Plasmodium falciparum causing malaria is yet reigning against drug design community when it comes to survival and defense. Continuous evolution and drug resistant character is foremost basis of parasite’s versatility. 3-oxoacyl-acyl-carrier protein synthase I/II in Plasmodium falciparum is discovered decisive in fatty acid synthesis machinery. Objectives of enzyme inhibition need structural characterization from its 3D structure. In present studies molecular modeling of 3-oxoacyl-acyl-carrier protein synthase I/II is achieved using in silico comparative modeling. ICM Molsoft algorithm was adopted for comparative modeling which provides an accurate and efficient module to build loops and side chains found non-identical in sequence. Energy parameters fell in thermodynamically stability zone. Modeled structure revealed appreciable measures when validated. Ramachandran plot signified the present work undertaken through conformational parameters _ (phi) and _ (psi) angles calculated from model with 83.2% residues in most favoured region. Further PROCHECK results confirmed acceptance of model through main and side-chain values. Root mean square distance of planarity found below 0.01. Beside some bad contacts, bond angles and bond lengths confer qualitative part of work. Structure of 3-oxoacyl-acyl-carrier protein synthase I/II can be important tool for structure based drug designing techniques to impel the search of new efficient inhibitors. Comparison of similar structures of parasite can further reveal mutational trends to study their evolution patterns.

DNA-synthesis, DNA-repair, and DNA imprinting processes require efficient conversion of homocysteine to methionine. This methylation is catalyzed by methylentetrahydrofolate reductase through reduction of 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate. Normal DNA synthesis is considered critical for physiological functions of body. The enzyme is coded by the gene with the symbol MTHFR on chromosome 1 location p36.3 in humans. At least 24 mutations in the MTHFR gene have been identified in people with homocystinuria. There is DNA sequence variants (genetic polymorphisms) associated with this gene. Two of the most investigated are C677T (rs1801133) and A1298C (rs1801131) single nucleotide polymorphisms (SNP). Mutations at C677T and A1298C which confer amino acid substitution Ala222Val and Glu429Ala respectively with a considerable reduced activity. This polymorphism and mild hyperhomocysteinemia are associated with neural tube defects in offspring, arterial and venous thrombosis, and cardiovascular disease. 677TT individuals are at a decreased risk for certain leukemia and colon cancer. The MTHFR gene could be one of the factors of overall schizophrenia risk. In silico analysis now has added important and wide range applications to proteomics from structure modeling to its functional levels. Several algorithms have been suggested from many authors to bring an accurate modeling at its best but ultimately every protein has its own variant features to be treated by the same algorithm. Studies in proteomics through computational techniques need complements between critical requirement for a protein and features available in an algorithm. Comparative modeling is now bridging the gap between available sequences and structures modeled with accuracy. Effective refinement techniques made it capable of driving models toward native structure. Structure of MTHFR can assist the study of involvement of this enzyme in the disorders and can provide better level of Understanding about structural aspects of it. We have modeled wild type and mutated type MTHFR using comparative modeling and structure validation has given appreciable values. This work can further account for the structure based drug design community in the search of MTHFR inhibitors.

The linear multi-objective capacitated transportation problem in which the supply and demand constraints are equality type, capacity restriction on each route are specified and the objectives are non commensurable and conflict in nature. The fuzzy programing technique (Linear, Hyperbolic and Exponential) is used to find optimal compromise solution of a multi-objective capacitated transportation problem has been presented in this paper. An example is illustrate the methodology. Also comparision is taken out, using same example.

Leprosy or Hansen disease is a slowly progressive infection caused by Mycobacterium leprae, affecting the skin and peripheral nerves and resulting in disabling deformities. Studies show that M. leprae binds to nasal epithelial cells in human after binding to fibronectin, using Beta-integrins (ITGB1) as receptors. The corresponding component on M. leprae, which binds to fibronectin, Fibronectin Attachment Protein (FAP), has been identified .The 3D structure of both the human (ITGB1) and M.leprae (FAP-L) protein involved in this mechanism are modeled using homology modeling. Hemolin, an insect-immune protein belonging to the immunoglobulin superfamily is found to have an efficient defense system against bacterial infections. So this protein is selected and its 3D structure is modeled too. The active compound Anacardic acid of marine brown alga Fucus vesiculosus and the compound Polyhydroxylated fucophlorethol of Anacardium occidentale is found to have antibacterial activity. Their structure was drawn using Chemsketch, combined and converted to *.pdb. The combination is docked with Hemolin protein. This docked compound is again redocked with the human ITGB1 protein using GRAMM-X. Again, the combination (Anacardic acid and Polyhydroxylated fucophlorethol) was docked with M. leprae which proves that the combination can be effective in curing Hansen disease.

Oxidative stress in plants causes the induction of several enzymes, including superoxide dismutase (EC 1.15.1.1), ascorbate peroxidase (EC 1.11.1.11) and glutathione reductase (EC 1.6.4.2). The first two are responsible for converting superoxide to H2O2 and its subsequent reduction to H2O, and the third is involved in recycling of ascorbate. Glutathione peroxidases (GPXs, EC 1.11.1.9) are a family of key enzymes involved in scavenging oxyradicals in animals. Only recently, indications for the existence of this enzyme in plants were reported. Genes with significant sequence homology to one member of the animal GPX family, namely phospholipid hydroperoxide glutathione peroxidase (PHGPX), were isolated from several plants. In this paper we report the homology modelling of the glutathione peroxidase protein from Ricinus communis L. and its interactions with its two substrates hydrogen peroxide and glutathione. Specific sites of interaction were identified and ligand binding pockets were also screened.

