ERC FUNDED PROJECTS

"Understanding structure-property relationships across lengthscales is key to the design of functional and structural materials and devices. Moreover, the complexity of modern devices extends to three dimensions and as such 3D characterization is required across those lengthscales to provide a complete understanding and enable improvement in the material’s physical and chemical behaviour. 3D imaging and analysis from the atomic scale through to granular microstructure is proposed through the development of electron tomography using (S)TEM, and ‘dual beam’ SEM-FIB, techniques offering complementary approaches to 3D imaging across lengthscales stretching over 5 orders of magnitude. We propose to extend tomography to include novel methods to determine atom positions in 3D with approaches incorporating new reconstruction algorithms, image processing and complementary nano-diffraction techniques. At the nanoscale, true 3D nano-metrology of morphology and composition is a key objective of the project, minimizing reconstruction and visualization artefacts. Mapping strain and optical properties in 3D are ambitious and exciting challenges that will yield new information at the nanoscale. Using the SEM-FIB, 3D ‘mesoscale’ structures will be revealed: morphology, crystallography and composition can be mapped simultaneously, with ~5nm resolution and over volumes too large to tackle by (S)TEM and too small for most x-ray techniques. In parallel, we will apply 3D imaging to a wide variety of key materials including heterogeneous catalysts, aerospace alloys, biomaterials, photovoltaic materials, and novel semiconductors. We will collaborate with many departments in Cambridge and institutes worldwide. The personnel on the proposal will cover all aspects of the tomography proposed using high-end TEMs, including an aberration-corrected Titan, and a Helios dual beam. Importantly, a postdoc is dedicated to developing new algorithms for reconstruction, image and spectral processing."

2 337 330 €

Start date: 2012-01-01, End date: 2017-12-31

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

One of the greatest challenges facing society is the sustainability of resources. At present, a step change in the sustainable use of resources is needed and catalysis lies at the heart of the solution by providing new routes to carbon dioxide mitigation, energy security and water conservation. It is clear that new high efficiency game-changing catalysts are required to meet the challenge. This proposal will focus on excellence in catalyst design by learning from recent step change advances in gold catalysis by challenging perceptions. Intense interest in gold catalysts over the past two decades has accelerated our understanding of gold particle-size effects, gold-support and gold-metal interactions, the interchange between atomic and ionic gold species, and the role of the gold-support interface in creating and maintaining catalytic activity. The field has also driven the development of cutting-edge techniques, particularly in microscopy and transient kinetics, providing detailed structural characterisation on the nano-scale and probing the short-range and often short-lived interactions. By comparison, our understanding of other metal catalysts has remained relatively static. The proposed programme will engender a step change in the design of supported-metal catalysts, by exploiting the learning and the techniques emerging from gold catalysis. The research will be set out in two themes. In Theme 1 two established key grand challenges will be attacked; namely, energy vectors and greenhouse gas control. Theme 2 will address two new and emerging grand challenges in catalysis namely the effective low temperature activation of primary carbon hydrogen bonds and CO2 utilisation where instead of treating CO2 as a thermodynamic endpoint, the aim will be to re-use it as a feedstock for bulk chemical and fuel production. The legacy of the research will be the development of a new catalyst design approach that will provide a tool box for future catalyst development.

