Beat the intellectual heat and invigorate yourself with a Delightful Evening tour of Chandigarh after the intense sessions and thought provoking discussions during QbD in Pharma Development World Congress. SELECTBIO cordially invites all conference participants to join us for Chandigarh by Evening Sightseeing Tour on April 17, 2015 in Chandigarh Tourism Open-Roof Double-Decker Tourist Coach. This trip will begin at 05:30 pm and will take about 2 and half hours.
The trip will include visit to Rose Garden, Capitol Complex, Sukhna Lake, Garden of Silence and Terrace Garden.
Ethnicity and Breast Cancer Risk: The Indian Saga & Role of NGS
Conference Talk by Dr. Ahmad
Talk Abstract: Carcinoma of the breast is one of the most prevalent cancers in Indian females, and the incidence of breast cancer has been increasing manifolds in India and so the burden of breast cancer on the Indian healthcare system has been steadily on rising also emphasizing the need for a cost-effective method for early detection of these cancers.
Unfortunately, it has been established that Indian patients develop breast cancer at a younger age than their Caucasian counterparts, the contributions of BRCA1 and BRCA2 (BRCA1/2) mutations in Indians are expected to be different than in Caucasians. Although identification of BRCA1 and BRCA2 has greatly increased our understanding of breast cancer genetics in populations of Western European descent, reports about the role of these genes in Indian patients are still very limited. In the current report results found by using next-generation sequencing (NGS) tools, the prevalence and distribution pattern of BRCA1/2 gene mutations in Indian patients will be discussed, this presentation also aims to present the current status of knowledge about the spectrum of BRCA pathogenic variants in Indian populations.The study highlights how Next-generation sequencing (NGS) based testing increases the sensitivity of mutation detection, and help in identifying patients at high risk of developing cancer. New advances in genomic technologies, such as next-generation sequencing (NGS), allow the sequencing and analysis of genes associated with a disease/cancer efficiently at a significantly lower cost as compared with the traditional methods.
Studies such as these will provide physicians and researchers much-needed evidence on the clinical utility of NGS for incorporation into routine genetic testing in clinical oncology practice and thrust the clinical research.
Road to the Biomarker discovery via NGS-based transcriptomics: a case study
ABSTRACT: One of the key reasons for a slower rate of discovery of new diagnostic or therapeutic molecules, in recent years, is lack of attention to thorough screening and identification of target molecules. If researchers do not identify the right target molecule it can result in failure at later stages of R & D or during clinical trials.
Exploring gene expression profiles is key to biomarker discovery, which in turn is crucial for diagnostics, prognostics, and therapeutics. With the advent of modern techniques such as the microarrays, NGS, and mass spectrophotometry, and parallel bio-IT approaches, there is a higher potential to generate more data and a more meaningful short-listing of potential target molecules. RNA-sequencing particularly offers hope to identify key transcript- and/or protein-isoforms associated with diseases. But the data need to be carefully analyzed and interpreted. This has been a non-obvious challenge. There seems to be a tremendous gap between general biologists, health professionals, molecular biologists, pharmacologists and computational biologists/bioinformaticians. My team has been doing some research in meeting such challenges, at IBAB (www.ibab.ac.in).We earlier developed a simple yet effective computational meta-analysis method. We also carefully compiled public transcriptomic data and developed a few software and databases for better analysis and interpretation of the data. Using the newly developed methods, we identified a list of genes and specific alternatively spliced forms of transcripts, which may be important for a type of male infertility (non-obstructive azoospermia – which we think is a good model to work towards better male contraceptives as well).Then they performed their own RNA-sequencing using clinical samples and validated the observations. are currently performing more data analysis, particularly in terms of network analysis, and pick crucial biomarker-candidates for non-obstructive azoospermia as well as a few other disease conditions, such as lung and breast cancer, as well.
Histone Acetyltransferase Inhibitors, From Screening to Optimization – A Tricky Track
Conference Talk by Dr Baell
Talk Abstract: There is currently great interest in compounds that modulate epigenetics. With respect to some epigenetic targets, such as histone decacetylases (HDACs), many inhibitors have been successfully developed and are in clinical trials for a variety of indications. Similarly, bromodomains have been shown, somewhat unexpectedly by some, to be highly druggable. However, there is an elephant in the room, and that is the histone acetyltransferase (HAT) family, which is large but essentially “undrugged” and barely has any compounds that could be considered to be useful tools. Why is it so hard to find good tool compounds for these enzymes?
Not so long ago we undertook HTS against a MYST HAT and eventually discovered a genuine hit that we have recently just optimized to nanomolar levels of inhibition. However, we encountered many problems en route. In this talk we will discuss such issues and how these could help explain why there are so few, if any, useful tool compounds for these enzymes.
