Unraveling the Multistimuli Responses of a Complex Dynamic System of Pseudopeptidic Macrocycles

Abstract

Dynamic combinatorial libraries (DCLs) are excellent benchmark models to study the stimuli-responsiveness of chemical networks. However, increasingly complex systems are difficult to analyze with simple data analysis methods, because many variables and connections must be considered for their full understanding. Here we propose the use of multivariate data analysis methods to bisect the evolution of a complex synthetic dynamic library of pseudopeptidic macrocycles, containing side chains with charges of different sign. Several stimuli (ionic strength, pH and the presence of a biogenic polyamine) were applied to the same dynamic chemical mixture, and the adaptation of the whole system was characterized by HPLC and analyzed with principal component analysis (PCA) and multivariate curve resolution-alternating least squares (MCR-ALS) methods. Both multivariate data analysis chemometric approaches are an excellent combination to extract both qualitative and semi-quantitative information about the adaptive process of the library upon the action of each stimulus. The resolution of the system with these chemometric tools proved to be especially useful when two inter-connected stimuli were combined in the same dynamic system. Our results demonstrate the utility of these two approaches for the analysis of complex dynamic chemical systems and open the way toward the application of these powerful tools in the emergent field of systems chemistry.