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Scalable, fast and accurate differential gene expression testing from millions of cells of multiple patients
Abstract Since the development of DNA microarrays and later RNA bulk sequencing, testing with statistically independent samples has been the standard method for detecting genes with different transcription patterns. Single-cell assays challenge these assumptions because individual cells are statistically dependent, and all proposed methodologies present mathematical limitations or computational bottlenecks that prevent a seamless integration of data from many cells and patients simultaneously. In this work, we solve this crucial limitation by introducing a Bayesian framework that retrieves the independence structure at the level of individual patients, separating differences across individuals from actual transcriptional differences. Leveraging multi-GPU and variational inference, our approach excels across different experimental designs and scales to analyse over 10 million cells. This framework enables single-cell differential expression analysis that can finally integrate datasets from large clinical cohorts, atlas projects, or drug-response screens with thousands of samples and millions of cells. Authors Giovanni Santacaterina, Niccolò Tosato, Salvatore Milite, Katsiaryna Davydzenka, Edoardo Insaghi, Guido Sanguinetti, Stefano Cozzini, Leonardo Egidi, Giulio Caravagna Journal Nature Communications 2026 Publication Date 19/06/2026 Consult the publication
Decoding the Grammar of Protein-Protein Interaction Interfaces with Multimodal Representations
Abstract Protein-protein interactions govern essential cellular processes, making the identification of interacting sites a central challenge in structural biology, with important implications for protein engineering and the development of targeted therapeutics. Existing prediction algorithms include sequence-based methods, which lack structural information, or structure-based approaches, which often struggle to effectively integrate evolutionary context. Here, we present ESM3-PPISites, a supervised model for residue-level classification of interfaces, leveraging the multimodal representations of the ESM3 Protein Language Model. To ensure a bias-free evaluation, a stringent redundancy filtering protocol is adopted, systematically eliminating latent homology between the training data and a curated benchmark set in both sequence and structural space. ESM3-PPISites achieves unprecedented accuracy, vastly outperforming current approaches. Our findings demonstrate that while ESM3 largest proprietary version yields the highest predictive power, targeted fine-tuning of its small open-weight counterpart significantly narrows the performance gap. We also show the practical impact of these predictions by integrating them as spatial restraints within the HADDOCK docking platform. When evaluated on an independent subset of 12 complexes from the Docking Benchmark v5, the prediction-guided pipeline strongly enhances the identification of near-native binding poses over blind docking, while reducing computational runtime by an order of magnitude. This framework establishes a scalable paradigm for high-throughput structural characterization of protein–protein interactions. Authors Yuri Gardinazzi, Edith Natalia Villegas Garcia, Sergio Senci, Davide Di Vora, Antonio Feltrin, Francesca Cuturello Journal Preprint Publication Date 09/06/2026 Consult the publication
Chirality Unlocks Sub-Terahertz Molecular Dynamics in Peptide Nanotubes
Abstract Low-frequency modes in the picosecond range play a key role in molecular recognition and biomolecular function. Here, we investigate how these dynamics at the interfaces of self-assembled peptide biomaterials relate to fine structural details of the supramolecular assembly. We resolve terahertz and mid-infrared modes in individual diphenylalanine nanotubes by nanoscale microspectroscopy, uncovering a direct correlation between supramolecular chirality, molecular arrangement, and picosecond dynamics at the nanotube-environment boundary. By combining THz and mid-IR nanoscopy with a multiscale strategy spanning single nanotubes and ensemble measurements, supported by density functional theory calculations, we access the intrinsic picosecond response of peptide assemblies beyond the limits of conventional microscopy and ensemble averaging. Heterochiral (D-L) nanotubes display sharp resonances, whereas homochiral (L-L) nanotubes exhibit a comparatively featureless sub-THz profile, revealing a clear chirality-dependent contrast. Mode assignments show that the heterochiral features are dominated by localized torsional and bending motions of phenyl rings relative to the peptide backbone. Overall, chirality-dependent THz fingerprints emerge as sensitive descriptors of peptide nanotube architecture, while low-frequency nanospectroscopy provides a route to interrogate biomaterial interfaces under biologically relevant conditions. Autori Rajat Kumar, Erica Scarel, Andrea Perucchi, Lisa Vaccari, Prasanta Kumar Datta, Francesco D’amico, Paola Di Pietro, Silvia Marchesan, Federica Piccirilli Rivista ChemrXiv Data di pubblicazione 11/03/2026 Consulta la pubblicazione