2 279 785 €

Start date: 2012-04-01, End date: 2017-03-31

Mathematical proofs have always been prone to error. Today, proofs can be hundreds of pages long and combine results from many specialisms, making them almost impossible to check. One solution is to deploy modern verification technology. Interactive theorem provers have demonstrated their potential as vehicles for formalising mathematics through achievements such as the verification of the Kepler Conjecture. Proofs done using such tools reach a high standard of correctness. However, existing theorem provers are unsuitable for mathematics. Their formal proofs are unreadable. They struggle to do simple tasks, such as evaluating limits. They lack much basic mathematics, and the material they do have is difficult to locate and apply. ALEXANDRIA will create a proof development environment attractive to working mathematicians, utilising the best technology available across computer science. Its focus will be the management and use of large-scale mathematical knowledge, both theorems and algorithms. The project will employ mathematicians to investigate the formalisation of mathematics in practice. Our already substantial formalised libraries will serve as the starting point. They will be extended and annotated to support sophisticated searches. Techniques will be borrowed from machine learning, information retrieval and natural language processing. Algorithms will be treated similarly: ALEXANDRIA will help users find and invoke the proof methods and algorithms appropriate for the task. ALEXANDRIA will provide (1) comprehensive formal mathematical libraries; (2) search within libraries, and the mining of libraries for proof patterns; (3) automated support for the construction of large formal proofs; (4) sound and practical computer algebra tools. ALEXANDRIA will be based on legible structured proofs. Formal proofs should be not mere code, but a machine-checkable form of communication between mathematicians.

2 430 140 €

Start date: 2017-09-01, End date: 2022-08-31

"Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications. The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."

1 480 548 €

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

One of the fundamental goals of theoretical computer science is to understand the possibilities and limits of efficient computation. This quest has two dimensions. The theory of algorithms focuses on finding efficient solutions to problems, while computational complexity theory aims to understand when and why problems are hard to solve. These two areas have different philosophies and use different sets of techniques. However, in recent years there have been indications of deep and mysterious connections between them. In this project, we propose to explore and develop the connections between algorithmic analysis and complexity lower bounds in a systematic way. On the one hand, we plan to use complexity lower bound techniques as inspiration to design new and improved algorithms for Satisfiability and other NP-complete problems, as well as to analyze existing algorithms better. On the other hand, we plan to strengthen implications yielding circuit lower bounds from non-trivial algorithms for Satisfiability, and to derive new circuit lower bounds using these stronger implications. This project has potential for massive impact in both the areas of algorithms and computational complexity. Improved algorithms for Satisfiability could lead to improved SAT solvers, and the new analytical tools would lead to a better understanding of existing heuristics. Complexity lower bound questions are fundamental but notoriously difficult, and new lower bounds would open the way to unconditionally secure cryptographic protocols and derandomization of probabilistic algorithms. More broadly, this project aims to initiate greater dialogue between the two areas, with an exchange of ideas and techniques which leads to accelerated progress in both, as well as a deeper understanding of the nature of efficient computation.

1 274 496 €

Start date: 2014-03-01, End date: 2019-02-28

The goal of crystal engineering is the design of functional crystalline materials in which the arrangement of basic structural building blocks imparts desired properties. The engineering of organic molecular crystals has, to date, relied largely on empirical rules governing the intermolecular association of functional groups in the solid state. However, many materials properties depend intricately on the complete crystal structure, i.e. the unit cell, space group and atomic positions, which cannot be predicted solely using such rules. Therefore, the development of computational methods for crystal structure prediction (CSP) from first principles has been a goal of computational chemistry that could significantly accelerate the design of new materials. It is only recently that the necessary advances in the modelling of intermolecular interactions and developments in algorithms for identifying all relevant crystal structures have come together to provide predictive methods that are becoming reliable and affordable on a timescale that could usefully complement an experimental research programme. The principle aim of the proposed work is to establish the use of state-of-the-art crystal structure prediction methods as a means of guiding the discovery and design of novel molecular materials. This research proposal both continues the development of the computational methods for CSP and, by developing a computational framework for screening of potential molecules, develops the application of these methods for materials design. The areas on which we will focus are organic molecular semiconductors with high charge carrier mobilities and, building on our recently published results in Nature [1], the development of porous organic molecular materials. The project will both deliver novel materials, as well as improvements in the reliability of computational methods that will find widespread applications in materials chemistry. [1] Nature 2011, 474, 367-371.

