Ribonucleotide Reductase (RNR) is an enzyme responsible for the reduction of ribonucleotides to their corresponding Deoxyribonucleotides (DNA), which is a building block for DNA replication and repair mechanisms. The key role of RNR in DNA synthesis and control in cell growth has made this an important target for anticancer therapy. Increased RNR activity has been associated with malignant transformation and tumor cell growth. In recent years, several RNR inhibitors, including Triapine, Gemcitabine and GTI-2040, have entered the clinical trials. Our current work focuses on an attempted to dock this inhibitors Flavin and Phenosafranine to curtail the action of human RNR2. The docked inhibitor Flavin and Phenosafranine binds at the active site with THR176, which are essential for free radical formation. The inhibitor must be a radical scavenger to destroy the tyrosyl radical or iron metal scavenger. The iron or radical site of R2 protein can react with one-electron reductants, whereby the tyrosyl radical is converted to a normal tyrosine residue. However, compounds such as Flavin and Phenosafranine were used in most of the cases to reduce the radical activity. The docking study was performed for the crystal structure of human RNR with the radical scavengers Flavin and Phenosafranine to inhibit the human RNR2. This helps to understand the functional aspects and also aids in the development of novel inhibitors for the human RNR2.

The massive development of biodiversity related information systems over the WWW (World Wide Web) has created much excitement in recent years. These arrays of new data sources are counterbalanced by the difficulty in knowing their location and nature. However, biologists and computer scientists have started to pull together in a rising tide of coherence and organization to address this issue. The fledging field of biodiversity informatics is expected to deliver major advances that could turn the WWW into a giant global biodiversity information system. The present paper briefly reviews the databases in preserving the biodiversity data.

The rapidly emerging field of comparative genomics has yielded dramatic results. Comparative genome analysis has become feasible with the availability of a number of completely sequenced genomes. Comparison of complete genomes between organisms allow for global views on genome evolution and the availability of many completely sequenced genomes increases the predictive power in deciphering the hidden information in genome design, function and evolution. Thus, comparison of human genes with genes from other genomes in a genomic landscape could help assign novel functions for un-annotated genes. Here, we discuss the recently used techniques for comparative genomics and their derived inferences in genome biology.

The neuropeptide galanin comes under the powerful and versatile modulators of classical neurotransmitters and is present in brain tissues, which are intimately involved in epileptogenesis. It acts as appealing targets for studying basic mechanisms of seizure initiation and arrest, and for the development of novel approaches for various neurodegenerative diseases. Galanin is widely distributed in the mammalian brain which controls various processes such as sensation of pain, learning, feeding, sexual behaviour, carcinogenesis, pathophysiology of neuroendocrine tumors and others. The function of galanin can be exploited through its interaction with three G-protein coupled receptors subtypes such as GalR1, GalR2 and GalR3. The N-terminal region of galanin comprises about highly conserved 15 amino acid residues, which act as the crucial region for agonist-receptor binding. We have constructed a theoretical structural model for the N-terminal region of galanin from Homo sapiens by homology modeling. The stereochemistry of the model was checked using PROCHECK. The functionally conserved regions were identified by surface mapping of phylogenetic information generated by online web algorithm ConSurf. The docking studies on the pharmacologically important galanin receptors with the theoretical model of N-terminal region of galanin predicted crucial residues for binding which would be useful in the development of novel leads for neurodegenerative disorders.

In recent years, virtual learning is growing rapidly. Universities, colleges, and secondary schools are now delivering training and education over the internet. Beside this, resources available over the WWW are huge and understanding the various techniques employed in the field of Bioinformatics is increasingly complex for students during implementation. Here, we discuss its importance in developing and delivering an educational system in Bioinformatics based on e-learning environment.

The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.