Henrique Musseli Cezar

• Kersten, Flore; Cortés, Natalia Mojica; Serrano, Albert; Heim, Joel Benjamin; Guyette, Jessica L. & Cezar, Henrique Musseli [Show all 11 contributors for this article] (2026). A Single Amino Acid in the A2 Linker of Cholera Toxin Affects the Efficiency of Toxin Disassembly and Resulting Toxicity. ACS Omega. 11(38), p. 57763–57780. doi: 10.1021/acsomega.6c07022. Full text in Research Archive Show summary

  Abstract Cholera toxin (CT) from Vibrio cholerae and heat-labile enterotoxin (LT) from enterotoxigenic Escherichia coli are highly related AB5-type protein toxins that contain a catalytic A1 subunit, an A2 linker, and a cell-binding homopentamer of B subunits. The two proteins bind the same GM1 receptor and have similar levels of enzymatic activity toward their shared Gsα target, yet CT is more potent than LT. This difference has been mapped to a sequence of 11 amino acids (residues 226–236) near the C-terminus of the A2 linker. We now identify a single amino acid, aspartic acid at position 229, as a key contributor to the function of CT: substituting it for glutamic acid 229 from LT reduced the toxicity of CT to the level of LT. Toxin disassembly by protein disulfide isomerase (PDI), which is an essential event in the intoxication process, was less efficient for CTD229E and LT than for wild-type CT. This was further confirmed by a CT variant, in which four residues were converted into the LT sequence (D229E, I230V, T232I, and H233Y). To test our previous hypothesis that the positioning of the A1 subunit over the B pentamer critically determines toxin disassembly and thus potency, we determined crystal structures of both toxin variants to 1.6 Å resolution and calculated the angle at which the A2 linker exits the pore. The conformations of the two toxin chimeras lie between CT and LT, with the A2 C-terminus of the CT quadruple variant adopting essentially the same fold as LT. The A subunits of the toxin variants as well as that of LT showed a higher conformational freedom than CT as determined by molecular dynamics simulations, suggesting that a more rigid positioning of the A subunit drives toxin disassembly and potency. Our collective data uncover the critical role of D229 in toxin folding and structural dynamics, which in turn impacts toxin potency through effects on the efficiency of PDI-driven toxin disassembly.

• Junior, Carlos Alberto Martins; Cezar, Henrique Musseli; Damasceno, Daniela Andrade & Miranda, Caetano Rodrigues (2026). Effects of van der Waals Interaction on N2 Adsorption on Carbon Nanotubes: Proposal for New Force Field Parameters. ACS Omega. doi: 10.1021/acsomega.5c12920. Full text in Research Archive Show summary

  The separation of carbon dioxide (CO2) from nitrogen gas (N2) in flue gas has become an emerging strategy to mitigate climate change. Molecular simulations are valuable to provide insights for the gas separation process. A careful choice of force fields is required to avoid unrealistic predictions of thermodynamic properties. Most studies use Lorentz–Berthelot combining rules (LB) to obtain the interaction between different species. In this context, we verified how accurate LB is in describing the interaction of N2 molecules and carbon nanostructures by comparing the interaction energies of LB with those from density functional theory (DFT) calculations. Carbon nanomaterials were selected because they are considered promising materials to perform N2/CO2 separation. The results show that the LB underestimates the interaction energies and affects the prediction of the fundamental properties of solid–fluid interfacial interactions. To overcome this, we parametrized a Lennard–Jones potential using DFT and considering van der Waals interactions. The proposed potential shows good transferability and agreement with ab initio calculations. Molecular simulations were performed to verify the effects of employing LB in predicting the amount of nitrogen gas adsorbed in carbon nanotubes (CNTs). LB predicts a lower density within them. Our results suggest that LB leads to different adsorption properties.