Grab the chance to get in touch with Dr Jonathan Baell, from Monash University, Australia at SELECTBIO“MedChem 2017” meeting on 14- 15 September, 2017 at Hotel Le Meridien, Bengaluru.
Freezing Essential Enzyme Motion for Catalysis: An Efficient Approach for Shikimate Kinase Inhibition
Conference Talk by Dr. Conception
Talk Abstract: Most of the approaches used in the structure-based design of inhibitors of enzymes are based on docking or virtual screening studies using the available crystal structures in which the enzyme is considered a rigid mold. However, enzymes are “dynamic” systems that are able to adopt diverse conformations during catalysis and this could also be exploited in inhibitor design since the flexibility is essential for catalysis. It seems reasonable that for enzyme inhibitor design, in addition to stabilizing a closed disposition of the active site that prevents the entry of the substrate(s), disabling the closure of the active site for catalysis could also be an interesting alternative strategy. This motion-based approach allows the design of ligands that target additional cavities generated during this motion but have limited (or no) access in the closed conformation.
The possible development of new antibiotics by the selective and effective inhibition of shikimate kinase (SK), which is an essential enzyme in bacteria that does not have any counterpart in human cells, is presented. Competitive reversible inhibitors of the SK enzyme from M. tuberculosis and H. pylori that block the closure of the active site by reducing the flexibility of the LID and SB domains were identified showing to have good in vitro activity.
Newer Metabolite and Pathway Identification Approaches to Metabolomics
Conference Talk by Dr. Pal
Talk Abstract: Identification of metabolites and inference of differentially regulated metabolic pathways are the key aims of metabolomics research. A common approach to this problem is to compare the experimental spectrum with the database archived metabolite information. However, databases store metabolite information at “standard condition” which are in most cases in variance to the experimental condition data is obtained. Consequently, a considerable fraction of the metabolites remains unidentified and the experimental spectrum unharvested.
Dr. Pal has developed a method based on matching the pattern of spectrum peaks rather than absolute tolerance thresholds, using a combination of geometric hashing and similarity scoring techniques. When applied to 2D NMR metabolomics data, tests with 719 metabolites from the Human Metabolome Database show that 100% of the metabolites can be assigned correctly when accurate data are available. A high success rate is obtained even in the presence of large chemical shift deviations such as 0.5 ppm in 1H and 3 ppm in 13C and missing peaks (up to 50%), compared to nearly no assignments obtained under these conditions with existing methods that employ a direct database search approach. A variation of the approach has been extended to obtain “peaks to pathways” information from NMR spectral data.
Dr. Debnath Pal is noted for his contributions in the area of protein structure, function, interaction and dynamics.
How Fetal Cell Free DNA (cfDNA) is Expanding the Frontiers of Non-Invasive Prenatal Testing?
Conference Talk by Dr. Bhatt
Talk Abstract: Fetal cfDNA can be reliably detected in the maternal circulation by 7 weeks gestation and its amount increases with gestational age, Cell-free DNA in maternal circulation, therefore, can be reliably used in clinical practice to screen for common aneuploidies (21,18, 13) and sex chromosome analysis.The recent advancements in DNA sequencing technology, as well as counting statistics, have also provided a timely opportunity to develop new methods for the non-invasive detection of fetal aneuploidy. Test performances and positive and negative predictive values are well established for the same.
Over the past few years, the NIPT using cell-free DNA is expanding in terms of addition of more content, specifically expanding to screening for microdeletion, rare chromosome trisomies, and copy number variation.
This presentation will give an insight into the following aspects of NIPT-
Clinical utility aspects of the expanded NIPT platforms
Systems Engineering Perspective of Human Metabolism through a Multiscale Model for Disease Analysis: A Cell to Human Framework
Conference Talk by Dr. Venkatesh
Talk Abstract: Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The characterization of the network involves interactions from genes to proteins to metabolites. In this hierarchical link from genotype to phenotype, metabolomics directly links to the phenotypic state. The analysis of metabolites present in a particular phenotype forms the basis of characterization of the system state of the cell/tissue. Using steady state and dynamical models along with metabolomics data, one can try to obtain insights into the system level properties.
The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to an undesirable physiological state termed as a disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly, the application of engineering methodologies to address human diseases from systems biological perspective have been reviewed by Dr. Venkatesh. His research also highlights its potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of diabetes and hypercholesterolemia. He has put forth a concept of cell-to- human framework comprising of five modules (data mining, networking, modeling, and experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The work emphasizes the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing effective therapies.
Dr. K V Venkatesh has an extensive research experience in the areas of Systems and Synthetic Biology and Biosystems Engineering. He has contributed significantly to research in the areas of quantification of biological networks including genetic, signaling and metabolic pathways.