SPPICES is a research project dedicated to advancing our understanding of protein dynamics and interactions by leveraging evolutionary insights. Building upon the groundbreaking achievements of AlphaFold2 and recent deep learning approaches, SPPICES aims to overcome current limitations by integrating evolutionary signals into structural bioinformatics. The project seeks to predict biologically relevant protein conformations and interactions more accurately, thereby illuminating the complex behaviors essential for protein function.
We aim to leverage AlphaFold2 (AF2) to predict multiple protein conformational states, both for individual proteins and multi-domain structures. Our approach involves guiding AF2's predictions through structural templates and strategic modifications of the input MSA.
SPPICES also seeks to understand and assess the structural ensembles of Intrinsically Disordered Proteins (IDPs). It aims to create new methods to analyze how these proteins evolve and develop a system to score and select their most biologically important conformations.
At the end of this project, we aim to develop robust computational tools for modeling and scoring protein interactions, with a particular focus on flexible and fuzzy interfaces. By leveraging the insights from our work on conformational states and disordered proteins, we will enhance our ability to predict dynamic protein-protein interactions.
By integrating evolutionary biology, structural bioinformatics, and cutting-edge deep learning methods, SPPICES seeks to revolutionize the precision and depth of protein structure predictions. This advancement will provide valuable insights into the molecular underpinnings of biological functions, significantly benefiting the scientific community, biotechnology, and medicine.
Institut de Biologie Intégrative de la Cellule (I2BC)
The project is coordinated by Diego Javier Zea, who brings expertise in structural bioinformatics and evolutionary biology.
****https://anr.fr/Project-ANR-24-CE45-0866
This JCJC (Young Researchers) project has been selected by ANR (French National Research Agency) in the AAPG 2024 under CE45 (Interfaces: Mathematics, Digital Sciences—Biology, Health). It is funded with €360,953 and will span 54 months, starting in December 2024.
Are you passionate about protein evolution, movements, interactions, disorder, or deep learning? Join our lab as a PhD student or Bioinformatics Engineer and work on cutting-edge research into intrinsically disordered proteins and conformational diversity using modern deep-learning tools.
You can postulate for the PhD position 🔗 HERE! To apply for the Bioinformatics Engineer position, follow 🔗 THIS LINK!