Ultrafast Intermolecular Dynamics of Nanoconfined Water in Swollen Lipid Cubic Mesophases
Abstract Understanding the structure and dynamics of the hydrogen-bond network ofwater in topologically distinct swollen lipidic mesophases, is fundamental fortheir application in biomedical, pharmaceutical, and food science fields. Here,a positive and non-linear correlation between water hydrogen-bond dynamicsand interfacial water population is uncovered in inverse bicontinuous swollenmesophases across an extended temperature range (298–340 K). Particularly,small-angle X-ray scattering determines the mesophase’s structural features,uncovering a temperature-driven re-entrant phenomenon (reappearance) ofPn̄ 3m phase upon heating. This topologically rich environment, however, hasno detectable impact on the temperature dependence of the intermolecularmodes of water, as revealed by terahertz absorption spectroscopy. Specifically,these modes show distinct dynamics: the stretching mode exhibits longerlifetimes than the libration mode, yet with a higher temperature-dependence,with approximately two-fold lower Arrhenius activation energies. In contrast,both stretching and libration modes exhibit a monotonic decrease in lifetimewith increasing temperature, due to the increasing disruption of thehydrogen-bond network. Atomistic molecular dynamics simulations enablethe quantification of interfacial water population, which shows a positivecorrelation with intermolecular lifetimes in a nonlinear manner, revealing anon-additive coupling between interfacial water population and waterhydrogen-bond network dynamics within these systems. Autori Eva Zunzunegui-Bru, Serena Rosa Alfarano, Patrick Züblin, Laura Baraldi,Hendrik Vondracek, Federica Piccirilli, Lisa Vaccari, and Raffaele Mezzenga Rivista Small Data di pubblicazione 03/10/2025 Consulta la pubblicazione
Evolutionary Constraints Guide AlphaFold2 in Predicting Alternative Conformations and Inform Rational Mutation Design
Abstract Investigating structural variability is essential for understanding protein biological functions. Although AlphaFold2 accurately predicts static structures, it fails to capture the full spectrum of functional states. Recent methods have used AlphaFold2 to generate diverse structural ensembles, but they offer limited interpretability and overlook the evolutionary signals underlying the predictions. In this work, we enhance the generation of conformational ensembles and identify sequence patterns that influence the alternative fold predictions for several protein families. Building on prior research that clustered multiple sequence alignments to predict fold-switching states, we introduce a refined clustering strategy that integrates protein language model representations with hierarchical clustering, overcoming limitations of density-based methods. Our strategy effectively identifies high-confidence alternative conformations and generates abundant sequence ensembles, providing a robust framework for applying direct coupling analysis (DCA). Through DCA, we uncover key coevolutionary signals within the clustered alignments, leveraging them to design mutations that stabilize specific conformations, which we validate using alchemical free energy calculations from molecular dynamics. Notably, our method extends beyond fold-switching, effectively capturing a variety of conformational changes. Authors Valerio Piomponi, Alberto Cazzaniga, Francesca Cuturello Journal Journal of Chemical Information and Modelling Publication Date 03/09/2025 Consult the publication
Rational optimization of D3R/GSK-3β dual target-directed ligands as potential treatment for bipolar disorder: Design, synthesis, X-ray crystallography, molecular dynamics simulations, in vitro ADME, and in vivo pharmacokinetic studies
