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Professor David Ascher
Professor

David Ascher

Email: 
Phone: 
+61 7 336 53991

Overview

Background

Prof David Ascher is currently an NHMRC Investigator and Director of the Biotechnology Program at the University of Queensland. He is also Head of Computational Biology and Clinical Informatics at the Baker Institute.

David’s research focus is in modelling biological data to gain insight into fundamental biological processes. One of his primary research interests has been developing tools to unravel the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. His group has developed a platform of over 40 widely used programs for assessing the molecular consequences of coding variants (>7 million hits/year).

Working with clinical collaborators in Australia, Brazil and UK, these methods have been translated into the clinic to guide the diagnosis, management and treatment of a number of hereditary diseases, rare cancers and drug resistant infections.

David has a B.Biotech from the University of Adelaide, majoring in Biochemistry, Biotechnology and Pharmacology and Toxicology; and a B.Sci(Hon) from the University of Queensland, majoring in Biochemistry, where he worked with Luke Guddat and Ron Duggleby on the structural and functional characterization of enzymes in the branched-chain amino acid biosynthetic pathway. David then went to St Vincent’s Institute of Medical Research to undertake a PhD at the University of Melbourne in Biochemistry. There he worked under the supervision of Michael Parker using computational, biochemical and structural tools to develop small molecules drugs to improve memory.

In 2013 David went to the University of Cambridge to work with Sir Tom Blundell on using fragment based drug development techniques to target protein-protein interactions; and subsequently on the structural characterisation of proteins involved in non-homologous DNA repair. He returned to Cambridge in 2014 to establish a research platform to characterise the molecular effects of mutations on protein structure and function- using this information to gain insight into the link between genetic changes and phenotypes. He was subsequently recruited as a lab head in the Department of Biochemistry and Molecular Biology at the University of Melbourne in 2016, before joining the Baker Institute in 2019 and the University of Queensland in 2021.

He is an Associate Editor of PBMB and Fronteirs in Bioinformatics, and holds honorary positions at Bio21 Institute, Cambridge University, FIOCRUZ, and the Tuscany University Network.

Availability

Professor David Ascher is:
Available for supervision
Media expert

Research impacts

We have successfully translated our computational tools into the clinic and industry, including:

  • Clinical detection of drug resistance from whole-genome sequencing of pathogens, including Tuburculosis and Leprosy
  • Genetic counselling for rare diseases and cancers with Addenbrooke's Hospital and Brazilian Ministry of Health
  • Patient stratification within clinical trials
  • Implementation within industry drug and biologics development programs

The tools we have developed have also been widely adopted within existing academic programs including:

  • Integration of intermolecular interaction calculations using our tool Arpeggio in the PDBe, the European resource for the collection, organisation and dissemination of data on biological macromolecular structures.
  • Integration of our missense tolerance scores within the widely used VEP tool for variant characterisation.
  • Implementation of our resistance prediction tools within the London School of Hygiene & Tropical Medicine's TB-Profiler tool.

Works

Search Professor David Ascher’s works on UQ eSpace

177 works between 2008 and 2024

21 - 40 of 177 works

2024

Journal Article

Lipid sulfoxide polymers as potential inhalable drug delivery platforms with differential albumin binding affinity

Ediriweera, Gayathri R., Butcher, Neville J., Kothapalli, Ashok, Zhao, Jiacheng, Blanchfield, Joanne T., Subasic, Christopher N., Grace, James L., Fu, Changkui, Tan, Xiao, Quinn, John F., Ascher, David B., Whittaker, Michael R., Whittaker, Andrew K. and Kaminskas, Lisa M. (2024). Lipid sulfoxide polymers as potential inhalable drug delivery platforms with differential albumin binding affinity. Biomaterials Science, 12 (11), 2978-2992. doi: 10.1039/d3bm02020g

Lipid sulfoxide polymers as potential inhalable drug delivery platforms with differential albumin binding affinity

2023

Journal Article

Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease

Serghini, Adam, Portelli, Stephanie, Troadec, Guillaume, Song, Catherine, Pan, Qisheng, Pires, Douglas E. V. and Ascher, David B. (2023). Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease. Human Molecular Genetics, 33 (3), 224-232. doi: 10.1093/hmg/ddad181

Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease

2023

Journal Article

CSM‐Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces

Rodrigues, Carlos H. M. and Ascher, David B. (2023). CSM‐Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces. Proteins: Structure, Function, and Bioinformatics. doi: 10.1002/prot.26615

