רשימת כל החוקרים בתחום באוניברסיטת בר-אילן
Prof. Efroni Sol
Lab website: http://systemsbiomed.org
Systems Biomedicine Laboratory
With an emphasis on the signaling network, the Systems Biomedicine Lab looks at the changes in the network during the transition from a normal state to a disease state. We use high throughput systems to measure biological quantities and we also use computational tools to project these measurements onto biological understanding through signaling pathways and network biology. We concentrate on understanding the cancer phenotype, mainly breast cancer and liver cancer, where we try to pinpoint malfunctions in network alterations, through RNA inhibition and RNA-seq (transcription easurements on massive parallel sequencing machine). We generate the data, as well as develop the omputational tools to explore the data. We devise algorithms to convert data into legible biology and thus define the biological measurements we need to make progress. Our ultimate goal is to provide targets for therapeutical intervention.
Prof. Haas Elisha
1) The problem of protein folding: The second genetic code is a code of the production of protein structure in which genetic information is expressed during the process of building complex and precise molecular structures. Deciphering the code involves studying the process of protein folding. Our research focuses on identification of intermediate situations of the folding process with an integrated approach based on genetic engineering, protein chemistry, and physical measurements using laser systems. We study the role of nonlocal interactions in the control of the folding pathways in an ensemble of refolding protein molecules. Our current emphasis is on the study of the role of very effective nonlocal interactions in the early phases of the refolding transition. We search for specific clusters of residues that form essential nonlocal interactions in order to create, in the long run, a typing of the sequence messages that appear in protein molecules and that are involved in the control of the folding pathways. We study many other aspects of the protein-folding problem, such as: the effect of crowding, the order of appearance of secondary structure elements, the question of downhill versus barrier-crossing mechanisms, residual structures in the unfolded state, etc.
2) Dynamic mechanisms of structure and enzyme activity: I view enzyme molecules as 'nano machines' which operate in the DH-DS plane in the direction of the chemical potential gradient. We are studying the rate of motion of chain elements, the correlation of such motions, effect of mutations, effect of ligand binding, crowding, and others. The research methods are based on various spectroscopic methods (CD, CPL, and ultra-fast fluorescence measurement).
3) Studies of the phenomenon of intrinsically unfolded proteins: Many proteins appear to have no well-defined native structure. Some of these are involved in neurodegenerative diseases. We are studying the problem of intrinsically unfolded proteins (IUPs) as models of partially unfolded protein molecules with the working hypothesis that these proteins are indeed folded, but with much flexibility.Our model is human a-synuclein and we are also studying it initial change of conformation upon transition to dimers or small oligomers, prior to fibrilization.
4) We are studying the conformational change of insulin upon binding to its receptor.
5) We are studying DNA bending in relation to specific sequences and to protein binding (collaboration with Prof. Mike Weiss of Case U.)
6) We have developed ultrafast time-resolved FRET methods which enable us to attack the above problems. We are now developing new instruments for measurements of 'double kinetics' using stopped flow system (ms resolution), laser T-jump system (ns time resolution), and P-jump (ms time resolution), as well as single-molecule fluorescence detection.
Dr. Hakim Ofir
A major question in our research is how cell-selective transcription program, which is the basis for cell type-specific functions, is progressively modulated during differentiation, faithfully transmitted through cell division, and attenuated to respond to external stimuli.
To address this question, we are studying three linked layers of transcription regulation:
