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
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
2022
Journal Article
cardioToxCSM: a web server for predicting cardiotoxicity of small molecules
Iftkhar, Saba, de Sá, Alex G. C., Velloso, João P. L., Aljarf, Raghad, Pires, Douglas E. V. and Ascher, David B. (2022). cardioToxCSM: a web server for predicting cardiotoxicity of small molecules. Journal of Chemical Information and Modeling, 62 (20), 4827-4836. doi: 10.1021/acs.jcim.2c00822
2022
Journal Article
CSM‐peptides: A computational approach to rapid identification of therapeutic peptides
Rodrigues, Carlos H. M., Garg, Anjali, Keizer, David, Pires, Douglas E. V. and Ascher, David B. (2022). CSM‐peptides: A computational approach to rapid identification of therapeutic peptides. Protein Science, 31 (10) e4442, 1-9. doi: 10.1002/pro.4442
2022
Journal Article
Identifying the molecular drivers of ALS-implicated missense mutations
Portelli, Stephanie, Albanaz, Amanda, Pires, Douglas Eduardo Valente and Ascher, David Benjamin (2022). Identifying the molecular drivers of ALS-implicated missense mutations. Journal of Medical Genetics, 60 (5) 108798, 1-7. doi: 10.1136/jmg-2022-108798
2022
Journal Article
VIVID: a web application for variant interpretation and visualisation in multidimensional analyses
Tichkule, Swapnil, Myung, Yoochan, Naung, Myo T., Ansell, Brendan R. E., Guy, Andrew J., Srivastava, Namrata, Mehra, Somya, Cacciò, Simone M, Mueller, Ivo, Barry, Alyssa E, van Oosterhout, Cock, Pope, Bernard, Ascher, David B and Jex, Aaron R (2022). VIVID: a web application for variant interpretation and visualisation in multidimensional analyses. Molecular Biology and Evolution, 39 (9) msac196. doi: 10.1093/molbev/msac196
2022
Journal Article
GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms
Paiva, Vinícius A., Mendonça, Murillo V., Silveira, Sabrina A., Ascher, David B., Pires, Douglas E. V. and Izidoro, Sandro C. (2022). GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms. Briefings in Bioinformatics, 23 (5) bbac178, 1-9. doi: 10.1093/bib/bbac178
2022
Journal Article
Sequence grammar underlying the unfolding and phase separation of globular proteins
Ruff, Kiersten M., Choi, Yoon Hee, Cox, Dezerae, Ormsby, Angelique R., Myung, Yoochan, Ascher, David B., Radford, Sheena E., Pappu, Rohit V. and Hatters, Danny M. (2022). Sequence grammar underlying the unfolding and phase separation of globular proteins. Molecular Cell, 82 (17), 3193-3208.e8. doi: 10.1016/j.molcel.2022.06.024
2022
Journal Article
toxCSM: comprehensive prediction of small molecule toxicity profiles
de Sá, Alex G.C., Long, Yangyang, Portelli, Stephanie, Pires, Douglas E.V. and Ascher, David B. (2022). toxCSM: comprehensive prediction of small molecule toxicity profiles. Briefings in Bioinformatics, 23 (5) bbac337, 1-11. doi: 10.1093/bib/bbac337
2022
Journal Article
Use of cluster analysis to characterise aortic stenosis phenotypes with treatable and untreatable risk
Sen, J., Pires, D., de Sá, A., Ascher, D., Wahir, S. and Marwick, T. (2022). Use of cluster analysis to characterise aortic stenosis phenotypes with treatable and untreatable risk. Heart, Lung and Circulation, 31, S44-S45. doi: 10.1016/j.hlc.2022.06.016
2022
Journal Article
HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase
Karmakar, Malancha, Cicaloni, Vittoria, Rodrigues, Carlos H. M., Spiga, Ottavia, Santucci, Annalisa and Ascher, David B. (2022). HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase. Current Research in Structural Biology, 4, 271-277. doi: 10.1016/j.crstbi.2022.08.001
2022
Journal Article
CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning
Rodrigues, Carlos H. M. and Ascher, David B (2022). CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning. Nucleic Acids Research, 50 (W1), W204-W209. doi: 10.1093/nar/gkac381
2022
Journal Article
Structural landscapes of PPI interfaces
