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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

179 works between 2008 and 2024

61 - 80 of 179 works

2021

Journal Article

PdCSM-PPI: Using graph-based signatures to identify protein-protein interaction inhibitors

Rodrigues, Carlos H.M., Pires, Douglas E.V. and Ascher, David B. (2021). PdCSM-PPI: Using graph-based signatures to identify protein-protein interaction inhibitors. Journal of Chemical Information and Modeling, 61 (11), 5438-5445. doi: 10.1021/acs.jcim.1c01135

PdCSM-PPI: Using graph-based signatures to identify protein-protein interaction inhibitors

2021

Journal Article

mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity

Nguyen, Thanh Binh, Myung, Yoochan, de Sá, Alex G. C., Pires, Douglas E. V. and Ascher, David B. (2021). mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity. NAR Genomics and Bioinformatics, 3 (4) lqab109, lqab109. doi: 10.1093/nargab/lqab109

mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity

2021

Journal Article

CSM-AB: graph-based antibody–antigen binding affinity prediction and docking scoring function

Myung, Yoochan, Pires, Douglas E. V. and Ascher, David B. (2021). CSM-AB: graph-based antibody–antigen binding affinity prediction and docking scoring function. Bioinformatics, 38 (4), 1141-1143. doi: 10.1093/bioinformatics/btab762

CSM-AB: graph-based antibody–antigen binding affinity prediction and docking scoring function

2021

Journal Article

A novel deep intronic variant strongly associates with Alkaptonuria

Lai, Chien-Yi, Tsai, I-Jung, Chiu, Pao-Chin, Ascher, David B., Chien, Yin-Hsiu, Huang, Yu-Hsuan, Lin, Yi-Lin, Hwu, Wuh-Liang and Lee, Ni-Chung (2021). A novel deep intronic variant strongly associates with Alkaptonuria. npj Genomic Medicine, 6 (1) 89, 89. doi: 10.1038/s41525-021-00252-2

A novel deep intronic variant strongly associates with Alkaptonuria

2021

Journal Article

Definition of the immune evasion-replication interface of rabies virus P protein

Zhan, Jingyu, Harrison, Angela R., Portelli, Stephanie, Nguyen, Thanh Binh, Kojima, Isshu, Zheng, Siqiong, Yan, Fei, Masatani, Tatsunori, Rawlinson, Stephen M., Sethi, Ashish, Ito, Naoto, Ascher, David B., Moseley, Gregory W. and Gooley, Paul R. (2021). Definition of the immune evasion-replication interface of rabies virus P protein. PLOS Pathogens, 17 (7) e1009729, 1-27. doi: 10.1371/journal.ppat.1009729

Definition of the immune evasion-replication interface of rabies virus P protein

2021

Journal Article

pdCSM-cancer: using graph-based signatures to identify small molecules with anticancer properties

Al-Jarf, Raghad, de Sá, Alex G. C., Pires, Douglas E. V. and Ascher, David B. (2021). pdCSM-cancer: using graph-based signatures to identify small molecules with anticancer properties. Journal of Chemical Information and Modeling, 61 (7), 3314-3322. doi: 10.1021/acs.jcim.1c00168

pdCSM-cancer: using graph-based signatures to identify small molecules with anticancer properties

2021

Journal Article

MTR3D: identifying regions within protein tertiary structures under purifying selection

Silk, Michael, Pires, Douglas E V, Rodrigues, Carlos H M, D’Souza, Elston N, Olshansky, Moshe, Thorne, Natalie and Ascher, David B (2021). MTR3D: identifying regions within protein tertiary structures under purifying selection. Nucleic Acids Research, 49 (W1), W438-W445. doi: 10.1093/nar/gkab428

MTR3D: identifying regions within protein tertiary structures under purifying selection

2021

Journal Article

mmCSM-PPI: predicting the effects of multiple point mutations on protein–protein interactions

Rodrigues, Carlos H. M., Pires, Douglas E. V. and Ascher, David B. (2021). mmCSM-PPI: predicting the effects of multiple point mutations on protein–protein interactions. Nucleic Acids Research, 49 (W1), W417-W424. doi: 10.1093/nar/gkab273

mmCSM-PPI: predicting the effects of multiple point mutations on protein–protein interactions

