The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

Although it is well accepted that the structure of amyloid fibrils is dominated by some form of antiparallel p-sheet, there are few details on the secondary structural arrangements of the constituent peptides and how these peptides pack together in the fibril. We describe here the use of scanning proline mutagenesis to map the secondary structural roles of each residue in amyloidogenic peptide fragments of the Alzheimer's amyloid peptide @IA4. In two series of fragments related to residues 15-23 and 12-26 of @IA4, we show that Pro replacement of any residue in the amyloidogenic sequence LVFFAED, corresponding to residues 17-23, leads to essentially complete loss of fibril formation and to excellent peptide solubility. Since peptidyl-prolyl bonds are incapable of forming standard extended chain conformations, the results suggest that residues 17-23 make up the @-sheet core of the fibrils formed by these fragments. In contrast to the proline replacements, alanine substitutions at residues 17, 18, and 20 have no effect on fibril formation, while replacement of Phe19 reduces fibril formation to 15% of the level found for the wild type sequence. Scanning proline mutagenesis should play a useful role in mapping the secondary structural features of larger amyloidogenic peptide sequences, including longer, physiologically relevant forms of @/A4. In addition, these results suggest explanations for some amyloidogenic effects observed in disease-related peptides and also suggest a possible role for aggregation-inhibiting insertion of prolines in protein evolution and protein design.

No abstract

Light-chain (L-chaln) amyloldoss Is characterzed by depit of Nbrillar aregtes composed of the N-

Traditionally, most drugs have been discovered using phenotypic or target-based screens. Subsequently, their indications are often expanded on the basis of clinical observations, providing additional benefit to patients. This review highlights computational techniques for systematic analysis of transcriptomics (Connectivity Map, CMap), side effects, and genetics (genome-wide association study, GWAS) data to generate new hypotheses for additional indications. We also discuss data domains such as electronic health records (EHRs) and phenotypic screening that we consider promising for novel computational repositioning methods.