• Cezar, Henrique Musseli; Berton, Giacomo; Lorenzetto, Tommaso; Zorzi, Sandro; Foumthuim, Cedrix J. Dongmo & Szostak, Szymon Mikolaj [Show all 15 contributors for this article] (2026). Self-Assembly of Unconventional Triphenylene-Based Frustrated Amphiphile in Solution. Langmuir. ISSN 0743-7463. 42(6), p. 4507–4517. doi: 10.1021/acs.langmuir.5c05203. Full text in Research Archive Show summary

  Unconventional amphiphilic molecules having a rigid hydrophobic central unit and flexible or semiflexible hydrophilic chains on the rim have proven valuable in several technological applications, for example, host–guest chemistry. The further presence of alternating hydrophobic and hydrophilic tails complicates the definition of clear core and shell regions, resulting in complex segregation and frustrated self-assembly. In this study, we investigate symmetric triphenylene-based amphiphilic derivatives with alternating benzyl and alkylsulfonate groups. We characterize their self-assembly in water and different solutions using several experimental techniques, including NMR, atomic force microscopy, dynamic light scattering, and small-angle X-ray and neutron scattering, alongside extensive molecular dynamics simulations, including both atomistic and coarse-grained integrative modeling with metainference. In aqueous solutions, these amphiphiles form stacked assemblies, adopting alternate up–down conformations driven by π-stacking of up to six molecules. The introduction of NaCl salt screens unfavorable electrostatic interactions, thus promoting further π-stacking and leading to the formation of larger elongated aggregates.

• Koynarev, Vladimir Rosenov; Nader, Manuela Leal; Borgos, Kari Kristine Almåsvold; Cezar, Henrique Musseli; Narayanan, Theyencheri & Porcar, Lionel [Show all 8 contributors for this article] (2025). Structural pores not required: Antimicrobial peptides induce ion permeabilization of lipid membranes through transient water channels. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 122(44). doi: 10.1073/pnas.2517944122. Full text in Research Archive Show summary

  Antimicrobial peptides (AMPs) are highly potent and broad-spectrum antibiotics, found as components of the innate immune system in almost all forms of life. Despite being commonly accepted that the mechanism of action of AMPs is associated with the permeabilization of the cell membrane, the structural and dynamical means by which this occurs are still heavily debated. In this work, we employ experimental time-resolved small angle X-ray scattering to follow in real time the AMP-induced ion transport in lipid vesicles, while simultaneously resolving the membrane structure and peptide partitioning. For several natural AMPs, we show that they can effectively permeabilize the lipid membrane despite only binding peripherally to the outer membrane leaflet. Our experiments reveal rapid ion transport associated with AMP binding, yielding salt equilibration in a few tens of milliseconds, while not detecting evidence of transversal and structurally stable peptide pores. On the contrary, new analysis of previously reported all-atom molecular dynamics simulations shows that lipid flip-flop, accelerated by the peripherally bound peptides, leads to the formation of transient, ion-conducting water channels. A corresponding diffusional model indicates that such short-lived, transient pores explain the observed ion transport better than stable pores.

• Cezar, Henrique Musseli; Bodenstein, Tilmann; Sveinsson, Henrik Andersen; Ledum, Morten; Reine, Simen & Bore, Sigbjørn Løland (2025). Learning atomic forces from uncertainty-calibrated adversarial attacks. npj Computational Materials. 11. doi: 10.1038/s41524-025-01703-5. Full text in Research Archive Show summary

  Adversarial approaches, which intentionally challenge machine learning models by generating difficult examples, are increasingly being adopted to improve machine learning interatomic potentials (MLIPs). While already providing great practical value, little is known about the actual prediction errors of MLIPs on adversarial structures and whether these errors can be controlled. We propose the Calibrated Adversarial Geometry Optimization (CAGO) algorithm to discover adversarial structures with user-assigned errors. Through uncertainty calibration, the estimated uncertainty of MLIPs is unified with real errors. By performing geometry optimization for calibrated uncertainty, we reach adversarial structures with the user-assigned target MLIP prediction error. Integrating with active learning pipelines, we benchmark CAGO, demonstrating stable MLIPs that systematically converge structural, dynamical, and thermodynamical properties for liquid water and water adsorption in a metal-organic framework within only hundreds of training structures, where previously many thousands were typically required.

