Biology subjects

Bussi, G.

Publications and source records attributed to Bussi, G..

17 recordsLinked to original sources

bioRxiv2026

From gHBfix to NBfix: Reweighting-Driven Refinement of Hydrogen-Bond Interactions in RNA Force Fields

Understanding RNA structural dynamics is essential for elucidating its biological functions, and molecular dynamics (MD) simulations provide an important atomistic complement to experimental approaches. However, the predictive power of MD is fundamentally limited by the accuracy of the underlying empirical Force Fields (FFs), particularly in capturing the delicate balance of non-bonded interactions. Here, we present a systematic reparameterization strategy that replaces the external gHBfix19 hydrogen-bond (H-bond) correction potential with an equivalent set of NBfix Lennard-Jones modifications within a state-of-the-art RNA FF. Using a quantitatively converged temperature replica-exchange MD ensemble of the GAGA tetraloop, we employed a reweighting-based optimization protocol to derive NBfix parameters that reproduce the thermodynamic effects of the original gHBfix19 terms. Sequential optimization of individual gHBfix19 components proved essential to ensure stable and transferable parameter refinement. The resulting fully reformulated NBfix-based variant, termed OL3CP-NBfix19, was validated on a representative set of RNA motifs, including tetranucleotides, A-form duplexes, and tetraloops. Across all tested systems, its performance is comparable to that of the reference gHBfix19 FF. By embedding the H-bond corrections directly into the standard non-bonded framework, the NBfix formulation eliminates external biasing potentials, simplifies practical deployment, and reduces computational overhead. Beyond this specific reparameterization, our results demonstrate a practical workflow for translating targeted H-bond corrections into native FF terms for efficient biomolecular simulations.

biophysics↗

bioRxiv2026

pH-dependent allosteric remodeling of a bacterial riboswitch couples alkaline activation to metal sensing

The widespread yybP-ykoY riboswitches control bacterial manganese (Mn) homeostasis by activating exporter expression in response to intracellular Mn2+ levels. The E. coli alx riboswitch distinctively couples Mn2+ sensing to cytoplasmic alkalinity, but the mechanism is unknown. We show that pH tunes the alx aptamers conformational sampling to modulate Mn2+ sensitivity. Single-molecule FRET reveals that Mn2+ stabilizes a docked three-way-junction conformation, and alkaline pH shifts this equilibrium to sensitize metal-dependent folding. Molecular dynamics simulations identify a loop whose low-pH-induced base pairing perturbs the adjacent helix, predicted to allosterically disrupt the Mn2+-binding state. In vivo reporters indicate that both this loop and the Mn2+-binding core are required for optimal pH-dependent translational activation: replacing the core with the non-pH-responsive mntP sequence abolishes activation. These results define how RNA allosterically integrates orthogonal metal and proton cues to enable combinatorial environmental sensing during alkaline stress.

biochemistry↗

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↗

bioRxiv2024

All-atom simulations elucidate the molecular mechanismunderlying RNA-membrane interactions

RNA-membrane interactions are starting to emerge as an important organizing force in both natural and synthetic biological systems. Notably, RNA molecules were recently discovered to be present on the extracellular surface of living cells, where they mediate intercellular signalling. Furthermore, RNA-membrane interactions influence the efficacy of lipid-based RNA delivery systems. However, the molecular terms driving RNA localisation at the membrane remain poorly understood. In this work, we investigate how RNA-phospholipid membrane interactions occur, by means of all-atom simulations. We find that among the four RNA nucleobases guanine exhibits the strongest interaction with the membrane due to extensive hydrogen bond formation. Additionally, we show that intra-RNA base pairing present in organised RNA structures significantly hinders RNA binding to the membrane. Elucidating the molecular details of RNA-membrane association will importantly contribute to improving the design of RNA-based drugs as well as lipid-based RNA delivery systems and to parsing out RNA transport and localisation mechanisms.

biophysics↗

bioRxiv2024

Exploring RNA destabilization mechanisms in biomolecular condensates through atomistic Simulations

Biomolecular condensates are currently recognized to play a key role in organizing cellular space and in orchestrating biochemical processes. Despite an increasing interest in characterizing their internal organization at the molecular scale, not much is known about how the densely crowded environment within these condensates affects the structural properties of recruited macromolecules. Here we adopted explicit-solvent all-atom simulations based on a combination of enhanced sampling approaches to investigate how the conformational ensemble of an RNA hairpin is reshaped in a highlyconcentrated peptide solution that mimics the interior of a biomolecular condensates. Our simulations indicate that RNA structure is greatly perturbed by this distinctive physico-chemical environment, which weakens RNA secondary structure and promotes extended non-native conformations. The resulting high-resolution picture reveals that RNA unfolding is driven by the effective solvation of nucleobases through hydrogen bonding and stacking interactions with surrounding peptides. This solvent effect can be modulated by the aminoacid composition of the model condensate as proven by the differential RNA behaviour observed in the case of arginine-rich and lysine-rich peptides.