1 499 906 €

Start date: 2012-10-01, End date: 2017-09-30

T cell engineering with chimeric antigen receptors has opened the door to effective immunotherapy. CARs are fusion genes encoding receptors whose extracellular domain comprises a single chain variable fragment (scFv) antibody that binds to a tumour surface epitope, while the intracellular domain comprises the signalling module of CD3ζ along with powerful costimulatory domains (e.g. CD28 and/or 4-1BB). CARs are a major breakthrough, since they allow bypassing HLA restrictions or loss, and they can incorporate potent costimulatory signals tailored to optimize T cell function. However, solid tumours present challenges, since they are often genetically unstable, and the tumour microenvironment impedes T cell function. The tumour vasculature is a much more stable and accessible target, and its disruption has catastrophic consequences for tumours. Nevertheless, the lack of affinity reagents has impeded progress in this area. The objectives of this proposal are to develop the first potent and safe tumour vascular-disrupting tumour immunotherapy using scFv’s and CARs uniquely available in my laboratory. I propose to use these innovative CARs to understand for the first time the molecular mechanisms underlying the interactions between anti-vascular CAR-T cells and tumour endothelium, and exploit them to maximize tumour vascular destruction. I also intend to employ innovative engineering approaches to minimize the chance of reactivity against normal vasculature. Lastly, I propose to manipulate the tumour damage mechanisms ensuing anti-vascular therapy, to maximize tumour rejection through immunomodulation. We are poised to elucidate critical interactions between tumour endothelium and anti-vascular T cells, and bring to bear cancer therapy of unparalleled power. The impact of this work could be transforming, given the applicability of tumour-vascular disruption across most common tumour types.

2 500 000 €

Start date: 2013-08-01, End date: 2018-07-31

APPLAUSE’s aim is to produce a body of evidence that illustrates how young people with mental health problems currently interact with both formal mental health services and informal social and familial support structures. Careful analysis of data gathered in the UK and Brazil will allow formulation of globally relevant insights into mental health care delivery for young people, which will be presented internationally as a resource for future health care service design. APPLAUSE will allow the collection of an important data set that does not currently exist in this field, and will look to other disciplines for innovative approaches to data analysis. Whist standard analysis may allow for snapshots of health service use, using innovative life course methods will allow us to to characterise patterns of complete service use of each individual participant’s experience of accessing mental health care and social support. Adolescence is a critical period in mental health development, which has been largely neglected by public health efforts. Psychiatric disorders rank as the primary cause of disability among individuals aged 10-24 years, worldwide. Moreover, many health risk behaviours emerge during adolescence and 70% of adult psychiatric disorders are preceded by mental health problems during adolescent years. However, delays to receiving care for psychiatric disorders, following disorder onset, avreage more than ten years and little is known about factors which impede access to and continuity of care among young people with mental health problems. APPLAUSE will analyse current access models, reports of individual experiences of positive and negative interactions with health care services and the culturally embedded social factors that impact on such access. Addressing this complex problem from a global perspective will advance the development of a more diverse and innovative set of strategies for improving earlier access to care.

1 499 948 €

Start date: 2014-01-01, End date: 2018-12-31

A technological revolution is currently taking place making it possible to noninvasively study metabolism in mammals (incl. humans) in vivo with unprecedented temporal and spatial resolution. Central to these developments is the phenomenon of hyperpolarization, which transiently enhances the magnetic resonance (MR) signals so much that real-time metabolic imaging and spectroscopy becomes possible. The first clinical translation of hyperpolarization MR technology has recently been demonstrated with prostate cancer patients. I have played an active role in these exciting developments, through design and construction of hyperpolarization MR setups that are defining the cutting-edge for in vivo preclinical metabolic studies. However, important obstacles still exist for the technology to fulfill its enormous potential. With this highly interdisciplinary proposal, I will overcome the principal drawbacks of current hyperpolarization technology, namely: 1) A limited time window for hyperpolarized MR detection; 2) The conventional use of potentially toxic polarizing agents; 3) The necessity to use supra-physiological doses of metabolic substrates to reach detectable MR signal I will develop a novel hyperpolarization instrument making use of photoexcited compounds as polarizing agents to produce hyperpolarized solutions containing exclusively endogenous compounds. It will become possible to deliver hyperpolarized solutions in a quasi-continuous manner, permitting infusion of physiological doses and greatly increasing sensitivity. I will also use a complementary isotope imaging technique, the so-called CryoNanoSIMS (developed at my institution over the last year), which can image isotopic distributions in frozen tissue sections and reveal the localization of injected substrates and their metabolites with subcellular spatial resolution. Case studies will include liver and brain cancer mouse models. This work is pioneering and will create a new frontier in molecular imaging.

