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Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition.We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the exnovo optimization of peptide based binders. Copyright

Intrinsically Disordered Proteins (IDPs) are characterized by the lack of well-defined 3-D structure and show high conformational plasticity. For this reason, they are a strong challenge for the traditional characterization of structure, supramolecular assembly and biorecognition phenomena. We show here how the fine tuning of protein orientation on a surface turns useful in the reliable testing of biorecognition interactions of IDPs, in particular α-Synuclein. We exploited atomic force microscopy (AFM) for the selective, nanoscale confinement of α-Synuclein on gold to study the early stages of α-Synuclein aggregation and the effect of small molecules, like dopamine, on the aggregation process. Capitalizing on the high sensitivity of AFM topographic height measurements we determined, for the first time in the literature, the dissociation constant of dopamine-α-Synuclein adducts., Scientific Reports, 4, ISSN:2045-2322

We present a method for designing artificial receptors capable of binding with high affinity to a chosen target organic molecule. The primary sequence of the peptide is optimized to maximize its binding affinity. Our algorithm builds on a combination of molecular dynamics, semiflexible docking, and replica exchange Monte Carlo and performs simultaneous sampling in sequence and conformational spaces carefully selecting the degree of flexibility in the mutated peptides. The approach is used to design a decapeptide able to bind efavirenz. The calculated binding energy of the designed peptide (approximately -12 kcal/mol) was confirmed experimentally by fluorescence measurements. NMR spectroscopy confirmed the interactions between the peptide and the efavirenz molecule predicted by the algorithm.