An in silico analysis of deleterious single nucleotide polymorphisms and molecular dynamics simulation of disease linked mutations in genes responsible for neurodegenerative disorder

Abstract

Mutation in two genes deglycase gene (DJ-1) and retromer complex component gene (VPS35) are linked with neurodegenerative disorder such as Parkinson's disease, Huntington's disease, and Alzheimer's disease. DJ-1 gene located at 1p36 chromosomal position and involved in PD pathogenesis through many pathways including mitochondrial dysfunction and oxidative injury. VPS35 gene located at 16q13-q21 chromosomal position and the two pathways, the Wnt signaling pathway, and retromer-mediated DMT1 missorting are proposed for basis of VPS35 related PD. The study focuses on identifying most deleterious SNPs through computational analysis. Result obtained from various bioinformatics tools shows that D149A is most deleterious in DJ-1 and A54W, R365H, and V717M are most deleterious in VPS35. To understand the functionality of protein comparative modeling of DJ-1 and VPS35 native and mutants was done by MODELLER. The generated structures are validated by two web servers–ProSa and RAMPAGE. Molecular dynamic simulation (MDS) analysis done for the most validated structures to know the functional and structural nature of native and mutants protein of DJ-1 and VPS35. Native structure of DJ-1 and VPS35 show more flexibility through MDS analysis. DJ-1 D149A mutant structures become more compact which shows the structural perturbation and loss of DJ-1 protein function which in turn are probable cause for PD. A54W, R365H, and V717M mutant protein of VPS35 also shows compactness which cause structure perturbation and absence of retromer function which likely to be linked to PD pathogenesis. This in silico study may provide a new insight for fundamental molecular mechanism involved in Parkinson’s disease.

Communicated by Ramaswamy H. Sarma     

IGFBP3 gene promoter methylation analysis and its association with clinicopathological characteristics of colorectal carcinoma

Molecular Biology Reports - Promoter methylation mediated silencing of tumor suppressor genes plays an important role in the tumorigenesis of colorectal carcinoma (CRC). Tumor suppressor gene,...     

Zebrafish AID is capable of deaminating methylated deoxycytidines

Activation-induced cytidine deaminase (AID) deaminates deoxycytidine (dC) to deoxyuracil (dU) at immunoglobulin loci in B lymphocytes to mediate secondary antibody diversification. Recently, AID has been proposed to also mediate epigenetic reprogramming by demethylating methylated cytidines (mC) possibly through deamination. AID overexpression in zebrafish embryos was shown to promote genome demethylation through G:T lesions, implicating a deamination-dependent mechanism. We and others have previously shown that mC is a poor substrate for human AID. Here, we examined the ability of bony fish AID to deaminate mC. We report that zebrafish AID was unique among all orthologs in that it efficiently deaminates mC. Analysis of domain-swapped and mutant AID revealed that mC specificity is independent of the overall high-catalytic efficiency of zebrafish AID. Structural modeling with or without bound DNA suggests that efficient deamination of mC by zebrafish AID is likely not due to a larger catalytic pocket allowing for better fit of mC, but rather because of subtle differences in the flexibility of its structure.     

Chemical activators: A novel and sustainable management approach for Meloidogyne incognita (Kofoid and White) Chitwood in Chamomilla recutita L

Use of chemical activator for the management of root-knot disease in medicinal and aromatic plants can become an attractive alternative to traditionally used nematicides. Large numbers of chemical molecules are present in the plants and are involved in the induction of different types of proteins. The purpose of our research study is to explore the possibilities of resistance factors that are inherent in the plant by treating them with few chemical activators to activate against root-knot nematode infection. Efforts were made to achieve a satisfactory suppression of root-knot nematode, Meloidogyne incognita, a serious menace to successful cultivation of chamomile, Matricaria recutita L. Rauch (syn. Matricaria chamomilla L. Fain. Asteraceae) causing root-knot disease through use of different chemical activators. Here we examined selected groups of resistance activator viz. Isonicotinamide, 2-chloronicotinic acid, 5-nitrosalicylic acid, 4-chlorosalicylic acid, DL-2 aminobutyric acid, 2-aminobutyric acid, O-acetylsalicylic acid, 4-amino salicylic acid, salicylic acid and these were used as soil drench using 3 week old seedlings transplanted to root-knot nematode infested pots. Maximum reduction in root-knot severity and nematode population occurred with 4-chlorosalicylic acid, O-acetyl salicylic acid, 2-chloronicotinic acid and gave significant flower yield advantages. Present experiment suggests a strong possibility of these activators in integrated management for protection against plant parasitic nematodes.     