2 199 146 €

Start date: 2016-09-01, End date: 2021-08-31

Charge and energy transfer are the key steps underlying most chemical reactions and biological transformations. The purely electronic dynamics that control such processes take place on attosecond time scales. A complete understanding of these dynamics on the electronic level therefore calls for new experimental methods with attosecond resolution that are applicable to aqueous environments. We propose to combine the element sensitivity of X-ray spectroscopy with attosecond temporal resolution and ultrathin liquid microjets to study electronic dynamics of relevance to chemical, biological and photovoltaic processes. We will build on our recent achievements in demonstrating femtosecond time-resolved measurements in the water, attosecond pho-toelectron spectroscopy on a liquid microjet and measuring and controlling attosecond charge migration in isolated molecules. We will first concentrate on liquid water to study its electronic dynamics following outer-valence ionization, the formation pathway of the solvated electron and the time scales and intermolecular Coulombic decay following inner-valence or core-level ionization. Second, we will turn to solvated species and measure electronic dynamics and charge migration in solvated molecules, transition-metal complexes and pho-toexcited nanoparticles. These goals will be achieved by developing several innovative experimental tech-niques. We will develop a source of isolated attosecond pulses covering the water window (285-538 eV) and combine it with a flat liquid microjet to realize attosecond transient absorption in liquids. We will complement these measurements with attosecond X-ray emission spectroscopy, Auger spectroscopy and a novel hetero-dyne-detected variant of resonant inelastic Raman scattering, exploiting the large bandwidth that is naturally available from attosecond X-ray sources.

2 750 000 €

Start date: 2018-04-01, End date: 2023-03-31

We use IR spectroscopy of trapped ions in a cryogenic FT-ICR spectrometer to probe non-covalent, “dispersion” interactions in large, gas-phase molecular ions. We will measure conformational equilibria by N-H frequency shifts, and correlate gas-phase IR frequency to the N-H-N bond angle in an ionic H-bond. Substituents on “onium” cations can adopt various conformations, whose energies map interaction potentials. Substituents on their proton-bound dimers interact non-covalently through dispersion forces, whose quantitative evaluation in large molecules has remained difficult despite dispersion becoming increasingly cited as a design principle in the construction of catalysts and materials. The non-covalent interactions bend the N-H-N bond, leading to large shifts in the IR frequency. The proton-bound dimer acts like a molecular balance where the non-covalent interaction, is set against the bending potential in an ionic hydrogen bond. Despite encouragingly accurate calculations for small molecules, experimental benchmarks for large molecules in the gas phase remain scarce, and there is evidence that the good results for small molecules may not extrapolate reliably to large molecules. The present proposal introduces a new experimental probe of non-covalent interactions, providing a sensitive test of the diverging results coming from various computational methods and other experiments. The experiment must be done on isolated molecules in the gas phase, as previous work has shown that solvation substantially cancels out the attractive potential. Accordingly, the proposed experimental design, which involves a custom-built spectrometer, newly available tunable IR sources, chemical synthesis of custom substrates, and quantum calculations up to coupled-cluster levels of theory, showcases how an interdisciplinary approach combining physical and organic chemistry can solve a fundamental problem that impacts how we understand steric effects in organic chemistry.