1. Transcription factor action.
2. Chromatin accessibility.
3. Three-dimensional (3D) genome organization.
Two of the critical determinants of gene expression patterns are the cooperative activity of multiple transcription factors, and selective accessibility of regulatory DNA elements. These two regulatory layers are tightly linked because transcription factors preferentially associate with accessible chromatin, and recruit chromatin remodeling enzymes that regulate this accessibility. Intriguingly, global mapping of regulatory DNA by ChIP and DHS experiments revealed that genes and regulatory elements mainly reside at great distance from the regulated genes. Hence, the study of the genome as linear is highly over-simplified. The use of chromosome conformation capture (3C) technology to detect long-range chromosomal interactions, has uncovered that regulatory elements loop over great genomic distances to their target loci, in complex association configurations, to exert their regulatory role. Above the scale of local genomic contacts, spatial congregation of genomic regions from different chromosomes, and from distant chromosomal loci, together with protein factors, give rise to functionally compartmentalized nuclear space. Non-random genome folding within the nuclear space is emerging as key contributor for regulating nuclear processes. The lab is focused on understanding the molecular basis of genome architecture and deciphering the regulatory role of nuclear topology, primarily in the context of gene expression. For studying how the transcription program is regulated, we use ChIP-seq to uncover target loci of specific transcription factors, and DHS-seq for identifying DNA regulatory elements of known and novel transcription factors. Furthermore, we apply 'C' technologies (3C, 4C, Hi-C) to unravel the folding patterns of the genome, to catalogue genes with their distant regulatory loci, and to characterize their nuclear spatial environment. Important aspect of our work is the use of high-resolution, high-throughput microscopy, to study the organization of genomic loci and nuclear functions. This unique merge of genomics and imaging is a powerful approach to understand the population data at the single-cell level. To address the biological questions, we combine studies in mammalian and plant model systems. We study the immediate transcriptional response of human T cells and Arabidopsis root cells to external signals, and we study the regulation of transcription programs during T-cell differentiation.
Dr. Ilany Amiyaal
I integrate behavioral ecology, network science, and social science, to study broad aspects of social behavior in the wild. I use empirical and theoretical methods to better understand behavioral phenomena. Much of my research focuses on the study of social networks and on principles of animal communication. Students in my lab can do field work on rock hyraxes in Ein Gedi, where we have been monitoring a population for more than 15 years, and/or analyze the data we collected and develop theoretical models. I am interested in questions such as:
- How do social networks affect longevity, reproductive success, and pathogen transmission?
- How do communication patterns interact with social structure?
- How do males and females choose who to mate with?
- What is the structure of different signals and how did they evolve?
Prof. Levanon Erez
The aim of my research is to develop the warranted technology and algorithms in order to delineate the full extent of RNA editing in human and animal models, determine the global editing levels in various physiological and pathological conditions, develop an affordable and accurate genomic wide screen and to understand their biological function, mainly in the nervous system and the role of editing in primate evolution.
Prof. Mehr Ramit
Lab website: http://immsilico2.lnx.biu.ac.il/
Computational Immunology Lab
My group performs research in computational immunology. We use mathematical models, computer simulations and bioinformatical analyses, in order to understand the dynamics of lymphocyte repertoires in the immune system. The immune response involves cells of various types, including B, T, and NK lymphocytes expressing a large diversity of receptors which recognize foreign antigens and self-molecules. The various cell types interact through a complicated network of communication, regulation and control mechanisms. This is what enables the immune system to perform the functions of danger recognition, decision, action, memory, and learning. The dynamics of immune cell repertoires are, as a result, highly complex and non-linear. My lab members develop various theoretical tools - mathematical models, computer simulations, and novel bioinformatical methods -in order to analyze the dynamics of the immune system in various situations and predict the results of experimental and medical interventions.
Examples of recent and current research topics:
1) Models and simulations of the dynamics of the development of T and B lymphocytes, the rearrangement of B cell and T cell antigen receptor genes, and subsequent selection, which is based on receptor-ligand interactions.
2) Models for the development of the natural killer (NK) cell repertoire, from receptor gene expression to selection of functional, non-harmful cells.
3) Studies of the competition between B lymphocyte clones during the humoral immune response, the process of hypermutation, and the creation of memory cells, including the explanation of the phenomenon of repertoire shift, isotype switch, and graph-theoretical analysis of B lymphocyte immunoglobulin gene phylogenetic trees.
