Abstract

Unstructured interactions between proteins and other molecules or surfaces are often described as nonspecific, and have received relatively little attention in terms of their role in biology. However, despite their lack of a specific binding structure, these unstructured interactions can in fact be very selective. The lack of a specific structure for these interactions makes them more difficult to study in a chemically meaningful way, but one approach is statistical, i.e. simply looking at a large number of different ligands and using that to understand the chemistry of binding. Surface-bound peptide arrays are useful in this regard, and have been used as a model previously for this purpose (Wang and Woodbury, 2014). In that study, the binding of several proteins, including β-galactosidase, to all possible dipeptides, tripeptides and tetrapeptides (using seven selected amino acids) was performed and analyzed in terms of the charge characteristics, hydrophobicity, etc., of the binding interaction. The current work builds upon that study by starting with a representative subset of the tetrapeptides characterized previously and either extending them by adding all possible combinations of one, two and three amino acids, or by concatenating 57 of the previously characterized tetrapeptides to each other in all possible combinations (including order). The extended and concatenated libraries were analyzed by binding either labeled β-galactosidase to them or by binding a mixture of 10 different labeled proteins of various sizes, hydrophobicities and charge characteristics to the peptide arrays. By comparing the binding signals from the tetrapeptides or amino acid extensions alone to the binding signals from the complete extended or concatenated sequences, it was possible to evaluate the extent to which affinity and specificity of the whole sequence depends on the subsequences that make it up. The conclusion is that while joining two component sequences together can either greatly increase or decrease overall binding and specificity (relative to the component sequences alone), the contribution to the binding affinity and specificity of the individual binding components is strongly dependent on their position in the peptide; component sequences that bind strongly at the C-terminus of the peptide do not necessarily add substantially to binding and specificity when placed at the N-terminus.

Abstract

Protein–surface interactions are of critical significance in both biological and man-made systems. While the term “specific binding” is normally reserved for the description of well-structured interactions, it is often the case in biology that there are unstructured interactions that greatly favor some protein interactions over others, a necessity in the highly crowded environment of the cell. In this study, surface-bound peptide arrays were used as a model to explore the range of protein–surface interactions and to better understand the kinds of “nonspecific” or unstructured interactions that take place at chemically complex surfaces. Three samples, β-galactosidase, α1-antitrypsin and a mixture of nine different proteins, were bound to arrays of nearly 5000 different peptides with a wide range of hydrophobicity, charge and peptide length. All three protein samples show higher binding affinity to positively charged peptides. While β-galactosidase binds poorly to very hydrophobic peptides, in terms of either absolute binding or relative to the mixture of proteins, α1-antitrypsin binds with higher affinity to more hydrophobic peptides. More surprising is the observation that β-galactosidase affinity for the surface does not simply increase with the length of the peptide, as one might expect, even when only the best binders are considered. Instead, its affinity (both absolute and relative to the protein mixture) peaks in the four-to-nine amino acid residue range and then decreases substantially by 12 amino acids. In contrast, α1-antitrypsin increases nearly monotonically with peptide length, in terms of both apparent affinity and binding relative to other proteins. Of particular significance in a practical sense, it was possible to obtain quite specific binding; the identity of the 100 peptides that showed the best apparent affinity for each of the three protein samples overlapped very little. Thus, using this approach it would be straightforward to develop surfaces covered with specific short peptide sequences with relatively specific protein interaction profiles.

Abstract

The initial electron transfer dynamics during photosynthesis have been studied in Rhodobacter sphaeroides reaction centers from wild type and 14 mutants in which the driving force and the kinetics of charge separation vary over a broad range. Surprisingly, the protein relaxation kinetics, as measured by tryptophan absorbance changes, are invariant in these mutants. By applying a reaction-diffusion model, we can fit the complex electron transfer kinetics of each mutant quantitatively, varying only the driving force. These results indicate that initial photosynthetic charge separation is limited by protein dynamics rather than by a static electron transfer barrier.

Fluorescence lifetime and anisotropy measurements were made on the red fluorescent protein (DsRed) from tropical coral of the Discosoma genus, both at single-molecule and bulk concentrations. As expected from previous work, the fluorescence lifetime of DsRed in solution is dependent on laser power, decreasing from an average fluorescence lifetime in the beam of about 3.3 ns at low power (3.5 ns if one extrapolates to zero power) to about 2.1 ns at 28 kW/cm². At the single-molecule level, exciting with 532 nm, 10 ps laser pulses at 80 MHz repetition rate, DsRed particles entering the laser beam initially have a lifetime of about 3.6 ns and convert to a form having a lifetime of about 3.0 ns with a quantum yield of photoconversion on the order of 10⁻³ (calculated in terms of photons per DsRed tetramer). The particles then undergo additional photoconversion with a quantum yield of roughly 10⁻⁵, generating a form with an average lifetime of 1.6 ns. These results may be explained by rapid photoconversion of one DsRed monomer in a tetramer, which acts as an energy transfer sink, resulting in a lower quantum yield for photoconversion of subsequent monomers. Multiparameter correlation and selective averaging can be used to identify DsRed in a mixture of fluorophores, in part exploiting the fact that fluorescent lifetime of DsRed changes as a function of excitation intensity.