scoring - Loop ScoringΒΆ
Tools and algorithms to score loops. The scoring system is split between an environment and scorers. Several scorers can be attached to the same environment containing the actual structural data of the current modelling problem. The environment is updated as the modelling proceeds and manages efficient spatial lookups to be used by the attached scorers.
In this example, we load a structure, setup a score environment, link a few scorers to it and finally score some loops:
from ost import io, seq
from promod3 import loop, scoring
# load data
ent = io.LoadPDB("data/1CRN.pdb")
ent_seq = seq.SequenceFromChain('A', ent.FindChain('A'))
# setup score environment linked to entity
score_env = scoring.BackboneScoreEnv(ent_seq)
score_env.SetInitialEnvironment(ent)
# setup scorers attached to that env.
clash_scorer = scoring.ClashScorer()
clash_scorer.AttachEnvironment(score_env)
cbeta_scorer = scoring.LoadCBetaScorer()
cbeta_scorer.AttachEnvironment(score_env)
# calculate scores for 10 residues starting at residue number 23.
# all required structural information comes from the environment
# that can evolve as the modelling proceeds.
print("Clash-Score", clash_scorer.CalculateScore(23, 10))
print("CBeta-Score", cbeta_scorer.CalculateScore(23, 10))
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