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Showing posts with the label QSAR

Workshop - "In-silico Drug Discovery Based on the Integration of Bioinformatics and Chemoinformatics"

The Workshop Drug discovery is an expensive and time taking process and therefore new approaches based on chemoinformatics and bioinformatics are being adopted.The knowledge of the 3D structures of protein targets is now playing a major role at all stages of drug discovery. The distinct nature of biological and chemical information requires the integrated capabilities of both bioinformatics and chemo-informatics to decipher existing and hidden relationships. Bioinformatics and chemo-informatics have largely evolved independently from biology and chemistry. Cheminformatics is an inter-disciplinary subject of storage, processing and retrieval of chemical information. Bioinformatics and chemoinformatics have significantly assisted in lead optimization, fingerprinting, pharmacophore designing, target identification, QSAR and their application can lead to discovery of new molecules. Molecular modeling using 3D graphics and optimization techniques helps the scientists to understand how drug...

Artificial neural networks-based approach to design ARIs using QSAR for diabetes mellitus

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...

Protein Structure and Drug Discovery Workshop

"Protein Structure and Drug Discovery" Workshop – Sept 30th to Oct 1st 2010 La Jolla, CA. Please join us at MolSoft's (   www.molsoft.com   ) "Protein Structure and Drug Design" Workshop in La Jolla, California USA. For more information and a registration form see:   www.molsoft.com/training.html This workshop is suitable for chemists and biologists who would like to learn more about computational drug discovery and bioinformatics. No prior knowledge in this field is required to participate. The workshop is presented by Prof. Ruben Abagyan (University of California San Diego) and Dr. Maxim Totrov (MolSoft). Price: $349 (Academics) $749 (Commercial) The workshops will consist of lectures, demonstrations, and "hands-on" computational experiments and will cover the following topics: - How To Display Fully Interactive 3D Molecules in PowerPoint and the Web - Sequence and Protein Structure Analysis - Protein Modeling and Simulations - Structure...