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 [Breimann25]. CPP enables the identification of physicochemical signatures underlying biological recognition processes. It thereby extends rational protein biology beyond mere sequence motifs.

Provided by

In AAanalysis this is the CPP class, with SequenceFeature for building parts and splits and CPPPlot for the figures. See the API reference and the tutorials.

The core idea of CPP is its feature concept:

../../_images/scheme_CPP1.png — Scheme of CPP feature (**Part-Split-Scale** combination) with example of feature creation, from [Breimann25].

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).

../../_images/scheme_CPP2.png — Scheme of sequence **Parts** comprising three basic parts from which each other can be derived from ([Breimann25]): 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:

../../_images/scheme_CPP3.png — Scheme of part **Splits**, exemplifying the three split types ([Breimann25]): segments, patterns, and periodic patterns.

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

../../_images/scheme_CPP4.png — Overview of **Split** classification and their count using default CPP settings, from [Breimann25].

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.