biophysics↗

bioRxiv2024

All atom molecular dynamics simulations enable ensemble refinement of flexible and mismodelled cryo-EM derived RNA structures

The advent of single-particle cryogenic electron microscopy (cryo-EM) has enabled near-atomic resolution imaging of large macromolecules, enhancing functional insights. However, current cryo-EM refinement tools condense all single-particle images into a single structure, which can misrepresent highly flexible molecules like RNAs. Here, we combine molecular dynamics simulations with cryo-EM density maps to better account for the structural dynamics of a complex and biologically relevant RNA macromolecule. Namely, using metainference, a Bayesian method, we reconstruct an ensemble of structures of the group II intron ribozyme, which better match experimental data, and we reveal inaccuracies of single-structure approaches in modeling flexible regions. An analysis of all RNA-containing structures deposited in the PDB reveal that this issue affects most cryo-EM structures in the 2.5--4 [A] range. Thus, RNA structures determined by cryo-EM require careful handling, and our method may be broadly applicable to other RNA systems.

molecular 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

Sampling globally and locally correct RNA 3D structures using ERNWIN, SPQR and experimental SAXS data

The determination of the three-dimensional structure of large RNA macromolecules in solution is a challenging task that often requires the use of several experimental and computational techniques. Small-angle X-ray spectroscopy can provide insight into some geometrical properties of the probed molecule, but this data must be properly interpreted in order to generate a three-dimensional model. Here, we propose a multiscale pipeline which introduces SAXS data into modelling the global shape of RNA in solution, which can be hierarchically refined until reaching atomistic precision in explicit solvent. The low-resolution helix model (ERNWIN) deals with the exploration of the huge conformational space making use of the SAXS data, while a nucleotide-level model (SPQR) removes clashes and disentangles the proposed structures, leading the structure to an all-atom representation in explicit solvent. We apply the procedure on five different structures up to 126 nucleotides with promising results.

molecular biology↗

bioRxiv2022

Exploration, representation and rationalization of the conformational phase-space of N-glycans

Despite their fundamental biological relevance, structure-property relationships in N-glycans are fundamentally lacking, and their highly multidimensional compositional and conformational phase-spaces remain largely unexplored. The torsional flexibility of the glycosidic linkages and the ring dynamics result in wide, rugged free-energy landscapes that are difficult to sample in molecular dynamics simulations. We show that a novel enhanced-sampling scheme combining replica-exchange with solute and collective-variable tempering, enabling transitions over all relevant energy barriers, delivers converged distributions of solvated N-glycan conformers. Several dimensionality-reduction algorithms are compared and employed to generate conformational free-energy maps in two-dimensions. Together with an originally developed conformation-based nomenclature scheme that uniquely identify glycan conformers, our modelling procedure is applied to reveal the effect of chemical substitutions on the conformational ensemble of selected high-mannose-type and complex glycans. Moreover, the structure-prediction capabilities of two commonly used glycan force fields are assessed via the theoretical prediction of experimentally available NMR J-coupling constants. The results confirm the key role of especially{omega} and {psi} torsion angles in discriminating between different conformational states, and suggest an intriguing correlation between the torsional and ring-puckering degrees of freedom that may be biologically relevant. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/496605v2_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1cca03org.highwire.dtl.DTLVardef@12c789org.highwire.dtl.DTLVardef@ea2298org.highwire.dtl.DTLVardef@18554b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2021

Towards Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Corrections

Atomistic molecular dynamics (MD) simulations represent established technique for investigation of RNA structural dynamics. Despite continuous development, contemporary RNA simulations still suffer from suboptimal accuracy of empirical potentials (force fields, ffs) and sampling limitations. Development of efficient enhanced sampling techniques is important for two reasons. First, they allow to overcome the sampling limitations and, second, they can be used to quantify ff imbalances provided they reach a sufficient convergence. Here, we study two RNA tetraloops (TLs), namely the GAGA and UUCG motifs. We perform extensive folding simulations and calculate folding free energies ({Delta}Gfold) with the aim to compare different enhanced sampling techniques and to test several modifications of the nonbonded terms extending the AMBER OL3 RNA ff. We demonstrate that replica exchange solute tempering (REST2) simulations with 12-16 replicas do not show any sign of convergence even when extended to time scale of 120 s per replica. However, combination of REST2 with well-tempered metadynamics (ST-MetaD) achieves good convergence on a time-scale of 5-10 s per replica, improving the sampling efficiency by at least two orders of magnitude. Effects of ff modifications on {Delta}Gfold energies were initially explored by the reweighting approach and then validated by new simulations. We tested several manually-prepared variants of gHBfix potential which improve stability of the native state of both TLs by up to ~2 kcal/mol. This is sufficient to conveniently stabilize the folded GAGA TL while the UUCG TL still remains under-stabilized. Appropriate adjustment of van der Waals parameters for C-H...O5 base-phosphate interaction are also shown to be capable of further stabilizing the native states of both TLs by ~0.6 kcal/mol.

