ABSEIL: A polypeptide helicity and ensemble prediction tool.

Nascent helicity in polypeptides and unfolded proteins arises from local structure formation and represents one of the earliest events in a protein folding reaction. Nascent helicity may also influence the physical properties of intrinsically disordered regions. For this reason, there has been great interest in statistical mechanical models that describe the coil→helix transitions that lead to nascent helicity. These models, collectively called helix-coil models, have been empirically parameterized using an extensive data set of circular dichroism (CD) measurements of natural and designed peptides that form various degrees of nascent helicity. The purpose of A Bayesian Statistical Engine to Infer HeLicity (ABSEIL) (https://abseil.oit.duke.edu/) is to allow users to submit polypeptide sequences to: (1) predict the overall helicity of the sequence; (2) predict the helicity of each residue; and (3) enumerate the ensemble of helix-coil configurations in order of their relative populations. The tool also allows users to search the database of peptide CD experiments on which the predictive model was trained. The website architecture allows for anonymous usage and enables administrative management. The web application server is managed by the Duke Office of Information Technology (OIT) system administrators and conforms to OIT's security and operational best practices.

Duke Scholars

Author Terrence Gilbert Oas Biochemistry

Author Scott C. Schmidler Statistical Science