schrodinger.application.bioluminate.reactive_residues module

Identify protein sequences that are likely:

  1. Deamidation sites.

Standard rules exist for determining deamidation sites, i.e. X-Asn-Y and X-Gln-Y are considered the hottest deamidation targets, with Y=Gly, Ala, Ser, and with the rate determined to some extent by the nature of X (higher for X = polar). There seems to be some correlation with flexibility at the region, as well.

  1. Oxidation sites.

Identification of potential oxidation sites would start with highlighting the His, Met, Cys, Trp and Tyr residues.

  1. Glycosylation sites (most common).

N-linked: Asn. Consensus sequence: Asn-X-Ser/Thr (X=! Pro) O-linked: Ser and Thr. No consensus sequence. We do not identify these. At greater detail, there is some indication that Asn-X-Ser/Thr-Y can be considered and the tendency toward glycosylation is impacted by Y. (See, e.g. Mellquist et al Biochemistry (1998) 12, 6833-7).

  1. Proteolysis hot spots.

These would be Asp residues. The cleavage can occur at either the N or C-terminal end.

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class schrodinger.application.bioluminate.reactive_residues.ReactiveResidues(st, search_pre_defined=True, custom_patterns=[])

Find the reactive residues on a protein based on sequence patterns.

generateCSVTable()

Analyze the given structure and return the results summary in a CSV table

getNumResidues()

return the total number of residues in the sequences that will be analyzed.

iterateResidues()

Iterate over all residues and yield ResidueData objects (or None if the residue is not reactive) Note that one residue can be multiple reactive types and yielded multiple times

class schrodinger.application.bioluminate.reactive_residues.ResidueData(res, res_type, alpha_carbon, neighbor_alphas, custom_color, sasa_by_atom)

A container holding the data about the reactive residue