• Ribeiro, Rafael Bicudo & Cezar, Henrique Musseli (2025). clusttraj: A Solvent-Informed Clustering Tool for Molecular Modeling. Journal of Chemical Theory and Computation. ISSN 1549-9618. 21(14), p. 6759–6768. doi: 10.1021/acs.jctc.5c00634. Full text in Research Archive Show summary

  Clustering techniques are consolidated as a powerful strategy for analyzing the extensive data generated from molecular modeling. In particular, some tools have been developed to cluster configurations from classical simulations with a standard focus on individual units, ranging from small molecules to complex proteins. Since the standard approach includes computing the root mean square deviation (RMSD) of atomic positions, accounting for the permutation between atoms is crucial for optimizing the clustering procedure in the presence of identical molecules. To address this issue, we present the clusttraj program, a solvent-informed clustering package that fixes inflated RMSD values by finding the optimal pairing between configurations. The program combines reordering schemes with the Kabsch algorithm to minimize the RMSD of molecular configurations before running a hierarchical clustering protocol. By considering evaluation metrics, one can determine the ideal threshold in an automated fashion and compare the different linkage schemes available. The program capabilities are exemplified by considering solute–solvent systems ranging from pure water clusters to a solvated protein or a small solute in different solvents. As a result, we investigate the dependence on different parameters, such as the system size and reordering method, and also the representativeness of the cluster medoids for the characterization of optical properties. clusttraj is implemented as a Python library and can be employed to cluster generic ensembles of molecular configurations that go beyond solute–solvent systems.

• Carrer, Manuel; Cezar, Henrique Musseli; Bore, Sigbjørn Løland; Ledum, Morten & Cascella, Michele (2024). Learning Force Field Parameters from Differentiable Particle-Field Molecular Dynamics. Journal of Chemical Information and Modeling. ISSN 1549-9596. 64, p. 5510–5520. doi: 10.1021/acs.jcim.4c00564. Full text in Research Archive Show summary

  We develop ∂-HylleraasMD (∂-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish a protocol for automated optimization of force field parameters. ∂-HyMD is templated on the recently released HylleraaasMD software, while using the JAX autodiff framework as the main engine for the differentiable dynamics. ∂-HyMD exploits an embarrassingly parallel optimization algorithm by spawning independent simulations, whose trajectories are simultaneously processed by reverse mode automatic differentiation to calculate the gradient of the loss function, which is in turn used for iterative optimization of the force-field parameters. We show that parallel organization facilitates the convergence of the minimization procedure, avoiding the known memory and numerical stability issues of differentiable molecular dynamics approaches. We showcase the effectiveness of our implementation by producing a library of force field parameters for standard phospholipids, with either zwitterionic or anionic heads and with saturated or unsaturated tails. Compared to the all-atom reference, the force field obtained by ∂-HyMD yields better density profiles than the parameters derived from previously utilized gradient-free optimization procedures. Moreover, ∂-HyMD models can predict with good accuracy properties not included in the learning objective, such as lateral pressure profiles, and are transferable to other systems, including triglycerides.

• Lang, Lucas; Cezar, Henrique Musseli; Adamowicz, Ludwik & Pedersen, Thomas Bondo (2024). Quantum Definition of Molecular Structure. Journal of the American Chemical Society. ISSN 0002-7863. 146(3), p. 1760–1764. doi: 10.1021/jacs.3c11467. Full text in Research Archive Show summary

  Molecular structure, a key concept of chemistry, has remained elusive from the perspective of all-particle quantum mechanics despite many efforts. Viewing molecular structure as a manifestation of strong statistical correlation between nuclear positions, we propose a practical method based on Markov chain Monte Carlo sampling and unsupervised machine learning. Application to the D3+ molecule unambiguously shows that it possesses an equilateral triangular structure. These results provide a major step forward in our understanding of molecular structure from fundamental quantum principles.

• Cezar, Henrique Musseli; Lanna, Teresa; Damasceno, Daniela; Kirch, Alexsandro & Miranda, Caetano (2024). Revisiting greenhouse gases adsorption in carbon nanostructures: Advances through a combined first-principles and molecular simulation approach. Applied Surface Science. ISSN 0169-4332. 671. doi: 10.1016/j.apsusc.2024.160659. Full text in Research Archive Show summary

  Carbon nanostructures are promising materials to improve the performance of current gas separation membrane technologies. From the molecular modeling perspective, an accurate description of the interfacial interactions is mandatory to understand the gas selectivity in the context of greenhouse gases applications. Most of the molecular dynamics simulations studies considered available force fields with the standard Lorentz-Berthelot (LB) mixing rules to describe the interaction among carbon dioxide (CO2), methane (CH4) and carbon structures. We performed a systematic study in which we showed the LB underestimates the interaction energies compared to the density functional theory (DFT) results. To improve the classical description, we propose a new parametrization for the cross-terms of the Lenard-Jones potential by fitting DFT forces and energies. The effects of the new parametrization on the gases adsorption within single-walled carbon nanotubes (SWCNTs), are investigated with Grand Canonical Monte Carlo simulations. We observed considerable differences in the CO2 and CH4 density within SWCNTs compared to those obtained with the standard approach. Our study highlights the importance of going beyond the traditional LB mixing rules in studies involving solid/fluid interfaces of confined systems. The revised mixing terms enhanced fluid/carbon interface description with excellent transferability ranging from SWCNTs to graphene.

