ERC FUNDED PROJECTS

Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations: - First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37); - Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells (Turk et al.,Cancer Res, 2009. 69(21)); - Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15); - Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204). I propose a comprehensive series of studies that will address thefollowing critical questions: - First, what is the scope of MDR-selective compounds? - Second, what is their mechanism of action? - Third, what is the optimal therapeutic modality? Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.

1 499 640 €

Start date: 2012-01-01, End date: 2016-12-31

We propose to elucidate the structural design principles of naturally occurring antibody complementarity-determining regions (CDRs) and to computationally design novel antibody functions. Antibodies represent the most versatile known system for molecular recognition. Research has yielded many insights into antibody design principles and promising biotechnological and pharmaceutical applications. Still, our understanding of how CDRs encode specific loop conformations lags far behind our understanding of structure-function relationships in non-immunological scaffolds. Thus, design of antibodies from first principles has not been demonstrated. We propose a computational-experimental strategy to address this challenge. We will: (a) characterize the design principles and sequence elements that rigidify antibody CDRs. Natural antibody loops will be subjected to computational modeling, crystallography, and a combined in vitro evolution and deep-sequencing approach to isolate sequence features that rigidify loop backbones; (b) develop a novel computational-design strategy, which uses the >1000 solved structures of antibodies deposited in structure databases to realistically model CDRs and design them to recognize proteins that have not been co-crystallized with antibodies. For example, we will design novel antibodies targeting insulin, for which clinically useful diagnostics are needed. By accessing much larger sequence/structure spaces than are available to natural immune-system repertoires and experimental methods, computational antibody design could produce higher-specificity and higher-affinity binders, even to challenging targets; and (c) develop new strategies to program conformational change in CDRs, generating, e.g., the first allosteric antibodies. These will allow targeting, in principle, of any molecule, potentially revolutionizing how antibodies are generated for research and medicine, providing new insights on the design principles of protein functional sites.

1 499 930 €

Start date: 2013-09-01, End date: 2018-08-31

The emergence of life is one of the most fascinating and yet largely unsolved questions in the natural sciences, and thus a significant challenge for scientists from many disciplines. There is growing evidence that ribonucleic acid (RNA) polymers, which are capable of genetic information storage and self-catalysis, were involved in the early forms of life. But despite recent progress, RNA synthesis without biological machineries is very challenging. The current project aims at understanding how to synthesize RNA in abiotic conditions. I will solve problems associated with three critical aspects of RNA formation that I will rationalize at a molecular level: (i) accumulation of precursors, (ii) formation of a chemical bond between RNA monomers, and (iii) tolerance for alternative backbone sugars or linkages. Because I will study problems ranging from the formation of chemical bonds up to the stability of large biopolymers, I propose an original computational multi-scale approach combining techniques that range from quantum calculations to large-scale all-atom simulations, employed together with efficient enhanced-sampling algorithms, forcefield improvement, cutting-edge analysis methods and model development. My objectives are the following: 1 • To explain why the poorly-understood thermally-driven process of thermophoresis can contribute to the accumulation of dilute precursors. 2 • To understand why linking RNA monomers with phosphoester bonds is so difficult, to understand the molecular mechanism of possible catalysts and to suggest key improvements. 3 • To rationalize the molecular basis for RNA tolerance for alternative backbone sugars or linkages that have probably been incorporated in abiotic conditions. This unique in-silico laboratory setup should significantly impact our comprehension of life’s origin by overcoming major obstacles to RNA abiotic formation, and in addition will reveal significant orthogonal outcomes for (bio)technological applications.

1 497 031 €

Start date: 2018-02-01, End date: 2023-07-31

In this project we will push the limits of microscale ultrasound-based technology to gain access to diagnostically important rare constituents of blood within minutes from blood draw. To meet the demands for shorter time from sampling to result in healthcare there is an increased interest to shift from heavy centralized lab equipment to point-of-care tests and patient self-testing. Key challenges with point-of-care equipment is to enable simultaneous measurement of many parameters at a reasonable cost and size of equipment. Therefore, microscale technologies that can take in small amounts of blood and output results within minutes are sought for. In addition, the high precision and potential for multi-stage serial processing offered by such microfluidic methods opens up for fast and automated isolation of rare cell populations, such as circulating tumor cells, and controlled high-throughput size fractionation of sub-micron biological particles, such as platelets, pathogens and extracellular vesicles. To achieve effective and fast separation of blood components we will expose blood to acoustic radiation forces in a flow-through format. By exploiting a newly discovered acoustic body force, that stems from local variations the acoustic properties of the cell suspension, we can generate self-organizing configurations of the blood cells. We will tailor and tune the acoustic cell-organization in novel ways by time modulation of the acoustic field, by altering the acoustic properties of the fluid by solute molecules, and by exploiting a novel concept of sound interaction with thermal gradients. The project will render new fundamental knowledge regarding the acoustic properties of single cells and an extensive theoretical framework for the response of cells in any aqueous medium, bounding geometry and sound field, potentially leading to new diagnostic methods.

1 999 720 €

Start date: 2019-11-01, End date: 2024-10-31