concern to be investigated and diagnosed at an early stage. This study aimed to analyze the pathogenic mutations in thyroid cancer to identify their potential inhibitors for therapeutic targets. RAS genes are the most common oncogenes, which encode proteins that play an essential role in cell signaling and have been frequently mutated in different cancer types. The mutation in these genes causes abnormal cell growth and fails to respond to death signals. In this study, we identified the most significant mutations in the RAS genes; thus, the highly pathogenic mutations were curated from thyroid cancer patients and analyzed for their pathogenicity effect. The physicochemical analysis predicted mutation in wild-type KRAS protein had adapted negative charge on single base substitution of G12D that may easily cause loss of interactions and result in critical differences in the structure and function of the protein. Furthermore, the native KRAS protein was mutated and screened against a library of druggable compounds from the ZINC drug repository. The molecular docking analysis revealed that G12D mutant KRAS protein form best-docked complex with Naldemedine with the highest binding affinity. The dynamic simulation results further justified the stability of Naldemedine as a potential inhibitor with high efficiency in MMPBSA value of -45.4867 kcal/mol of being treated as a potential drug for papillary thyroid carcinoma. Further in vivo and in vitro validation of Naldemedine and its efficiency as a drug for the targeted pathogenic KRAS mutation is required.

Biomineralization associated alkaline phosphatase as a potential marker of bone metastasis in the patients with invasive breast cancer.

Breast Cancer is the most predominant form of cancer among women worldwide. It has been rigorously studied for biomarker identifications and therapeutic targets. However, various potential genes and their clinical relevance to breast cancer remain unexplored. The heterogeneity of breast cancer is one of the major challenges in early detection. Several studies have reported the significant role of alkaline phosphate (ALP) in the regulation of tumor growth and overall free survival in the pathogenesis of different cancer, including breast cancer which may offer unique therapeutic targets. Therefore, these findings demand a comprehensive study for the biogenesis of ALP genes. This study aims to expression profiling of alkaline phosphate genes in breast cancer and to identify the key pathways and molecular mechanisms underlying breast cancer proliferation and progression. In this study, the transcriptome profiling of invasive breast carcinoma samples was performed and analyzed. We identified that all the ALP genes were downregulated in both Invasive Lobular and Invasive Ductal Carcinoma patients. To understand the underlying molecular mechanism and the clinical significance for these genes in breast cancer, the expression values of genes were measured in adjacent normal and tumor tissues of patients followed by network analysis and functional enrichment analysis. The overall analysis revealed the highly aberrant expression of ALPL gene among all four ALP genes. We identified the functional significance of RUNX2 and WNT3A in deregulating ALPL. Therefore, our findings suggests that downregulation of ALPL could be a potential marker gene for invasive breast carcinoma progression towards bone metastasis.

A computational overview on phylogenetic characterization, pathogenic mutations, and drug targets for Ebola virus disease.

The World Health Organization declared Ebola virus disease (EVD) as the major outbreak in the 20th century. EVD was first identified in 1976 in South Sudan and the Democratic Republic of the Congo. EVD was transmitted from infected fruit bats to humans via contact with infected animal body fluids. The Ebola virus (EBOV) has a genome size of ∼18,959 bp. It encodes seven distinct proteins: nucleoprotein (NP), glycoprotein (GP), viral proteins VP24, VP30, VP35, matrix protein VP40, and polymerase L is considered a prime target for potential antiviral strategies. The current US FDA-approved anti-EVD vaccine, ERVERBO, and the other equally effective anti-EBOV combinations of three fully human monoclonal antibodies such as REGN-EB3, primarily target the envelope glycoprotein. This work elaborates on the EBOV's phylogenetic structure and the crucial mutations associated with viral pathogenicity.

A systemic approach to explore the mechanisms of drug resistance and altered signaling cascades in extensively drug-resistant tuberculosis.