Alzheimer’s disease is an incurable, degenerative, and terminal disease. It is associated with mutations in Amyloid Precursor Protein (APP), Presenilin 1 (PS1), Presenilin 2 (PS2), or Apolipoprotein E (APOE). 3D structures of these 4 proteins were generated using Homology Modeling. Active compounds of medicinal herbs- Canscora decussate, Nardostachys jatamansi and Mucuna pruriens were selected as these three herbs have properties of memory enhancement. Chemical structures of the active component of these herbs were drawn using chemsketch, combined & converted to *.pdb. The four proteins were successfully docked with Canscora decussate- Nardostachys jatamansi –Mucuna pruriens’s active component combination.

In the present paper nine molecules has been docked in the Acyl-CoA carboxylase carboxyltransferase domain 5 (AccD5) at GLY-193, GLY-194, GLY-434, ALA-435 pocket with very low energies. Six binding site on the crystallographic structure of AccD5 are examined with the structure-based design program DOCK. The active compounds found are polycyclic (aromatic as well as aliphatic) and nitrogen heterocyclic. Each molecule gave a good number of conformations showing the flexible behavior of the ligand. The total energy of receptor-ligand complexes has also been calculated.

There has been a steady rise in the number of patients suffering from Alzheimer’s disease (AD) all over the world. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. The patient’s records are collected from National Institute on Aging, USA. The Sample consisted of initial visits of 496 subjects seen either as control or as patients. Patients were concerned about their memory at the National Institute on Aging. It also consisted of patients and caregiver interviews. This research work presents different models for the classification of different stages of Alzheimer’s disease using various machine learning methods such as Neural Networks, Multilayer Perceptron, Bagging, Decision tree, CANFIS and Genetic algorithms. The classification accuracy for CANFIS was found to be 99.55% which was found to be better when compared to other classification methods. Based on the outcome of classification accuracies, various management and treatment strategies such as pharmacotherapeutic and non pharmacotherapeutic interventions for mild, moderate and severe AD were elucidated, which can be of enormous use for the medical professionals in diagnosis and treatment of AD.

Researches on archaeal microorganisms continue to excite the scientific community. Their unique adaptations that cater to hypersaline, hyperthermic, and hypothermic circumstances have incited research to manipulate those attributes for use in virtually every aspect of life. Adaptations in membrane, enzymes, and protein structures and components have potential applications in areas including electronics, agriculture, aquaculture, medicine, pharmaceuticals, food science, and nutrition. Although the time and effort required to new find archaeal homologues may be great, many believe that the economic and environmental benefits of such a breakthrough would be considerable enough to outweigh the challenges. An analysis of the archeal genome Aeropyrum pernix, showed that certain regions earlier thought to be ‘non-coding’ have significant sequence similarity to other protein sequences from archaea and other species. The available sequence analysis tools were used to identify a number of potential protein coding regions in these putative ‘non coding’ regions. We could identify 907 such regions and 282 of them apparently code for proteins present in archeal or other species. The remaining 625 regions are mostly start /stop conflicts. Of the 282 protein coding regions, only 64 code for proteins with homologues of known function. A good number of proteins show homology to proteins that are important for the survival of the organism. Hence these novel regions may be referred as homologues to coding regions. In addition Genome sequence collections should be regularly checked to improve gene prediction by sequence similarity and greater effort is required to make gene definitions consistent across related species.

Protein identification using mass spectrometry is an indispensable tool for proteomics which in recent days has evolved to give better understanding of the biology of cell and its functioning. Proteomics has wide application in diagnosing diseases such as cancer, Alzheimer’s disease etc. The data obtained from the diagnostic tools like LC-MS is to be interpreted accurately so as to obtain the correct qualitative and quantitative information about the peptides present in the biological sample. Such interpretation requires and exhaustive knowledge and review about different tools that can be employed and their comparison. This article focuses on comparison of different proteomic tools available for the MS data processing and interpretation. The accuracy demanded during protein identification can be fulfilled by tag based approaches, than PMF or PFF systems. Although, there is a need of standardized matrices for the comparison of the protein identification tools, identifying the single best package for each application from the available literature is at present extremely difficult as each package has its own advantage over other. The datasets and thresholds used in these kinds of comparisons have a critical importance on the outcome of such experiments, and that the high variability in machine and experimental setups complicates analysis. The state of data standards and lack of benchmarks therefore makes it difficult to make an effective comparison. While the increasing availability of data in public repositories and tightening standards will no doubt ameliorate the problem, until this basic benchmarking problem is overcome, no single package or approach can conclusively be declared to outperform all others, expect, perhaps, in the specific circumstances used in particular studies.

The enormous amount of data resources are available on web, this makes integrative Bioinformatics research more important in life sciences research. Bioinformatics is about searching biological databases, comparing sequences, looking at protein structures, and solving biological and biomedical problems using a computer. Huge amount of online bioinformatics tools and data are available, so systems integration has become very important for further progress. Today, bioinformatics hosts heavily on the Web. But the Web is geared towards human interaction rather than automated processing. The approach of a Semantic Web facilitates this automation by annotating web content and by applying adequate reasoning languages. Semantic Web infrastructure utilizes the scalable Oracle Resource Description Framework (RDF) Data Model as the repository and Seamark Navigator for browsing and searching the data.