Biology subjects

Kmiecik, S.

Publications and source records attributed to Kmiecik, S..

15 recordsLinked to original sources

bioRxiv2026

Hierarchical Breakdown of RNA Structure Prediction in CASP16: From Reliable Local Features to Speculative Multimer Assembly

CASP16 provided a community-wide benchmark for assessing RNA structure prediction, including the first large-scale blind assessment of RNA-RNA multimer prediction. CASP16 results showed that accurate three-dimensional modeling, especially for RNA-RNA multimers, remains a major challenge across the field. In this work, we use the submissions of our group (LCBio) as a diagnostic case study to examine the current limits of RNA structure prediction. In the official CASP16 best-of-submitted-models analysis, our workflow ranked first in the RNA-RNA multimer category and remained competitive for monomers. This makes the submitted model set useful for examining why high-ranking multimer predictions can still deviate substantially from experimental structures. We combine hierarchical analysis with representative case studies to connect this field-wide limitation to specific structural failure modes, showing that prediction accuracy decreases from relatively reliable canonical base-pairing and local helical organization to less reliable non-canonical interactions, stacking geometry, tertiary motifs, and assembly-level features. In RNA-RNA multimers, errors in monomer structure can combine with uncertainty in interface geometry and model selection, reducing the accuracy of the assembled complexes. These findings point to monomer structure accuracy, interface modeling, and model selection as key areas for improving RNA-RNA multimer prediction.

bioinformatics↗

bioRxiv2026

Order of Message and Address Domain Engagement Determines Productive β-Endorphin Binding to the μ-Opioid Receptor

Understanding {beta}-endorphin binding to the -opioid receptor (OR) is crucial for designing safer analgesics. The peptide comprises a message domain mediating activation and an address domain conferring selectivity. Using 1,000 independent CABS-dock simulations, without prior binding-site knowledge, we analysed binding trajectories to compare alternative binding pathways. Message-first binding is most frequently sampled but rarely reaches native-like structures (5.0%). In contrast, address-first binding occurs less often yet shows a 3.8-fold higher success rate (18.8%, p < 0.001). These results refine the message-address model and suggest that early address-domain engagement promotes productive OR binding.

bioinformatics↗

bioRxiv2026

Antagonist binding actively disrupts interleukin-1 receptor dynamics to block co-receptor recruitment

The interleukin-1 receptor type 1 (IL1R1) is a central regulator of inflammatory signaling and functions as a molecular switch, yet it remains unclear how agonists and antagonists that bind the same primary site produce opposite signaling outcomes. Available structural data define inactive and active endpoint conformations but do not explain how antagonist binding dynamically prevents co-receptor recruitment. Here, we combine all-atom molecular dynamics simulations with multiscale flexibility modeling using CABS-flex to systematically compare the intrinsic dynamics of IL1R1 across its unbound, agonist-bound, antagonist-bound, and co-receptor-bound states. Although both agonists and antagonists engage the same conserved interface on the D1/D2 domains, they induce fundamentally different dynamic responses in the receptor. Agonist binding progressively stabilizes interdomain coupling and promotes a stepwise transition toward a signaling-competent conformation. In contrast, antagonist binding selectively increases flexibility of the distal D3 domain, particularly at the co-receptor binding interface, thereby preventing progression along the activation pathway. Importantly, the interaction patterns and dynamic signatures observed in the simulations are consistent with experimentally identified binding determinants, mutational data, and structural features associated with receptor activation and inhibition. These results demonstrate that IL1R1 antagonism is an active, allosteric, dynamics-driven process rather than a simple failure to stabilize an active conformation. Together, this work provides a mechanistic framework that reconciles existing structural and functional observations and highlights receptor dynamics as a key determinant of signaling control in the interleukin-1 system.

