Modeling and Interpretation of Interaction Space

Molecular weight, van der Waals volume, molecular surface area, number of hydrogen bond donors and acceptors, polarizability, electronegativity, logP, NMR shifts, chromatographic retention times etc. 

Binary representation Presence or absence of particular structural features in a molecule can be represented by bitstrings. Binary representation can also be used to characterize values of physico-chemical properties over or below a certain limit. 

Z-scales are obtained by principal component analysis of physico-chemical properties of monomers. E.g., the first Z-scales of amino adds describe hydrophobicity (z1), steric bulk/polarisability (z2) and polarity (z3) of the amino acids. 

Chimeric biopolymers are formed by interchanging sequence portions of two native biopolymers. Eg. the number 1 can be taken to represent physico-chemical properties of asequence portion of the first native biopolymer, whereas the number 0 (or -1) can be taken to represent the physico-chemical properties of the corresponding sequence portion of the other native biopolymer. 

PCM modeling aims to find an empirical relation (a PCM equation or model) that describes the interaction activities of the biopolymer-molecule pairs as accurate as possible. To this end, various linear and nonlinear correlation methods can be used. Nonlinear methods have hitherto been used to only a limited extent. The method of prime choice has been partial least-squares projection to latent structures (PLS), which has been found to work very satisfactorily in PCM. PCA is also an important data-preprocessing tool in PCM modeling. Modeling includes statistical model-validation techniques such as cross validation, external prediction, and variable-selection and signal-correction methods to obtain statistically valid models. (For general overviews of modeling methods see [10]). 

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