Rapid protein stability prediction using deep learning representations.

Predicting the thermodynamic stability of proteins is a common and widely used step in protein engineering, and when elucidating the molecular mechanisms behind evolution and disease. Here, we present RaSP, a method for making rapid and accurate predictions of changes in protein stability by leveraging deep learning representations. RaSP performs on-par with biophysics-based methods and enables saturation mutagenesis stability predictions in less than a second per residue. We use RaSP to calculate ∼ 230 million stability changes for nearly all single amino acid changes in the human proteome, and examine variants observed in the human population. We find that variants that are common in the population are substantially depleted for severe destabilization, and that there are substantial differences between benign and pathogenic variants, highlighting the role of protein stability in genetic diseases. RaSP is freely available-including via a Web interface-and enables large-scale analyses of stability in experimental and predicted protein structures

A comprehensive map of human glucokinase variant activity

Abstract Background Glucokinase (GCK) regulates insulin secretion to maintain appropriate blood glucose levels. Sequence variants can alter GCK activity to cause hyperinsulinemic hypoglycemia or hyperglycemia associated with GCK-maturity-onset diabetes of the young (GCK-MODY), collectively affecting up to 10 million people worldwide. Patients with GCK-MODY are frequently misdiagnosed and treated unnecessarily. Genetic testing can prevent this but is hampered by the challenge of interpreting novel missense variants. Result Here, we exploit a multiplexed yeast complementation assay to measure both hyper- and hypoactive GCK variation, capturing 97% of all possible missense and nonsense variants. Activity scores correlate with in vitro catalytic efficiency, fasting glucose levels in carriers of GCK variants and with evolutionary conservation. Hypoactive variants are concentrated at buried positions, near the active site, and at a region of known importance for GCK conformational dynamics. Some hyperactive variants shift the conformational equilibrium towards the active state through a relative destabilization of the inactive conformation. Conclusion Our comprehensive assessment of GCK variant activity promises to facilitate variant interpretation and diagnosis, expand our mechanistic understanding of hyperactive variants, and inform development of therapeutics targeting GCK

Additional file 4 of A comprehensive map of human glucokinase variant activity

Additional file 4. Review history

Additional file 2 of A comprehensive map of human glucokinase variant activity

Additional file 2

Additional file 1 of A comprehensive map of human glucokinase variant activity

Additional file 1: Fig. S1. Expression of GCK variants. Fig. S2. Co-expression of GKRP and GCK. Fig. S3. Imputed map of glucokinase variant activity. Fig. S4. Activity scores mapped onto GCK ribbon diagram. Fig. S5. Evolutionary analysis of GCK homologous sequences. Fig. S6. Correlations between evolutionary conservation and activity scores. Fig. S7. Rosetta ΔΔG heatmaps. Fig. S8. Positions predicted to shift GCK towards the closed conformation are enriched at the allosteric activator site.Please check additional files if captured correctly.Error during converting author query response. Please check the eproofing link or feedback pdf for detail

Additional file 3 of A comprehensive map of human glucokinase variant activity

Additional file 3