Biology subjects

Pokorna, P.

Publications and source records attributed to Pokorna, P..

9 recordsLinked to original sources

bioRxiv2025

U2 snRNP recognizes the branch site through a loaded-spring strand-invasion mechanism

Recognition of the branch sequence (BS) by U2 snRNP is a pivotal step in pre-mRNA splicing and spliceosome assembly. Structural studies suggest that BS recognition occurs through a toe-hold-mediated strand-invasion mechanism, in which U2 snRNA progressively base-pairs with the intron to form the branch helix. However, given the limited complementarity between U2 snRNA and the intronic BS, it remains unclear how such strand invasion can occur spontaneously. Here, using all-atom and coarse-grained molecular dynamics simulations, we show that strand invasion proceeds spontaneously once the toehold region is engaged and the TAT-SF1 factor is released. The key finding is that the branch-stem loop (BSL) of U2 snRNA is maintained in a supercoiled, high-energy conformation by TAT-SF1, which acts as a molecular latch holding the BSL in a poised "loaded-spring" state. Displacement of TAT-SF1 allows the BSL to relax, releasing the stored conformational energy that drives strand invasion through local strand-slip and base-pair exchange. Moreover, the simulations reveal that strand invasion can proceed bidirectionally, refining previous models of U2-BS pairing. This work establishes a loaded-spring mechanism as a key physical driver of toehold-mediated strand invasion underlying branch-site recognition within early spliceosome.

molecular biology↗

bioRxiv2025

RNA G-Quadruplex Emerges from a Coil-Like Ensemble via Multiple Pathways

RNA G-quadruplexes (rG4s) are vital structural elements in gene regulation and genome stability. In untranslated regions of mRNAs, rG4s influence translation efficiency and mRNA localization. Additionally, rG4s of long non-coding RNAs and telomeric RNA play roles in RNA processing and cellular aging. Despite their significance, atomic-level folding mechanisms of rG4s remain poorly understood due to their complexity. We used enhanced-sampling all-atom molecular dynamics simulations to model the folding of an r(GGGA)3GGG sequence into a parallel-stranded rG4. The folding pathways suggest that RNA initially adopts a compact coil- like ensemble, marked by dynamic guanine stacking and pairing. The three-quartet rG4 builds up gradually from the coil via diverse routes involving strand rearrangements and guanine incorporations. While the folding mechanism is multi-pathway, various two-quartet rG4s seem to be a common transitory ensemble for most routes. Our simulations also exposed force-field imbalances, with the predicted folding free energy of +12.5 kcal/mol deviating from experiments. Additionally, the enhanced sampling protocol, combining well-tempered metadynamics with solute tempering, faced productivity challenges on the multidimensional free-energy surface. Overall, this study provides atomistic insights into rG4 folding, emphasizing compact coil-like ensembles as key precursors, while revealing limitations in simulating non-canonical RNA structures.

biophysics↗

bioRxiv2024

Analysis of Mutations in Precision Oncology using The Automated, Accurate, and User-Friendly Web Tool PredictONCO

Next-generation sequencing technology has created many new opportunities for clinical diagnostics, but it faces the challenge of functional annotation of identified mutations. Various algorithms have been developed to predict the impact of missense variants that influence oncogenic drivers. However, computational pipelines that handle biological data must integrate multiple software tools, which can add complexity and hinder non-specialist users from accessing the pipeline. Here, we have developed an online user-friendly web server tool PredictONCO that is fully automated and has a low barrier to access. The tool models the structure of the mutant protein in the first step. Next, it calculates the protein stability change, pocket level information, evolutionary conservation, and changes in ionisation of catalytic amino acid residues, and uses them as the features in the machine-learning predictor. The XGBoost-based predictor was validated on an independent subset of held-out data, demonstrating areas under the receiver operating characteristic curve (ROC) of 0.95 and 0.94, and the average precision from the precision-recall curve 0.98 and 0.94 for structure-based and sequence-based predictions, respectively. Finally, PredictONCO calculates the docking results of small molecules approved by regulatory authorities. We demonstrate the applicability of the tool by presenting its usage for variants in two cancer-associated proteins, cellular tumour antigen p53 and fibroblast growth factor receptor FGFR1. Our free web tool will assist with the interpretation of data from next-generation sequencing and navigate treatment strategies in clinical oncology: https://loschmidt.chemi.muni.cz/predictonco/.

bioinformatics↗

bioRxiv2024

A Computational Workflow for Analysis of Missense Mutations in Precision Oncology

Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individuals tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutations effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving the balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available at https://loschmidt.chemi.muni.cz/predictonco/.

cancer biology↗

bioRxiv2023

Parallel G-quadruplex folds via multiple paths involving G-tract stacking and structuring from coil ensemble

G-quadruplexes (G4s) are non-canonical nucleic acid structures that fold through complex processes. Characterization of G4 folding landscape contributes to comprehending G4 roles in gene regulation but is challenging for experiments and computations. Here we investigate the folding of a three-quartet parallel DNA G4 with (GGGA)3GGG sequence using all-atom explicit-solvent enhanced-sampling molecular dynamics (MD) simulations. We suggest an early formation of guanine stacks in the G-tracts, which behave as semi-rigid blocks in the folding process. The parallel G4 folding is initiated by the formation of a collapsed compact coil-like ensemble. Structuring of the G4 from the coil then proceeds via various cross-like, hairpin, slip-stranded, and two-quartet ensembles and can bypass the G-triplex structure. While parallel G-hairpins are extremely unstable when isolated, they are more stable inside the coil structure. Folding of parallel G4 does not appear to involve any salient intermediates and, instead, it is an extremely multiple-pathway process. On the methodology side, we show that the AMBER DNA force field predicts the folded G4 to be less stable than the unfolded ensemble, uncovering substantial force-field issues. Overall, we provide unique atomistic insights into the folding landscape of parallel-stranded G4 but also reveal limitations of the state-of-the-art MD techniques.

molecular biology↗

bioRxiv2022

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations.