molecular biology↗

bioRxiv2025

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo-EM densities observed around the Tetrahymena ribozyme at 2.2-2.3 [A] resolution, collected through target R1260 in the CASP16 competition. 26 groups participated in this solvation cryo-ensemble prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo-EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo-EM densities using Pearson correlation, Spearman correlation, mutual information, and precision-recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo-EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo-EM maps. We propose that further community-wide blind challenges can drive and evaluate progress in modeling water, ions and other previously hidden components of biomolecular systems.

biophysics↗

bioRxiv2025

When Does Molecular Dynamics Improve RNA Models? Insights from CASP15 and Practical Guidelines

Molecular dynamics (MD) simulations are increasingly applied to refine biomolecular models, yet their practical value in RNA structure prediction remains unclear. Here, we systematically benchmarked the effect of MD on RNA models submitted to the CASP15 community experiment, using Amber with the RNA-specific {chi}OL3 force field. Across 61 models representing diverse targets, we find that short simulations (10-50 ns) can provide modest improvements for high-quality starting models, particularly by stabilizing stacking and non-canonical base pairs. In contrast, poorly predicted models rarely benefit and often deteriorate, regardless of their CASP difficulty class. Longer simulations (>50 ns) typically induced structural drift and reduced fidelity. Based on these findings, we provide practical guidelines for selecting suitable input models, defining optimal simulation lengths, and diagnosing early whether refinement is viable. Overall, MD works best for fine-tuning reliable RNA models and for quickly testing their stability, not as a universal corrective method.

bioinformatics↗

bioRxiv2025

Flexible docking of cyclic peptides to proteins using CABS-dock

Cyclic peptides are promising therapeutics, but their flexible docking remains challenging. We present a protocol based on the well-established CABS-dock method, enhanced with cyclic restraints and Rosetta refinement. The approach was evaluated on 38 benchmark complexes previously used in other docking method studies. While selecting the truly best model remains difficult, near-native solutions are frequently sampled. CABS-dock offers global, unbiased docking without prior binding site knowledge, making it valuable for pose generation, structural ensemble modeling, and integration into AI-driven peptide-protein docking workflows.

bioinformatics↗

bioRxiv2024

Delving into human α1,4-galactosyltransferase acceptor specificity: the role of enzyme dimerization

Human 1,4-galactosyltransferase (A4galt), a Golgi apparatus-resident GT, synthesizes Gb3 glycosphingolipid (GSL) and P1 glycotope on glycoproteins (GPs), which are receptors for Shiga toxin types 1 and 2. Despite the significant role of A4galt in glycosylation processes, the molecular mechanisms underlying its varied acceptor specificities remain poorly understood. Here, we attempted to elucidate A4galt specificity towards GSLs and GPs by exploring its interaction with GTs with various acceptor specificities, GP-specific {beta}1,4-galactosyltransferase 1 (B4galt1) and GSL-specific {beta}1,4-galactosyltransferase isoenzymes 5 and 6 (B4galt5 and B4galt6). Using a novel NanoBiT assay, we found that A4galt can form homodimers and heterodimers with B4galt1 and B4galt5 in two cell lines, human embryonic kidney cells (HEK293) and Chinese hamster ovary cells (CHO-Lec2). We found that A4galt-B4galts heterodimers preferred N-terminally tagged interactions, while in A4galt homodimers, the favored localization of the fused tag depended on the cell line used. Furthermore, by employing AlphaFold for state-of-the-art structural prediction, we analyzed the interactions and structures of these enzyme complexes. Our analysis highlighted that the A4galt-B4galt5 heterodimer exhibited the highest prediction confidence, indicating a significant role of A4galt heterodimerization in determining enzyme specificity toward GSLs and GPs. These findings enhance our knowledge of A4galt acceptor specificity and may contribute to a better comprehension of pathomechanisms of the Shiga toxin-related diseases.

biochemistry↗

bioRxiv2024

Depletion of essential GroEL protein in Escherichia coli using Clp-Interacting Peptidic Protein Erasers (CLIPPERs)