2 446 125 €

Start date: 2019-05-01, End date: 2024-04-30

The development of longer lasting, higher energy density and cheaper rechargeable batteries represents one of the major technological challenges of our society, batteries representing the limiting components in the shift from gasoline-powered to electric vehicles. They are also required to enable the use of more (typically intermittent) renewable energy, to balance demand with generation. This proposal seeks to develop and apply new NMR metrologies to determine the structure and dynamics of the multiple electrode-electrolyte interfaces and interphases that are present in these batteries, and how they evolve during battery cycling. New dynamic nuclear polarization (DNP) techniques will be exploited to extract structural information about the interface between the battery electrode and the passivating layers that grow on the electrode materials (the solid electrolyte interphase, SEI) and that are inherent to the stability of the batteries. The role of the SEI (and ceramic interfaces) in controlling lithium metal dendrite growth will be determined in liquid based and all solid state batteries. New DNP approaches will be developed that are compatible with the heterogeneous and reactive species that are present in conventional, all-solid state, Li-air and redox flow batteries. Method development will run in parallel with the use of DNP approaches to determine the structures of the various battery interfaces and interphases, testing the stability of conventional biradicals in these harsh oxidizing and reducing conditions, modifying the experimental approaches where appropriate. The final result will be a significantly improved understanding of the structures of these phases and how they evolve on cycling, coupled with strategies for designing improved SEI structures. The nature of the interface between a lithium metal dendrite and ceramic composite will be determined, providing much needed insight into how these (unwanted) dendrites grow in all solid state batteries. DNP approaches coupled with electron spin resonance will be use, where possible in situ, to determine the reaction mechanisms of organic molecules such as quinones in organic-based redox flow batteries in order to help prevent degradation of the electrochemically active species. This proposal involves NMR method development specifically designed to explore a variety of battery chemistries. Thus, this proposal is interdisciplinary, containing both a strong emphasis on materials characterization, electrochemistry and electronic structures of materials, interfaces and nanoparticles, and on analytical and physical chemistry. Some of the methodology will be applicable to other materials and systems including (for example) other electrochemical technologies such as fuel cells and solar fuels and the study of catalysts (to probe surface structure).

3 498 219 €

Start date: 2019-10-01, End date: 2024-09-30

"Many problems in computer science can be cast as state-space search, where the objective is to find a path from an initial state to a goal state in a directed graph called a ""state space"". State-space search is challenging due to the state explosion problem a.k.a. ""curse of dimensionality"": interesting state spaces are often astronomically large, defying brute-force exploration. State-space search has been a core research problem in Artificial Intelligence since its early days and is alive as ever. Every year, a substantial fraction of research published at the ICAPS and SoCS conferences is concerned with state-space search, and the topic is very active at general AI conferences such as IJCAI and AAAI. Algorithms in the A* family, dating back to 1968, are still the go-to approach for state-space search. A* is a graph search algorithm whose only ""intelligence"" stems from a so-called ""heuristic function"", which estimates the distance from a state to the nearest goal state. The efficiency of A* depends on the accuracy of this estimate, and decades of research have pushed the envelope in devising increasingly accurate estimates. In this project, we question the ""A* + distance estimator"" paradigm and explore three new directions that go beyond the classical approach: 1. We propose a new paradigm of declarative heuristics, where heuristic information is not represented as distance estimates, but as properties of solutions amenable to introspection and general reasoning. 2. We suggest moving the burden of creativity away from the human expert by casting heuristic design as a meta-optimization problem that can be solved automatically. 3. We propose abandoning the idea of exploring sequential paths in state spaces, instead transforming state-space search into combinatorial optimization problems with no explicit sequencing aspect. We argue that the ""curse of sequentiality"" is as bad as the curse of dimensionality and must be addressed head-on."

1 997 510 €

Start date: 2019-02-01, End date: 2024-01-31

The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches. These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer. Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language). We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems. We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.

