AI-driven ensemble and pocket profiling for patient-specific targeting of intrinsically disordered proteins (IDPs) in neurodegeneration and oncology

Prof. Dr. Orkide Coskuner Weber would like to join your consortium, You can find her Specialized Profile below.

She is a computational biophysicist and molecular biotechnologist working at the interface of bioinformatics, protein structure dynamics, intrinsically disordered proteins, molecular simulations, artificial intelligence and emerging quantum computing approaches. Her research focuses on neurodegenerative diseases, especially Alzheimer’s and Parkinson’s disease, and aims to understand how sequence variation, structural disorder, conformational ensembles and environmental factors give rise to pathology. She develops a new theoretical and computational framework, disordered mechanics, for order–disorder transitions in complex biological systems, and she integrates ensemble-based descriptors with multi-omics, imaging and clinical data in a systems biomedicine context. She has a strong track record in interdisciplinary collaborations, student supervision, external funding and programme development, and She is deeply committed to teaching and mentoring at the interface of biology, physics, chemistry, computer science and medicine.

Proposed contribution (as Partner): We contribute a computational pipeline that integrates (i) disorder-aware sequence/structure modelling, (ii) ensemble generation and calibration, and (iii) transient pocket/interaction-site discovery in IDPs and flexible proteins. The output is a set of patient-relevant, actionable molecular features e.g., variant-dependent ensemble shifts, pocket persistence maps, and candidate binding hot-spots supporting precision stratification and therapeutic hypothesis generation.
Personalised medicine relevance: The method is designed to incorporate patient-specific variants (SNVs), isoforms/proteoforms, and omics-informed context, enabling prediction of how individual molecular differences alter conformational landscapes and druggability thereby informing patient stratification and personalised intervention strategies.

Expected joint outcomes: A validated workflow for PM-oriented molecular stratification and target/druggability assessment, plus a sharable toolkit and pilot results on one or two representative use cases aligned with consortium strengths.