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.
Suryaprakash Sambhara, DVM, Ph.D
Chief, Immunology Section, Influenza Division, CDC, Atlanta, USA
Making sense of pathogen sensors of Innate Immunity: Utility of their ligands as antiviral agents and adjuvants for vaccines.
Currently used antiviral agents act by inhibiting viral entry, replication, or release of viral progeny. However, recent emergence of drug-resistant viruses has become a major public health concern as it is limiting our ability to prevent and treat viral diseases. Furthermore, very few antiviral agents with novel modes of action are currently in development. It is well established that the innate immune system is the first line of defense against invading pathogens. The recognition of diverse pathogen-associated molecular patterns (PAMPs) is accomplished by several classes of pattern recognition receptors (PRRs) and the ligand/receptor interactions trigger an effective innate antiviral response. In the past several years, remarkable progress has been made towards understanding both the structural and functional nature of PAMPs and PRRs. As a result of their indispensable role in virus infection, these ligands have become potential pharmacological agents against viral infections. Since their pathways of action are evolutionarily conserved, the likelihood of viruses developing resistance to PRR activation is diminished. I will discuss the recent developments investigating the potential utility of the ligands of innate immune receptors as antiviral agents and molecular adjuvants for vaccines.
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.
John Stanley, Satheesh Babu, Ramacahandran T and Bipin Nair
Pt-Pd decorated TiO2 nanotube array for the non-enzymatic determination of glucose in neutral medium
Rapidly expanding diabetic population and the complications associated with elevated glycemic levels necessitates the need for a highly sensitive, selective and stable blood glucose measurement strategy. The high sensitivity and selectivity of enzymatic sensors together with viable manufacturing technologies such as screen-printing have made a great social and economic impact. However, the intrinsic nature of the enzymes leads to lack of stability and consequently reduces shelf life and imposes the need for stringent storage conditions. As a result much effort has been directed towards the development of ‘enzyme-free’ glucose sensors (Park et al. 2006). In this paper, a non-enzymatic amperometric sensor for selective and sensitive direct electrooxidation of glucose in neutral medium was fabricated based on Platinum-Palladium (Pt–Pd) nanoparticle decorated titanium dioxide (TiO2) nanotube arrays. Highly ordered TiO2 nanotube arrays were obtained using a single step anodization process (Grimes C A and Mor G K 2009) over which Pt–Pd nanoparticles where electrochemically deposited. Scanning Electron Microscopy (SEM) analysis revealed the diameter of the TiO2 nanotubes to be approximately 40 nm. Elemental analysis after electrochemical deposition confirms the presence of Pt–Pd. Electrochemical characterization of the sensor was carried out using cyclic voltammetry technique (−1.0 to +1.0V) in phosphate buffer saline (PBS) pH 7.4. All further glucose oxidation studies were performed in PBS (pH 7.4). The sensor exhibited good linear response towards glucose for a concentration range of 1 μM to 20mM with a linear regression coefficient of R = 0.998. The electrodes are found to be selective in the presence of other commonly interfering molecules such as ascorbic acid, uric acid, dopamine and acetamidophenol. Thus a nonenzymatic sensor with good selectivity and sensitivity towards glucose in neutral medium has been developed.