Computational approach for elucidating interactions of cross-species miRNAs and their targets in Flaviviruses.

BACKGROUND & OBJECTIVES: Combating viral diseases has been a challenging task since time immemorial. Available molecular approaches are limited and not much effective for this daunting task. MicroRNA based therapies have shown promise in recent times. MicroRNAs are tiny non-coding RNAs that regulate translational repression of target mRNA in highly specific manner. METHODS: In this study, we have determined the target regions for human and viral microRNAs in the conserved genomic regions of selected viruses of Flaviviridae family using miRanda and performed a comparative target selectivity analysis among them. RESULTS: Specific target regions were determined and they were compared extensively among themselves by exploring their position to determine the vicinity. Based on the multiplicity and cooperativity analysis, interaction maps were developed manually to represent the interactions between top-ranking miRNAs and genomes of the viruses considered in this study. Self-organizing map (SOM) was used to cluster the best-ranked microRNAs based on the vital physicochemical properties. INTERPRETATION & CONCLUSION: This study will provide deep insight into the interrelation of the viral and human microRNAs interactions with the selected Flaviviridae genomes and will help to identify cross-species microRNA targets on the viral genome.

A Complex Network of MicroRNAs Expressed in Brain and Genes Associated with Amyotrophic Lateral Sclerosis.

Amyotrophic Lateral Sclerosis (ALS) is a rare neurological disease affecting mainly motor neurons and often leads to paralysis and death in extreme cases. For exploring the role of microRNAs in genes regulation in ALS disease, miRanda was employed for prediction of target sites of miRNAs expressed in various parts of brain and CNS on 35 genes associated with ALS. Similar search was conducted using TargetScan and PicTar for prediction of target sites in 3' UTR only. 1456 target sites were predicted using miRanda and more target sites were found in 5' UTR and CDS region as compared to 3' UTR. 11 target sites were predicted to be common by all the algorithms and, thus, these represent the most significant sites. Target site hotspots were identified and were recognized as hotspots for multiple miRNAs action, thus, acting as favoured sites of action for the repression of gene expression. The complex interplay of genes and miRNAs brought about by multiplicity and cooperativity was explored. This investigation will aid in elucidating the mechanism of action of miRNAs for the considered genes. The intrinsic network of miRNAs expressed in nervous system and genes associated with ALS may provide rapid and effective outcome for therapeutic applications and diagnosis.

Analyzing a Potential Drug Target N-Myristoyltransferase of Plasmodium falciparum Through In Silico Approaches.

BACKGROUND: Despite concerted global efforts to combat malaria, malaria elimination is still a remote dream. Fast evolution rate of malarial parasite along with its ability to respond quickly to any drug resulting in partial or complete resistance has been a cause of concern among researcher communities. MATERIALS AND METHODS: Molecular modeling approach was adopted to gain insight about the structure and various analyses were performed. Modeller 9v3, Protparam, Protscale, MEME, NAMD and other tools were employed for this study. PROCHECK and other tools were used for stereo-chemical quality evaluation. RESULTS AND CONCLUSION: It was observed during the course of study that this protein contains 32.2% of aliphatic amino acids among which Leucine (9.5%) is predominant. Theoretical pI of 8.39 identified the protein as basic in nature and most of the amino acids present in N-Myristoyltransferase are hydrophobic (46.1%). Secondary structure analysis shows predominance of alpha helices and random coils. Motif analyses revealed that this target protein contains 2 signature motifs, i.e., EVNFLCVHK and KFGEGDG. Apart from motif search, three-dimensional model was generated and validated and the stereo-chemical quality check confirmed that 97.7% amino acid residues fall in the core region of Ramachandran plot. Molecular dynamics simulation resulted in maximum 1.3 Å Root Mean Square Deviation (RMSD) between the initial structure and the trajectories obtained later on. The template and the target molecule has shown 1.5 Å RMSD for the C alpha trace. A docking study was also conducted with various ligand molecules among which specific benzofuran compounds turned out to be effective. This derived information will help in designing new inhibitor molecules for this target protein as well in better understanding the parasite protein.

In silico characterization of Shikimate Kinase of Shigella flexneri: a potential drug target.

Shigella flexneri is a major pathogen responsible for Shigellosis causing massive morbidity among young population and imposes huge socio-economic burden. In this study, Shikimate Kinase (SK) from S. flexneri was characterized in silico and disordered regions were predicted. Motifs and domains were calculated using computational tools. A three dimensional model of Shikimate Kinase of S.flexneri was constructed using Shikimate Kinase of E.coli (PDBID: 1KAG_A) as template by comparative modeling approach. Molecular dynamics calculations were carried out to check the stable conformation embedded in water sphere with least RMSD possible. Perusal of backbone conformation of the modeled structure by PROCHECK revealed that more than 98% of the residues fell in the allowed regions and ERRAT results confirmed good quality of modeled structure. Active site and its important residues were predicted for the derived model. Disulphide bridges were estimated by computational method and most probable pattern of cysteine residues was found in the pairs 8-22. Results of this study will shed light on the structural aspects of Shikimate Kinase of S. flexneri and will aid in rational drug designing.

