RESUMEN
The larger size and diversity of phage display peptide libraries enhance the probability of finding clinically valuable ligands. A simple way of increasing the throughput of selection is to mix multiple peptide libraries with different characteristics of displayed peptides and use it as biopanning input. In phage display, the peptide is genetically coupled with a biological entity (the phage), and the representation of peptides in the selection system is dependent on the propagation capacity of phages. Little is known about how the characteristics of displayed peptides affect the propagation capacity of the pooled library. In this work, next-generation sequencing (NGS) was used to investigate the amplification capacity of three widely used commercial phage display peptide libraries (Ph.D.™-7, Ph.D.™-12, and Ph.D.™-C7C from New England Biolabs). The three libraries were pooled and subjected to competitive propagation, and the proportion of each library in the pool was quantitated at two time points during propagation. The results of the inter-library competitive propagation assay led to the conclusion that the propagation capacity of phage libraries on a population level is decreased with increasing length and cyclic conformation of displayed peptides. Moreover, the enrichment factor (EF) analysis of the phage population revealed a higher propagation capacity of the Ph.D.TM-7 library. Our findings provide evidence for the contribution of the length and structural conformation of displayed peptides to the unequal propagation rates of phage display libraries and suggest that it is important to take peptide characteristics into account once pooling multiple combinatorial libraries for phage display selection through biopanning.
Asunto(s)
Bacteriófagos , Biblioteca de Péptidos , Péptidos/química , Técnicas de Visualización de Superficie Celular , Bacteriófagos/genética , Conformación MolecularRESUMEN
Amyloid aggregation is associated with many diseases and may also occur in therapeutic protein formulations. Addition of co-solutes is a key strategy to modulate the stability of proteins in pharmaceutical formulations and select inhibitors for drug design in the context of diseases. However, the heterogeneous nature of this multicomponent system in terms of structures and mechanisms poses a number of challenges for the analysis of the chemical reaction. Using insulin as protein system and polysorbate 80 as co-solute, we combine a spatially resolved fluorescence approach with single molecule microscopy and machine learning methods to kinetically disentangle the different contributions from multiple species within a single aggregation experiment. We link the presence of interfaces to the degree of heterogeneity of the aggregation kinetics and retrieve the rate constants and underlying mechanisms for single aggregation events. Importantly, we report that the mechanism of inhibition of the self-assembly process depends on the details of the growth pathways of otherwise macroscopically identical species. This information can only be accessed by the analysis of single aggregate events, suggesting our method as a general tool for a comprehensive physicochemical characterization of self-assembly reactions.