MODELING AND DOCKING STUDIES OF BIOLOGICAL DATA STAT4 INVOLVED IN CANCER CHUKKA SANTHAIAH 1 & A.RAMA MOHAN REDDY 2 1 Department of Computer Science and Engineering, S. V. University, Tirupati, Andhra Pradesh, India 2 Department of Computer Science and Eng, Head & Prof of C.S.E Dept, S.V.University, Tirupati, Andhra Pradesh, India ABSTRACT The amount and variety of data in natural sciences increases rapidly. Data abstraction, Data manipulation and Pattern discovery techniques are of great need in order to deal with such large quantities. Integration between different sources of data is also of major interest, as complex relations may arise. Biology is a good example of a field that provides extensive, highly variable and multi-sources data. The technical advances achieved by the genomics, metabolomics, transcriptomics and proteomics technologies in recent years have significantly increased the amount of data that are available for biologists to analyze different aspects of an organism. Bioinformatics is an interdisciplinary research area at the interface between computer science and biological science. In order to identify a better drug for cancer, STAT4 (signal transducers and activators of transcription) protein was choosed as target. A three dimensional (3D) model of the STAT4 is generated based on the crystal structure of 1Y1U template by using Modeller software. With the aid of the molecular mechanics and molecular dynamics methods, the final model is obtained and is further assessed by Procheck and Verify 3D graph programs, which showed that the final refined model is reliable. With this model, a flexible docking study is performed with different drugs. From the docking studies, we also suggest that MET3, ARG4, THR5 in STAT4 domain are three important residues in binding. The hydrogen bonding interactions play an important role for stability of the complex. Our results may be helpful for further experimental investigations. KEYWORDS: Biological Data, Cancer, Docking Studies, Naphazoline, Modeling and STAT4 INTRODUCTION Bioinformatics differs from a related field known as computational biology. Bioinformatics is limited to sequence, structural, and functional analysis of genes and genomes and their corresponding products and is often considered computational molecular biology. However, computational biology encompasses all biological areas that involve computation. For example, mathematical modeling of ecosystems, population dynamics, application of the game theory in behavioral studies, and phylogenetic construction using fossil records all employ computational tools, but do not necessarily involve biological macromolecules. There are a variety of other advanced skill sets that can add value to this background: molecular evolution and systematics, physical chemistry kinetics, thermodynamics and statistical mechanics, statistics and probabilistic methods, database design and implementation, algorithm development, molecular biology laboratory methods and others. A understanding of biological processes has grown and deepened, it isn't surprising, then, that the disciplines of computational biology and, more recently, bioinformatics, have evolved from the intersection of classical biology, mathematics, and computer science. International Journal of Computer Science and Engineering (IJCSE) ISSN 2278-9960 Vol. 2, Issue 1, Feb 2013, 19-28 © IASET