Prof. Meirovitch Eva
Protein function is determined by both structure and dynamics. NMR spin relaxation is the single most useful method for studying protein dynamics. Uniform isotope labeling with 15N and 13C renders almost every atom in the protein NMR active. We found that the commonly used method for translating experimental NMR spin relaxation data into an insightful dynamic picture, called model-free (MF), is oversimplified. This implies often inaccurate, and at times misleading, dynamic pictures.To improve the analysis, we developed a new approach for treating NMR spin relaxation data in protein. The theory underlying this approach, the Slowly Relaxing Local Structure (SRLS), has been developed by Freed and co-workers at Cornell University in the course of the years. This is a many-body stochastic coupled rotator approach. The rotators represent particles reorienting stochastically in solution. In the context of biological macromolecules, in particular proteins, the particles of interest are moieties such as the 15N-1H bond, or the13CH2D methyl group, which bear the NMR nucleus observed (15N in the former case and 2H in the latter case). These nuclei represent “the probe”. Each “probe” is involved in the global motion of the protein and in site-specific motions. Thus, both hydrodynamic information and intra-molecular flexibility can be elucidated. The mutual correlation (coupling) between these motions, the appropriate symmetry of the physical quantities involved, and realistic local geometry are not accounted for properly in the MF approach. SRLS accounts for all of these important factors. SRLS has been shown to be significantly more accurate and physically insightful than MF. So far our efforts focused on the dynamic properties of the protein backbone using 15N-1H as probe, and the dynamic properties of protein side chains using the methyl group 13CH2D as probe. A new picture of protein dynamics has emerged. This is a consequence of the fact that using over-simplified methods can lead not only to quantitatively inaccurate, but also to qualitatively erroneous results.Efforts to extend the capabilities of SRLS are underway. Work related with new applications is in progress. We also contemplate combining SRLS with molecular dynamics simulations. The development of effective user-friendly software for distribution in the protein dynamics community is pursued. It should be noted that the field of research described lies at the interface of Magnetic Resonance, NMR spin relaxation, liquid dynamics, statistical mechanics, structural biology and protein NMR.
Prof. Neumann Avidan
Bio-mathematical modeling and bio-informatics analysis and simulation in the fields of virology, immunology and clinical kinetics in general.
Viral dynamics and evolution (in particular of HIV, HCV, HBV but also CMV, Ebola, malaria and other infectives) and how is it affected by anti-viral therapy and by the immune response. Optimization of therapy for Hepatitis C, Hepatitis B and AIDS. Models of immune response, immune repertoire and immune memory. Models of the pathogenesis of auto-immunity and of its treatment (in particular Lupus).
Models of neural degeneration.
Models of the interaction between the immune system and the neural system.
Host genetic diversity and its effects on infectious disease.
Kinetics of clinical markers.
Development of a bio-informatics computational platform for the automatization and optimization of
clinical kinetics analysis and modeling.
Bio-informatics software tools for modeling and analysis of bio-kinetic data.
Prof. Ofran Yanay
Systems Biology, Bioinformatics and Molecular Recognition
Our lab combines computational and experimental tools to study molecular interactions and their relationship to biological function and disease. We analyze biological networks in search of molecular mechanisms that account for the control and dynamics of these networks. Using clinical data collected from patients with different diseases, we compare the molecular interactions in disease to those observed in normal cells. We also develop tools to predict molecular interactions, and design molecules that can bind to specific biological macromolecules.
Dr. Opatowsky Yarden
Structural Studies of Cell Signaling Assemblies
We use structural and biochemical methods to study how cytokines activate receptors to initiate precise signaling events across the cell membrane. Receptor tyrosine kinases (RTKs) are key players in the control of a wide range of cellular processes including proliferation, differentiation, migration and survival. They are composed of an extracellular domain to which specific ligands bind, a single-pass transmembrane helix, and an intracellular tyrosine kinase domain flanked by regulatory regions. We seek to understand how the extracellular event of ligand binding to the receptor is translated into an accurate intracellular response. We are also interested in structural investigations of coordinated signaling through assemblies of RTKs and co-receptors. Through the parallel use of X-ray crystallography and single-particle electron microscopy, we address basic mechanistic questions concerning the early stages of cell signaling.
Dr. Paas Yoav
Biophysics, Pharmacology, and Structure of Ion Channels
Our laboratory is interested in Cys-loop receptors. The latter are ionic channels activated by neurotransmitters such as acetylcholine, serotonin, glycine, gamma-aminobutyric acid (GABA), histamine, or glutamate. Cys-loop receptors play a key role in our day-to-day functions, from body motions to cognitive processes, as they mediate and regulate fast transmission of chemo-electric signals throughout the nervous system. Being physiologically important, impairment of Cys-loop receptor activity leads to neurological disorders such as epilepsy, irritable bowel syndrome, addiction to nicotine, exaggerated startle responses, and other disorders. More specifically, we focus on molecular aspects of Cys-loop receptors at high resolution, as follows:
1) Biophysical aspects that include mechanisms of channel gating, mechanisms of ionic permeation and ionic selectivity, and mechanisms underlying coupling of the neurotransmitter-binding site to channel activity.
2) Pharmacological aspects that include mechanisms of ligand recognition and rational drug design. The research in our laboratory employs the following techniques: recombinant DNA technology, protein engineering, protein purification, protein crystallization, ligand-binding assays, electrophysiological recordings of ionic currents, and computer-assisted structural modeling.
