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.

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 (Aβ42) aggregation or amyloidosis is contemplated as a unique hallmark characteristic of Alzheimer’s disease (AD). Due to aberrant accrual and aggregation of Aβ42 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 Aβ42 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 (Aβ42) fibril structure. Hence, we could postulate that these herbal compounds could be potential inhibitors of Aβ42 fibrils; these anti-aggregation agents need to be considered in treating AD.

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.

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.

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.

In vitro efficacy and in silico analysis of cefixime-ofloxacin combination for Salmonella Typhi from bloodstream infection

AIMS

Recently, the cefixime-ofloxacin combination is approved by Drug Controller General of India to treat typhoid fever. We sought to evaluate the antimicrobial activity of cefixime-ofloxacin combination against Salmonella Typhi.

METHODS AND RESULTS

A total of 283 nonduplicate S. Typhi isolates collected during 2012-2014 were included in this study. Minimum inhibitory concentration (MIC) of cefixime and ofloxacin was determined by using broth microdilution method. Combinational testing was performed by using checkerboard assay. In checkerboard assay, synergistic activity was seen in 11% of isolates, while the majority of the isolate showed indifference and none of them showed antagonism. An in silico strategy, an alternative to the animal model, was carried out to understand drug interaction and toxicity. Molecular docking results elucidated that cefixime and ofloxacin are capable of inhibiting the cell wall synthesis and DNA replication, respectively. Computational ADMET analysis showed no toxicity and no drug-drug interaction between cefixime and ofloxacin.

CONCLUSION

Cefixime-ofloxacin combination could be effective against moderately susceptible fluoroquinolone S. Typhi but not fluoroquinolone-resistant isolates.

SIGNIFICANCE AND IMPACT OF THE STUDY

Cefixime-ofloxacin combination with no drug-drug interaction and nontoxic predicted through computational analysis did not show antagonism against S. Typhi in in vitro. Although this study showed no adverse effects with the cefixime-ofloxacin combination, further studies on pharmacokinetic and pharmacodynamic (PK-PD) parameters of cefixime and ofloxacin combination are warranted.

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 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.

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.

Nature of cation-pi interactions and their role in structural stability of immunoglobulin proteins

Cation-pi interactions are known to be important contributors to protein stability and ligand-protein interactions. In this study, we have analyzed the influence of cation-pi interactions in single chain immunoglobulin proteins. We observed 87 cation-pi interactions in a data set of 33 proteins. These interactions are mainly formed by long-range contacts, and there is preference of Arg over Lys in these interactions. Arg-Tyr interactions are predominant among the various pairs analyzed. Despite the scarcity of interactions involving Trp, the average energy for Trp-cation interactions is quite high. This information suggests that the cation-pi interactions involving Trp might be of high relevance to the proteins. Secondary structure analysis reveals that cation-pi interactions are formed preferably between residues in which at least one is in beta-strand. Proteins having beta-strand regions have the highest number of cation-pi interaction-forming residues.