Biology subjects

Capelli, R.

Publications and source records attributed to Capelli, R..

10 recordsLinked to original sources

bioRxiv2026

Calcium-Driven Activation of Gelsolin: Mechanism and the Active-State Ensemble

Gelsolin is a master regulator of the actin cytoskeleton whose activity is controlled by large Ca2+ dependent conformational transitions of its 6 domains (G1-G6). Despite decades of biochemical and cellular studies, the structural basis of activation of the full-length protein remains poorly understood because active gelsolin is highly dynamic and has largely escaped structural characterization. Here, we combine small-angle X-ray scattering, DEER-EPR spectroscopy, and structure-based molecular dynamics simulations to investigate the transition from the compact inactive state to the actin-binding active form. This integrative approach reveals that activation proceeds through a sequential and domain-dependent mechanism, where different regions of the protein respond to Ca2+ with distinct kinetics and conformational trajectories. Rather than converging toward a single active structure, activated gelsolin populates a heterogeneous ensemble of plastic conformations characterized by asymmetric domain arrangements and extensive structural variability. The two major domain triplets (G1-G3 and G4-G6) display markedly different dynamic behaviors, while actin-binding surfaces are exposed according to a defined hierarchy and remain differentially accessible within the active ensemble, suggesting specialized functional roles for different domains during filament engagement. Together, these findings provide a time- and domain-resolved view of gelsolin activation, establish a structural framework for interpreting its diverse biological functions, and offer new opportunities for targeting gelsolin-associated diseases.

biophysics↗

bioRxiv2026

Assessing multi-eGO Predictions of PDZ2-Peptide Binding across Mutations

Accurately predicting how mutations alter protein-peptide binding remains challenging for molecular simulations because both conformational sampling and binding kinetics are computationally demanding. Here, we investigate whether multi-eGO, a hybrid transferable/structure-based atomistic-resolution model previously developed and validated for protein-small molecule interactions, can be transferred to protein-peptide binding without peptide-specific retraining. Using the PDZ2 domain of protein tyrosine phosphatase basophil-like in complex with the peptide EQVTAV as a benchmark, we first show that multi-eGO reproduces the structural dynamics of PDZ2 and the equilibrium binding thermodynamics of the wild-type complex. The model substantially accelerates both binding and unbinding relative to experiment but accurately preserves the resulting equilibrium dissociation constant. We then introduce conservative mutations in PDZ2 and in the peptide and evaluate their effects on binding without repeating the computationally expensive training procedure. Multi-eGO reproduces the experimentally observed changes in equilibrium dissociation constants, with strong agreement across PDZ2 mutants and moderate agreement when the peptide is also mutated. In contrast, the individual association and dissociation rate constants show substantially weaker agreement with experiment. The results indicate that the simplified energy landscape of multi-eGO limits the quantitative prediction of absolute kinetics while preserving thermodynamic information relevant to relative binding affinity. These findings establish multi-eGO as a computationally efficient approach for protein-peptide recognition and for predicting and rank-ordering the effects of conservative mutations on binding affinity.

biochemistry↗

bioRxiv2025

Electric Field-Induced Destabilization and Surface Modulation of Aβ42 Fibrils in Molecular Simulations: Theoretical Implications for DC Stimulation in Alzheimer's Disease