Abstract Bipolar disorder is a complex neuropsychiatric condition with a significant unmet medical need, as current treatments lack disease-modifying properties and multimodal therapeutic effects. To overcome the limitations of single-target drugs, we designed dual-target ligands that combine partial agonism at the dopamine D3 receptor (D3R) with inhibition of glycogen synthase kinase-3β (GSK-3β). We previously identified ARN24161 (1) as a promising prototype, demonstrating partial agonism at D3R (EC50 = 10.1 nM, % Eff. = 26.3) and GSK-3β inhibition (IC50 = 561 nM). However, its drug-like properties remained suboptimal. To optimize this compound, we initiated a multidisciplinary refinement campaign, leveraging computational modeling and crystallographic data to fine-tune the balance between D3R and GSK-3β activity, reduce P-glycoprotein (P-gp) affinity, and improve the pharmacokinetic profile. This effort led to the identification of ARN25297 (5), a moderately balanced dual-target ligand that exhibits partial agonism at D3R (EC50 = 13.1 nM, % Eff. = 17.1) and potent GSK-3β inhibition (IC50 = 47.0 nM). Notably, ARN25657 (16) emerged as the most well-balanced candidate, demonstrating enhanced D3R partial agonism (EC50 = 15.2 nM, % Eff. = 37.7) alongside strong GSK-3β inhibition (IC50 = 19.3 nM). Compound 16 also exhibited the lowest P-gp inhibition and significant improvements in in vitro ADME properties compared to prototype 1, while maintaining a balanced dual target profile. Although the PK profile of 16 remained comparable to that of prototype 1, these findings lay the groundwork for further lead optimization and structural refinement, driving future in vivo proof-of-concept toward innovative therapeutic strategies for bipolar disorder and related neuropsychiatric conditions. Autori RMC Di Martino, D Russo, I Penna, Andrea Dalle Vedove, R Spabnuolo, G Ottonello, M Summa, J Desantis, A Valeri, L Pruccoli, SK Tripathi, A Tarozzi, Paola Storici, S Girotto, R Bertorelli, A Armirotti, G Cruciani, T Bandiera, A Cavalli, G Bottegoni Rivista European Journal of Medicinal Chemistry Data di pubblicazione 25/06/2025 Consulta la pubblicazione
FL30: an epidermal growth factor kinase inhibitor overcoming T790M and C797S mutations through unique conformational modulation mechanism
Abstract Tyrosine kinase inhibitors (TKIs) targeting the oncogene Epidermal Growth Factor Receptor (EGFR) are widely used in the treatment of non-small cell lung cancer (NSCLC). In this context, the introduction of fourth-generation TKIs has significantly advanced targeted therapy for T790M and C797S EGFR mutations. Current therapeutic strategies are increasingly focusing on the design of orthoallosteric TKIs, which have shown promise in stabilizing the inactive conformation of mutated EGFR. In this context, we report the discovery of FL30, a small molecule with a flavone core that exhibits nanomolar potency against the EGFR-L858R/T790M mutation, even in the presence of the C797S mutation. The IC50 comparable to the Osimertinib – one of the most renowned EGFR-TKIs – emphasizes the remarkable success of the design approach. In NSCLC models, FL30 effectively inhibits cancer growth and EGFR phosphorylation selectively in cells with the EGFR mutations. Kinetic studies, molecular modeling, and Plasmon Internal Reflection Surface-Enhanced Infrared Absorption (PIR-SEIRA) microscopy suggests that FL30 binds to the orthosteric site while inducing the transition of the mutant EGFR toward an inactive-like state. These findings highlight FL30’s potential for further optimization and propose a novel approach for developing targeted therapies that combine orthosteric binding with allosteric modulation. Autori Elena Romagnoli, Emiliano Laudadio, Giovanna Mobbili, Leonardo Sorci, Giovanni Birarda, Federica Piccirilli, Lisa Vaccari, Hendrik Vondracek, Brenad Romaldi, Massimo Marcaccio, Paola Storici, Marta Semrau, Roberta Galeazzi, Andrea Toma, Vincenzo Aglieri, Pierluigi Stipa, Tatiana Armeni, Cristina Minnelli Rivista International Journal of Biological Macromolecules Data di pubblicazione 21/06/2025 Consulta la pubblicazione
A supported lipid bilayer to model solid-ordered membrane domains