Epidemiology and prediction of brown leaf rust of mulberry caused by Peridiopsora mori

Brown leaf rust (BLR) caused by Peridiopsora mori is one of the major foliar diseases of mulberry (Morus sp.) in the subtropical hills of eastern India. The disease appeared in first week of August and continued up to September with maximum severity in second and third week of September. The disease symptoms appeared at atmospheric temperature (27.00–20.07°C), relative humidity (92.14–82.43%), rainfall (11.20 cm) and rainy days (7) of the preceding week. Disease severity (>50 PDI) was observed at temperature (26.29–19.29°C), relative humidity (94.14–80.14%), rainfall (4.12 cm) and number of rainy days (2–3 days). Apparent rate of infection was found high at temperature (27.00–19.83°C), relative humidity (94.67–85.00%), rainfall (4.6 cm) and rainy days (2) of the preceding week. The correlation coefficient between disease severity and average meteorological factors of the preceding 7 days revealed that BLR disease severity showed significant negative correlation with minimum temperature. It was also revealed that contribution of maximum and minimum temperature 42.23% and 35.21%, maximum and minimum relative humidity (RH) 11.23% and 10.69% and rainfall and number of rainy days 0.11% and 0.50%, respectively towards development of BLR disease severity. Multiple regression analysis revealed that average of maximum and minimum temperatures and minimum RH of preceding 7 days were found to maximally influence BLR disease severity.     

Seasonal variations in the mating-related traits of Drosophila melanogaster

The Indian subcontinent shows high levels of seasonal weather variation, but the extent to which mating-related traits (mating latency, copulation duration and number of progeny produced) are being affected by such variations in Drosophila species remain poorly understood. In the present study, we analyzed the effects of seasonal change (humidity and temperature) on mating-related traits of Drosophila melanogaster by mimicking natural conditions in the laboratory. The light body color phenotype is collected in large numbers during the rainy season, while the dark phenotype is prevalent in the winter. We found that a short-term stress, in the form of reduced humidity or temperature, causes a strong climatic selection pressure, which leads to assortative mating and longer copulation duration of the dark phenotype. By contrast, the light phenotype shows higher assortative mating and longer copulation duration after short-term high humidity or high temperature stress. Higher assortative mating and increased copulation duration results in high progeny numbers which may be a cause for the high prevalence of the dark phenotype in winter and the light phenotype in the rainy season. Thus, besides plasticity, seasonal changes in mating propensity can be a potential cause of the change in the frequency of the dark and light phenotypes of D. melanogaster during different seasons.     

Modulation of interaction of mutant TP53 and wild type BRCA1 by alkaloids: a computational approach towards targeting protein-protein interaction as a futuristic therapeutic intervention strategy for breast cancer impediment

Protein–protein interactions (PPI) are a new emerging class of novel therapeutic targets. In order to probe these interactions, computational tools provide a convenient and quick method towards the development of therapeutics. Keeping this in view the present study was initiated to analyse interaction of tumour suppressor protein p53 (TP53) and breast cancer associated protein (BRCA1) as promising target against breast cancer. Using computational approaches such as protein–protein docking, hot spot analyses, molecular docking and molecular dynamics simulation (MDS), stepwise analyses of the interactions of the wild type and mutant TP53 with that of wild type BRCA1 and their modulation by alkaloids were done. Protein–protein docking method was used to generate both wild type and mutant complexes of TP53-BRCA1. Subsequently, the complexes were docked using sixteen different alkaloids, fulfilling ADMET and Lipinski’s rule of five criteria, and were compared with that of a well-known inhibitor of PPI, namely nutlin. The alkaloid dicentrine was found to be the best docked alkaloid among all the docked alklaloids as well as that of nutlin. Furthermore, MDS analyses of both wild type and mutant complexes with the best docked alkaloid i.e. dicentrine, revealed higher stability of mutant complex than that of the wild one, in terms of average RMSD, RMSF and binding free energy, corroborating the results of docking. Results suggested more pronounced interaction of BRCA1 with mutant TP53 leading to increased expression of mutated TP53 thus showing a dominant negative gain of function and hampering wild type TP53 function leading to tumour progression.     

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%–~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.