CSM‐Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces

2023

Journal Article

Uncovering the molecular drivers of NHEJ DNA repair-implicated missense variants and their functional consequences

Al-Jarf, Raghad, Karmakar, Malancha, Myung, Yoochan and Ascher, David B. (2023). Uncovering the molecular drivers of NHEJ DNA repair-implicated missense variants and their functional consequences. Genes, 14 (10) 1890, 1-11. doi: 10.3390/genes14101890

Uncovering the molecular drivers of NHEJ DNA repair-implicated missense variants and their functional consequences

2023

Journal Article

Identifying innate resistance hotspots for SARS-CoV-2 antivirals using in silico protein techniques

Portelli, Stephanie, Heaton, Ruby and Ascher, David B. (2023). Identifying innate resistance hotspots for SARS-CoV-2 antivirals using in silico protein techniques. Genes, 14 (9) 1699, 1-13. doi: 10.3390/genes14091699

Identifying innate resistance hotspots for SARS-CoV-2 antivirals using in silico protein techniques

2023

Journal Article

Understanding the complementarity and plasticity of antibody–antigen interfaces

Myung, Yoochan, Pires, Douglas E. V. and Ascher, David B (2023). Understanding the complementarity and plasticity of antibody–antigen interfaces. Bioinformatics, 39 (7) btad392, 1-7. doi: 10.1093/bioinformatics/btad392

Understanding the complementarity and plasticity of antibody–antigen interfaces

2023

Journal Article

LEGO-CSM: a tool for functional characterization of proteins

Nguyen, Thanh Binh, de Sá, Alex G. C., Rodrigues, Carlos H. M., Pires, Douglas E. V. and Ascher, David B. (2023). LEGO-CSM: a tool for functional characterization of proteins. Bioinformatics, 39 (7) btad402, 1-4. doi: 10.1093/bioinformatics/btad402

LEGO-CSM: a tool for functional characterization of proteins

2023

Journal Article

Identifying the molecular drivers of pathogenic aldehyde dehydrogenase missense mutations in cancer and non-cancer diseases

Jessen-Howard, Dana, Pan, Qisheng and Ascher, David B. (2023). Identifying the molecular drivers of pathogenic aldehyde dehydrogenase missense mutations in cancer and non-cancer diseases. International Journal of Molecular Sciences, 24 (12) 10157, 1-18. doi: 10.3390/ijms241210157

Identifying the molecular drivers of pathogenic aldehyde dehydrogenase missense mutations in cancer and non-cancer diseases

2023

Journal Article

DDMut: predicting effects of mutations on protein stability using deep learning

Zhou, Yunzhuo, Pan, Qisheng, Pires, Douglas E. V., Rodrigues, Carlos H. M. and Ascher, David B. (2023). DDMut: predicting effects of mutations on protein stability using deep learning. Nucleic Acids Research, 51 (W1), W122-W128. doi: 10.1093/nar/gkad472

DDMut: predicting effects of mutations on protein stability using deep learning

2023

Journal Article

epitope1D: accurate taxonomy-aware B-cell linear epitope prediction

da Silva, Bruna Moreira, Ascher, David B. and Pires, Douglas E. V. (2023). epitope1D: accurate taxonomy-aware B-cell linear epitope prediction. Briefings in Bioinformatics, 24 (3) bbad114, 1-8. doi: 10.1093/bib/bbad114

epitope1D: accurate taxonomy-aware B-cell linear epitope prediction

2023

Journal Article

Insights from spatial measures of intolerance to identifying pathogenic variants in developmental and epileptic encephalopathies

Silk, Michael, de Sá, Alex, Olshansky, Moshe and Ascher, David B. (2023). Insights from spatial measures of intolerance to identifying pathogenic variants in developmental and epileptic encephalopathies. International Journal of Molecular Sciences, 24 (6) 5114, 1-9. doi: 10.3390/ijms24065114

Insights from spatial measures of intolerance to identifying pathogenic variants in developmental and epileptic encephalopathies

2023

Journal Article

CSM-Toxin: a web-server for predicting protein toxicity

Morozov, Vladimir, Rodrigues, Carlos H. M. and Ascher, David B. (2023). CSM-Toxin: a web-server for predicting protein toxicity. Pharmaceutics, 15 (2) 431, 1-8. doi: 10.3390/pharmaceutics15020431