biophysics↗

bioRxiv2021

Arginine multivalency stabilizes protein/RNA condensates

Biomolecular condensates assembled through liquid-liquid phase separation (LLPS) of proteins and RNAs are currently recognized to play an important role in cellular organization. Their assembly depends on the formation of a network of transient, multivalent interactions between flexible scaffold biomolecules. Understanding how protein and RNA sequences determine these interactions and ultimately regulate the phase separation is an open key challenge. Recent in vitro studies have revealed that arginine and lysine residues, which are enriched in most cellular condensates, have markedly distinct propensities to drive the LLPS of protein/RNA mixtures. Here, we employ explicit-solvent atomistic Molecular Dynamics (MD) simulations to shed light on the microscopic origin of this difference by investigating mixtures of polyU oligonucleotides with either polyR/polyK peptides. In agreement with experiments, our simulations indicate that arginine has a higher affinity for polyU than lysine both in highly diluted conditions and in concentrated solutions with a biomolecular density comparable to cellular condensate. The analysis of intermolecular contacts suggests that this differential behavior is due to the propensity of arginine side chains to simultaneously form a higher number of specific interactions with oligonucleotides, including hydrogen bonds and stacking interactions. Our results provide a molecular description of how the multivalency of the guanidinium group enables the coordination of multiple RNA groups by a single arginine residue, thus ultimately stabilizing protein/RNA condensates.

biophysics↗

bioRxiv2020

Conformational Ensembles of Non-Coding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations

The 5' untranslated region (UTR) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome is a conserved, functional and structured genomic region consisting of several RNA stem-loop elements. While the secondary structure of such elements has been determined experimentally, their three-dimensional structures are not known yet. Here, we predict structure and dynamics of five RNA stem loops in the 5'-UTR of SARS-CoV-2 by extensive atomistic molecular dynamics simulations, more than 0.5ms of aggregate simulation time, in combination with enhanced sampling techniques. We compare simulations with available experimental data, describe the resulting conformational ensembles, and identify the presence of specific structural rearrangements in apical and internal loops that may be functionally relevant. Our atomic-detailed structural predictions reveal a rich dynamics in these RNA molecules, could help the experimental characterisation of these systems, and provide putative three-dimensional models for structure-based drug design studies.

biophysics↗

bioRxiv2020

Directional translocation resistance of Zika xrRNA

xrRNAs from flaviviruses survive in host cells for their exceptional dichotomic response to the unfolding action of different enzymes. They can be unwound, and hence copied, by replicases, and yet can resist degradation by exonucleases. How the same stretch of xrRNA can encode such diverse responses is an open question. Here, by using atomistic models and translocation simulations, we uncover an elaborate and directional mechanism for how stress propagates when the two xrRNA ends, 5' and 3', are driven through a pore. Pulling the 3' end, as done by replicases, elicits a progressive unfolding; pulling the 5' end, as done by exonucleases, triggers a counterintuitive molecular tightening. Thus, in what appears to be a remarkable instance of intra-molecular tensegrity, the very pulling of the 5' end is what boosts resistance to translocation and consequently to degradation. The uncovered mechanistic principle might be co-opted to design molecular meta-materials.

biophysics↗

bioRxiv2020

Fine-tuning of the AMBER RNA Force Field with a New Term Adjusting Interactions of Terminal Nucleotides

