Identification and Computational Analysis of Rare Variants of Known Hearing Loss Genes Present in Five Deaf Members of a Pakistani Kindred

Hearing loss (HL) is the most common neurosensory defect in humans that affects the normal communication. Disease is clinically and genetically heterogeneous, rendering challenges for the molecular diagnosis of affected subjects. This study highlights the phenotypic and genetic complexity of inherited HL in a large consanguineous Pakistan kindred. Audiological evaluation of all affected individuals revealed varying degree of mild to profound sensorineural HL. Whole exome (WES) of four family members followed by Sanger sequencing revealed candidate disease-associated variants in five known deafness genes: GJB2 (c.231G>A; p.(Trp77 *)), SLC26A4 (c.1337A>G; p.(Gln446Arg)), CDH23 (c.2789C>T; p.(Pro930Leu)), KCNQ4 (c.1672G>A; p.(Val558Met)) and MPDZ (c.4124T>C; p.(Val1375Ala)). All identified variants replaced evolutionary conserved residues, were either absent or had low frequencies in the control databases. Our in silico and 3-Dimensional (3D) protein topology analyses support the damaging impact of identified variants on the encoded proteins. However, except for the previously established “pathogenic” and “likely pathogenic” categories for the c.231G>A (p.(Trp77 *)) allele of GJB2 and c.1377A>G (p.(Gln446Arg)) of SLC26A4, respectively, all the remaining identified variants were classified as “uncertain significance” based on the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines. Our study highlights the complexity of genetic traits in consanguineous families, and the need of combining the functional studies even with the comprehensive profiling of multiple family members to improve the genetic diagnosis in complex inbred families

Phenolic contents-based assessment of therapeutic potential of Syzygium cumini leaves extract

Syzygium cumini (S. cumini) is an evergreen tropical plant that is well recognized for its therapeutic potential of common diseases. In this study, the therapeutic potential and biomedical application of S. cumini are assessed in vitro and in vivo to find its effectiveness for different complications. The methanolic crude extract of S. cumini leaves were screened for total phenolic and flavonoid content. In vitro, the DPPH scavenging assay, XTT assay, prothrombin and activated partial thromboplastin time were used to assess antioxidant, cytoprotective and thrombolytic activity of the S. cumini extract, respectively. The anti-inflammatory potential and the analgesic activity of the S. cumini extract were analyzed in rabbits by the Carrageenan induced paw edema method and the writhing method, respectively. Phytochemical analysis showed the presence of considerable amounts of total phenolic (369.75 � 17.9 mg GAE/g) and flavonoid (75.8 � 5.3 mgRE/g) content in the S. cumini extract. The DPPH assay demonstrated a higher antioxidant potential (IC-50 value of 133 ?g/ml), which was comparable to the IC-50 of ascorbic acid (122.4 ?g/ml). Moreover, the S. cumini extract showed a dose dependent cytoprotective effect against H2O2 treated bone marrow mesenchymal stem cells (BM-MSCs). S. cumini also possesses significant anticoagulant activity with a prothrombin time of 28.3 � 1.8 seconds vs 15.8 � 0.2 seconds of control, p<0.05. The leaf extract also demonstrated an analgesic effect in rabbits as indicated by the decrease in writhing (12.2 � 1.7 control vs. 3.7 � 0.6 treated) and anti-inflammatory activity in rabbits paw with a protection against inflammation of 64.1 � 2.4%. Our findings suggest that the methanolic extract of S. cumini leaves has antioxidant, cytoprotective, anticoagulant, analgesic and anti-inflammatory properties, and therefore, can be applied for treating cardiovascular diseases and cancers. - 2019 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Scopu

Hypothesis Modelling and simulation of mutant alleles of breast cancer metastasis suppressor 1 (BRMS1) gene