Abstract Membrane models are widely used to mimic the behaviour of native plasma membranes and to simulate interactions occurring at their interface. Such models can be built up with different molecular compositions, ranging from single phospholipids to more complex, heterogeneous mixtures of phospho- and sphingo-lipids, possibly enriched with cholesterol and proteins. In particular, mixing different lipids and cholesterol is instrumental to promote the formation of phase-separated, ordered domains, which resemble the structure of lipid rafts, specialized functional domains of real membranes. According to the specific lipid composition, physical characteristics of the rafts can be tuned, such as fluidity, strongly related to membrane biological activity. Here, we introduce a novel three-component membrane model constituted by the mixing of a saturated phospholipid, 1,2-dimyristoyl-sn–glycero-3-phosphocholine (DMPC), sphingomyelin and cholesterol to mimic the presence of solid ordered rafts and to study their behaviour. Differential scanning calorimetry, neutron reflectometry, and atomic force microscopy were synergistically applied to gain information on the membrane’s transverse and lateral organization, as well as on its thermotropic behaviour. The membrane model benefits from the use of DMPC, a lipid (i) characterized by an accessible transition temperature; (ii) saturated; (iii) fluid at physiological temperature and (iv) commercially available in both protiated and deuterated forms. The proposed model, along with the wide range of biophysical techniques employed, constitutes an ideal system to study the molecular mechanisms and the physical properties that govern membrane functions, such as molecular signalling and membrane trafficking. Autori Sally Helmy, Paola Brocca, Alexandros Koutsioubas, Stephen C.L. Hall, Luca Puricelli, Pietro Parisse, Loredana Casalis, Valeria Rondelli Rivista Journal of Colloid and Interface Science Data di pubblicazione 14/03/2025 Consulta la pubblicazione
Interpreting and Steering Protein Language Models through Sparse Autoencoders
Abstract The rapid advancements in transformer-based language models have revolutionized natural language processing, yet understanding the internal mechanisms of these models remains a significant challenge. This paper explores the application of sparse autoencoders (SAE) to interpret the internal representations of protein language models, specifically focusing on the ESM-2 8M parameter model. By performing a statistical analysis on each latent component’s relevance to distinct protein annotations, we identify potential interpretations linked to various protein characteristics, including transmembrane regions, binding sites, and specialized motifs. We then leverage these insights to guide sequence generation, shortlisting the relevant latent components that can steer the model towards desired targets such as zinc finger domains. This work contributes to the emerging field of mechanistic interpretability in biological sequence models, offering new perspectives on model steering for sequence design. Authors Edith Natialia Villegas Garcia, Alessio Ansuini Journal Workshop on Generative and Experimental Perspectives for Biomolecular Design @ ICLR 2025 Publication Date 13/02/2025 Consult the publication
Ultrasensitive detection and quantification of bovine Deltapapillomavirus in the semen of healthy horses.
Abstract BPV1, BPV2, BPV13, and BPV14 are all genotypes of bovine delta papillomaviruses (δPV), of which the first three cause infections in horses and are associated with equine sarcoids. However, BPV14 infection has never been reported in equine species. In this study, we examined 58 fresh and thawed commercial semen samples from healthy stallions. In 34 (58.6%), bovine δPV DNA was detected and quantified using droplet digital polymerase chain reaction (ddPCR). Real time quantitative PCR (qPCR) was able to identify bovine δPV DNA in 5 samples (8.6%). Of the BPV-infected semen samples, 15 were positive for BPV2 (~ 44.1%) on ddPCR and 4 (~ 11.7%) on qPCR; 12 (~ 35.3%) for BPV14 on ddPCR and 1 (~ 3%) by qPCR; 4 (~ 11.7%) for BPV1 on ddPCR, whereas qPCR failed to reveal this infection; 3 (~ 8.8%) for BPV13 on ddPCR; and BPV13 infection was not detected by qPCR. Our study showed for the first time that BPV14 is an additional infectious agent potentially responsible for infection in horses, as its transcripts were detected and quantified in some semen samples. Large-scale BPV14 screening is necessary to provide substantial data on the molecular epidemiology for a better understanding of the geographical divergence of BPV14 prevalence in different areas and how widespread BPV14 is among equids. Autori Anna Cutarelli, Francesca De Falco, Francesco Serpe, Simona Izzo, Giovanna Fusco, Cornel Catoi, Sante Roperto Rivista Scientific Report Data di pubblicazione 04/01/2025 Consulta la pubblicazione
Limiting serine availability during tumor progression promotes muscle wasting in cancer cachexia
