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
Fields of research
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Funding
Current funding
Supervision
Availability
- Professor David Ascher is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Post-transcriptional gene regulation: towards a better understanding of pathogenesis and medical applications
Principal Advisor
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Doctor Philosophy
Machine Learning for Protein Dynamics: Predicting Post-Translational Modifications and Mutation Effects
Principal Advisor
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Doctor Philosophy
Computational approaches to engineer and modulate G protein-coupled receptors
Principal Advisor
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Doctor Philosophy
Towards the accurate functional characterisation of protein coding mutations
Principal Advisor
Other advisors: Dr Stephanie Portelli, Dr Thanh-Binh Nguyen
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Doctor Philosophy
Deep Learning Algorithms for Polygenic Genotype-Phenotype Predictions and the development of genetics computation tools
Principal Advisor
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Doctor Philosophy
Improving rational antibody design using machine learning
Principal Advisor
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Doctor Philosophy
Using Deep Learning in Cell & Gene Therapy
Principal Advisor
Other advisors: Dr Thanh-Binh Nguyen, Dr Stephanie Portelli
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Doctor Philosophy
Protein structure guided precision medicine
Principal Advisor
Other advisors: Professor Phil Hugenholtz, Dr Stephanie Portelli
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Doctor Philosophy
Rational protein engineering and inhibition
Principal Advisor
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Doctor Philosophy
Computer-aided drug design: predicting and mitigating drug toxicity
Principal Advisor
Other advisors: Dr Stephanie Portelli
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Doctor Philosophy
Exploring Cardiotoxicity Risk Factors
Principal Advisor
Other advisors: Dr Thanh-Binh Nguyen
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Doctor Philosophy
Developing structure-based deep learning methods to predict mutation effects on proteins
Principal Advisor
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Doctor Philosophy
Personalising treatments for genetic diseases
Principal Advisor
Other advisors: Dr Stephanie Portelli
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Doctor Philosophy
Use of structural phylogeny and reconciliation in molecular phylogenetics
Associate Advisor
Other advisors: Dr Kate Bowerman, Professor Phil Hugenholtz
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Doctor Philosophy
Unravelling the Physicochemical Drivers of Biomolecular Self-Assembly though Multiscale Simulations
Associate Advisor
Other advisors: Dr Evelyne Deplazes, Professor Megan O'Mara
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Doctor Philosophy
Computational design of targeted lipid technologies
Associate Advisor
Other advisors: Professor Megan O'Mara
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Doctor Philosophy
Therapeutic Resolution of Inflammation in the Central Nervous System for Neuroprotection in Parkinson's Disease
Associate Advisor
Other advisors: Professor Avril Robertson
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Doctor Philosophy
Breaking the chain of inflammation through targetting NLR proteins
Associate Advisor
Other advisors: Professor Avril Robertson
Media
Enquiries
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