Biology subjects

Parakra, R.

Publications and source records attributed to Parakra, R..

3 recordsLinked to original sources

bioRxiv2026

MInt-HDX: Leveraging Hydrogen-Deuterium Exchange Mass Spectrometry and Machine-Learning to Improve Protein-Ligand Docking.

Understanding protein structural dynamics is central to elucidating biological function and guiding therapeutic discovery. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) typically offers peptide-level, and sometimes residue-level, time-dependent insights into protein structure, conformational dynamics and/or ligand binding. Yet, translating HDX-MS data into atomic-resolution insights and deriving mechanistic understanding remains a key challenge. Integrative strategies which utilize HDX-MS to inform computational modeling or simulations, traditionally leverage HDX-MS data with physics-based approaches through the calculation of protection factors models. Here, we developed MInt-HDX, a hybrid physics-based, machine- learning framework trained on differential HDX-MS signatures across 11 protein-ligand systems or 1032 individual peptides, using eXtreme Gradient Boosting (XGBoost) to guide small-molecule ligand docking and pose selection. By leveraging XGBoost-predicted interacting residues with three-dimensional clustering and convex-hull geometric algorithms, MInt-HDX first generates HDX-guided candidate docking sites in 3D for physics-based molecular docking and then, following docking, employs HDX-MS-informed XGBoost filtering and scoring functions for ligand- pose ranking. MInt-HDX was validated across 3 protein-ligand systems, consistently resulting in Ligand-RMSD within 3 [A] of the crystallographic ligand conformation, individual steps of MInt- HDX were optimized and its overall performance was assessed against HDX-MS data quality factors and benchmarked against common physics-based and machine learning based docking approaches. Together, this work highlights how machine learning, informed by HDX-MS and aided by physics-based approaches, can bridge the gap between solution-phase HDX-MS data and structural modeling to accelerate protein-ligand discovery pipelines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/738285v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1bf4574org.highwire.dtl.DTLVardef@68f3c8org.highwire.dtl.DTLVardef@5cd2c1org.highwire.dtl.DTLVardef@10a82c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Identification of an intrinsically disordered region (IDR) in arginyltransferase 1 (ATE1)

Arginyltransferase 1 (ATE1) catalyzes arginylation, an important post-translational modification (PTM) in eukaryotes that plays a critical role in cellular homeostasis. The disruption of ATE1 function is implicated in mammalian neurodegenerative disorders and cardiovascular maldevelopment, while post-translational arginylation has also been linked to the activities of several important human viruses such as SARS-CoV-2 and HIV. Despite the known significance of ATE1 in mammalian cellular function, past biophysical studies of this enzyme have mainly focused on yeast ATE1, leaving the mechanism of arginylation in mammalian cells unclear. In this study, we sought to structurally and biophysically characterize mouse (Mus musculus) ATE1. Using size-exclusion chromatography (SEC), small angle X-ray scattering (SAXS), and hydrogen deuterium exchange mass spectrometry (HDX-MS), assisted by AlphaFold modeling, we found that mouse ATE1 is structurally more complex than yeast ATE1. Importantly, our data indicate the existence of an intrinsically disordered region (IDR) in all mouse ATE1 splice variants. However, comparative HDX-MS analyses show that yeast ATE1 does not have such an IDR, consistent with prior X-ray, cryo-EM, and SAXS analyses. Furthermore, bioinformatics approaches reveal that mammalian ATE1 sequences, as well as in a large majority of other eukaryotes, contain an IDR-like sequence positioned in proximity to the ATE1 GNAT active-site fold. Computational analysis suggests that the IDR likely facilitates the formation of the complex between ATE1 and tRNAArg, adding a new complexity to ATE1 structure and providing new insights for future studies of ATE1 functions. For Table of Contents Use Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/609426v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@130d030org.highwire.dtl.DTLVardef@1b40613org.highwire.dtl.DTLVardef@1fb0ae5org.highwire.dtl.DTLVardef@88426d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2020

Altered structure and dynamics of pathogenic cytochrome c variants correlate with increased apoptotic activity

Mutation of cytochrome c in humans causes mild autosomal dominant thrombocytopenia. The role of cytochrome c in platelet formation, and molecular mechanism underlying the association of cytochrome c mutations with thrombocytopenia remains unknown, although a gain-of-function is most likely. Cytochrome c contributes to several cellular processes, with exchange between conformational states proposed to regulate changes in function. Here we use experimental and computational approaches to determine whether pathogenic variants share changes in structure and function, and to understand how these changes might occur. We find that three pathogenic variants (G41S, Y48H, A51V) cause an increase in apoptosome activation and peroxidase activity. Molecular dynamics simulations of these variants, and two non-naturally occurring variants (G41A, G41T), indicate that increased apoptosome activation correlates with increased overall flexibility of cytochrome c, particularly movement of the Ω loops. This suggests that the binding of cytochrome c to apoptotic protease activating factor-1 (Apaf-1) may involve an "induced fit" mechanism which is enhanced in the more conformationally mobile variants. In contrast, peroxidase activity did not significantly correlate with protein dynamics suggesting that the mechanism by which the variants alter peroxidase activity is not related to the conformation dynamics of the hexacoordinate heme Fe state of cytochrome c analyzed in the simulations. Recent suggestions that conformational mobility of specific regions of cytochrome c underpins changes in reduction potential and the alkaline transition pK were not supported. These data highlight that conformational dynamics of cytochrome c drives some but not all of its properties and activities.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biochemistry↗