Biology subjects

Sokolova, B.

Publications and source records attributed to Sokolova, B..

5 recordsLinked to original sources

bioRxiv2026

Peptide-to-protein data aggregation using Fisher's method improves target identification in chemical proteomics

Protein-level statistical tests in proteomics aimed at obtaining p-value are conventionally made on protein abundances aggregated from peptide data. This integral approach overlooks peptide-level heterogeneity and ignores important information coded in individual peptide data, while protein p-value can also be obtained by Fishers method of combining peptide p-values using chi-square statistics. Here we test this latter approach across diverse chemical proteomics datasets based on assessments of protein expression, solubility and protease accessibility. Using the top four peptides ranked by their p-values consistently outperformed protein-level analysis and avoided biases introduced by inclusion of deviant peptides or imputation of missing peptide values. Fishers method provides a simple and robust strategy, improving identification of regulated/shifted proteins in diverse proteomics assays.

bioinformatics↗

bioRxiv2025

High-ratiO partiaL proteolysiS with carriER proteome (HOLSER) Enables Global Structure Profiling and Site-resolved Elucidation of Ligand-Protein Interactions

Understanding how cellular proteins interact with their environment, including endogenous and exogeneous molecules, is critical for elucidating mechanisms of cellular regulation and drug action. Partial proteolysis-based techniques offer peptide-level resolution of ligand-induced conformational changes but are limited by modest proteome coverage and depth, as well as sensitivity to the experimental conditions. To overcome these limitations, we developed higH ratiO partiaL proteolysiS with carriER proteome (HOLSER), an efficient workflow that features extended digestion time for reduced peptide yield variability as well as tandem mass tag multiplexing that includes full digests for enhanced proteome depth and sequence coverage as well as higher precision of peptide abundance measurements. We demonstrate HOLSER capabilities of probing structural changes on the scale of specific binding sites for kinase target mapping, individual protein domains for structural mapping of the FKBP-mTOR complex in response to rapamycin as well as global proteome structure profiling.

biochemistry↗

bioRxiv2025

Beyond the known cuts: trypsin specificity in native proteins

Trypsin is a serine protease that plays a pivotal role in protein digestion, being extensively used in various proteomics workflows due to its cleavage profile and specificity. Understanding trypsins enzymatic behavior is thus critical. We have employed Above-Filter Digestion Proteomics (AFDIP) to investigate trypsins cleavage preferences in HeLa cell lysates, preserving the proteins native state. We quantified over 18,000 unique peptides and correlated their emergence rates with cleavage window sequence motifs and physicochemical properties. Contrary to previous studies performed on denatured proteomes, we found that in native proteins cleavages at lysine residues were more abundant and faster than at arginine residues, and that physicochemical properties of the peptides affected their emergence times. These findings may need to be taken into account when interpreting the results of limited proteolysis experiments as well as when designing a food protein with extremely fast digestion times.

biochemistry↗

bioRxiv2025

Above-Filter Digestion Proteomics reveals drug targets and localizes ligand binding site

While a number of efficient chemical proteomics methods are available for determining protein targets of pharmaceutical drugs, each approach exhibits its own "blind spot" and development of complementary techniques is needed. Here, we introduce the Above-Filter Digestion Proteomics (AFDIP) approach based on the monitoring of the rate of trypsin digestion. Digestion rate is decreased at the site of ligand binding to its target protein, while other sites may simultaneously experience an increase the digestion rate. Molecular dynamics (MD) simulations revealed that this increase may be due to allosteric structural changes related to backbone flexibility. We showcase the utility of AFDIP for deconvoluting the targets of versatile drugs and metabolites. Like other techniques, AFDIP allows for a two-dimensional analysis, with the second dimension based on drug concentration. AFDIP exhibits structural resolution, identifying drug target binding sites within [≤]10 [A], and for larger proteins often [≤]5 [A] of the crystallography-determined binding sites. Compared to earlier introduced limited proteolysis approaches, AFDIP provides easier sample preparation, deeper proteome analysis and broader sequence coverage. AFDIP is expected to find its place among the most efficient chemical proteomics methods currently available.

biochemistry↗

bioRxiv2024

ThermoTargetMiner as a proteome integral solubility alteration target database for prospective drugs against lung cancer

Knowledge of the targets of therapeutic compounds is vital for understanding their action mechanisms and side effects, but such valuable data is seldom available. The multiple complementary techniques needed for comprehensive target characterization must combine data reliability with sufficient analysis throughput. Here, we leveraged the Proteome Integral Solubility Alteration (PISA) assay to characterize the targets of 67 approved and experimental compounds against two main lung cancer subtypes, which is now provided through the website https://thermotargetminer.serve.scilifelab.se/app/thermotargetminer. Novel target candidates (pro-targets) were found for 77% of the tested molecules. Comparison of the protein solubility shifts in lysate vs. living cells highlighted the targets directly interacting with the compounds. We verified that the drug PEITC exerts cytotoxicity through the inhibition of a pro-target PAFAH1B. As PISA is now joining the arsenal of fast and reliable target characterization techniques, the presented database, ThermoTargetMiner, will become a useful resource in lung cancer research.

biochemistry↗