1 500 000 €

Start date: 2016-04-01, End date: 2021-03-31

This proposal seeks to develop a novel technique for fluid and particle manipulations, based upon exploiting the mechanical interactions between acoustic waves and phononic. The new platform involves generating surface acoustic waves (SAWs) on piezoelectric chips, but, unlike previous work, the ultrasonic waves are first coupled into a phononic lattice, which is placed in the path of the ultrasonic wave. The phononic lattice comprises a miniaturised array of mechanical elements which modulates the sound in a manner analogous to how light is “patterned” using a hologram. However, whilst in an optical hologram, the pattern is created by exploiting the differences in refractive indices of the elements of the structure, here the ultrasonic field is modulated both by the elastic contrast between the elements in the array, as well as by the dimensions of the array and its surrounding matrix (including the size and pitch of the features within the array). The result of passing the acoustic wave through a phononic crystal is the formation of new and complex ultrasonic landscapes. As part of the proposed work we aim to understand the physics of this technology and to exploit its development in a range of medical devices. We will show that by using phononic crystals it is possible to create highly controllable patterns of acoustic field intensities, which propagate into the fluid, creating pressure differences that result in unique flow patterns to enable a new platform for including biological sample processing, medical diagnostics, drug delivery and blood clotting devices – all on low cost disposable devices. Different frequencies of ultrasound will interact with different phononic structures to give different functions, providing a toolbox of different functions. Just as in electronics, where discrete components are combined to create circuits, so we propose to combine different phononic lattices to create fluidic microcircuits with important new applications.

2 208 594 €

Start date: 2014-04-01, End date: 2019-03-31

Heterogeneous biomolecular mechanisms at the surface of cellular membranes are often fundamental to generate function and dysfunction in living systems. These processes are governed by transient and dynamical macromolecular interactions that pose tremendous challenges to current analytical tools, as the majority of these methods perform best in the study of well-defined and poorly dynamical systems. This proposal aims at a radical innovation in the characterisation of complex processes that are dominated by structural order and disorder, including those occurring at the surface of biological membranes such as cellular signalling, the assembly of molecular machinery, or the regulation vesicular trafficking. I outline a programme to realise a vision where the combination of experiments and theory can delineate a new analytical platform to study complex biochemical mechanisms at a multiscale level, and to elucidate their role in physiological and pathological contexts. To achieve this ambitious goal, my research team will develop tools based on the combination of nuclear magnetic resonance (NMR) spectroscopy and molecular simulations, which will enable probing the structure, dynamics, thermodynamics and kinetics of complex protein-protein and protein-membrane interactions occurring at the surface of cellular membranes. The ability to advance both the experimental and theoretical sides, and their combination, is fundamental to define the next generation of methods to achieve our transformative aims. We will provide evidence of the innovative nature of the proposed multiscale approach by addressing some of the great questions in neuroscience and elucidate the details of how functional and aberrant biological complexity is achieved via the fine tuning between structural order and disorder at the neuronal synapse.

1 999 945 €

Start date: 2019-06-01, End date: 2024-05-31

During the past decades the PI has helped shape the research field of computer simulation of biomolecular systems at the atomic level. He has carried out one of the first molecular dynamics (MD) simulations of proteins, and has since then contributed many different methodological improvements and developed one of the major atomic-level force fields for simulations of proteins, carbohydrates, nucleotides and lipids. Methodology and force field have been implemented in a set of programs called GROMOS (GROningen MOlecular Simulation package), which is currently used in hundreds of academic and industrial research groups from over 50 countries on all continents. It is proposed to develop a next generation of molecular models, force fields, multi-scaling simulation methodology and software for biomolecular simulations which is at least an order of magnitude more accurate in terms of energetics, and which is 1000 times more efficient through the use of coarse-grained molecular models than the currently available software and models.

