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.

Structure-based pharmacophore modeling, virtual screening approaches to identifying the potent hepatitis C viral protease and polymerase novel inhibitors.

Hepatitis C is an infectious disease that leads to acute and chronic liver illnesses. Currently, there are no effective vaccines against this deadly virus. Direct acting antiviral (DAA) drugs are given in the combination with ribavirin and pegylated interferon which lead to adverse effects. Through in silico analysis, the structure-based docking study was performed against NS3/4A protease and NS5B polymerase proteins of HCV. In the current study, multiple e-pharmacophore-based virtual screening methods such as HTVS, SP, and XP were carried out to screen natural compounds and enamine databases. Our result outcomes revealed that CID AE-848/13196185 and CID AE-848/36959205 compounds show good binding interactions with protease protein. In addition, CID 15081408 and CID 173568 show better binding interactions with the polymerase protein. Further to validate the docking results, we performed molecular dynamics simulation for the top hit compounds bound with protease and polymerase proteins to illustrate conformational differences in the stability compared with the active site of the cocrystal inhibitor. Thus, the current study emphasizes these compounds could be an effective drug to treat HCV.

Barriers of healthcare professionals in utilizing the service of drugs and poison information Centre: A cross-sectional study.

Background: Health care professionals (HCPs) have been using drugs and poison information centre (DIC) less frequently in recent years. The purpose of this study was to identify the barriers that inhibit HCPs from using the DIC service in a tertiary care hospital, as well as the factors that assist HCPs in using DIC more effectively. Methods: A cross-sectional study was conducted among HCPs in Sri Ramachandra Institute of Higher Education and Research, Chennai. HCPs were given a semi-structured questionnaire that was developed and validated by a subject expert, a public health expert, and a clinical psychologist, and their barriers and facilitators in accessing drug information services were recorded. Findings: A total of 405 HCPs responded to the survey. Among the identified barriers, the top 3 were: HCPs found it easier to use mobile internet (31%) and the department's reference library (25%) instead of contacting DIC for any drug/poison information. In addition, 17% of HCPs stated that they were too busy. The factors that may assist HCPs utilize DIC more effectively were more awareness is required to demonstrate the functionalities of DIC (24%), and a mobile application is required (23%). Conclusion: Today's HCPs have easy access to a variety of drug information resources, and many prefer to do their own drug/poison research. As current generation HCPs find it more convenient to use mobile internet than contacting DIC, the creation of a mobile application for drug information service may enhance the number of questions from HCPs.

Codon usage of human hepatitis C virus clearance genes in relation to its expression.

Hepatitis C virus (HCV) infection is among the leading causes of hepatocellular carcinoma and liver cirrhosis globally, with a high economic burden. The disease progression is well established, but less is known about the spontaneous HCV infection clearance. This study tries to establish the relationship between codon biasness and expression of HCV clearance candidate genes in normal and HCV infected liver tissues. A total of 112 coding sequences comprising 151 679 codons were subjected to the computation of codon indices, namely relative synonymous codon usage, an effective number of codon (Nc), frequency of optimal codon, codon adaptation index, codon bias index, and base compositions. Codon indices report of GC3s, GC12, hydropathicity, and aromaticity implicates both mutational and translational selection in the candidate gene set. This was further correlated with the differentially expressed genes among the selected genes using BioGPS. A significant correlation is observed between the gene expression of normal liver and cancerous liver tissues with codon bias (Nc). Gene expression is also correlated with relative codon bias values, indicating that CCL5, APOA2, CD28, IFITM1, and TNFSF4 genes have higher expression. These results are quite encouraging in selecting the high responsive genes in HCV clearance. However, there could be additional genes which could also orchestrate the clearance role with the above mentioned first line of defensive genes.

Review on chemogenomic approaches towards hepatitis C viral targets.

Hepatitis C virus (HCV) is the most prevalent viral pathogen that infects more than 185 million people worldwide. HCV infection leads to chronic liver diseases such as liver cirrhosis and hepatocellular carcinoma. Direct-acting antivirals (DAAs) are the recent combination therapy for HCV infection with reduced side effects than prior therapies. Sustained virological response (SVR) acts as a gold standard marker to monitor the success of antiviral treatment. Older treatment therapies attain 50-55% of SVR compared with DAAs which attain around 90-95%. The current review emphasizes the recent chemogenomic updates that have been unfolded through structure-based drug design of HCV drug target proteins (NS3/4A, NS5A, and NS5B) and ligand-based drug design of DAAs in achieving a stable HCV viral treatment strategies.

Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV).

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide 'ELRSELIGY' of phosphoprotein and 'YPLLWSFAM' of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.

Pharmacophore feature prediction and molecular docking approach to identify novel anti-HCV protease inhibitors.

Discovering a potential drug for HCV treatment is a challenging task in the field of drug research. This study initiates with computational screening and modeling of promising ligand molecules. The foremost modeling method involves the identification of novel compound and its molecular interaction based on pharmacophore features. A total of 197 HCV compounds for NS3/4A protein target were screened for our study. The pharmacophore models were generated using PHASE module implemented in Schrodinger suite. The pharmacophore features include one hydrogen bond acceptor, one hydrogen bond donor, and three hydrophobic sites. As a result, based on mentioned hypothesis the model ADHHH.159 corresponds to the CID 59533233. Furthermore, docking was performed using maestro for all the 197 compounds. Among these, the CID 59533313 and 59533233 possess the best binding energy of -11.75 and -10.40 kcal/mol, respectively. The interactions studies indicated that the CID complexed with the NS3/4A protein possess better binding affinity with the other compounds. Further the compounds were subjected to calculate the ADME properties. Therefore, it can be concluded that these two compounds could be a potential alternative drug for the development of HCV.

Deciphering molecular properties and docking studies of hepatitis C and non-hepatitis C antiviral inhibitors - A computational approach.

BACKGROUND: Hepatitis C is an infectious liver disease with high mortality rate which is caused by Hepatitis C virus. Several treatment methods have been applied to combat this deadly virus including interferons, vaccine and direct acting antivirals (DAAs). However, the later shows promising effects in HCV treatment with lower adverse effect. Specifically, the DAAs target the non-structural proteins (NS3 and NS5B). PURPOSE: The objective of the present study is to hypothesize an alternative antiviral inhibitor for HCV from the available other antivirals. METHODS: Computation of 2D molecular descriptors for the selected antiviral inhibitors followed by clustering the descriptor features. The closely clustered compounds were subjected to the interaction studies against the HCV target protein to validate the cluster result. RESULTS AND DISCUSSION: The clustering result showed that indinavir (HIV inhibitor) and AT130 (HBV inhibitor) molecule are close to the HCV inhibitor. The indinavir complexed with NS3 protein shows -5.33kcal/mol and AT-130 complexed with NS5B protein possess the binding energy of -8.87kcal/mol. The docking interaction study indicated a better binding affinity than other viral inhibitors. CONCLUSION: From the descriptor based feature similarity analysis and the interaction study, it can be concluded that indinavir and AT-130 could be a potential alternative agent for HCV treatment.

Individual and Co Transport Study of Titanium Dioxide NPs and Zinc Oxide NPs in Porous Media.

The impact of pH and ionic strength on the mobility (individual and co-transport) and deposition kinetics of TiO2 and ZnO NPs in porous media was systematically investigated in this study. Packed column experiments were performed over a series of environmentally relevant ionic strengths with both NaCl (0.1-10 mM) and CaCl2 (0.01-0.1mM) solutions and at pH 5, 7, and 9. The transport of TiO2 NPs at pH 5 was not significantly affected by ZnO NPs in solution. At pH 7, a decrease in TiO2 NP transport was noted with co-existence of ZnO NPs, while at pH 9 an increase in the transport was observed. At pH 5 and 7, the transport of ZnO NPs was decreased when TiO2 NPs was present in the solution, and at pH 9, an increase was noted. The breakthrough curves (BTC) were noted to be sensitive to the solution chemistries; the decrease in the breakthrough plateau with increasing ionic strength was observed under all examined pH (5, 7, and 9). The retention profiles were the inverse of the plateaus of BTCs, as expected from mass balance considerations. Overall, the results from this study suggest that solution chemistries (ionic strength and pH) are likely the key factors that govern the individual and co-transport behavior of TiO2 and ZnO NPs in sand.