2021

Journal Article

Mercury methylation by metabolically versatile and cosmopolitan marine bacteria

Lin, Heyu, Ascher, David B., Myung, Yoochan, Lamborg, Carl H., Hallam, Steven J., Gionfriddo, Caitlin M., Holt, Kathryn E. and Moreau, John W. (2021). Mercury methylation by metabolically versatile and cosmopolitan marine bacteria. The ISME Journal, 15 (6), 1810-1825. doi: 10.1038/s41396-020-00889-4

Mercury methylation by metabolically versatile and cosmopolitan marine bacteria

2021

Journal Article

Author Correction: Exploring the structural distribution of genetic variation in SARS-CoV-2 with the COVID-3D online resource

Portelli, Stephanie, Olshansky, Moshe, Rodrigues, Carlos H. M., D’Souza, Elston N., Myung, Yoochan, Silk, Michael, Alavi, Azadeh, Pires, Douglas E. V. and Ascher, David B. (2021). Author Correction: Exploring the structural distribution of genetic variation in SARS-CoV-2 with the COVID-3D online resource. Nature Genetics, 53 (2), 254-254. doi: 10.1038/s41588-020-00775-x

Author Correction: Exploring the structural distribution of genetic variation in SARS-CoV-2 with the COVID-3D online resource

2021

Journal Article

Structure-guided machine learning prediction of drug resistance mutations in Abelson 1 kinase

Zhou, Yunzhuo, Portelli, Stephanie, Pat, Megan, Rodrigues, Carlos H.M., Nguyen, Thanh-Binh, Pires, Douglas E.V. and Ascher, David B. (2021). Structure-guided machine learning prediction of drug resistance mutations in Abelson 1 kinase. Computational and Structural Biotechnology Journal, 19, 5381-5391. doi: 10.1016/j.csbj.2021.09.016

Structure-guided machine learning prediction of drug resistance mutations in Abelson 1 kinase

2021

Journal Article

pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures

Velloso, João Paulo L., Ascher, David B. and Pires, Douglas E. V. (2021). pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures. Bioinformatics Advances, 1 (1) vbab031, vbab031. doi: 10.1093/bioadv/vbab031

pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures

2021

Book Chapter

Identifying genotype-phenotype correlations via integrative mutation analysis

Airey, Edward, Portelli, Stephanie, Xavier, Joicymara S, Myung, Yoo Chan, Silk, Michael, Karmakar, Malancha, Velloso, João P L, Rodrigues, Carlos H M, Parate, Hardik H, Garg, Anjali, Al-Jarf, Raghad, Barr, Lucy, Geraldo, Juliana A, Rezende, Pâmela M, Pires, Douglas E V and Ascher, David B (2021). Identifying genotype-phenotype correlations via integrative mutation analysis. Artificial neural networks. (pp. 1-32) edited by Hugh Cartwright. New York, NY, United States: Humana. doi: 10.1007/978-1-0716-0826-5_1

Identifying genotype-phenotype correlations via integrative mutation analysis

2021

Journal Article

Distinguishing between PTEN clinical phenotypes through mutation analysis

Portelli, Stephanie, Barr, Lucy, de Sá, Alex G.C., Pires, Douglas E.V. and Ascher, David B. (2021). Distinguishing between PTEN clinical phenotypes through mutation analysis. Computational and Structural Biotechnology Journal, 19, 3097-3109. doi: 10.1016/j.csbj.2021.05.028

Distinguishing between PTEN clinical phenotypes through mutation analysis

2021

Journal Article

Unveiling six potent and highly selective antileishmanial agents via the open source compound collection ‘Pathogen Box’ against antimony-sensitive and -resistant Leishmania braziliensis

Souza Silva, Juliano A., Tunes, Luiza G., Coimbra, Roney S., Ascher, David B., Pires, Douglas E.V. and Monte-Neto, Rubens L. (2021). Unveiling six potent and highly selective antileishmanial agents via the open source compound collection ‘Pathogen Box’ against antimony-sensitive and -resistant Leishmania braziliensis. Biomedicine and Pharmacotherapy, 133 111049, 111049. doi: 10.1016/j.biopha.2020.111049

Unveiling six potent and highly selective antileishmanial agents via the open source compound collection ‘Pathogen Box’ against antimony-sensitive and -resistant Leishmania braziliensis

2020

Journal Article

A missense mutation in the MLKL brace region promotes lethal neonatal inflammation and hematopoietic dysfunction