Abstract Cancer cachexia is a multifactorial syndrome characterized by a progressive loss of body weight occurring in about 80% of cancer patients, frequently representing the leading cause of death. Dietary intervention is emerging as a promising therapeutic strategy to counteract cancer-induced wasting. Serine is the second most-consumed amino acid (AA) by cancer cells and has emerged to be strictly necessary to preserve skeletal muscle structure and functionality. Here, we demonstrate that decreased serine availability during tumor progression promotes myotubes diameter reduction in vitro and induces muscle wasting in in vivo mice models. By investigating the metabolic crosstalk between colorectal cancer cells and muscle cells, we found that incubating myotubes with conditioned media from tumor cells relying on exogenous serine consumption triggers pronounced myotubes diameter reduction. Accordingly, culturing myotubes in a serine-free medium induces fibers width reduction and suppresses the activation of the AKT-mTORC1 pathway with consequent impairment in protein synthesis, increased protein degradation, and enhanced expression of the muscle atrophy-related genes Atrogin1 and MuRF1. In addition, serine-starved conditions affect myoblast differentiation and mitochondrial oxidative metabolism, finally inducing oxidative stress in myotubes. Consistently, serine dietary deprivation strongly strengthens cancer-associated weight loss and muscle atrophy in mice models. These findings uncover serine consumption by tumor cells as a previously undisclosed driver in cancer cachexia, opening new routes for possible therapeutic approaches. Autori Erica Pranzini, Livio Muccillo, Ilaria Nesi, Alice Santi, Caterina Mancini, Giulia Lori, Massimo Genovese, Tiziano Lottini, Giuseppina Comito, Anna Caselli, Annarosa Arcangeli, Lina Sabatino, Vittorio Colantuoni, Maria Letizia Taddei, Paolo Cirri, Paolo Paoli Rivista Cell Death Discovery Data di pubblicazione 21/12/2024 Consulta la pubblicazione
Ferritin adsorption onto chrysotile asbestos fibers influences the protein secondary structure
Abstract Asbestos fiber exposure triggers chronic inflammation and cancer. Asbestos fibers can adsorb different types of proteins. The mechanism of this adsorption, not yet completely understood, has been studied in detail mainly with serum albumin and was shown to induce structural changes in the bound protein. The findings of these works regarded mainly the changes of the protein structure, independently of any relation with asbestos-related diseases. For the first time, we have focused our attention to the consequences of the interaction between asbestos fibers and ferritin, a protein involved in iron metabolism, which is strongly modified in asbestos-related diseases. Even if it is known that ferritin can be adsorbed by asbestos fibers, the results of this interaction for the ferritin secondary structure has not previously been studied. One consequence of asbestos-ferritin interaction, is the formation of the so-called ferruginous/asbestos bodies (ABs). In the AB-coating material, the secondary structure of ferritin is modified, and at present, it is unclear whether or not this modification is a direct consequence of the asbestos interaction. In the present study, chrysotile asbestos, more than other asbestos fiber types tested, was found to rapidly bind holo-ferritin, and the presence of iron seemed to play a key role in this process, since iron-free apo-ferritin was adsorbed at a lower level, and iron-saturated chrysotile lost its ferritin-adsorbing capacity. To directly study the details of ferritin adsorption on asbestos fibers, High Resolution Transmission Electron Microscopy (HR-TEM) was employed together with FTIR microspectroscopy and Infrared nanoscopy, which to the best of our knowledge, have not previously been used for this purpose. Chrysotile-bound apo-ferritin underwent a significant change in secondary structure, showing a shift from a prevalent α-helix to a β-sheet conformation. Conversely, the adsorbed holo-ferritin structure appeared to be only weakly modified. These findings add a new potential mechanism to the toxic activities of asbestos: the fibers can modify the structure, and very likely, the function of adsorbed proteins. This, in relation to ferritin, could be a key mechanism in cell iron homeostasis alteration, typically reported in asbestos-related diseases. Autori Martina Zangari, Federica Piccirilli, Lisa Vaccari, Cristian Radu, Paola Zacchi, Annalisa Bernareggi, Sara Leone, Giuliano Zabucchi, Violetta Borelli Rivista Helyon Data di pubblicazione 30/10/2024 Consulta la pubblicazione