Abstract: Computational tools occupy the prime position in the analysis of large volume of post-genomic data. These tools have advantage over the wet lab experiments in terms of high coverage, cost and time. Breast cancer is the most common cancer in females worldwide. It is a genetically heterogeneous disorder and many genes are involved in the pathway of the disease. Mutations in metastasis suppressor gene are the major cause of the disease. In this study, the effects of mutations in breast cancer metastasis suppressor 1gene upon protein structure and function were examined by means of computational tools and information from databases.This study can be useful to predict the potential effect of every allelic variant, devise new biological experiments and to interpret and predict the patho-physiological impact of new mutations or non-synonymous polymorphisms. Key words: Breast cancer; BRMS1; Mutation analysis; Homology modeling Background: In now a days, computers are as likely to be used by biologists as by any other highly trained professionals, more specifically in field of bioinformatics; which is focused on making predictions about biological systems and to analyze biological data related to different diseases like cancer [1]. As in computational biology tools are used to predict if two proteins interact or not, if prediction is accurate then computational biology could further be used to analyze biological data obtained from a wet lab experiment. This field can be further broken down into molecular modeling and bioinformatics. Several bioinformatics methods are applied for the different mutational disease analysis [2]. Many of them are based on protein sequence, but several are structure-based, as the latter are more reliable and provide more information. In this work, we have built a homology model of mutated BRMS1 gene applying the most updated available methods of Homology modelling through MODELLER, [3] and have investigated the effects of mutations of BRMS1 using different software, including SNAP it is a neural-network based method which evaluates the single amino acid substitution effects on protein functions [4]. I-Mutant2.0 is a web server used for the prediction of protein stability changes upon single-sit

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach

Allergens have the ability to enter the body and cause illness. Leukotriene is the widespread allergen which could stimulate mast cells to discharge histamine which causes allergy symptoms. An effective strategy for treating leukotriene-induced allergy is to find the inhibitors of leukotriene or histamine activity from phytochemicals. For this purpose, a library of 8,500 phytochemicals was generated using MOE software. The structures of histamine-1 receptor and cysteinyl leukotriene receptor-1 were predicted by the homology modeling method through the SWISS model. The phytochemicals were docked with predicted structures of histamine-1 and cysteinyl leukotriene receptor-1 in MOE software to determine the binding affinity of the phytochemicals against the targets. Moreover, chemoinformatics properties and ADMET of phytochemicals were assessed to find the drug likeness behavior of compounds. Compound ID 10054216 has the lowest S-score value for H-1 receptor that is -18.9186 kcal/mol which is lower than the value of standard -15.167 kcal/mol. The other compounds 393471, 71448939, 10722577, and 442614 also showed good S-score values than the standard. Moreover, compound ID 11843082 has the lowest S-score value for CL1R that is -15.481 kcal/mol which is lower than the value of standard -12.453 kcal/mol. The other compounds 72284, 5282102, 66559251, and 102506430 also showed good S-score values than the standard. In this research article, we performed molecular docking to find the best inhibitors against H1R and CL1R and their antiallergic efficacy. This in silico knowledge will be helpful in near future for the design of novel, safe, and less costing H-1 receptor and CL1R inhibitors with the aim to improve human life quality

Screening of drug candidates against Endothelin-1 to treat hypertension using computational based approaches: Molecular docking and dynamics simulation.

Hypertension (HTN) is a major risk factor for cardiovascular and renal diseases, cerebrovascular accidents (CVA) and a prime underlying cause of worldwide morbidity and mortality. Hypertension is a complex condition and a strong interplay of multiple genetic, epigenetic and environmental factors is involved in its etiology. Previous studies showed an association of overexpression of genes with hypertension. Satisfactory control of Blood Pressure (BP) levels is not achieved in a major portion of hypertensive patients who take antihypertensive drugs. Since existing antihypertensive drugs have many severe or irreversible side effects and give rise to further complications like frequent micturition and headaches, dizziness, dry irritating cough, hypoglycemia, GI hemorrhage, impaired left ventricular function, hyperkalemia, Anemia, angioedema and azotemia. There is a need to identify new antihypertensive agents that can inhibit the expression of these overexpressed genes contributing to hypertension. The study was designed to identify drug-able targets against overexpressed genes involved in hypertension to intervene the disease. The structure of the protein encoded by an overexpressed gene Endothelin-1 was retrieved from Protein Database (PDB). A library of five thousand phytochemicals was docked against Endothelin-1. The top four hits against Endothelin-1 protein were selected based on S score and Root Mean Square Deviation (RMSD). S score is a molecular docking score which is used to determine the preferred orientation, binding mode, site of the ligand and binding affinity. RMSD refines value for drug target identification. Absorption, distribution, metabolism, excretion, and toxicity profiling (ADMET) was done. The study provides novel insights into HTN etiology and improves our understanding of BP pathophysiology. These findings help to understand the impact of gene expression on BP regulation. This study might be helpful to develop an antihypertensive drug with a better therapeutic profile and least side effects