In Silico Structural and Functional Annotation of Hypothetical Proteins of Vibrio cholerae O139

In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

In-Silico Drug Design: A revolutionary approach to change the concept of current Drug Discovery Process.

Computational methods play a central role in modern drug discovery process. It includes the design and management of small molecule libraries, initial hit identification through virtual screening, optimization of the affinity as well as selectivity of hits and improving the physicochemical properties of the lead compounds. In this review article, computational drug designing approaches have been elucidated and discussed. The key considerations and guidelines for virtual chemical library design and whole drug discovery process. Traditional approach for discovery of a new drug is a costly and time consuming affair besides not being so productive. A number of potential reasons witness choosing the In-silico method of drug design to be a more wise and productive approach. There is a general perception that applied science has not kept pace with the advances of basic science. Therefore, there is a need for the use of alternative tools to get answers on efficacy and safety faster, with more certainty and at lower cost. In-silico drug design can play a significant role in all stages of drug development from the initial lead designing to final stage clinical development.

Curent advances and stretegies for reducing the side effects of radiation therapies used for various types of cancers.

Cancer originates from the abnormal expression or activation of positive regulators and functional suppression of negative regulators. The World Health Organization (WHO) estimates that 84 million people will die of cancer between 2005 and 2015 without intervention. Research suggests that one-third of cancer deaths can be avoided through prevention. Major cancer treatment modalities are surgery, radiation therapy and chemotherapy. Radiation therapy is an important cancer treatment method and is used for approximately 50% of all cancer patients with varying success. Therapy uses high-energy waves or particles to destroy cancer cells. It can be used basically for three main reasons: to achieve high radiation dose into tumors; minimizing dose into surrounding normal tissues; to avoid complications as far as possible. The recent advances in this treatment method have led to the improvement in cancer death statistics. It can also be combined with surgery or chemotherapy for better results. This review covers general applications, various side effects/agents and factors affecting to get rid of these effects and strategies to improve radiation therapy.

Fish antifreeze proteins: Computational analysis and physicochemical characterization.

Antifreeze proteins (AFPs) protect organisms from freezing and shows great diversity in structure, and they have been found in a variety of organisms. In this study, a total of 15 antifreeze proteins of fish were selected where they represent distinct physicochemical and structural features. The present paper uses bioinformatics approach to describe the physiochemical, functional and structural properties of Antifreeze proteins. Several Physico-chemical properties such as pI, EC, AI, GRAVY and instability index are computed and provide data about these proteins and their properties. The result of primary structure analysis infers that, fish antifreeze proteins are mostly hydrophobic. Disulfide bridges and secondary structures were analyzed using CYS_REC and SOPMA respectively. The three dimensional structure of Antifreeze proteins is predicted by using three homology modeling server Geno3D, Swiss-model and CPHmodels. The model was evaluated with PROCHECK, WHAT IF, and ProSA programs. Model visualization and analysis was done with Pymol. These structures will provide a good foundation for functional analysis of experimentally derived crystal structures.

Fish antifreeze proteins: Computational analysis and physicochemical characterization.

Antifreeze proteins (AFPs) protect organisms from freezing and shows great diversity in structure, and they have been found in a variety of organisms. In this study, a total of 15 antifreeze proteins of fish were selected where they represent distinct physicochemical and structural features. The present paper uses bioinformatics approach to describe the physiochemical, functional and structural properties of Antifreeze proteins. Several Physico-chemical properties such as pI, EC, AI, GRAVY and instability index are computed and provide data about these proteins and their properties. The result of primary structure analysis infers that, fish antifreeze proteins are mostly hydrophobic. Disulfide bridges and secondary structures were analyzed using CYS_REC and SOPMA respectively. The three dimensional structure of Antifreeze proteins is predicted by using three homology modeling server Geno3D, Swiss-model and CPHmodels. The model was evaluated with PROCHECK, WHAT IF, and ProSA programs. Model visualization and analysis was done with Pymol. These structures will provide a good foundation for functional analysis of experimentally derived crystal structures.