CPP: Identifying Physicochemical Signatures

The central algorithm of the AAanalysis framework is Comparative Physicochemical Profiling (CPP), a sequence-based feature engineering algorithm for interpretable protein prediction [Breimann25a]. CPP enables the identification of physicochemical signatures underlying biological recognition processes. It thereby extends rational protein biology beyond mere sequence motifs.

The core idea of CPP is its feature concept:

Scheme of CPP feature (Part-Split-Scale combination) with example of feature creation, from [Breimann25a].

All possible parts are sub-parts or combinations of the Target Middle Domain (TMD), Juxta Middle Domain N-terminal (JMD-N), and Juxta Middle Domain N-terminal (JMD-C).

Scheme of sequence Parts comprising three basic parts from which each other can be derived from ([Breimann25a]): target middle domain (TMD), N- and C-terminal juxta middle domain (JMD-N and JMD-C).

These names were generalized from the first application of CPP on predicting substrates of γ-secretase, which is a pivotal intramembrane protease implicated in cancer and Alzheimer´s disease. γ-Secretases cleaves its substrates within their transmembrane domain (TMD) and their N- and C-terminal juxtamembrane domains (JMDs) are of high importance for recognition. The three different split types (Segment, Pattern, and PeriodicPattern) are exemplified for the two prominent γ-secretase substrates: the amyloid precursor protein (APP) and NOTCH1:

Scheme of part Splits, exemplifying the three split types ([Breimann25a]): segments, patterns, and periodic patterns.

CPP uses by default 120 continuous (segments) and 210 discontinuous (patterns and periodic patterns) splits:

Overview of Split classification and their count using default CPP settings, from [Breimann25a].

Scales can be chosen from AAontology, our two-level scale classification, based on their category or subcategory classification. To then select a redundancy-reduced scale set, AAanalysis provides the AAclust clustering wrapper.