Determination of RNA structural-dynamic properties is challenging for experimental methods. Thus atomistic molecular dynamics (MD) simulations represent a helpful technique complementary to experiments. However, contemporary MD methods still suffer from limitations of force fields (ffs), including imbalances in the non-bonded ff terms. We have recently demonstrated that some improvement of state-of-the-art AMBER RNA ff can be achieved by adding a new term for H-bonding called gHBfix, which increases tuning flexibility and reduces the risk of side-effects. Still, the first gHBfix version did not fully correct simulations of short RNA tetranucleotides (TNs). TNs are key benchmark systems due to availability of unique NMR data, although giving too much weight on improving TN simulations can easily lead to over-fitting to A-form RNA. Here we combine the gHBfix version with another term called tHBfix, which separately treats H-bond interactions formed by terminal nucleotides. This allows to refine simulations of RNA TNs without affecting simulations of other RNAs. The approach is in line with adopted strategy of current RNA ffs, where the terminal nucleotides possess different parameters for the terminal atoms than the internal nucleotides. The combination of gHBfix with tHBfix significantly improves the behavior of RNA TNs during well-converged enhanced-sampling simulations. TNs mostly populate canonical A-form like states while spurious intercalated structures are largely suppressed. Still, simulations of r(AAAA) and r(UUUU) TNs show some residual discrepancies with the primary NMR data which suggests that future tuning of some other ff terms might be useful.

biophysics↗

bioRxiv2018

IMPROVING THE PERFORMANCE OF THE RNA AMBER FORCE FIELD BY TUNING THE HYDROGEN-BONDING INTERACTIONS

Molecular dynamics (MD) simulations became a leading tool for investigation of structural dynamics of nucleic acids. Despite recent efforts to improve the empirical potentials (force fields, ffs), RNA ffs have persisting deficiencies, which hamper their utilization in quantitatively accurate simulations. Previous studies have shown that at least two salient problems contribute to difficulties in description of free-energy landscapes of small RNA motifs: (i) excessive stabilization of the unfolded single-stranded RNA ensemble by intramolecular base-phosphate and sugar-phosphate interactions, and (ii) destabilization of the native folded state by underestimation of stability of base pairing. Here, we introduce a general ff term (gHBfix) that can selectively fine-tune non-bonding interaction terms in RNA ffs, in particular the H-bonds. gHBfix potential affects the pair-wise interactions between all possible pairs of the specific atom types, while all other interactions remain intact, i.e., it is not a structure-based model. In order to probe the ability of the gHBfix potential to refine the ff non-bonded terms, we performed an extensive set of folding simulations of RNA tetranucleotides and tetraloops. Based on these data we propose particular gHBfix parameters to modify the AMBER RNA ff. The suggested parametrization significantly improves the agreement between experimental data and the simulation conformational ensembles, although our current ff version still remains far from being flawless. While attempts to tune the RNA ffs by conventional reparametrizations of dihedral potentials or non-bonded terms can lead to major undesired side effects as we demonstrate for some recently published ffs, gHBfix has a clear promising potential to improve the ff performance while avoiding introduction of major new imbalances.

biochemistry↗

bioRxiv2018

Analyze Nucleic Acids Structures and Trajectories with Barnaba.

RNA molecules are highly dynamic systems characterized by a complex interplay between sequence, structure, dynamics, and function. Molecular simulations can potentially provide powerful insights into the nature of these relationships. The analysis of structures and molecular trajectories of nucleic acids can be non-trivial because it requires processing very high-dimensional data that are not easy to visualize and interpret.\n\nHere we introduce Barnaba, a Python library aimed at facilitating the analysis of nucleic acids structures and molecular simulations. The software consists of a variety of analysis tools that allow the user to i) calculate distances between three-dimensional structures using different metrics, ii) back-calculate experimental data from three-dimensional structures, iii) perform cluster analysis and dimensionality reductions, iv) search three-dimensional motifs in PDB structures and trajectories and v) construct elastic network models (ENM) for nucleic acids and nucleic acids-protein complexes.\n\nIn addition, Barnaba makes it possible to calculate torsion angles, pucker conformations and to detect base-pairing/base-stacking interactions. Barnaba produces graphics that conveniently visualize both extended secondary structure and dynamics for a set of molecular conformations. The software is available as a command-line tool as well as a library, and supports a variety of 1le formats such as PDB, dcd and xtc 1les. Source code, documentation and examples are freely available at https://github.com/srnas/barnaba under GNU GPLv3 license.

bioinformatics↗

bioRxiv2017

Conformational Ensemble of RNA Oligonucleotides from Reweighted Molecular Simulations

We determine the conformational ensemble of four RNA tetranucleotides by using available nuclear magnetic spectroscopy data in conjunction with extensive atomistic molecular dynamics simulations. This combination is achieved by applying a reweighting scheme based on the maximum entropy principle. We provide a quantitative estimate for the population of different conformational states by considering different NMR parameters, including distances derived from nuclear Overhauser effect intensities and scalar coupling constants. We show the usefulness of the method as a general tool for studying the conformational dynamics of flexible biomolecules as well as for detecting inaccuracies in molecular dynamics force fields.

biophysics↗