Bio Saga Blog - A Chronicle of Life Sciences & Informatics

Greetings from Department of Bioinformatics, Alagappa University It gives us immense pleasure to announce that the Department of Bioinformatics, Alagappa University, Karaikudi is organizing 4th National Symposium cum Workshop on “Recent Trends in Structural Bioinformatics and Computer Aided Drug Design [SBCADD’2012]” during Feb 20th – 23rd, 2012. The motive of the National symposium cum workshop is to provide theoretical and practical exposure of Structural Bioinformatics and Computer Aided Drug Design among academicians and technocrats in order to cater the industrial and academic need. We have invited eminent personalities from reputed organizations, who will enlighten the participants in the related fields. Please download the brochure containing information and registration details along with this invitation for your kind perusal. We extend humble invitation to you and your colleagues to participate actively in the workshop and make it a big success. It will be appreciated if you c...

This is no Sci-Fi but reel to real! Yes we can in deed program the DNA for real Now!  Bioinformatics scientists have built two logic gates for what they hope will become a new programming language for drug design as well as chemical and agricultural product engineering. The accomplishment seems hardly noteworthy except that these logic gates are made of E. coli. The two computational switches are based on two strains of the common bacterium. Researchers are now working to assemble them to perform computations. This genetic programming software would resemble any other programming language, says Kevin Clancy, senior staff scientist for bioinformatics at Life Technologies Corp. The Carlsbad, CA, company is funding the work, which is being done by researchers at the UC San Francisco School of Pharmacy. Life Tech plans to commercialize the technology. The software would convert instructions into a DNA sequence to be inserted into a bacterial, yeast or mammal cell. "It allows you ...

In this article, in the first part, we propose an artificial neural network-based intelligent technique to determine the quantitative structure-activity relationship (QSAR) among known aldose reductase inhibitors (ARIs) for diabetes mellitus using two molecular descriptors, i.e., the electronegativity and molar volume of functional groups present in the main ARI lead structure. We have shown that the multilayer perceptron-based model is capable of determining the QSAR quite satisfactorily, with high  R -value. Usually, the design of potent ARIs requires the use of complex computer docking and quantum mechanical (QM) steps involving excessive time and human judgement. In the second part of this article, to reduce the design cycle of potent ARIs, we propose a novel ANN technique to eliminate the computer docking and QM steps, to predict the total score. The MLP-based QSAR models obtained in the first part are used to predict the potent ARIs, using the experimental data reported by Hu...