Gillian Murphy, Ph.D.
Professor, Department of Oncology, University of Cambridge, UK
A novel strategy for targeting metalloproteinases in cancer
Epithelial tumours evolve in a multi-step manner, involving both inflammatory and mesenchymal cells. Although intrinsic factors drive malignant progression, the influence of the micro-environment of neoplastic cells is a major feature of tumorigenesis. Extracellular proteinases, notably the metalloproteinases, are key players in the regulation of this cellular environment, acting as major effectors of both cell-cell and cell-extracellular matrix (ECM) interactions. They are involved in modifying ECM integrity, growth factor availability and the function of cell surface signalling systems, with consequent effects on cellular differentiation, proliferation and apoptosis.This has made metalloproteinases important targets for therapeutic interventions in cancer and small molecule inhibitors focussed on chelation of the active site zinc and binding within the immediate active site pocket were developed. These were not successful in early clinical trials due to the relative lack of specificity and precise knowledge of the target proteinase(s) in specific cancers. We can now appreciate that it is essential that we understand the relative roles of the different enzymes (of which there are over 60) in terms of their pro and anti tumour activity and their precise sites of expression The next generations of metalloproteinase inhibitors need the added specificity that might be gained from an understanding of the structure of individual active sites and the role of extra catalytic domains in substrate binding and other aspects of their biology. We have prepared scFv antibodies to the extra catalytic domains of two membrane metalloproteinases, MMP-14 and ADAM17, that play key roles in the tumour microenvironment. Our rationale and experiences with these agents will be presented in more detail.
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.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
![Delegate Talk: Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors @ Sathyam Hall | Vallikavu | Kerala | India](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/bicb.jpg)
Rajasekhar Chekkara, Venkata Reddy Gorla and Sobha Rani Tenkayala
Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors
Polo-like kinase 1 (PLK1) is a significant enzyme with diverse biological actions in cell cycle progression, specifically mitosis. Suppression of PLK1 activity by small molecule inhibitors has been shown to inhibit cancer, being BI 2536 one of the most potent active inhibitor of PLK1 mechanism. Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies were carried out for a set of 54 compounds belonging to Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK1 inhibitors. A six-point pharmacophoremodel AAADDR, with three hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R) was developed by Phase module of Schrdinger suite Maestro 9. The generated pharmacophore model was used to derive a predictive atom-based 3D quantitative structure-activity relationship analysis (3D-QSAR) model for the training set (r2 = 0.88, SD = 0.21, F = 57.7, N = 44) and for test set (Q2 = 0.51, RMSE = 0.41, PearsonR = 0.79, N = 10). The original set of compounds were docked into the binding site of PLK1 using Glide and the active residues of the binding site were analyzed. The most active compound H18 interacted with active residues Leu 59, Cys133 (glide score = −10.07) and in comparison of BI 2536, which interacted with active residues Leu 59, Cys133 (glide score = −10.02). The 3D-QSAR model suggests that hydrophobic and electron-withdrawing groups are essential for PLK1 inhibitory activity. The docking results describes the hydrogen bond interactions with active residues of these compounds. These results which may support in the design and development of novel PLK1 inhibitors.
![Delegate Talk: A Novel Versatile Human Cell Based In Vitro High Throughput Genotoxicity Screen @ Acharya Hall | Vallikavu | Kerala | India](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/gtm.jpg)
Sunilkumar Sukumaran, Ayyappan Nair, Madhuri Subbiah, Gunja Gupta, Lakshmi Rajakrishna, Pradeep Savanoor Raghavendra, Subbulakshmi Karthikeyan, Salini Krishnan Unni and Ganesh Sambasivam
Genotoxicity is defined as DNA damage that leads to gene mutations which can become tumorigenic. Genotoxicity testing is important to ensure drug safety and is mandatory prior to Phase I/II clinical trials of new drugs. The results from genetic toxicology studies help to identify hazardous drugs and environmental genotoxins. Currently, among others there are four tests recommended by regulatory authorities (Ames test-bacterial, chromosome aberrations; in vitro gene mutation-eukaryotic cells and in vivo test). These assays are laborious, time consuming, require large quantities of test compounds and limited by throughput challenges. The site and mechanism of genotoxicity are not revealed by these assays and data obtained from bacterial tests might not translate the same in mammals. To address these we have developed a novel, versatile, human cell based, high throughput, reporter based genotoxicity screen (Anthem’s Genotox screen). This screen is performed on genetically engineered human cell lines that express 3 reporter genes under transcriptional control of ‘early DNA damage sensors’ (p53, p21 and GADD153). These genes are involved in DNA repair, cell cycle arrest and/or apoptosis. p21 and GADD are also known to be induced in a p53 independent manner. p53 blocks G1/S transition of cell cycle while the p53 independent DNA damage block G2/M transition. Identification of the mechanism of genotoxicity helps in rational drug designing. Additionally, the platform can be used to screen other potential genotoxins from cosmetics, food and environment. Initial validation studies of the Genotox screen was performed with over 60 compounds chosen from a variety of chemical classes. The genotoxic potential of metabolites was tested using rat liver S9 fractions. The results demonstrated a sensitivity of 86.7–92.3% and a specificity of 70–78.6% when compared with currently available in vitro genotoxicity assays. This Genotox screen would prove to be an invaluable human cell based tool to weed out potential genotoxins in various industries.