BACKGROUND AND AIM: The persistence of extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis (MTB) continue to pose a significant challenge to the treatment and control of tuberculosis infections worldwide. XDR-MTB strains exhibit resistance against first-line anti-TB drugs, fluoroquinolones, and second-line injectable drugs. The mechanisms of drug resistance of MTB remains poorly understood. Our study aims at identifying the differentially expressed genes (DEGs), associated gene networks, and signaling cascades involved in rendering this pathogen resistant to multiple drugs, namely, isoniazid, rifampicin, and capreomycin. METHODS: We used the microarray dataset GSE53843. The GEO2R tool was used to prioritize the most significant DEGs (top 250) of each drug exposure sample between XDR strains and non-resistant strains. The validation of the 250 DEGs was performed using volcano plots. Protein-protein interaction networks of the DEGs were created using STRING and Cytoscape tools, which helped decipher the relationship between these genes. The significant DEGs were functionally annotated using DAVID and ClueGO. The concomitant biological processes (BP) and molecular functions (MF) were represented as dot plots. RESULTS AND CONCLUSION: We identified relevant molecular pathways and biological processes, such as cell wall biogenesis, lipid metabolic process, ion transport, phosphopantetheine binding, and triglyceride lipase activity. These processes indicated the involvement of multiple interconnected mechanisms in drug resistance. Our study highlighted the impact of cell wall permeability, with the dysregulation of the mur family of proteins, as essential factors in the inference of resistance. Additionally, upregulation of genes responsible for ion transport such as ctpF, arsC, and nark3, emphasizes the importance of transport channels and efflux pumps in potentially driving out stress-inducing compounds. This study investigated the upregulation of the Lip family of proteins, which play a crucial role in triglyceride lipase activity. Thereby illuminating the potential role of drug-induced dormancy and subsequent resistance in the mycobacterial strains. Multiple mechanisms such as carboxylic acid metabolic process, NAD biosynthetic process, triglyceride lipase activity, phosphopantetheine binding, organic acid biosynthetic process, and growth of symbiont in host cell were observed to partake in resistance of XDR-MTB. This study ultimately provides a platform for important mapping targets for potential therapeutics against XDR-MTB.

Identification of marker genes in Alzheimer's disease using a machine-learning model.

Alzheimer's Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.

Decoding Conformational Imprint of Convoluted Molecular Interactions Between Prenylflavonoids and Aggregated Amyloid-Beta42 Peptide Causing Alzheimer's Disease.

Protein misfolding occurs due to the loss of native protein structure and adopts an abnormal structure, wherein the misfolded proteins accumulate and form aggregates, which result in the formation of amyloid fibrils that are associated with neurodegenerative diseases. Amyloid beta (Aß42) aggregation or amyloidosis is contemplated as a unique hallmark characteristic of Alzheimer's disease (AD). Due to aberrant accrual and aggregation of Aß42 in extracellular space, the formation of senile plaques is found in AD patients. These senile plaques occur usually in the cognitive and memory region of the brain, enfeebles neurodegeneration, hinders the signaling between synapse, and disrupts neuronal functioning. In recent years, herbal compounds are identified and characterized for their potential as Aß42 inhibitors. Thus, understanding their structure and molecular mechanics can provide an incredible finding in AD therapeutics. To describe the structure-based molecular studies in the rational designing of drugs against amyloid fibrils, we examined various herbal compounds that belong to prenylflavonoids. The present study characterizes the trends we identified at molecular docking studies and dynamics simulation where we observed stronger binding orientation of bavachalcone, bavachin, and neobavaisoflavone with the amyloid-beta (Aß42) fibril structure. Hence, we could postulate that these herbal compounds could be potential inhibitors of Aß42 fibrils; these anti-aggregation agents need to be considered in treating AD.

Understanding the structure-function relationship of HPRT1 missense mutations in association with Lesch-Nyhan disease and HPRT1-related gout by in silico mutational analysis.

