Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning.

Despite the importance of Aβ aggregation in Alzheimer's disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from studies. For example, proline and alanine scanning mutagenesis of Aβ proposed core regions important for aggregation. However, we lack even this limited mutagenesis data for the more disease-relevant Aβ Thus, to better understand the molecular determinants of Aβ aggregation in a cell-based system, we combined a yeast DHFR aggregation assay with deep mutational scanning.

Multiplex assessment of protein variant abundance by massively parallel sequencing.

Determining the pathogenicity of genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes requires generalizable, scalable assays. We describe variant abundance by massively parallel sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance simultaneously.

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm.

Analysis of Large-Scale Mutagenesis Data To Assess the Impact of Single Amino Acid Substitutions.

Mutagenesis is a widely used method for identifying protein positions that are important for function or ligand binding. Advances in high-throughput DNA sequencing and mutagenesis techniques have enabled measurement of the effects of nearly all possible amino acid substitutions in many proteins. The resulting large-scale mutagenesis data sets offer a unique opportunity to draw general conclusions about the effects of different amino acid substitutions.

A Molecular Evolutionary Reference for the Human Variome.

Widespread sequencing efforts are revealing unprecedented amount of genomic variation in populations. Such information is routinely used to derive consensus reference sequences and to infer positions subject to natural selection. Here, we present a new molecular evolutionary method for estimating neutral evolutionary probabilities (EPs) of each amino acid, or nucleotide state at a genomic position without using intraspecific polymorphism data.

Signatures of natural selection on mutations of residues with multiple posttranslational modifications.

Posttranslational modifications (PTMs) regulate molecular structures and functions of proteins by covalently binding to amino acids. Hundreds of thousands of PTMs have been reported for the human proteome, with multiple PTMs known to affect tens of thousands of lysine (K) residues. Our molecular evolutionary analyses show that K residues with multiple PTMs exhibit greater conservation than those with a single PTM, but the difference is rather small.

Performance of computational tools in evaluating the functional impact of laboratory-induced amino acid mutations.

Site-directed mutagenesis is frequently used by scientists to investigate the functional impact of amino acid mutations in the laboratory. Over 10,000 such laboratory-induced mutations have been reported in the UniProt database along with the outcomes of functional assays. Here, we explore the performance of state-of-the-art computational tools (Condel, PolyPhen-2 and SIFT) in correctly annotating the function-altering potential of 10,913 laboratory-induced mutations from 2372 proteins.

Rampant purifying selection conserves positions with posttranslational modifications in human proteins.

Posttranslational modifications (PTMs) are chemical alterations that are critical to protein conformation and activation states. Despite their functional importance and reported involvement in many diseases, evolutionary analyses have produced enigmatic results because only weak or no selective pressures have been attributed to many types of PTMs. In a large-scale analysis of 16,836 PTM positions from 4,484 human proteins, we find that positions harboring PTMs show evidence of higher purifying selection in 70% of the phosphorylated and N-linked glycosylated proteins.