Prof. Unger Ron
My research interest is the interface between Biology and Computer Science. We are interested in exploring this interface from two directions: how advanced computational techniques can help to address fundamental biological questions and how biology can inspire new computational approaches. Within this framework, we are involved in projects spanning a wide range of topics such as: Designing simple models to better understand protein structure and protein folding dynamics, studying ncRNA molecules, molecular computation and system biology.
1) Studying simple models of protein folding: We are using simple models to address the fundamental questions related to protein folding. Such models capture the essence of the fundamental questions, while being simple enough to enable thorough computational analysis. Using this approach, we have demonstrated the usefulness of genetic algorithms for structure calculations, study the importance of local interactions, analyze protein folding assisted by chaperons, and study long-range interactions in proteins.
2) Studying ncRNA molecules: The importance of short noncoding RNA molecules (ncRNA) in controlling various biological processes became evident in the last several years. Traditional sequence analysis tools are generally not suitable to identify such molecules on a genomic scale. We use a variety of sophisticated computer science methods ranging from suffix trees to SVMs to detect, compare, and characterize ncRNA molecules. This work is done in collaboration with Prof. Shula Michaeli, an experimentalist who is working on understanding the function of ncRNA molecules in parasites.
3) Molecular Computation: The exquisite selectivity and specificity of complex protein-based networks suggest that similar principles can be used to devise biological systems that will be able to directly implement any logical circuit as a parallel asynchronous computation. We have designed a scheme for protein molecules that would serve as the basic computational element by functioning as a NAND logical gate, utilizing DNA tags for recognition, and phosphorylation and exonuclease reactions for information processing.
4) System Biology, the robustness of biological systems: We are analyzing genomic networks (like protein - protein interactions, genetic double mutants) in order to understand how biological systems gain their robustness. We are intrigued by the regularity of the overall features of these networks while they consist of so many different underlying components. Thus, we look for global properties, in addition to being scale-free and local, that may induce robustness.
Lab website: http://odem.md.biu.ac.il/
DRUG DISCOVERY LAB http://medweb.md.biu.ac.il/research/avraham-samson/
Development of computational tools for drug design
To assist drug design, we are developing computational tools to predict ligand binding sites. In the past, we developed a structure based program using normal mode accompanied exposure changes to predict ligand binding sites with 90% accuracy. As one would expect we are currently attempting to increase the accuracy to 100%. In addition, we are developing ligand optimization programs based on local motion in the binding site. In particular, we are optimizing drugs which bind to acetylcholine receptors, and acetylcholine esterases, and improve concentration in patients with Alzheimer's and dementia.
Calculation of biomolecular motion and correlation with biological activity
To capture the motion involved in biological mechanisms, we are developing computational tools using molecular dynamics and normal modes. With these tools, we were able to calculate the motion associated with channel opening of the acetylcholine receptor, and show how this motion is inhibited by binding of snake toxin. In addition, we could calculate the conformational change exhibited by prion proteins and show the infection propagation in the mad cow disease. We are currently calculating motion of various biomolecules such as HIV glycoproteins, enzymes, receptors, channels, and the ribosome to explain biological activity.
NMR protein structure determination
We are determining the three-dimensional structure of proteins using NMR spectroscopy. In the past, we solved the structure of snake toxin, receptors, and HIV peptides. Now, we are determining the structures of small proteins, and peptides. In particular, we are solving the structure of prion peptides to test if our predicted conformational changes may be observed thus uncovering prion infectivity. In addition, we are using NMR spectroscopy to verify our bioinformatic predictions of drug design.
Prof. Izhak Haviv
CANCER PERSONALIZED MEDICINE AND DIAGNOSTIC GENOMICS
Project 1: Tumor Microenvironment and wound healing:
1) Characterization of the changes in tumor neighbors, specifically, functional genomic screens and epigenetic profiling of cancer associated fibroblasts and macrophages.
2) Mechanistic studies on existing finding linking particular genes with cancer promotion by neighboring cells.
Project 2: Genome-wide characterization of silent chromatin-associated non-coding RNASilent chromatin isolated via specific histone marks (H3K9-methylation and H3K27-methylation) harbors non-coding RNA (our unpublished results), which are molecules that change dramatically during biological developmental and environmental homeostatic responses. This project would involve manipulating the level of these molecules, and measuring the impact of this perturbation on cell function, such as cancer growth, survival, or migration.