1 320 000 €

Start date: 2008-11-01, End date: 2014-09-30

Enzymes created by Nature are still more selective and can be orders of magnitude more efficient than man-made catalysts, in spite of recent advances in the design of de novo catalysts and in enzyme redesign. The optimal engineering of either small molecular or of complex biological catalysts requires both (i) accurate quantitative computational methods capable of a priori assessing catalytic efficiency, and (ii) molecular design principles and corresponding algorithms to achieve, understand and control biomolecular catalytic function and mechanisms. Presently, the computational design of biocatalysts is challenging due to the need for accurate yet computationally-intensive quantum mechanical calculations of bond formation and cleavage, as well as to the requirement for proper statistical sampling over very many degrees of freedom. Pioneering enhanced sampling and analysis methods have been developed to address crucial challenges bridging the gap between the available simulation length and the biologically relevant timescales. However, biased simulations do not generally permit the direct calculation of kinetic information. Recently, I and others pioneered simulation tools that can enable not only accurate calculations of free energies, but also of the intrinsic molecular kinetics and the underlying reaction mechanisms as well. I propose to develop more robust, automatic, and system-tailored sampling algorithms that are optimal in each case. I will use our kinetics-based methods to develop a novel theoretical framework to address catalytic efficiency and to establish molecular design principles to key design problems for new bio-inspired nanocatalysts, and to identify and characterize small molecule modulators of enzyme activity. This is a highly interdisciplinary project that will enable fundamental advances in molecular simulations and will unveil the physical principles that will lead to design and control of catalysis with Nature-like efficiency.

1 499 999 €

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

Recent evidence demonstrates that cancer is overtaking cardiovascular disease as the number one cause of mortality in Europe. This is largely due to the lack of preventative measures for common (e.g. breast) or highly fatal (e.g. ovarian) human cancers. Most cancers are multifactorial in origin. The core hypothesis of this research programme is that the extremely high risk of BRCA1/2 germline mutation carriers to develop breast and ovarian cancer is a net consequence of cell-autonomous (direct effect of BRCA mutation in cells at risk) and cell non-autonomous (produced in distant organs and affecting organs at risk) factors which both trigger epigenetic, cancer-initiating effects. The project’s aims are centered around the principles of systems medicine and built on a large cohort of BRCA mutation carriers and controls who will be offered newly established cancer screening programmes. We will uncover how ‘cell non-autonomous’ factors work, provide detail on the epigenetic changes in at-risk tissues and investigate whether these changes are mechanistically linked to cancer, study whether we can neutralise this process and measure success in the organs at risk, and ideally in easy to access samples such as blood, buccal and cervical cells. In my Department for Women’s Cancer we have assembled a powerful interdisciplinary team including computational biologists, functionalists, immunologists and clinician scientists linked to leading patient advocacy groups which is extremely well placed to lead this pioneering project to develop the fundamental understanding of cancer development in women with BRCA mutations. To reset the epigenome, re-establishing normal cell identity and consequently reducing cancer risk without the need for surgery and being able to monitor the efficacy using multicellular epigenetic outcome predictors will be a major scientific and medical breakthrough and possibly applicable to other chronic diseases.

2 497 841 €

Start date: 2017-09-01, End date: 2022-08-31

Recent advances in magnetic resonance (MR) acquisition technology are providing us with images of the human brain of increasing detail and resolution. While these images hold promise to greatly increase our understanding of such a complex organ, the neuroimaging community relies on tools (e.g. SPM, FSL, FreeSurfer) which, being over a decade old, were designed to work at much lower resolutions. These tools do not consider brain substructures that are visible in present-day scans, and this inability to capitalize on the vast improvement of MR is hampering progress in the neuroimaging field. In this ambitious project, which lies at the nexus of medical histology, neuroscience, biomedical imaging, computer vision and statistics, we propose to build a set of next-generation computational tools that will enable neuroimaging studies to take full advantage of the increased resolution of modern MR technology. The core of the tools will be an ultra-high resolution probabilistic atlas of the human brain, built upon multimodal data combining from histology and ex vivo MR. The resulting atlas will be used to analyze in vivo brain MR scans, which will require the development of Bayesian segmentation methods beyond the state of the art. The developed tools, which will be made freely available to the scientific community, will enable the analysis of MR data at a superior level of structural detail, opening completely new opportunities of research in neuroscience. Therefore, we expect the tools to have a tremendous impact on the quest to understand the human brain (in health and in disease), and ultimately on public health and the economy.

