Sándor Szalma

Abstract The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public–private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics 1 .

A new empirical approach to model the solvent effects in protein−membrane complexes is proposed. The generalized Born (GB) approximation is extended by including an implicit membrane (IM) in the calculation of the electrostatic contribution to the solvation free energy (GB/IM model). In addition, nonpolar solvation energy terms are calculated on the basis of the solvent-accessible surface approximation including the effect of membrane (SA/IM model). The generalized Born−solvent-accessible surface area (GBSA) model with implicit membrane (GBSA/IM) is implemented in the CHARMm package and is applicable for energy calculations and molecular dynamics simulations. The potential of the new method for studying large molecular systems is demonstrated with the example of two transmembrane proteins, bacteriorhodopsin and rhodopsin. The results show a clear directional asymmetry of the solvation energy during translocation of the proteins through the membrane, which is suggested to be an alternative explanation of the known “positive-inside” rule. The method is also tested in nanosecond molecular dynamics (MD) simulations of the influenza virus HA2 (1:20) fusion peptide. Interestingly, when starting from two different initial positions of peptide, during the 3 ns runs, the helical fragment consistently adopts a tilted (∼20−25°) orientation with respect to the membrane in very close agreement with the known electron paramagnetic resonance (EPR) data. We also found an excellent agreement between the pKs of the N-terminal amino group computed for the final MD structures and the known NMR titration data.

Abstract The UK Biobank Pharma Proteomics Project (UKB-PPP) is a collaboration between the UK Biobank (UKB) and thirteen biopharmaceutical companies characterising the plasma proteomic profiles of 54,306 UKB participants. Here, we describe results from the first phase of UKB-PPP, including protein quantitative trait loci (pQTL) mapping of 1,463 proteins that identifies 10,248 primary genetic associations, of which 85% are newly discovered. We also identify independent secondary associations in 92% of cis and 29% of trans loci, expanding the catalogue of genetic instruments for downstream analyses. The study provides an updated characterisation of the genetic architecture of the plasma proteome, leveraging population-scale proteomics to provide novel, extensive insights into trans pQTLs across multiple biological domains. We highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement proteins, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug target discovery by extending the genetic proxied effect of PCSK9 levels on lipid concentrations, cardio- and cerebro-vascular diseases, and additionally disentangle specific genes and proteins perturbed at COVID-19 susceptibility loci. This public-private partnership provides the scientific community with an open-access proteomics resource of unprecedented breadth and depth to help elucidate biological mechanisms underlying genetic discoveries and accelerate the development of novel biomarkers and therapeutics.