Researchers have created a new artificial intelligence (AI) model, DeepMVP, that identifies connections between protein modifications and genetic mutations that cause disease. The AI model significantly improves upon existing models. DeepMVP facilitates the development of new treatments by providing insights into disease mechanisms.
DeepMVP works by analysing how modifications to proteins, known as post-translational modifications (PTMs), are affected by genetic mutations. PTMs influence protein function and stability, and defects in PTMs have been linked to various diseases. The AI uses deep learning algorithms and protein structure prediction tools to model protein structures and simulate ligand-binding dynamics. This enables the identification of small molecule binding-associated PTMs that can influence drug binding across human proteins.
This AI-driven method enables accurate modelling of protein structures, including the prediction of PTM-modified regions. By understanding how mutations disrupt these modifications, researchers can develop targeted therapies to correct the dysfunction. The DeepMVP model represents a significant advancement in the field, offering a powerful tool for drug discovery and personalised medicine.
