Maximizing the potential of aggressive mouse tumor models in preclinical drug testing.

Atypical teratoid rhabdoid tumor (ATRT) is an aggressive embryonal brain tumor among infants and young children. Two challenges exist for preclinical testing in ATRT. First, genetically quiet, ATRT is a difficult tumor to target molecularly. Tumor cells need to divide to propagate tumor growth-intercepting the common crossroads in cell cycle progression is a feasible strategy. KIF11 is needed for bipolar spindle formation in metaphase. We identified KIF11 as a universal target of all ATRT-molecular-subtypes. Ispinesib, a KIF11-inhibitor, effectively inhibited tumor proliferation in all seven cell lines. A second challenge-a major challenge in preclinical drug testing in-vivo among aggressive tumor models, is the narrow therapeutic window to administer drugs within the limited murine lifespan. Our most aggressive ATRT tumor model was lethal in all mice within ~ 1 month of tumor implantation. Such short-surviving mouse models are difficult to employ for preclinical drug testing due to the narrow time window to administer drugs. To overcome this time restriction, we developed a clinical staging system which allowed physically-fit mice to continue treatment, in contrast to the conventional method of fixed drug-dose-duration regimen in preclinical testing which will not be feasible in such short-surviving mouse models. We validated this approach in a second embryonal brain tumor, medulloblastoma. This is a clinically relevant, cost-efficient approach in preclinical testing for cancer and non-cancer disease phenotypes. Widely used preclinical mouse models are not the most accurate and lack the aggressive tumor spectrum found within a single tumor type. Mice bearing the most aggressive tumor spectrum progress rapidly in the limited murine life-span, resulting in a narrow therapeutic window to administer drugs, and are thus difficult to employ in preclinical testing. Our approach overcomes this challenge. We discovered ispinesib is efficacious against two embryonal brain tumor types

Decision control system

Since the remote controlled UAVs have certain limitations dictated by weather conditions, controller skill, equipment modernization etc., autonomous UAVs have been used to replace the remote controlled UAVs in recent time but these unmanned drones are not as skilful as their human controlled counterparts. To use autonomous drones an effective command decision system (task allocation between the UAVs) has to be setup so as to make these unmanned drones as efficient as the manned drones. The command decision system is based on the strategies developed using game theory whose primary function is to create a reasoning model that mimics a human modus operandi. This paper discusses about the efficient task allocation in-between the members of a UAV squadron also referred to as a swarm under different scenarios. In the first scenario the UAV are required to attack any target that they come across while carrying out search operations in an unknown territory. Here the targets destroyed, using different strategies that are developed from negotiation scheme and greedy algorithm is studied. Based on the performance (outcome- time taken to destroy the targets) the game theories are compared. In the second scenario the UAVs have to escort the bomber/transport through a hostile territory assumed to be completely under enemy radar surveillance. The interceptors that come within range of the bomber/transport are destroyed by the UAVs using different strategies developed from the Borda count and the greedy Algorithm method and the mission success is studied. The different strategies are compared and it is found that negotiation scheme performs better than the greedy algorithm in the search and destroy scenario while the strategy developed using Borda count performs better than the strategy developed using the greedy algorithm in the Escort scenario.Master of Science (Aerospace Engineering

Synthetic Studies to Bielschowskysin Macrocyclic Precursors

Ph.DDOCTOR OF PHILOSOPH

Chemical synthesis, modification and mimicry of the GPI anchor

Glycophosphatidylinositol (GPI) anchors are complex glycolipids which typically anchor extracellular proteins onto the lipid membranes of eukaryotic cells. Although providing a natural platform in which to present or transfer functional molecules onto cells and viruses, GPI anchors are difficult biologics to generate in a homogenously pure form. It is also difficult, though not impossible, to elucidate and confirm their structures unambiguously. Today, chemical synthesis offers not only the versatility to make both complex and simplified GPI mimics and tools, but also the means to directly relate an exact GPI structure to its biological function. These synthetic GPIs may be further modified to allow the chemical attachment of any functional molecule, and not solely proteins, in a biologically compatible manner. Fluorescent labels and affinity tags can be exploited to investigate a particular biological response or process. Alternatively, synthetic glycans of GPI anchors can be employed to elicit a particular immune response or to generate GPI-specific antibodies. In this chapter, we shall overview the structure and synthesis of GPI anchors, and give perspectives on the biological study and therapeutic potential of synthetically-derived GPI biologics

A macrolactonisation approach to the cembrane carbocycle of bielschowskysin

By judicious choice of a conformationally constraining unit to predispose cyclisation to a 15-membered ring, we present a straightforward strategy to a cembranolide precursor of bielschowskysin by the Sonogashira coupling of two readily prepared fragments (from D-glucose and L-malic acid) followed by a facile beta-acylketene macrolactonisation reaction

N-Terminal-Based Targeted, Inducible Protein Degradation in Escherichia coli.

Dynamically altering protein concentration is a central activity in synthetic biology. While many tools are available to modulate protein concentration by altering protein synthesis rate, methods for decreasing protein concentration by inactivation or degradation rate are just being realized. Altering protein synthesis rates can quickly increase the concentration of a protein but not decrease, as residual protein will remain for a while. Inducible, targeted protein degradation is an attractive option and some tools have been introduced for higher organisms and bacteria. Current bacterial tools rely on C-terminal fusions, so we have developed an N-terminal fusion (Ntag) strategy to increase the possible proteins that can be targeted. We demonstrate Ntag dependent degradation of mCherry and beta-galactosidase and reconfigure the Ntag system to perform dynamic, exogenously inducible degradation of a targeted protein and complement protein depletion by traditional synthesis repression. Model driven analysis that focused on rates, rather than concentrations, was critical to understanding and engineering the system. We expect this tool and our model to enable inducible protein degradation use particularly in metabolic engineering, biological study of essential proteins, and protein circuits

MLDB: macromolecule ligand database

MLDB (macromolecule ligand database) is a knowledge base containing ligands co-crystallized with the three-dimensional structures available in the Protein Data Bank. The proposed knowledge base serves as an open resource for the analysis and visualization of all ligands and their interactions with macromolecular structures. MLDB can be used to search ligands, and their interactions can be visualized both in text and graphical formats. MLDB will be updated at regular intervals (weekly) with automated Perl scripts. The knowledge base is intended to serve the scientific community working in the areas of molecular and structural biology. It is available free to users around the clock and can be accessed at http://dicsoft2.physics.iisc.ernet.in/mldb/