Site saturation mutagenesis of 500 human protein domains reveals the contribution of protein destabilization to genetic disease

Abstract

Missense variants that change the amino acid sequences of proteins cause one third of human genetic diseases1. Tens of millions of missense variants exist in the current human population, with the vast majority having unknown functional consequences. Here we present the first large-scale experimental analysis of human missense variants across many different proteins. Using DNA synthesis and cellular selection experiments we quantify the impact of >500,000 variants on the abundance of >500 human protein domains. This dataset - Human Domainome 1.0 - reveals that >60% of pathogenic missense variants reduce protein stability. The contribution of stability to protein fitness varies across proteins and diseases, and is particularly important in recessive disorders. Mutational effects on stability are largely conserved in homologous domains, allowing accurate stability prediction across entire protein families using energy models. Combining stability measurements with protein language models annotates functional sites. Domainome 1.0 demonstrates the feasibility of assaying human protein variants at scale and provides a large consistent reference dataset for clinical variant interpretation and the training and benchmarking of computational methods.

Genetics, energetics and allostery during a billion years of hydrophobic protein core evolution

“…For each protein we measured the stability of a median of 8,500 randomly sampled genotypes using a highly-validated selection assay that quantifies the cellular concentration of folded protein over at least three orders of magnitude 18,20,45,64,65 . The cellular protein abundance measurements were well correlated for each protein between replicate experiments (median Pearson correlation coefficient r=0.78, Fig.…”

“…Indeed the exclusion of water by the burial of hydrophobic side chains -the hydrophobic effectis considered the major driving force in protein folding [5][6][7][8][9][10] , and buried core residues are both highly conserved during evolution and very sensitive to mutation [11][12][13][14] . In contrast, solvent-exposed residues on the surfaces of proteins are faster evolving with mutations typically having much smaller effects on stability 1,[15][16][17][18][19][20] . Surface residues can, however, be important for function, for example forming binding interfaces.…”

“…At the other extreme, mutations in cores might have largely independent effects, for example if core side-chain packing is highly malleable, allowing re-packing in many different combinations [30][31][32][33][34][35][36][37][38][39] . Unfortunately, quantifying the effects of individual mutations [15][16][17]19,20,[40][41][42] or pairs of mutations 18,[43][44][45] provides little information about the genetic and energetic architecture of cores as it only explores very local sequence space, revealing the outcome when one or two side chains are changed. Rather, what is needed are experiments where the side chains of many buried core positions are simultaneously changed in many different combinations, an approach referred to as combinatorial mutagenesis or core randomisation 3,[46][47][48][49][50][51][52][53] .…”

Energetic portrait of the amyloid beta nucleation transition state

“…A second key aspect of our approach is the use of a kinetic selection assay where enrichments report on the rate of a reaction. This is not true for most mutation-selection-sequencing experiments, where enrichments depend on thermodynamic stabilities 30,50,51 .…”