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Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most NP-protein binding approaches use 'tags' such as biotin or His-tags to provide high affinity; protein surface recognition provides a versatile alternative strategy. Generating high affinity NP-protein interactions is challenging however, due to dielectric screening at physiological ionic strengths. We report here the co-engineering of nanoparticles and protein to provide high affinity binding. In this strategy, 'supercharged' proteins provide enhanced interfacial electrostatic interactions with complementarily charged nanoparticles, generating high affinity complexes. Significantly, the co-engineered protein-nanoparticle assemblies feature high binding affinity even at physiologically relevant ionic strength conditions. Computational studies identify both hydrophobic and electrostatic interactions as drivers for these high affinity NP-protein complexes.

The biological functions of proteins closely depend on their conformational dynamics. This aspect is especially relevant for intrinsically disordered proteins (IDP) for which structural ensembles often offer more useful representations than individual conformations. Here we employ extensive enhanced sampling temperature replica-exchange atomistic simulations (TREMD) and deep learning dimensionality reduction to study the conformational ensembles of the human heat shock protein B8 and its pathological mutant K141E, for which no experimental 3D structures are available. First, we combined homology modelling with TREMD to generate high-dimensional data sets of 3D structures. Then, we employed a recently developed machine learning based post-processing algorithm, EncoderMap, to project the large conformational data sets into meaningful two-dimensional maps that helped us interpret the data and extract the most significant conformations adopted by both proteins during TREMD. These studies provide the first 3D structural characterization of HSPB8 and reveal the effects of the pathogenic K141E mutation on its conformational ensembles. In particular, this missense mutation appears to increase the compactness of the protein and its structural variability, at the same time rearranging the hydrophobic patches exposed on the protein surface. These results offer the possibility of rationalizing the pathogenic effects of the K141E mutation in terms of conformational changes.