1 450 075 €

Start date: 2016-09-01, End date: 2021-08-31

The frontier in cancer therapy of orchestrating the immune system to attack tumors is producing unprecedented survival benefit in some patients. The corollary is lack of efficacy both in ostensibly responsive tumor types as well as others that are mostly non-responsive. The basis lies in pre-existing and adaptive resistance mechanisms that circumvent induction of tumor-reactive cytotoxic T cells (CTLs) capable of infiltrating solid tumors and eliminating cancer cells. A priori, cancers induced by expression of human papillomavirus oncogenes should be responsive to immunotherapy: these cancers encode immunogenic neo-antigens – the oncoproteins E6/7 – necessary for their manifestation. Rather, such tumors are poorly responsive to immunotherapies. Results from my lab and others using mouse models of HPV-induced cancer have established an actionable hypothesis: during tumorigenesis, such tumors erect multiple barriers to the induction, infiltration, and killing of cancer cells by tumor antigen-reactive CTLs. These include overarching systemic antigen-nonspecific immunosuppression mediated by expanded populations of myeloid cells in spleen and lymph nodes, complemented by immune response-impairing barriers operative in the tumor microenvironment. A spectrum of models will probe these barriers, genetically and pharmacologically, establishing their functional importance, alone and in concert. A major focus will be on how oncogene-expressing keratinocytes elicit a marked expansion of immunosuppressive myeloid cells in spleen and lymph nodes, and how these myeloid cells in turn inhibit development and activation of CD8 T cells and antigen-presenting dendritic cells. Then we’ll assess the therapeutic potential of barrier-breaking strategies combined with immuno-stimulatory modalities. This project will deliver new knowledge about multi-faceted barriers to immunotherapy in these refractory cancers, helping lay the groundwork for efficacious immunotherapy.

2 500 000 €

Start date: 2020-01-01, End date: 2024-12-31

Non-invasive genomic analysis of cancer can revolutionize the study of tumour evolution, heterogeneity, and drug resistance. Clinically applied, this can transform current practice in cancer diagnosis and management. Cell-free DNA in plasma contains tumour-specific sequences. This circulating tumour DNA (ctDNA) is a promising source of genomic and diagnostic information, readily accessible non-invasively. The study of ctDNA is therefore timely and of great importance. But it is also very challenging. Measurement can be complex, and high-quality samples are not easily obtained. Though progress has been made, much remains to be discovered. My lab pioneered the use of targeted sequencing to analyse mutations in ctDNA. We recently developed a ground-breaking paradigm for analysing evolving cancer genomes in plasma DNA, combining ctDNA quantification with exome-sequencing of serial plasma samples. Applied to extensive sets of clinical samples my lab has characterized, this will enable large-scale exploration of acquired drug resistance with unprecedented resolution. CancerExomesInPlasma aims to use ctDNA for genome-wide analysis of tumour evolution, as a means for non-invasive, unbiased discovery of genes and pathways involved in resistance to cancer therapy.

1 769 380 €

Start date: 2014-05-01, End date: 2019-04-30

Breast cancer is a major cause of death in the United States and the Western World. Advanced medical technologies and therapeutic strategies are necessary for the successful detection, diagnosis, and treatment of breast cancer. Here, we propose to use novel technologies (tissue microarrays (TMA) and automated quantivative bioimaging (AQUA)) to identify new therapeutic and prognostic markers for human breast cancer. More specifically, we will study the activation status of a new signaling pathway which we have implicated in breast cancer pathogenesis, using both mouse animal models and cells in culture. For this purpose, we will study the association of CAPER expression with pre-malignant lesions and progression from pre-malignancy to full-blown breast cancer. We expect that this new molecular marker will allow us to improve diagnostic accuracy for individual patients, enhancing both the prognostic predictions as well as the prediction of drug responsiveness for a given patient.

1 500 000 €

Start date: 2010-01-01, End date: 2014-12-31