Rodrigues, Carlos H. M., Pires, Douglas E. V., Blundell, Tom L. and Ascher, David B. (2022). Structural landscapes of PPI interfaces. Briefings in Bioinformatics, 23 (4) bbac165, 1-10. doi: 10.1093/bib/bbac165
2022
Journal Article
Evaluating hierarchical machine learning approaches to classify biological databases
Rezende, Pâmela M., Xavier, Joicymara S., Ascher, David B., Fernandes, Gabriel R. and Pires, Douglas E. V. (2022). Evaluating hierarchical machine learning approaches to classify biological databases. Briefings in Bioinformatics, 23 (4) bbac216, 1-14. doi: 10.1093/bib/bbac216
2022
Journal Article
cropCSM: designing safe and potent herbicides with graph-based signatures
Pires, Douglas E V, Stubbs, Keith A, Mylne, Joshua S and Ascher, David B (2022). cropCSM: designing safe and potent herbicides with graph-based signatures. Briefings in Bioinformatics, 23 (2) bbac042. doi: 10.1093/bib/bbac042
2022
Journal Article
Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures
Pan, Qisheng, Nguyen, Thanh Binh, Ascher, David B and Pires, Douglas E V (2022). Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures. Briefings in Bioinformatics, 23 (2) bbac025. doi: 10.1093/bib/bbac025
2022
Journal Article
Known allosteric proteins have central roles in genetic disease
Abrusán, György, Ascher, David B. and Inouye, Michael (2022). Known allosteric proteins have central roles in genetic disease. PLoS Computational Biology, 18 (2) e1009806, 1-28. doi: 10.1371/journal.pcbi.1009806
2022
Journal Article
epitope3D: a machine learning method for conformational B-cell epitope prediction
da Silva, Bruna Moreira, Myung, YooChan, Ascher, David B. and Pires, Douglas E. V. (2022). epitope3D: a machine learning method for conformational B-cell epitope prediction. Briefings in Bioinformatics, 23 (1) bbab423, 1-8. doi: 10.1093/bib/bbab423
2022
Journal Article
Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria
Sharma, Mahima, Lingford, James P., Petricevic, Marija, Snow, Alexander J. D., Zhang, Yunyang, Järvå, Michael A., Mui, Janice W.-Y., Scott, Nichollas E., Saunders, Eleanor C., Mao, Runyu, Epa, Ruwan, da Silva, Bruna M., Pires, Douglas E. V., Ascher, David B., McConville, Malcolm J., Davies, Gideon J., Williams, Spencer J. and Goddard-Borger, Ethan D. (2022). Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria. Proceedings of the National Academy of Sciences, 119 (4), e2116022119. doi: 10.1073/pnas.2116022119
2022
Journal Article
CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function
Nguyen, Thanh Binh, Pires, Douglas E. V. and Ascher, David B. (2022). CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function. Briefings in Bioinformatics, 23 (1) bbab512, 1-8. doi: 10.1093/bib/bbab512
2021
Journal Article
TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction
Uthayopas, Korawich, de Sá, Alex G.C., Alavi, Azadeh, Pires, Douglas E.V. and Ascher, David B. (2021). TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction. Molecular Therapy - Nucleic Acids, 26, 536-546. doi: 10.1016/j.omtn.2021.08.016
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
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
Machine Learning for Protein Dynamics: Predicting Post-Translational Modifications and Mutation Effects
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
Improving rational antibody design using machine learning
Principal Advisor
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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
Exploring Cardiotoxicity Risk Factors
Principal Advisor
Other advisors: Dr Thanh-Binh Nguyen
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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
Computational approaches to engineer and modulate G protein-coupled receptors
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
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
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
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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