The amyloid-{beta} peptide 42 (A{beta}42) forms fibrillar aggregates that are a hallmark of Alzheimers disease. While recent pharmacologic therapeutic strategies targeting A{beta}42 fibrils and oligomers have shown promising results, safer and more effective approaches are still needed. Non-invasive brain stimulation (NIBS) techniques such as repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been increasingly explored as a possible complementary intervention, but the molecular mechanisms by which static electric fields could influence amyloid aggregation remain poorly understood. Here, we use atomistic molecular dynamics simulations to investigate the effects of static electric fields on A{beta}42 fibrils. We examine the response of an ex vivo fibril structure, with reconstructed N-terminal regions, to increasing field strengths under different structural restraint conditions. Our results show that the electric field perturbs the disordered N-terminal "fuzzy coat," altering its conformational dynamics and reducing its interactions with the fibril core. This reorganization modifies the surface properties of the fibril, potentially impairing secondary nucleation. Additionally, simulations with unrestrained fibril ends reveal increased fluctuations in core residues, particularly near the N-terminus, indicating a destabilizing effect that may hinder fibril elongation. While the field strengths used here exceed those typical of NIBS, our findings provide a molecular-level rationale for how electric fields could modulate fibril propagation and support further experimental investigations under physiologically relevant conditions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/678267v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@9b6a01org.highwire.dtl.DTLVardef@14ca26forg.highwire.dtl.DTLVardef@3c42ccorg.highwire.dtl.DTLVardef@458b4f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Constant-pH simulation of the human β2 adrenergic receptor inactivation

Understanding the molecular basis of pH-dependent G protein-coupled receptor (GPCR) signaling is crucial for comprehending physiological regulation and drug design. Here, we investigate the human {beta}2 adrenergic receptor ({beta}2AR), a prototypical GPCR whose function is sensitive to pH conditions. Employing extensive constant-pH molecular dynamics simulations, we provide a detailed atomistic characterization of {beta}2AR inactivation across physiologically relevant pH values (4-9). Our simulations reveal that {beta}2AR inactivation is closely linked to protonation events at critical residues, notably E2686x30 involved in the ionic lock formation. Furthermore, we find that inactivation occurs without direct sodium binding to the ion-binding pocket around residue D792x50. Instead, sodium ions predominantly interact with D1133x32, effectively blocking deeper entry toward the traditional binding site. These results challenge existing mechanistic models and highlight the necessity of accurately modeling electrostatics in GPCR simulations. Our findings underscore the potential of constant-pH methodologies to advance the understanding of GPCR dynamics, influencing both fundamental biology and therapeutic strategies.

biophysics↗

bioRxiv2024

Structural and functional role of residues undergoing hereditary spastic paraplegias-linked mutations: insights from a simulation of the spiral to ring transition in katanin

Several dozen mutations in the large human spastin enzyme assembly have been associated with mobility impairment in hereditary spastic paraplegias. Some of them impact the structural determinants of two functional conformations of the protein, spiral and ring. Here we investigate the possible effect of the mutations on the transition between the two conformations, which is essential for the enzymatic function. By performing a variety of molecular simulations (including metadynamics) on the closely related protein katanin, we suggest that about one fourth of the known disease-associated mutations affect the transition and/or the stability of a previously unrecognized intermediate. The protocol used here can be applied to the study of conformational changes in other large biomolecular complexes. Significance StatementBy combining molecular dynamics and enhanced sampling simulations with custom-designed collective variables, we explore transient intermediate states in a large protein assembly, the severing enzyme katanin. This enzyme plays a critical role in neuronal microtubule remodeling. By targeting the transition between the spiral and ring conformations of the protein, we reveal mechanisms associated with neurodegenerative mutations that impair the function of spastin, a structurally and functionally similar enzyme. These findings provide insights that may inform future therapeutic strategies. They also expand our ability to simulate molecular processes relevant to health and disease, as our approach can be readily applied to study structural changes in other complex biological systems.

biophysics↗

bioRxiv2024

Calcium-driven In Silico Inactivation of a Human Olfactory Receptor

Conformational changes as well as molecular determinants related to the activation and inactivation of olfactory receptors are still poorly understood due to the intrinsic difficulties in the structural determination of this GPCR family. Here, we perform, for the first time, the in silico inactivation of the human olfactory receptor OR51E2, highlighting the possible role of calcium in this receptor state transition. Using molecular dynamics simulations, we show that a divalent ion in the ion binding site, coordinated by two acidic residues at positions 2.50 and 3.39 conserved across most ORs, stabilizes the receptor in its inactive state. In contrast, protonation of the same two acidic residues is not sufficient to drive inactivation within the {micro}s timescale of our simulations. Our findings suggest a novel molecular mechanism for OR inactivation, potentially guiding experimental validation and offering insights into the possible broader role of divalent ions in GPCR signaling.