CSM-Toxin: a web-server for predicting protein toxicity

2023

Journal Article

embryoTox: using graph-based signatures to predict the teratogenicity of small molecules

Aljarf, Raghad, Tang, Simon, Pires, Douglas E. V. and Ascher, David B. (2023). embryoTox: using graph-based signatures to predict the teratogenicity of small molecules. Journal of Chemical Information and Modeling, 63 (2), 432-441. doi: 10.1021/acs.jcim.2c00824

embryoTox: using graph-based signatures to predict the teratogenicity of small molecules

2023

Journal Article

DockNet: high-throughput protein–protein interface contact prediction

Williams, Nathan P., Rodrigues, Carlos H. M., Truong, Jia, Ascher, David B. and Holien, Jessica K. (2023). DockNet: high-throughput protein–protein interface contact prediction. Bioinformatics, 39 (1) btac797, 1-3. doi: 10.1093/bioinformatics/btac797

DockNet: high-throughput protein–protein interface contact prediction

2022

Journal Article

SARS-CoV-2 Africa dashboard for real-time COVID-19 information

Xavier, Joicymara S., Moir, Monika, Tegally, Houriiyah, Sitharam, Nikita, Abdool Karim, Wasim, San, James E., Linhares, Joana, Wilkinson, Eduan, Ascher, David B., Baxter, Cheryl, Pires, Douglas E. V. and de Oliveira, Tulio (2022). SARS-CoV-2 Africa dashboard for real-time COVID-19 information. Nature Microbiology, 8 (1), 1-4. doi: 10.1038/s41564-022-01276-9

SARS-CoV-2 Africa dashboard for real-time COVID-19 information

2022

Journal Article

A bias of Asparagine to Lysine mutations in SARS-CoV-2 outside the receptor binding domain affects protein flexibility

Boer, Jennifer C., Pan, Qisheng, Holien, Jessica K., Nguyen, Thanh-Binh, Ascher, David B. and Plebanski, Magdalena (2022). A bias of Asparagine to Lysine mutations in SARS-CoV-2 outside the receptor binding domain affects protein flexibility. Frontiers in Immunology, 13 954435, 1-13. doi: 10.3389/fimmu.2022.954435

A bias of Asparagine to Lysine mutations in SARS-CoV-2 outside the receptor binding domain affects protein flexibility

2022

Journal Article

A recurrent de novo splice site variant involving DNM1 exon 10a causes developmental and epileptic encephalopathy through a dominant-negative mechanism

Parthasarathy, Shridhar, Ruggiero, Sarah McKeown, Gelot, Antoinette, Soardi, Fernanda C, Ribeiro, Bethânia F R, Pires, Douglas E V, Ascher, David B, Schmitt, Alain, Rambaud, Caroline, Represa, Alfonso, Xie, Hongbo M, Lusk, Laina, Wilmarth, Olivia, McDonnell, Pamela Pojomovsky, Juarez, Olivia A, Grace, Alexandra N, Buratti, Julien, Mignot, Cyril, Gras, Domitille, Nava, Caroline, Pierce, Samuel R, Keren, Boris, Kennedy, Benjamin C, Pena, Sergio D J, Helbig, Ingo and Cuddapah, Vishnu Anand (2022). A recurrent de novo splice site variant involving DNM1 exon 10a causes developmental and epileptic encephalopathy through a dominant-negative mechanism. The American Journal of Human Genetics, 109 (12), 2253-2269. doi: 10.1016/j.ajhg.2022.11.002

A recurrent de novo splice site variant involving DNM1 exon 10a causes developmental and epileptic encephalopathy through a dominant-negative mechanism

2022

Book Chapter

Using graph-based signatures to guide rational antibody engineering

Ascher, David B., Kaminskas, Lisa M., Myung, Yoochan and Pires, Douglas E. V. (2022). Using graph-based signatures to guide rational antibody engineering. Computer-aided antibody design. (pp. 375-397) New York, NY, United States: Humana Press. doi: 10.1007/978-1-0716-2609-2_21