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here we used extended set of microsecond-scale MD trajectories (400 s in total) to study two FUS-RNA constructs previously characterized by NMR spectroscopy. The FUS protein contains well-structured RNA Recognition Motif domain followed by presumably disordered RGG tail and bind RNA stem-loop hairpins. Our simulations provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data, as in detail documented. We further propose that the dynamics is so rich that its converged description would not be achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops which can explain the NOE data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate them.

molecular biology↗

bioRxiv2022

Spontaneous binding of single-stranded RNAs to RRM proteins visualised by unbiased atomistic simulations with rescaled RNA force field

Recognition of single-stranded RNA (ssRNA) by RNA recognition motif (RRM) domains is an important class of protein-RNA interactions. Many such complexes were characterized using NMR and/or X-ray crystallography techniques, revealing ensemble-averaged pictures of the bound states. However, it is becoming widely accepted that better understanding of protein-RNA interactions would be obtained from ensemble descriptions. Indeed, earlier molecular dynamics (MD) simulations of bound states indicated visible dynamics at the RNA-RRM interfaces. Here, we report the first atomistic simulation study of spontaneous binding of short RNA sequences to RRM domains of HuR and SRSF1 proteins. Using millisecond-scale aggregate ensemble of unbiased simulations we were able to observe a few dozens of binding events. The HuR RRM3 utilizes a pre-binding state to navigate the RNA sequence to its partially disordered bound state and then to dynamically scan its different binding registers. The SRFS1 RRM2 binding is more straightforward but still multiple-pathway. The present study necessitated development of a goal-specific force-field modification scaling down the intramolecular vdW interactions of the RNA which also improves description of the RNA-RRM bound state. Our study opens a new avenue for large-scale atomistic investigations of binding landscapes of protein-RNA complexes and future perspectives of such research are discussed.

molecular biology↗

bioRxiv2021

Recognition of N6-methyladenosine by the YTHDC1 YTH domain studied by molecular dynamics and NMR spectroscopy: The role of hydration

The YTH domain of YTHDC1 belongs to a class of protein "readers", recognizing the N6-methyladenosine (m6A) chemical modification in mRNA. Static ensemble-averaged structures revealed details of N6-methyl recognition via a conserved aromatic cage. Here, we performed molecular dynamics (MD) simulations along with nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC) to examine how dynamics and solvent interactions contribute to the m6A recognition and negative selectivity towards unmethylated substrate. The structured water molecules surrounding the bound RNA and the methylated substrates ability to exclude bulk water molecules contribute to the YTH domains preference for m6A. Intrusions of bulk water deep into the binding pocket disrupt binding of unmethylated adenosine. The YTHDC1s preference for the 5'-Gm6A-3' motif is partially facilitated by a network of water-mediated interactions between the 2-amino group of the guanosine and residues in the m6A binding pocket. The 5'-Im6A-3' (where I is inosine) motif can be recognized too but disruption of the water network lowers affinity. The D479A mutant also disrupts the water network and destabilizes m6A binding. Our interdisciplinary study of YTHDC1 protein/RNA complex reveals an unusual physical mechanism by which solvent interactions contributes towards m6A recognition.

biophysics↗

bioRxiv2020

UNCG RNA tetraloop as a formidable force-field challenge for MD simulations

Explicit solvent atomistic molecular dynamics (MD) simulations represent an established technique to study structural dynamics of RNA molecules and an important complement for diverse experimental methods. However, performance of molecular mechanical (MM) force fields (ffs) remains far from satisfactory even after decades of development, as apparent from a problematic structural description of some important RNA motifs. Actually, some of the smallest RNA molecules belong to the most challenging systems for MD simulations and, among them, the UNCG tetraloop is saliently difficult. We report a detailed analysis of UNCG MD simulations, depicting the sequence of events leading to the loss of the UNCG native state during MD simulations. We identify molecular interactions, backbone conformations and substates that are involved in the process. The total amount of MD simulation data analyzed in this work is close to 1.3 millisecond. Then, we unravel specific ff deficiencies using diverse quantum mechanical/molecular mechanical (QM/MM) and QM calculations. Comparison between the MM and QM methods shows discrepancies in the description of the 5-flanking phosphate moiety and both signature sugar-base interactions. Our work indicates that poor behavior of the UNCG tetraloop in simulations is a complex issue that cannot be attributed to one dominant and straightforwardly correctable factor. Instead, there is a concerted effect of multiple ff inaccuracies that are coupled and amplifying each other. We attempted to improve the simulation behavior by some carefully-tailored interventions but the results are still far from satisfactory, underlying the difficulties in development of accurate nucleic acids ffs.

biophysics↗