New, universal tools for targeted protein degradation in bacteria can help to accelerate protein function studies and antimicrobial research. We have developed a new method for degrading bacterial proteins using plasmid-encoded degrader peptides which deliver target proteins for degradation by a highly conserved ClpXP protease. We demonstrated the mode of action of the degraders on a challenging essential target, GroEL. The studies in bacteria were complemented by in vitro binding and structural studies. Expression of degrader peptides resulted in a temperature-dependent growth inhibition and depletion of GroEL levels over time. The reduction of GroEL levels was accompanied by dramatic proteome alterations. The presented method offers a new alternative approach for regulating protein levels in bacteria without genomic modifications or tag fusions. Our studies demonstrate that ClpXP is an attractive protease for the future use in bacterial targeted protein degradation.

molecular biology↗

bioRxiv2021

A3D Database: Structure-based Protein Aggregation Predictions for the Human Proteome

MotivationProtein aggregation is associated with highly debilitating human disorders and constitutes a major bottleneck for producing therapeutic proteins. Our knowledge of the human protein structures repertoire has dramatically increased with the recent development of the AlphaFold (AF) deep-learning method. This structural information can be used to understand better protein aggregation properties and the rational design of protein solubility. This article uses the Aggrescan3D (A3D) tool to compute the structure-based aggregation predictions for the human proteome and make the predictions available in a database form. ResultsHere, we present the A3D Database, in which we analyze the AF-predicted human protein structures (for over 17 thousand non-membrane proteins) in terms of their aggregation properties using the A3D tool. Each entry of the A3D Database provides a detailed analysis of the structure-based aggregation propensity computed with A3D. The A3D Database implements simple but useful graphical tools for visualizing and interpreting protein structure datasets. We discuss case studies illustrating how the database could be used to analyze physiologically relevant proteins. Furthermore, the database enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. Availability and implementationA3D Database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome

bioinformatics↗

bioRxiv2021

A3D 2.0 update for the prediction and optimization of protein solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

bioinformatics↗

bioRxiv2021

Protein-protein docking with large-scale backbone flexibility

Most of the protein-protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein-protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein-protein complexes, we obtained acceptable quality models for a significant number of cases.

bioinformatics↗

bioRxiv2020

Protocols for rational design of protein solubility and aggregation properties using Aggrescan3D standalone

Protein aggregation is a major hurdle in the development and manufacturing of protein-based therapeutics. Development of aggregation-resistant and stable protein variants can be guided by rational redesign using computational tools. Here, we describe the architecture and functionalities of the Aggrescan3D (A3D) standalone package for the rational design of protein solubility and aggregation properties based on three-dimensional protein structures. We present the case studies of the three therapeutic proteins, including antibodies, exploring the practical use of the A3D standalone tool. The case studies demonstrate that protein solubility can be easily improved by the A3D prediction of non-destabilizing amino acid mutations at the protein surfaces.

bioinformatics↗

bioRxiv2020

Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein-peptide complex structures and model scoring. We evaluated the proposed protocol on the set of 7 different GPCR-peptide complexes (including one containing a cyclic peptide) for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface RMSD measure.

bioinformatics↗

bioRxiv2019

Protocols for all-atom reconstruction and high-resolution refinement of protein-peptide complex structures

Structural characterizations of protein-peptide complexes may require further improvements. These may include reconstruction of missing atoms and/or structure optimization leading to higher accuracy models. In this work, we describe a workflow that generates accurate structural models of peptide-protein complexes starting from protein-peptide models in C-alpha representation generated using CABS-dock molecular docking. First, protein-peptide models are reconstructed from their C-alpha traces to all-atom representation using MODELLER. Next, they are refined using RosettaFlexPepDock. The described workflow allows for reliable all-atom reconstruction of CABS-dock models and their further improvement to high-resolution models.

bioinformatics↗

bioRxiv2019

Protocols for fast simulations of protein structure flexibility using CABS-flex and SURPASS

Conformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods, since experimental characterization can be difficult. Depending on protein system size; computational tools may require large computational resources or significant simplifications in the modeled systems to speed-up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.

bioinformatics↗