• Sen, Samiran; Cezar, Henrique Musseli; Ledum, Morten; Li, Xinmeng & Cascella, Michele (2024). Phase Coexistence in Hamiltonian Hybrid Particle-Field Theory Using a Multi-Gaussian Approach. Journal of Physical Chemistry B. ISSN 1520-6106. 128(47), p. 11739–11747. doi: 10.1021/acs.jpcb.4c05525. Full text in Research Archive Show summary

  This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle-field (HhPF) theory, aimed at capturing phase co-existence phenomena in mesoscopic molecular simulations. By employing a linear combination of two Gaussians, we demonstrate that HhPF can generate potentials with attractive and steric components analogous to Lennard-Jones potentials, which are crucial for modeling phase co-existence. We compare the performance of this method with the Multi-Gaussian Core Model (MGCM) in simulating liquid-gas coexistence for a single-component system across various densities and temperatures. Our results show that HhPF effectively captures detailed information on phase co-existence and interfacial phenomena, including micro-configuration transitions and increased interfacial fluctuations at higher temperatures. Notably, the phase boundaries obtained from HhPF simulations align more closely with those of Lennard-Jones systems compared to the MGCM results. This work advances the hybrid particle-field methodology to address phase co-existence without requiring modifications to the equation of state or introducing additional interaction energy functional terms, offering a promising approach for mesoscale molecular simulations of complex systems.

• Cezar, Henrique Musseli; Bjørnestad, Victoria Ariel; Prévost, Sylvain François; Lund, Reidar & Cascella, Michele (2024). Beyond Core–Shell Micellar Structures: Complex Structures in Simple Surfactants. Small Structures. doi: 10.1002/sstr.202400553. Full text in Research Archive Show summary

  Small-angle X-ray/neutron scattering (SAXS/SANS) techniques provide valuable nanostructural information of self-assembling molecules. However, extracting the information from these experiments can be a challenging task, usually relying on predetermined assumptions. Conventional models for surfactant micelles consider a core–shell structure with a hydrophobic tail encapsulated by the hydrophilic part. This approach is successful in many cases but can fail even for common surfactants such as Triton X-100 (TX-100). SAXS and SANS combined with Metainference molecular simulations are employed to investigate TX-100 assemblies, showing how more complex models, with diffuse core–shell boundaries, multilayering, and polydispersity, are needed to explain the aggregation. This is the first time that Metainference is employed with SAXS and SANS simultaneously to obtain the structural ensemble of assemblies. Compared to regular micelles formed by chemically similar C12EO10 molecules, the role of the hydrophobic core in micellization is discussed, finding that the relatively shorter and less hydrophobic tail of TX-100 favors polymorphism.

• Carrer, Manuel; Nielsen, Josefine Eilsø; Cezar, Henrique Musseli; Lund, Reidar; Cascella, Michele & Silva, Thereza Amelia Soares da (2023). Accelerating Lipid Flip-Flop at Low Concentrations: A General Mechanism for Membrane Binding Peptides. The Journal of Physical Chemistry Letters. 14(31), p. 7014–7019. doi: 10.1021/acs.jpclett.3c01284. Full text in Research Archive Show summary

  We report a physicochemical investigation of the lipid transport properties of model lipid membranes in the presence of the antimicrobial peptide indolicidin through comparisons of experimental SANS/SAXS scattering techniques to fully atomistic molecular dynamics simulations. In agreement with the experiment, we show that upon peripheral binding of the peptides, even at low concentrations, lipid flip-flop dynamics is greatly accelerated. Computer modeling elucidates the interplay between structural changes and lipid dynamics induced by peptides and proposes a mechanism for the mode of action of antimicrobial peptides, assessing the major role of entropy for the catalysis of the flipping events. The mechanism introduced here is universal for all peptides with preferential peripheral binding to the membrane as it does not depend on the specific amino acid sequence.