The nucleotide salvage pathway is used to recycle degraded nucleotides (purines and pyrimidines); one of the enzymes that helps to recycle purines is hypoxanthine guanine phosphoribosyl transferase 1 (HGPRT1). Therefore, defects in this enzyme lead to the accumulation of DNA and nucleotide lesions and hence replication errors and genetic disorders. Missense mutations in hypoxanthine phosphoribosyl transferase 1 (HPRT1) are associated with deficiencies such as Lesch-Nyhan disease and chronic gout, which have manifestations such as arthritis, neurodegeneration, and cognitive disorders. In the present study, we collected 88 non-synonymous single nucleotide polymorphisms (nsSNPs) from the UniProt, dbSNP, ExAC, and ClinVar databases. We used a series of sequence-based and structure-based in silico tools to prioritize and characterize the most pathogenic and stabilizing or destabilizing nsSNPs. Moreover, to obtain the structural impact of the pathogenic mutations, we mapped the mutations to the crystal structure of the HPRT protein. We further subjected these mutant proteins to a 50 ns molecular dynamics simulation (MDS). The MDS trajectory showed that all mutant proteins altered the structural conformation and dynamic behavior of the HPRT protein and corroborated its association with LND and gout. This study provides essential information regarding the use of HPRT protein mutants as potential targets for therapeutic development.

A comparative computational approach toward pharmacological chaperones (NN-DNJ and ambroxol) on N370S and L444P mutations causing Gaucher's disease.

Gaucher's disease (GD) is the most commonly known lysosomal disorder that occurs due to mutations in the ß-glucocerebrosidase (GBA) protein. Our previous findings (Thirumal Kumar, Eldous, Mahgoub, George Priya Doss, Zayed, 2018) and other reports concluded that the mutations N370S and L444P are the most significant mutations that could cause disruptions in protein stability and structure. These disruptions lead to protein misfolding and result in a diseased condition. Enzyme Replacement Therapy (ERT) and Pharmacological chaperone therapy (PCT) are currently used to treat GD caused by mutations in the GBA protein. The extreme disparity in cost between ERT and chaperone therapy, shifted the attention toward chaperone therapy. The most common chaperones in the market and trial phases to treat GD are Isofagomine, Miglustat, Eliglustat, NN-DNJ, and Ambroxol. In the era of personalized medicine, it is often necessary to understand the drug likeliness of each chaperone. In this context, the present study utilized molecular docking analysis to understand the interaction behavior of the chaperone toward the native and the two mutants N370S and L444P. The molecular dynamics simulation analyses performed on chaperones (NN-DNJ and Ambroxol) interaction showed that the chaperone NN-DNJ possesses better affinity toward the protein with N370S mutation whereas chaperone Ambroxol showed better activity against both the significant mutations (N370S and L444P). This study is expected to serve as a platform for drug repurposing.

Computational and modeling approaches to understand the impact of the Fabry's disease causing mutation (D92Y) on the interaction with pharmacological chaperone 1-deoxygalactonojirimycin (DGJ).

Fabry's disease (FD) is the second most commonly occurring lysosomal storage disorders (LSDs). The mutations in α-galactosidase A (GLA) protein were widely found to be causative for the Fabry's disease. These mutations result in alternate splicing methods that affect the stability and function of the protein. The mutations near the active site of the protein results in protein misfolding. In this study, we have retrieved the missense mutation data from the three public databases (NCBI, UniProt, and HGMD). We used multiple in silico tools to predict the pathogenicity and stability of these mutations. Mutations in the active sites (D92Y, C142Y, D170V, and D266N) of the protein were screened for the phenotyping analysis using SNPeffect 4.0. Mutant D92Y was predicted to increase the amyloid propensity as well as severely reduce the protein stability and the remaining mutations showed no significant results by SNPeffect 4.0. Protein dynamics simulations (PDS) were performed to understand the behavior of the proteins due to the mutations. The simulation results showed that the D92Y mutant was more severe (higher deviation, loss of intramolecular hydrogen bonds, and lower compactness) than the other protein mutants (C142Y, D170V, and D266N). Further, the action of pharmacological chaperone 1-deoxygalactonojirimycin (DGJ) over the severe mutation was studied using the molecular docking analysis. Chaperone DGJ, an iminosugar plays a convincing role in repairing the misfolded protein and helps the protein to achieve its normal function. From the molecular docking analysis, we observed that both the native protein and protein with D92Y mutation followed similar interaction patterns. Further, the docked complexes (native-DGJ and mutant-DGJ) were subjected to PDS analysis. From the simulation analysis, we observed that DGJ had shown the better effect on the protein with the D92Y mutation. This elucidates that DGJ can still be used as a promising chaperone to treat the FD caused by mutations of GLA protein.

