K. Satyamoorthy, Ph.D.
Director, Life Sciences Centre, Manipal University, India
Epigenetic Changes due to DNA Methylation in Human Epithelial Tumors
Extensive global hypomethylation in the genome and hypermthylation of selective tumor specific suppressor genes appears to be a hallmark of human cancers. Data suggests that hypermethylation of promoter region in genes is more closely related to subsequent gene expression; contrary to gene-body DNA methylation. The intricate balance between these two may contribute to the progressive process of development, differentiation and carcinogenesis. Epigenetic changes encompass, apart from DNA methylation, chromatin modifications through post-translational changes in histones and control by miRNAs. At the genome level, effects from these are compounded by copy number variations (CNVs) which may ultimately influence protein functions. From clinical perspective, changes in DNA methylation occur very early which are reversible and are influenced by environmental factors. Therefore, these can be potential resource for identifying therapeutic targets as well as biomarkers for early screening of cancer. Our current efforts in profiling genome wide DNA methylation changes in oral, cervical and breast cancers through DNA methylation microarray analysis has revealed number of alterations critical for survival, progression and metastatic behavior of tumors. Bioinformatics and functional analysis revealed several key regulatory molecules controlled by DNA methylation and suggests that DNA methylation changes in several CpG islands appear to co-segregate in the regions of miRNAs as well as in the CNVs. We have validated the signatures for methylation of CpG islands through bisufite sequencing for essential genes in clinical samples and have undertaken transcriptional and functional analysis in tumor cell lines. These results will be presented.
Kal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA
A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry
With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways. Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists. As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery. While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories. Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site. As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty. In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases. We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase. We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.
Jeff Perry, Ph.D.
Assistant Professor, University of California, Riverside
Combined Crystallography and SAXS Methods for Studying Macromolecular Complexes
Recent developments in small angle X-ray scattering (SAXS) are rapidly providing new insights into protein interactions, complexes and conformational states in solution, allowing for detailed biophysical quantification of samples of interest1. Initial analyses provide a judgment of sample quality, revealing the potential presence of aggregation, the overall extent of folding or disorder, the radius of gyration, maximum particle dimensions and oligomerization state. Structural characterizations may include ab initio approaches from SAXS data alone, or enhance structural solutions when combined with previously determined crystal/NMR domains. This combination can provide definitions of architectures, spatial organizations of the protein domains within a complex, including those not yet determined by crystallography or NMR, as well as defining key conformational states. Advantageously, SAXS is not generally constrained by macromolecule size, and rapid collection of data in a 96-well plate format provides methods to screen sample conditions. Such screens include co-factors, substrates, differing protein or nucleotide partners or small molecule inhibitors, to more fully characterize the variations within assembly states and key conformational changes. These analyses are also useful for screening constructs and conditions that are most likely to promote crystal growth. Moreover, these high throughput structural determinations can be leveraged to define how polymorphisms affect assembly formations and activities. Also, SAXS-based technologies may be potentially used for novel structure-based screening, for compounds inducing shape changes or associations/diassociations. This is addition to defining architectural characterizations of complexes and interactions for systems biology-based research, and distinctions in assemblies and interactions in comparative genomics. Thus, SAXS combined with crystallography/NMR and computation provides a unique set of tools that should be considered as being part of one’s repertoire of biophysical analyses, when conducting characterizations of protein and other macromolecular interactions.
1 Perry JJ & Tainer JA. Developing advanced X-ray scattering methods combined with crystallography and computation. Methods. 2013 Mar;59(3):363-71.