• Cezar, Henrique Musseli & Cascella, Michele (2023). SANS Spectra with PLUMED: Implementation and Application to Metainference. Journal of Chemical Information and Modeling. ISSN 1549-9596. 63(16), p. 4979–4985. doi: 10.1021/acs.jcim.3c00724. Full text in Research Archive Show summary

  Using small-angle scattering with either X-ray or neutron sources has become common in the investigation of soft-matter systems. These experiments provide information about the coarse shape of the scattered objects, but obtaining more-detailed information can usually only be achieved with the aid of molecular simulations. In this Application Note, we report the implementation of an extension in PLUMED to compute the small-angle neutron scattering (SANS), which can be used for data processing as well for enhanced sampling, in particular with the metainference method to bias simulations and sample structures with a resulting spectrum in agreement with an experimental reference. Our implementation includes a resolution function that can be used to smear the SANS intensities according to beamline error sources and is compatible with both all-atom and coarse-grained simulations. Scripts to aid in the calculation of the scattering lengths when the system is coarse-grained and to aid in preparing the inputs are provided. We illustrate the use of the implementation with metainference by performing coarse-grained simulations of beta-octylglucoside and dodecylphosphocholine micelles in water. With different software and different Hamiltonians, we show that the metainference SANS bias can drive micelles to be split and to change shapes to achieve a better agreement with the experimental reference.

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• Cezar, Henrique Musseli (2026). Integrative modelling of amphiphiles with metainference. Full text in Research Archive Show summary

  Extracting high-resolution structural information from small-angle scattering often relies on fitting analytical models, such as core-shell models, to the scattering data. While successful for many systems, this approach becomes challenging for amphiphiles where the packing is complex or unknown. In these cases, molecular simulations can be of great help, providing models with atomic-level detail. However, the quality of the models depends on the quality of the underlying force fields and the simulated time scales, and agreement with scattering curves is, in principle, not guaranteed. In this tutorial, I present metainference [1] as a solution to bridge molecular dynamics simulations and experimental data. Metainference is a Bayesian framework that enhances sampling by using experimental data (for example, SAXS and SANS) to bias the simulation toward the correct structural ensemble, compensating for potential force field inaccuracies. I will outline the methodology for performing these simulations and briefly cover simulation setup and practical workflows with PLUMED. [2] The capabilities of this approach will be illustrated by recent applications. I will demonstrate how this method allows one to resolve ensembles without a priori assumptions. This includes unusual shapes such as the toroidal and multi-domain structures found in Triton X-100 [3] or the stacked assemblies of triphenylene-based amphiphiles driven by π-stacking. [4] These examples highlight how integrative modeling can aid the interpretation of scattering data for complex soft-matter systems. References [1] Bonomi et al., Sci. Adv. 2016, 2, e150117. [2] Cezar & Cascella, J. Chem. Inf. Model. 2023, 63, 4979–4985. [3] Cezar et al., Small Struct. 2025, 6, 2400553. [4] Cezar et al., ChemRxiv 2025, DOI: 10.26434/chemrxiv-2025-l9qzc-v2 (under review).

• Cezar, Henrique Musseli (2025). Beyond the core-shell model for surfactants with molecular simulations. Full text in Research Archive
• Cezar, Henrique Musseli; Bjørnestad, Victoria Ariel; Lund, Reidar & Cascella, Michele (2024). Metainference simulations to interpret small-angle scattering experiments of non-conventional surfactants. Full text in Research Archive
• Cezar, Henrique Musseli; Bjørnestad, Victoria Ariel; Lund, Reidar & Cascella, Michele (2024). Metainference simulations to interpret small angle scattering experiments of non-conventional surfactants. Full text in Research Archive
• Cezar, Henrique Musseli; Bjørnestad, Victoria Ariel; Lund, Reidar & Cascella, Michele (2024). Metainference simulations to interpret small angle scattering experiments. Full text in Research Archive
• Cezar, Henrique Musseli; Bjørnestad, Victoria Ariel; Prévost, Sylvain François; Lund, Reidar & Cascella, Michele (2024). Metainference simulations to interpret small angle scattering experiments. Full text in Research Archive

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