Towards the early detection of ductal carcinoma (a common type of breast cancer) using biomarkers linked to the PPAR(γ) signaling pathway.

Breast cancer is a leading cause of morbidity and mortality among women comprising about 12% females worldwide. The underlying alteration in the gene expression, molecular mechanism and metabolic pathways responsible for incidence and progression of breast tumorigenesis are yet not completely understood. In the present study, potential biomarker genes involved in the early progression for early diagnosis of breast cancer has been detailed. Regulation and Gene profiling of Ductal Carcinoma In-situ (DCIS), Invasive Ductal Carcinoma (IDC) and healthy samples have been analyzed to follow their expression pattern employing normalization, statistical calculation, DEGs annotation and Protein-Protein Interaction (PPI) network. We have performed a comparative study on differentially expressed genes among Healthy vs DCIS, Healthy vsIDC and DCIS vs IDC. We found MCM102 and SLC12A8as consistently over-expressed and LEP, SORBS1, SFRP1, PLIN1, FABP4, RBP4, CD300LG, ID4, CRYAB, ECRG4, G0S2, FMO2, ADAMTS5, CAV1, CAV2, ABCA8, MAMDC2, IGFBP6, CLDN11, TGFBR3as under-expressed genes in all the 3 conditions categorized for pre-invasive and invasive ductal breast carcinoma. These genes were further studied for the active pathways where PPAR(γ) signaling pathway was found to be significantly involved. The gene expression profile database can be a potential tool in the early diagnosis of breast cancer.

Prospects and progress in the production of valuable carotenoids: Insights from metabolic engineering, synthetic biology, and computational approaches.

Carotenoids are isoprenoid pigments synthesized exclusively by plants and microorganisms and play critical roles in light harvesting, photoprotection, attracting pollinators and phytohormone production. In recent years, carotenoids have been used for their health benefits due to their high antioxidant activity and are extensively utilized in food, pharmaceutical, and nutraceutical industries. Regulation of carotenoid biosynthesis occurs throughout the life cycle of plants, with vibrant changes in composition based on developmental needs and responses to external environmental stimuli. With advancements in metabolic engineering techniques, there has been tremendous progress in the production of industrially valuable secondary metabolites such as carotenoids. Application of metabolic engineering and synthetic biology has become essential for the successful and improved production of carotenoids. Synthetic biology is an emerging discipline; metabolic engineering approaches may provide insights into novel ideas for biosynthetic pathways. In this review, we discuss the current knowledge on carotenoid biosynthetic pathways and genetic engineering of carotenoids to improve their nutritional value. In addition, we investigated synthetic biological approaches for the production of carotenoids. Theoretical biology approaches that may aid in understanding the biological sciences are discussed in this review. A combination of theoretical knowledge and experimental strategies may improve the production of industrially relevant secondary metabolites.

Influence of PCOS in Obese vs. Non-Obese women from Mesenchymal Progenitors Stem Cells and Other Endometrial Cells: An in silico biomarker discovery.