Project 3: More molecular disease-specific RNA and epigenetic genome-wide profiling at the aim of understanding key disease phenotypes, such as predisposition, progression, or drug response. This project will develop through collaborations in other Israeli institutes, as well as existing collaborations in Australia, such as the prostate cancer ICGC focus on androgen receptor mechanism of action and epigenetic characterization.
Dr. Itay Onn
The molecular basis of chromosome organization and its impact on growth, development and disease
In cells the DNA is organized by proteins into a structure known as chromatin. The first level of chromatin organization is mediated by histones. Both the nature of higher-order chromatin organization and the proteins involved in the process are mostly unknown. Yet, this organization is important for both genome functionality and integrity. Cohesin is a member of a conserved family of protein complexes called Structural Maintenance of Chromosomes (SMC). Cohesin and other SMCs are involved in a broad spectrum of functions that include chromatin organization, transcription regulation, cell differentiation, and maintenance of genome integrity. Furthermore, aneuploidy, cancer and developmental syndromes are associated with malfunction of SMC proteins, indicating their medical importance. The term cohesinopathy collectively describes a growing number of cohesin-associated diseases, although the molecular basis of these disorders is elusive. The complex architecture of cohesin and the complicated features of its in vivo activity have impeded attempts to elucidate its molecular functions. To overcome these difficulties we developed a holistic approach utilizing biochemistry, genetics and molecular biology to study the molecular mechanism of cohesin in the yeast Saccharomyces cerevisiae. In addition, we are interested in understanding how malfunction of cohesin is affecting development and tumorigenesis.The wide range of cohesin activities in the cell requires a dynamic regulation. A differential array of modifications and auxiliary factors regulate cohesin activity. However, neither the characterization of these regulators is complete nor their effect on cohesin activity is well understood. We study how cohesin is regulated throughout the cell cycle and in response to environmental and cellular stimuli such as DNA damage. We use a genome-wide approach to gain a detailed map of cohesin’s modifications and interactions with auxiliary factors. Moreover, we believe that mutations that impair cohesin regulation play a part in cohesinopathy. Our long term goal is to search for such mutations in cancer-derived cell lines and other clinical relevant syndromes and to study their contribution the pathology. Our current knowledge of the processes shaping the chromosome is incomplete. Dissecting the activity and regulation of cohesin on the molecular level will provide new insight into fundamental processes in the cell. Furthermore, it may be used for developing new therapeutic approaches to cancer and other human disorders.
Dr. Moshe Dessau
Structural biology of infectious diseases: RNA viruses entry and invasion of eukaryotic parasites
In our lab we use structural and biophysical approaches for studying the organization and dynamics of macromolecular assemblies. Our goal of the research is to determine how protein structure and interactions determine the guiding principles and mechanisms of viral and parasitic infection. We generally interested in two different systems:
How do viruses assemble and how do they enter and exit the cells they infect? Can we combine our structural understanding of viral entry with progressive methods in biophysics and cell biology to develop novel strategies for vaccine design?
We are particularly interested in creating a complete structural narrative for the penetration of viruses into their host-cell. To release their genome into the cytoplasm, enveloped viruses required to attach to their host-cell and undergo a membrane fusion step in which the viral membrane fuses with the host-cell endosomal membrane. The glycoproteins on the virus surface are key components of these events. Structural analyses of these proteins are at the central part in our research. Viral structural proteins are also the major antigens recognized by protective antibodies. Understanding the mechanism of action of neutralizing antibodies will provide novel information for vaccine design.
What are the unique structural features of eukaryotic parasites? How can we exploit structural investigation of unique biological processes in eukaryotic parasites to design novel therapeutics?
Almost One-third of the global burden of human disease comes from diverse array of human parasites therefore there is an urgent and pressing public health need for research on parasites. The complexity of parasites life cycle and biology poses a major challenge for understanding their mode of action at the molecular level. Parasites have many unique and fascinating processes that are not found in other eukaryotes. By using structural biology, the most powerful tool for understanding protein function at the atomic level, our goal is to identify drug targets or vaccine candidates. Our vision is that by determine macromolecular structures from parasite pathogens would provide invaluable mechanistic insights on vital processes of the parasites and would suggest novel strategies for inhibiting infection.