Hildebrand, Joanne M., Kauppi, Maria, Majewski, Ian J., Liu, Zikou, Cox, Allison J., Miyake, Sanae, Petrie, Emma J., Silk, Michael A., Li, Zhixiu, Tanzer, Maria C., Brumatti, Gabriela, Young, Samuel N., Hall, Cathrine, Garnish, Sarah E., Corbin, Jason, Stutz, Michael D., Di Rago, Ladina, Gangatirkar, Pradnya, Josefsson, Emma C., Rigbye, Kristin, Anderton, Holly, Rickard, James A., Tripaydonis, Anne, Sheridan, Julie, Scerri, Thomas S., Jackson, Victoria E., Czabotar, Peter E., Zhang, Jian-Guo, Varghese, Leila ... Silke, John (2020). A missense mutation in the MLKL brace region promotes lethal neonatal inflammation and hematopoietic dysfunction. Nature Communications, 11 (1) 3150, 3150. doi: 10.1038/s41467-020-16819-z

A missense mutation in the MLKL brace region promotes lethal neonatal inflammation and hematopoietic dysfunction

2020

Journal Article

The impact of size and charge on the pulmonary pharmacokinetics and immunological response of the lungs to PLGA nanoparticles after intratracheal administration to rats

Haque, Shadabul, Pouton, Colin W., McIntosh, Michelle P., Ascher, David B, Keizer, David W, Whittaker, Michael R. and Kaminskas, Lisa M. (2020). The impact of size and charge on the pulmonary pharmacokinetics and immunological response of the lungs to PLGA nanoparticles after intratracheal administration to rats. Nanomedicine: Nanotechnology, Biology, and Medicine, 30 102291, 102291. doi: 10.1016/j.nano.2020.102291

The impact of size and charge on the pulmonary pharmacokinetics and immunological response of the lungs to PLGA nanoparticles after intratracheal administration to rats

2020

Journal Article

ThermoMutDB: a thermodynamic database for missense mutations

Xavier, Joicymara S, Nguyen, Thanh-Binh, Karmarkar, Malancha, Portelli, Stephanie, Rezende, Pâmela M, Velloso, João P L, Ascher, David B and Pires, Douglas E V (2020). ThermoMutDB: a thermodynamic database for missense mutations. Nucleic Acids Research, 49 (D1), D475-D479. doi: 10.1093/nar/gkaa925

ThermoMutDB: a thermodynamic database for missense mutations

2020

Journal Article

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches

Portelli, Stephanie, Myung, Yoochan, Furnham, Nicholas, Vedithi, Sundeep Chaitanya, Pires, Douglas E. V. and Ascher, David B. (2020). Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches. Scientific Reports, 10 (1) 18120, 1-13. doi: 10.1038/s41598-020-74648-y

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches

2020

Journal Article

DynaMut2 : Assessing changes in stability and flexibility upon single and multiple point missense mutations

Rodrigues, Carlos H.M., Pires, Douglas E.V. and Ascher, David B. (2020). DynaMut2 : Assessing changes in stability and flexibility upon single and multiple point missense mutations. Protein Science, 30 (1), 60-69. doi: 10.1002/pro.3942

DynaMut2 : Assessing changes in stability and flexibility upon single and multiple point missense mutations

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

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    Computational approaches to engineer and modulate G protein-coupled receptors

    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

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

    Principal Advisor

  • Doctor Philosophy

    Improving rational antibody design using machine learning

    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

    Exploring Cardiotoxicity Risk Factors

    Principal Advisor

    Other advisors: Dr Thanh-Binh Nguyen

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    Personalising treatments for genetic diseases

    Principal Advisor

    Other advisors: Dr Stephanie Portelli

  • Doctor Philosophy

    Use of structural phylogeny and reconciliation in molecular phylogenetics

    Associate Advisor

    Other advisors: Dr Kate Bowerman, Professor Phil Hugenholtz

  • Doctor Philosophy

    Unravelling the Physicochemical Drivers of Biomolecular Self-Assembly though Multiscale Simulations

    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

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

    Associate Advisor

    Other advisors: Professor Avril Robertson

  • Doctor Philosophy

    Breaking the chain of inflammation through targetting NLR proteins

    Associate Advisor

    Other advisors: Professor Avril Robertson

Media

Enquiries

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