David B. Ascher

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Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and(More)
MOTIVATION Mutations play fundamental roles in evolution by introducing diversity into genomes. Missense mutations in structural genes may become either selectively advantageous or disadvantageous to the organism by affecting protein stability and/or interfering with interactions between partners. Thus, the ability to predict the impact of mutations on(More)
Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better(More)
DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is a central component of nonhomologous end joining (NHEJ), repairing DNA double-strand breaks that would otherwise lead to apoptosis or cancer. We have solved its structure in complex with the C-terminal peptide of Ku80 at 4.3 angstrom resolution using x-ray crystallography. We show that the(More)
Hepatitis C virus (HCV) infection affects more than 170 million people. The high genetic variability of HCV and the rapid development of drug-resistant strains are driving the urgent search for new direct-acting antiviral agents. A new class of agents has recently been developed that are believed to target the HCV protein NS5A although precisely where they(More)
Drug resistance is a major challenge for the treatment of many diseases and a significant concern throughout the drug development process. The ability to understand and predict the effects of mutations on protein-ligand affinities and their roles in the emergence of resistance would significantly aid treatment and drug design strategies. In order to study(More)
BACKGROUND Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the(More)
Inhibition of insulin-regulated aminopeptidase (IRAP) has been demonstrated to facilitate memory in rodents, making IRAP a potential target for the development of cognitive enhancing therapies. In this study, we generated a 3-D model of the catalytic domain of IRAP based on the crystal structure of leukotriene A4 hydrolase (LTA4H). This model identified two(More)
The murine monoclonal antibody WO2 specifically binds the N-terminal region of the amyloid beta peptide (Abeta) associated with Alzheimer's disease. This region of Abeta has been shown to be the immunodominant B-cell epitope of the peptide and hence is considered to be a basis for the development of immunotherapeutic strategies against this prevalent cause(More)
Reducing amyloid-β peptide (Aβ) burden at the pre-symptomatic stages of Alzheimer’s disease (AD) is currently the advocated clinical strategy for treating this disease. The most developed method for targeting Aβ is the use of monoclonal antibodies including bapineuzumab, solanezumab and crenezumab. We have synthesized these antibodies and used surface(More)