Interaction map and selection of microRNA targets in Parkinson's disease-related genes.

Parkinson's disease (PD) is a complex multigenic neurodisorder frequently occurring in elderly persons. To investigate noncoding tiny microRNA mediated gene regulation, miRanda (version 1.0b) was used to predict human miRNA target sites on selected 29 genes related to PD. To verify output generated from miRanda, a similar analysis was performed only for microRNA target sites in 3'UTR using TargetScan (version 5.1). Data extracted by miRanda elucidates the mode of microRNA action based on the location of target sites in the Parkinson genes. Sites prone to action of multiple miRNAs were identified as "hot spots." Important properties of each miRNA including multiplicity and cooperativity appear to contribute towards a complex interplay between miRNAs and their targets. Two sets of predicted results were explored for the occurrence of target sites of 112 miRNAs expressed in midbrain. Overall, convergence of results predicted by two algorithms revealed that 48 target sites for midbrain-specific miRNA occur in close proximity in 9 genes. This study will pave a way for selection of potential miRNA candidates for Parkinson's disease-related genes for quick therapeutic applications and diagnosis.

Structural model of the Plasmodium falciparum thioredoxin reductase:a novel target for antimalarial drugs.

BACKGROUND: Malaria, a scourge of mankind, imposes a huge socioeconomic burden in tropical countries. Emergence of multi-drug resistant malarial parasites impels us to explore novel drug targets. Thioredoxin reductase is a promising antimalarial drug target. METHODS: The Thioredoxin reductase enzyme of Plasmodium falciparum was characterized in silico and protein disorder was predicted using available online tools. Since the crystal structure of Thioredoxin reductase of P. falciparum is not yet available, its three-dimensional structure was constructed by homology modeling using the high-resolution Thioredoxin reductase type 2 of mouse as a template. Obtained model was further refined by Molecular Dynamics (MD). RESULTS: The model was stable during the simulation with the equilibrium root mean square deviation (RMSD) value of 1.2 A. Stereochemical evaluation revealed that 99.1% residues of the constructed model lie in the most favoured and allowed regions, thus, indicating a good quality model. CONCLUSION: Results of this study will provide an insight into the structure of the Thioredoxin reductase of malarial parasite and aid in rational drug designing.

Comparative characterization of commercially important xylanase enzymes.

Xylanase is an industrially important enzyme having wide range of applications especially in paper industry. It is crucial to gain an understanding about the structure and functional aspects of various xylanases produced from diverse sources. In this study, a bioinformatics and molecular modeling approach was adopted to explore properties and structure of xylanases. Physico-chemical properties were predicted and prediction of motifs, disulfide bridges and secondary structure was performed for functional characterization. Apart from these analyses, three dimensional structures were constructed and stereo-chemical quality was evaluated by different structure validation tools. Comparative catalytic site analysis and assessment was performed to extract information about the important residues. Asn72 was found to be the common residue in the active sites of the proteins P35809 and Q12603.

Application of Kohonen maps for solving the classification puzzle in AGC kinase protein sequences.

Availability of enormous number of sequences in public domain databases warrants the need for effective tools for clustering and classification of such data. AGC protein kinase family is known to contain many enzymes involved in important cellular processes. In the present study, 21 important physicochemical parameters were calculated for 115 sequences of AGC kinase family belonging to mouse and human. Kohonen maps, also known as Self Organizing Maps (SOM) were employed for the identification of clusters of similar sequences, projection and visualization of high dimensional data spaces owing to their capability of preserving topological relationships between the features. This simplistic approach can provide a method not only for studying intricate interplay of features and minute differences even in the members of same protein family but also for recognition of certain unifying common features. Each cluster obtained using SOM in this study has a distinct characteristic that sets it apart from the other clusters.

Database management system for the control of malaria in Arunachal Pradesh, India.

UNLABELLED: The Arunachal Pradesh state in India is epidemic for malaria, caused by P.vivax and P.falciparum. Despite the implementation of several control strategies, the outbreak of malaria in the state is mainly due to lack of proper information regarding the disease. Hence, we completed a database to help implement appropriate control strategy for the public health officials in Arunachal Pradesh. AVAILABILITY: www.envisiict.org.