Using graph-based signatures to guide rational antibody engineering

2022

Journal Article

A structural biology community assessment of AlphaFold2 applications

Akdel, Mehmet, Pires, Douglas E. V., Pardo, Eduard Porta, Jänes, Jürgen, Zalevsky, Arthur O., Mészáros, Bálint, Bryant, Patrick, Good, Lydia L., Laskowski, Roman A., Pozzati, Gabriele, Shenoy, Aditi, Zhu, Wensi, Kundrotas, Petras, Serra, Victoria Ruiz, Rodrigues, Carlos H. M., Dunham, Alistair S., Burke, David, Borkakoti, Neera, Velankar, Sameer, Frost, Adam, Basquin, Jérôme, Lindorff-Larsen, Kresten, Bateman, Alex, Kajava, Andrey V., Valencia, Alfonso, Ovchinnikov, Sergey, Durairaj, Janani, Ascher, David B., Thornton, Janet M. ... Beltrao, Pedro (2022). A structural biology community assessment of AlphaFold2 applications. Nature Structural and Molecular Biology, 29 (11), 1056-1067. doi: 10.1038/s41594-022-00849-w

A structural biology community assessment of AlphaFold2 applications

2022

Journal Article

kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors

Zhou, Yunzhuo, Al‐Jarf, Raghad, Alavi, Azadeh, Nguyen, Thanh Binh, Rodrigues, Carlos H. M., Pires, Douglas E. V. and Ascher, David B. (2022). kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors. Protein Science, 31 (11) e4453, 1-11. doi: 10.1002/pro.4453

kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors

Funding

Current funding

  • 2023 - 2027
    Improving genetic diagnosis of autoimmune and autoinflammatory disease through an integrated multi-omics approach (MRFF 2022 GHFM - administered by ANU)
    The Australian National University
    Open grant

Supervision

Availability

Professor David Ascher is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Computational approaches to engineer and modulate G protein-coupled receptors

    Principal Advisor

  • Doctor Philosophy

    Post-transcriptional gene regulation: towards a better understanding of pathogenesis and medical applications

    Principal Advisor

  • Doctor Philosophy

    Personalising treatments for genetic diseases

    Principal Advisor

    Other advisors: Dr Stephanie Portelli

  • Doctor Philosophy

    Deep Learning Algorithms for Polygenic Genotype-Phenotype Predictions and the development of genetics computation tools

    Principal Advisor

  • Doctor Philosophy

    Towards the accurate functional characterisation of protein coding mutations

    Principal Advisor

    Other advisors: Dr Stephanie Portelli, Dr Thanh-Binh Nguyen

  • Doctor Philosophy

    Improving rational antibody design using machine learning

    Principal Advisor

  • Doctor Philosophy

    Machine Learning for Protein Dynamics: Predicting Post-Translational Modifications and Mutation Effects

    Principal Advisor

  • Doctor Philosophy

    Using Deep Learning in Cell & Gene Therapy

    Principal Advisor

    Other advisors: Dr Thanh-Binh Nguyen, Dr Stephanie Portelli

  • Doctor Philosophy

    Protein structure guided precision medicine

    Principal Advisor

    Other advisors: Professor Phil Hugenholtz, Dr Stephanie Portelli

  • Doctor Philosophy

    Rational protein engineering and inhibition

    Principal Advisor

  • Doctor Philosophy

    Computer-aided drug design: predicting and mitigating drug toxicity

    Principal Advisor

    Other advisors: Dr Stephanie Portelli

  • Doctor Philosophy

    Developing structure-based deep learning methods to predict mutation effects on proteins

    Principal Advisor

  • Doctor Philosophy

    Exploring Cardiotoxicity Risk Factors

    Principal Advisor

    Other advisors: Dr Thanh-Binh Nguyen

  • Doctor Philosophy

    Therapeutic Resolution of Inflammation in the Central Nervous System for Neuroprotection in Parkinson's Disease

    Associate Advisor

    Other advisors: Professor Avril Robertson

  • Doctor Philosophy

    Use of structural phylogeny and reconciliation in molecular phylogenetics

    Associate Advisor

    Other advisors: Dr Kate Bowerman, Professor Phil Hugenholtz

  • Doctor Philosophy

    Allosteric modulation of synaptic proteins by endogenous and modified sterols

    Associate Advisor

    Other advisors: Dr Evelyne Deplazes, Professor Megan O'Mara

  • Doctor Philosophy

    Computational design of targeted lipid technologies

    Associate Advisor

    Other advisors: Professor Megan O'Mara

  • Doctor Philosophy

    Breaking the chain of inflammation through targetting NLR proteins

    Associate Advisor

    Other advisors: Professor Avril Robertson

Media

Enquiries

Contact Professor David Ascher directly for media enquiries about their areas of expertise.

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