Final Activity Report Summary - PTMFOLDX (Predicting Structural Effects of Motif Sequence Variations on Posttranslational Protein Modifications)
Since the sequencing of the human genome which shed light on the complete set of our genes, we have moved to the elucidation of the function of these genes. Each gene can be translated into a protein and these proteins act together to direct cell growth and duplication, produce or convert energy, process signals from the environment or build the framework for cellular structures. Often, physical interaction between two proteins is required to execute such functions. In the special case of posttranslational modifications, a small portion of one protein, a peptide, is recognised by a second protein in order to be modified for specific tasks, such as anchoring the protein into membranes or being turned on or off in signal relay networks.
Our project aimed to improve methodology to predict which peptides can be recognised by proteins for posttranslational modifications by combining information from the peptide sequence with models of the 3-dimensional structure of the interaction complex. Moreover, we have shown that our methodology can be generalised to the prediction of any peptide-protein and peptide-peptide interaction.
Among others, the most significant application of our methodology in this project has been to predict the interaction of short peptides with each other leading to the formation of higher order amyloid fibres. These fibres are implicated in a range of amyloid deposit diseases, including neurodegenerative disorders, such as Parkinson's or Alzheimer's. Our prediction tool, termed Waltz, not only outperforms other methods in benchmarks but, more importantly, has been validated by the experimental verification of 48 novel peptides predicted to form amyloid fibres. Our predictor, Waltz, can be used to identify the portions of a protein that are prone to amyloid fibre formation in known disease proteins as well as screen for proteins not yet known to relate to amyloid diseases. Additionally, we can predict if a mutation could have disease-causing effects through amyloid fibre deposits. This brings us several steps closer to finding new genetic markers for diagnosis of a wide variety of amyloid-related diseases and shedding more light on their underlying molecular basis, which ultimately could be exerted for new treatments in the future.
Our project aimed to improve methodology to predict which peptides can be recognised by proteins for posttranslational modifications by combining information from the peptide sequence with models of the 3-dimensional structure of the interaction complex. Moreover, we have shown that our methodology can be generalised to the prediction of any peptide-protein and peptide-peptide interaction.
Among others, the most significant application of our methodology in this project has been to predict the interaction of short peptides with each other leading to the formation of higher order amyloid fibres. These fibres are implicated in a range of amyloid deposit diseases, including neurodegenerative disorders, such as Parkinson's or Alzheimer's. Our prediction tool, termed Waltz, not only outperforms other methods in benchmarks but, more importantly, has been validated by the experimental verification of 48 novel peptides predicted to form amyloid fibres. Our predictor, Waltz, can be used to identify the portions of a protein that are prone to amyloid fibre formation in known disease proteins as well as screen for proteins not yet known to relate to amyloid diseases. Additionally, we can predict if a mutation could have disease-causing effects through amyloid fibre deposits. This brings us several steps closer to finding new genetic markers for diagnosis of a wide variety of amyloid-related diseases and shedding more light on their underlying molecular basis, which ultimately could be exerted for new treatments in the future.