biophysics↗

bioRxiv2023

Machine Learning-based Modeling of Olfactory Receptors: Human OR51E2 as a Case Study

Atomistic-level investigation of olfactory receptors (ORs) is a challenging task due to the experimental/computational difficulties in the structural determination/prediction for members of this family of G-protein coupled receptors. Here we have developed a protocol that performs a series of molecular dynamics simulations from a set of structures predicted de novo by recent machine learning algorithms and apply it to a well-studied receptor, the human OR51E2. Our study demonstrates the need for simulations to refine and validate such models. Furthermore, we demonstrate the need for the sodium ion at a binding site near D2.50 and E3.39 to stabilize the inactive state of the receptor. Considering the conservation of these two acidic residues across human ORs, we surmise this requirement also applies to the other [~]400 members of this family.

biochemistry↗

bioRxiv2021

An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors

A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.

biochemistry↗

bioRxiv2020

On the accuracy of molecular simulation-based predictions of koff values: a Metadynamics study

Molecular simulations have made great progresses in predicting koff values--the kinetic constant of drug unbinding, a key parameter for modern pharmacology--yet computed values under- or over-estimate experimental data in a system- and/or technique-dependent way. In an effort at gaining insights on this issue, here we used an established method to calculate koff values--frequency-adaptive metadynamics with force field-- and a subsequent QM/MM descriptions of the interactions. First, using force field-based metadynamics, we calculate koff of the Positron Emission Tomography (PET) ligand iperoxo targeting the human muscarinic acetylcholine receptor M2. In line with previously performed in silico studies, the prediction (3.7 {+/-} 0.7 * 10-4 s-1) turned out to differ significantly from the experimentally measured value (1.0 {+/-} 0.2 * 10-2 s-1). Next, we use DFT-based QM/MM simulations to show that this discrepancy arises from erroneous force field energetics at the transition state. It turns out that this discrepancy is partly caused by lack of electronic polarization and/or charge transfer in commonly employed force field. We expect these issues to arise also in other systems where charged portions of the system play a pivotal role, such as protein- or DNA-protein complexes. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/015396v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1ee4e1aorg.highwire.dtl.DTLVardef@49ba0forg.highwire.dtl.DTLVardef@565f25org.highwire.dtl.DTLVardef@80940e_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2019

Chasing the full free energy landscape of neuroreceptor/ligand unbinding by metadynamics simulations

Predicting the complete free energy landscape associated with protein-ligand un-binding would greatly help designing drugs with highly optimized pharmacokinetics. Here we investigate the unbinding of the iperoxo agonist to its target human neuroreceptor M2, embedded in a neuronal membrane. By feeding out-of-equilibrium molecular simulations data in a classification analysis, we identify the few essential reaction coordinates of the process. The full landscape is then reconstructed using an exact enhanced sampling method, well-tempered metadynamics in its funnel variant. The calculations reproduce well the measured affinity, provide a rationale for mutagenesis data and show that the ligand can escape via two different routes. The allosteric modulator LY2119620 turns out to hamper both escapes routes, thus slowing down the unbinding process, as experimentally observed. This computationally affordable protocol is totally general and it can be easily applied to determine the full free energy landscape of membrane receptors/drug interactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/544577v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@cfc6b2org.highwire.dtl.DTLVardef@fde50corg.highwire.dtl.DTLVardef@c8a893org.highwire.dtl.DTLVardef@1b36a12_HPS_FORMAT_FIGEXP M_FIG Graphical TOC Entry C_FIG

biophysics↗