Chemical validation of a druggable site on Hsp27/HSPB1 using in silico solvent mapping and biophysical methods.

Destabilizing mutations in small heat shock proteins (sHsps) are linked to multiple diseases; however, sHsps are conformationally dynamic, lack enzymatic function and have no endogenous chemical ligands. These factors render sHsps as classically "undruggable" targets and make it particularly challenging to identify molecules that might bind and stabilize them. To explore potential solutions, we designed a multi-pronged screening workflow involving a combination of computational and biophysical ligand-discovery platforms. Using the core domain of the sHsp family member Hsp27/HSPB1 (Hsp27c) as a target, we applied mixed solvent molecular dynamics (MixMD) to predict three possible binding sites, which we confirmed using NMR-based solvent mapping. Using this knowledge, we then used NMR spectroscopy to carry out a fragment-based drug discovery (FBDD) screen, ultimately identifying two fragments that bind to one of these sites. A medicinal chemistry effort improved the affinity of one fragment by ~50-fold (16 µM), while maintaining good ligand efficiency (~0.32 kcal/mol/non-hydrogen atom). Finally, we found that binding to this site partially restored the stability of disease-associated Hsp27 variants, in a redox-dependent manner. Together, these experiments suggest a new and unexpected binding site on Hsp27, which might be exploited to build chemical probes.

Robust Sequence Determinants of α-Synuclein Toxicity in Yeast Implicate Membrane Binding.

Protein conformations are shaped by cellular environments, but how environmental changes alter the conformational landscapes of specific proteins in vivo remains largely uncharacterized, in part due to the challenge of probing protein structures in living cells. Here, we use deep mutational scanning to investigate how a toxic conformation of α-synuclein, a dynamic protein linked to Parkinson's disease, responds to perturbations of cellular proteostasis. In the context of a course for graduate students in the UCSF Integrative Program in Quantitative Biology, we screened a comprehensive library of α-synuclein missense mutants in yeast cells treated with a variety of small molecules that perturb cellular processes linked to α-synuclein biology and pathobiology. We found that the conformation of α-synuclein previously shown to drive yeast toxicity-an extended, membrane-bound helix-is largely unaffected by these chemical perturbations, underscoring the importance of this conformational state as a driver of cellular toxicity. On the other hand, the chemical perturbations have a significant effect on the ability of mutations to suppress α-synuclein toxicity. Moreover, we find that sequence determinants of α-synuclein toxicity are well described by a simple structural model of the membrane-bound helix. This model predicts that α-synuclein penetrates the membrane to constant depth across its length but that membrane affinity decreases toward the C terminus, which is consistent with orthogonal biophysical measurements. Finally, we discuss how parallelized chemical genetics experiments can provide a robust framework for inquiry-based graduate coursework.

Site-specific incorporation of quadricyclane into a protein and photocleavage of the quadricyclane ligation adduct.

The quadricyclane (QC) ligation is a bioorthogonal reaction between a quadricyclane moiety and a nickel bis(dithiolene) derivative. Here we show that a QC amino acid can be incorporated into a protein site-specifically using the pyrrolysine-based genetic code expansion platform, and subsequently used for ligation chemistry. Additionally, we exploited the photolability of the QC ligation product to render the adduct cleavable with a handheld UV lamp. We further developed a protein purification method that involves QC ligation of biotin to a protein of interest, capture on streptavidin resin, and finally release using only UV light. The QC ligation thus brings novel chemical manipulations to the realm of bioorthogonal chemistry.

Statistical Coupling Analysis-Guided Library Design for the Discovery of Mutant Luciferases.

Directed evolution has proven to be an invaluable tool for protein engineering; however, there is still a need for developing new approaches to continue to improve the efficiency and efficacy of these methods. Here, we demonstrate a new method for library design that applies a previously developed bioinformatic method, Statistical Coupling Analysis (SCA). SCA uses homologous enzymes to identify amino acid positions that are mutable and functionally important and engage in synergistic interactions between amino acids. We use SCA to guide a library of the protein luciferase and demonstrate that, in a single round of selection, we can identify luciferase mutants with several valuable properties. Specifically, we identify luciferase mutants that possess both red-shifted emission spectra and improved stability relative to those of the wild-type enzyme. We also identify luciferase mutants that possess a >50-fold change in specificity for modified luciferins. To understand the mutational origin of these improved mutants, we demonstrate the role of mutations at N229, S239, and G246 in altered function. These studies show that SCA can be used to guide library design and rapidly identify synergistic amino acid mutations from a small library.