Publikationer pr. år
Publikationer pr. år
Publikationer pr. år
The explosion of biomedical data such as in genomics, structural biology and pharmacology can provide new opportunities to improve our understanding of human physiology and disease. G protein-coupled receptors (GPCRs) mediate a vast variety of critical biological processes and provide an ideal case study on the focused integration of these amounts of data with innovative computational tools to gain novel insights into receptor biology. My PhD focused on how to harness the biodata revolution i) to identify new trends in GPCR drug discovery, ii) to investigate how subtle genetic variations can imbalance GPCR signalling, iii) to discover novel human signalling systems and iv) to understand the determinants of selectivity between receptors and their signalling partners.
I am now trying to to provide a basis for genetics-based personalised drug prescriptions for some of the most commonly used CNS drugs acting on G protein-coupled receptors (GPCRs), and to create a public research platform to characterise GPCR genetic variants (funded by Lunbeck)
What are the current trends in GPCR drug discovery? (I)
We reported a recent analysis of all GPCR drugs and agents in clinical trials, which revealed current trends across drug targets, molecule types and therapeutic indications. The field is readily exploring previously untargeted receptors such as peptide and protein GPCRs and is investigating new types of agents such as monoclonal antibodies, recombinant proteins and allosteric modulators. The advent of GPCR structures are starting to impact drug discovery and new opportunities are emerging for GPCR targeted agents in oncology and metabolic diseases.
What is the prevalence of natural genetic variation in GPCRs? (II)
By integrating genomics data and GPCR structure data we found that several GPCRs targeted by drugs show extensive genetic variation in the human population. We showed that this variation occurs in parts of the GPCR protein that matter for the drug response. For example, we observed polymorphisms in the GPCR targeted by morphine and painkillers, which may explain why antidotes to an opioid overdose may not always work. This is a good example of how an integrative, data-science based approach can provide new insights and potentially have an impact on society and healthcare
Can we identify new hormones for uncharacterised (orphan) receptors? (III)
We investigated the human peptide signalling system and universal characteristics of peptide ligands and their cognate receptors. With these insights, we select putative peptide binding receptors among class A orphan GPCRs and design a library of potentially new endogenous peptide ligands. We identified multiple new receptor-ligand pairs in a multifaceted screening approach, with 26 new ligands paired with 5 receptors among additional indicative pairings for 5 receptors.
How is receptor-G protein selectivity determined? (IV)
We laid the foundation for understanding the molecular basis of coupling selectivity within individual receptors and G proteins. Universally conserved patterns of amino acids in the G proteins are recognised by individual receptors differently through distinct residues - like non-identical cuts in keys (receptors) opening the same lock (G proteins).
I am conducting my research as a member of the Gloriam Group.
As the president of the CBioVikings, RSG International Society for Computational Biology (ISCB), I have been trying to provide a networking platform and learning opportunity for Bioinformaticians and computational Biologists in the Copenhagen Area.
Twitter: @alexshauser
Positions
03/2019-03/2024: 5-year Postdoc contract: "Advancing personalised medicine for psychiatric diseases through integrative GPCR pharmacogenomics"
11/2016-04/2017: Research visit to the Babu group working on natural variation data form 60,000 individuals
05/2016-05/2017: President of CBioVikings, RSG ISCB
11/2015-03/2019: PhD Fellow "Computational receptor biology - Data science approaches to physiological ligand discovery, G protein selectivity and pharmacogenomics", (Suppervisor: Professor David Gloriam), University of Copenhagen, Denmark
08/2015-11/2015: Research Assistant (David Gloriam) , University of Copenhagen, Denmark
06/2014-08/2015: Masters's thesis “Determination of orphan receptor physiological peptide agonists by a novel evolutionary fingerprint method” (David Gloriam), University of Copenhagen, Denmark
01/2014-05/2014: Internship “virtual screening, molecular modeling and peptide docking” (Dr. Björn Windshügel), European Screening Port GmbH (Fraunhofer Institute for Molecular Biology, IME), Hamburg, Germany
05/2012-08/2012: Research exchange “Investigation and design of methionine aminopeptidase inhibitors using 3D-QSAR and molecular docking“, University of Hyderabad, India
08/2011-12/2011: Research exchange in Helsinki, Finland
Education
2015: MSc in Molecular Medicine (comp. profile), University of Münster, Germany
2013: BSc in Biosciences, University of Münster, Germany
I 2015 blev FN-landende enige om 17 Verdensmål til at standse fattigdom, beskytte planeten og sikre velstand for alle. Denne persons arbejde bidrager til følgende verdensmål:
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Publikation: Bidrag til tidsskrift › Konferenceabstrakt i tidsskrift › Forskning › peer review
15/12/2017
1 element af Mediedækning
Presse/medie
11/05/2017
1 Mediebidrag
Presse/medie
Hauser, A. S. (Ophavsmand), Zenodo, 2021
DOI: 10.5281/zenodo.4632863, https://zenodo.org/record/4632863
Datasæt
Hauser, A. S. (Ophavsmand), Zenodo, 2021
DOI: 10.5281/zenodo.4629649, https://zenodo.org/record/4629649
Datasæt
Hauser, A. S. (Ophavsmand), Zenodo, 2021
DOI: 10.5281/zenodo.4629651, https://zenodo.org/record/4629651
Datasæt