Poster abstracts
Poster number 114 submitted by Haosheng Wen
A Curated AlphaFold 2 / AlphaFill Cadherinosome
Haosheng Wen (Biophysics graduate program), Wei Hsiang Weng (Biophysics graduate program), Marcos Sotomayor (Department of Chemistry and Biochemistry)
Abstract:
Cadherins are transmembrane proteins that play important roles in cell-cell adhesion, morphogenesis, signaling, and mechanotransduction. There are over 100 members of the cadherin superfamily in the human genome, and many have been structurally characterized. However, reliable atomistic structural models for most members are still missing. AlphaFold2, an artificial intelligence program developed by Google's DeepMind team has been used to generate highly accurate protein models of millions of proteins, including all cadherins present in the human genome. Despite AlphaFold2’s remarkably overall accuracy, cadherin models still have low-confidence regions with structural disorder, lack calcium ions at cadherin linker regions, and often display non-physiological architectures. Here we present curated AlphaFold2 models of human cadherins obtained by trimming their signal peptides, prodomains, and disordered/low confidence regions when applicable. We also added calcium ions to linker regions using AlphaFill and re-arranged the position of key structural elements of cadherins, such as their transmembrane domains, to obtain physiologically relevant conformations. The optimized models can be better used to perform structural and computational investigations of human cadherins.
Keywords: Protein design, Human cadherins