Amino acid mutations in disease

Research project Amino acid mutations in disease

Assessing the likely effect of amino acid mutations on a protein (and the organism it is in)

We developed the DEOGEN approach, which predicts whether a particular amino acid variant in a human protein is likely to cause a 'rare' disease in the person carrying that mutation in their genetic material. The advantage of our approach is that we try to 'contextualise' the protein as much as possible by including information such as whether it is encoded by an essential gene or whether it interacts with many other proteins. The effect the mutation directly has on the protein is important, but the kind of protein it is and what role it has in the organism is equally relevant. We have extended this concept in the DEOGEN2 approach, where the predictions can be visualised in a highly interactive web server part of the MutaFrame project. In addition, we are further working in collaboration with Prof. Rooman (ULB) on understanding the 'molecular phenotype' of mutations, i.e. their direct effect on the protein itself. In the TumorScope project, these principles are extended towards distinguishing driver from passenger mutations in cancer, where the former are responsible for the cancer to develop, and the latter are random mutations that occur because of the fast growth and mutation rate of the cancer cells.

Funding

ICITY-RDI.BRU (Jan. 1, 2014-Dec. 31, 2023)
A software framework for identifying molecular causes of human diseases (Mutaframe)

TumorScope (Oct. 1, 2019-Sept. 30, 2024)
In this interdisciplinary research project (IRP) from the VUB, we leverage the unique expertise and data present at the VUB and the UZ Brussel to create a general framework to store and analyze raw medical data, both at the image and molecular level, in relation to solid tumors, their clinical behavior and response to therapies. An integrated research platform, which conforms to GDPR and patient legislation, will enable AI-driven extraction of new information on breast and brain tumors, as well as sarcomas. Combined with expert insights from clinicians, we will work towards assisting and improving the decision-making process in especially multi-disciplinary oncology consults (MOC).

Hosmart-AI (April 1, 2021-March 31, 2025)
<a href="https://www.hosmartai.eu">Hosmart-AI</a> is a European project to develop a marketplace for AI solutions in the health sector. We contribute one of the 'pilots' in this grant, based on TumorScope.

Resources

DEOGEN2 (Software tool, In-house)

ST resource  DEOGEN2
Predicting the effect of amino acid mutations in human proteins