Dr. Gur Yaari
Please see the lab's website:
Computational systems biology lab
Our lab develops computational and statistical tools to process and analyze high-throughput biological data. The research is multidisciplinary and involves elements from mathematics, statistics, physics, computer science, biology and medicine. Our main focus is studying the adaptive immune system from a system/repertoire perspective. In particular, we are interested in understanding lymphocyte (T and B cells) repertoire dynamics in healthy individuals as well as in illness states such as infections, autoimmune diseases, aging and cancer. We apply advanced molecular biology methods to produce large sequencing data sets of human lymphocyte receptors, and analyze them using dedicated computational pipelines, in order to obtain meaningful biological insights into the adaptive immune system.
Examples of current research topics:
1) Analysis of Lymphocyte Receptor Repertoires
2) Develop computational pipelines for processing high-throughput antibody sequencing data
3) Use high-throughput sequencing data to infer molecular mechanisms of adaptive immunity
4) Develop statistical tools for gene set expression differential analysis
Prof. Dan T. Major
Our group is involved in:
1) Development of quantum simulation tools for nuclear quantum effects in enzyme catalysis. This entails development of new path-integral methods for the simulations of zero-point energy and tunneling effects in condensed phase environments. Several new methods are being developed and are incorporated into simulation platforms for enzymatic reactions.
2) Development of hybrid quantum mechanics/molecular mechanics methods. This includes the development of specific reaction parameter semi-empirical Hamiltonians for use in enzyme simulations. Additionally, we also develop novel perturbation approaches wherein a low-level Hamiltonian is perturbed into a higher level one with a view to enhance accuracy at a reduced computational cost.
3) Study dynamical effects and tunnelling in enzyme catalysis through hydrogen transfer reactions. This involves studying several important enzyme systems such as the hydride transfer in dihydrofolate reductase and formate dehydrogenase.
4) Enzyme mechanisms through heavy atom kinetic isotope effects. This approach entails the study of the reaction mechanism in deaminase and decarboxylase enzymes via heavy atom kinetic isotope effects.
5) Enzyme mechanisms in a variety of systems, such as
- Terpenes (monoterpenes and sesquiterpenes)
- Racemases (alanine racemase, proline racemase, serine racemase)
- Dihydrofolate reductase and formate dehydrogenase
Dr Gal Chechik
Molecular biology of the brain
Research: Our lab focuses on learning in brains and machines. Brains develop and change following experience. Using a wide variety of neurobiological data from electrophysiology to in-situ hybridization and RNA sequencing, we quantify how plasticity is implemented in neural tissues, and how the brain adapts on multiple timescales. More specifically, this includes changes in the brain transcriptome during development and adolescence, reconstructing synaptic pathways, and comparing the transciptome of human brains to that of other species. To achieve these goals, we also develop large-scale machine learning and data analysis approaches. We develop algorithms that allow machines to represent complex signals and learn effectively from examples. We use these approaches to analyze images and to characterize spatio-temporal patterns of brain transcriptome.
Prof. Hanoch Senderowitz
The laboratory of cheminformatics and computer aided drug design.
Our laboratory combines basic scientific research with translational research for the development, implementation and application of new computational methodologies for the design of new and improved drugs. Such methods have been shown in the past to greatly accelerate drug design efforts. The research conducted in the lab involves modeling the structure and mode of action of pharmaceutically relevant bio-targets using advanced molecular dynamics (MD) methods, studying the factors governing the interactions between such targets and their potential ligands, virtually screening for and designing of new ligands and predicting the pharmacological profile of drug candidates. This research is interdisciplinary, at the interface between chemistry, biology and computer sciences, and is done in close collaboration with experimentalists. The main computational tools employed in our research are advanced molecular dynamics simulations, docking simulations, pharmacophore modeling and machine learning tools.
Some of the projects currently on-going in the lab are:
1) Studying the structure and energetic of CFTR, the main protein implicated in Cystic Fibrosis. In this project we look at the wild-type protein as well as in many of its mutants.
2) Discovery of new therapies for Cystic Fibrosis that exert their effect through CFTR.
3) Drug discovery for rare neurodegenerative diseases such as the Vanishing White Matter Disease and Duchene Muscular Dystrophy.
4) Studying the structure and energies of bioactive conformations of drug molecules, namely the conformations such molecules adopt when binding their bio-targets.
5) Development of chemoinformatic tools for the analysis of screening libraries.
6) Development of new machine learning algorithms and their application for the design of improved photovoltaic cells made entirely of metal oxides.