PCV: An Alignment Free Method for Finding Homologous Nucleotide Sequences and its Application in Phylogenetic Study.

Online retrieval of the homologous nucleotide sequences through existing alignment techniques is a common practice against the given database of sequences. The salient point of these techniques is their dependence on local alignment techniques and scoring matrices the reliability of which is limited by computational complexity and accuracy. Toward this direction, this work offers a novel way for numerical representation of genes which can further help in dividing the data space into smaller partitions helping formation of a search tree.

In-silico identification of inhibitors against mutated BCR-ABL protein of chronic myeloid leukemia: a virtual screening and molecular dynamics simulation study.

Aberrant and proliferative expression of the oncogene BCR-ABL in the bone marrow cells had been proven as the prime cause of chronic myeloid leukemia (CML). It has been established that tyrosine kinase domain of BCR-ABL protein is a potential therapeutic target for the treatment of CML. Imatinib is considered as a first-generation drug that can inhibit the enzymatic action by inhibiting the ATP binding with BCR-ABL protein.

Exploring dual inhibitors for STAT1 and STAT5 receptors utilizing virtual screening and dynamics simulation validation.

Signal transducer and activator of transcription (STAT) proteins are latent cytoplasmic transcription factors that transduce signals from cytokines and growth factors to the nucleus and thereby regulate the expression of a variety of target genes. Although mutations of STATs have not been reported in human tumors but the activity of several members of the family, such as STAT1 and STAT5, is deregulated in a variety of human carcinoma. STAT1 and STAT5 share a structural similarity with a highly conserved SH2 domain which is responsible for the activation of STAT proteins on interaction with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization.

Identification of Dual Natural Inhibitors for Chronic Myeloid Leukemia by Virtual Screening, Molecular Dynamics Simulation and ADMET Analysis.

Chronic myeloid leukemia (CML) is a disease of bone marrow stem cells caused by excessive growth and accumulation of granulocytes in the blood. Aberrant expression of the BCR-ABL proteins in bone marrow stem cells have found out in 95 % cases of CML. Tyrosine Kinase domains (SH2 and SH3) of BCR-ABL proteins are the potent targets to inhibit the process.

Exploration of new drug-like inhibitors for serine/threonine protein phosphatase 5 of Plasmodium falciparum: a docking and simulation study.

Protein phosphorylation is an important mechanism that implicates in physiology of any organism including parasitic protozoa. Metallic protein Ser/Thr protein phosphatase 5 (PP5) controls various cellular signaling pathways of Plasmodium falciparum. The structure and inhibitory mechanism of PP5 in P.

Virtual Screening of compounds to 1-deoxy-Dxylulose 5-phosphate reductoisomerase (DXR) from Plasmodium falciparum.

The 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) protein (Gen Bank ID AAN37254.1) from Plasmodium falciparum is a potential drug target. Therefore, it is of interest to screen DXR against a virtual library of compounds (at the ZINC database) for potential binders as possible inhibitors.

Multimodal fusion framework: a multiresolution approach for emotion classification and recognition from physiological signals.

The purpose of this paper is twofold: (i) to investigate the emotion representation models and find out the possibility of a model with minimum number of continuous dimensions and (ii) to recognize and predict emotion from the measured physiological signals using multiresolution approach. The multimodal physiological signals are: Electroencephalogram (EEG) (32 channels) and peripheral (8 channels: Galvanic skin response (GSR), blood volume pressure, respiration pattern, skin temperature, electromyogram (EMG) and electrooculogram (EOG)) as given in the DEAP database. We have discussed the theories of emotion modeling based on i) basic emotions, ii) cognitive appraisal and physiological response approach and iii) the dimensional approach and proposed a three continuous dimensional representation model for emotions.

Designing allosteric modulators for active conformational state of m-glutamate G-protein coupled receptors.

G-protein coupled receptors (GPCRs) are found to be attractive drug targets for the treatment of various neuronal diseases. Allosteric modulators have their role in enhancing or suppressing the effect of glutamate on mGluRs. Structure of mGluR1 was generated with the help of Modeller software by considering human B2-adrenergic GPCR protein as template.

A prediction model for oral bioavailability of drugs using physicochemical properties by support vector machine.

Objective: A computational model for predicting oral bioavailability is very important both in the early stage of drug discovery to select the promising compounds for further optimizations and in later stage to identify candidates for clinical trials. In present study, we propose a support vector machine (SVM)-based kernel learning approach carried out at a set of 511 chemically diverse compounds with known oral bioavailability values.

Material And Methods: For each drug, 12 descriptors were calculated.

A comparative study of support vector machine, artificial neural network and bayesian classifier for mutagenicity prediction.

Mutagenicity is the capability of a chemical to carry out mutations in genetic material of an organism. In order to curtail expensive drug failures due to mutagenicity found in late development or even in clinical trials, it is crucial to determine potential mutagenicity problems as early as possible. In this work we have proposed three different classifiers, i.