Polycystic ovary syndrome (PCOS) is endocrine system disease which affect women ages 18 to 44 where the women's hormones are imbalance. Recently it has been reported to occur in early age. Alteration of normal gene expression in PCOS has shown negative effects on long-term health issues. PCOS has been the responsible factor for the infertility in women of reproductive age group. Early diagnosis and treatment can improve the women's health suffering from PCOS. Earlier Studies shows correlation of PCOS upon insulin resistance with significant outcome, Current study shows the linkage between PCOS with obesity and non-obese patients. Gene expression datasets has been downloaded from GEO (control and PCOS affected patients). Normalization of the datasets were performed using R based on RMA and differentially expressed gene (DEG) were selected on the basis of p-value 0.05 followed by functional annotation of selected gene using Enrich R and DAVID. The DEGs were significantly related to PCOS with obesity and other risk factors involved in disease. The Gene Enrichment Analysis suggests alteration of genes and associated pathway in case of obesity. Current study provides a productive groundwork for specific biomarkers identification for the accurate diagnosis and efficient target for the treatment of PCOS.

A Molecular Docking and Dynamics Approach to Screen Potent Inhibitors Against Fosfomycin Resistant Enzyme in Clinical Klebsiella pneumoniae.

Klebsiella pneumoniae, BA6753 was cultured from a patient in the Clinical Microbiology Laboratory of Christian Medical College. K. pneumoniae, BA6753 has a multidrug resistance plasmid encoding novel FosA variant-7, fosfomycin resistance enzyme. Minimal side effects and a wide range of bactericidal activity of fosfomycin have resulted in its expanded clinical use that prompts the rise of fosfomycin-resistant strains. At present, there are no effective inhibitors available to conflict the FosA-medicated fosfomycin resistance. To develop effective FosA inhibitors, it is crucial to understand the structural and dynamic properties of resistance enzymes. Hence, the present study focuses on the identification of potent inhibitors that can effectively bind to the fosfomycin resistance enzyme, thus predispose the target to inactivate by the second antibiotic. Initially, a series of active compounds were screened against the resistant enzyme, and the binding affinities were confirmed using docking simulation analysis. For efficient activity, the binding affinity of the resistance enzyme ought to be high with the inhibitor than the fosfomycin drug. Consequently, the enzyme-ligand complex which showed higher binding affinity than the fosfomycin was employed for subsequent analysis. The stability of the top scoring enzyme-ligand complex was further validated using molecular dynamics simulation studies. On the whole, we presume that the compound 19583672 demonstrates a higher binding affinity for the resistance enzyme comparing to other compounds and fosfomycin. We believe that further enhancement of the lead compound can serve as a potential inhibitor against resistance enzyme in drug discovery process. J. Cell. Biochem. 118: 4088-4094, 2017. © 2017 Wiley Periodicals, Inc.

Influence of V54M mutation in giant muscle protein titin: a computational screening and molecular dynamics approach.

Recent genetic studies have revealed the impact of mutations in associated genes for cardiac sarcomere components leading to dilated cardiomyopathy (DCM). The cardiac sarcomere is composed of thick and thin filaments and a giant muscle protein known as titin or connectin. Titin interacts with T-cap/telethonin in the Z-line region and plays a vital role in regulating sarcomere assembly. Initially, we screened all the variants associated with giant protein titin and analyzed their impact with the aid of pathogenicity and stability prediction methods. V54M mutation found in the hydrophobic core region of the protein associated with abnormal clinical phenotype leads to DCM was selected for further analysis. To address this issue, we mapped the deleterious mutant V54M, modeled the mutant protein complex, and deciphered the impact of mutation on binding with its partner telethonin in the titin crystal structure of PDB ID: 1YA5 with the aid of docking analysis. Furthermore, two run molecular dynamics simulation was initiated to understand the mechanistic action of V54M mutation in altering the protein structure, dynamics, and stability. According to the results obtained from the repeated 50 ns trajectory files, the overall effect of V54M mutation was destabilizing and transition of bend to coil in the secondary structure was observed. Furthermore, MMPBSA elucidated that V54M found in the Z-line region of titin decreases the binding affinity of titin to Z-line proteins T-cap/telethonin thereby hindering the protein-protein interaction.