Jiajia Niu, Jichun Zhao, Liqing Yue, Wanchen Zang, Zhe Jin, Cuiliu Fu, Chen Chen, Li Dong, Youliang Zhu, Xiaojie Li
{"title":"A screening strategy for vinyl acetate materials for solid-phase microextraction based on dynamic vapor sorption.","authors":"Jiajia Niu, Jichun Zhao, Liqing Yue, Wanchen Zang, Zhe Jin, Cuiliu Fu, Chen Chen, Li Dong, Youliang Zhu, Xiaojie Li","doi":"10.1038/s42004-026-02034-2","DOIUrl":"https://doi.org/10.1038/s42004-026-02034-2","url":null,"abstract":"<p><p>In solid-phase microextraction (SPME) research, selecting a coating adsorbent with good compatibility for target molecules can be difficult, and there is no specific migration testing method for vinyl acetate monomer, which is commonly used in the production of food contact materials (FCMs). First, 13 metal-organic frameworks (MOFs) with different structural characteristics and surface chemical environments were prepared and divided into three groups (good, medium, and poor) based on the dynamic vapor sorption (DVS) method. The distinction of superiority and inferiority determined by the DVS method was completely consistent with that determined by the extraction effect of the SPME probe, and the data from the two variables exhibited a statistically significant positive correlation. Then, the electrostatic potential (ESP) distribution on the typical material surface and target molecule and the charge density difference (CDD) of their interaction during adsorption were obtained using a computational simulation method. The results showed that ZIF-68 and ZIF-70 had the highest adsorption energy, which was consistent with the adsorption performance. Finally, ZIF-68 was selected as the optimal adsorption material, and the extraction conditions were optimized. The optimized method was successfully applied to test the specific migration amounts of several ethylene vinyl acetate (EVA) copolymer materials.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147856012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Narjes Ansari, Félix Aviat, Jérôme Hénin, Jean-Philip Piquemal, Louis Lagardère
{"title":"Dual-LAO for calculating fast and robust relative binding free energies of simple and complex transformations.","authors":"Narjes Ansari, Félix Aviat, Jérôme Hénin, Jean-Philip Piquemal, Louis Lagardère","doi":"10.1038/s42004-026-02022-6","DOIUrl":"https://doi.org/10.1038/s42004-026-02022-6","url":null,"abstract":"<p><p>Relative binding free energy (RBFE) calculations are a cornerstone of rational hit-to-lead and lead optimization in modern drug discovery. However, the high computational cost and limited reliability in tackling large or complex molecular transformations often prevent their routine, high-throughput use. Here we introduce Dual-LAO, a novel, highly efficient method for calculating RBFE. Building on the Lambda-ABF-OPES framework, this method combines a dual-topology setup and suitable restraints to dramatically accelerate free energy convergence. We demonstrate that Dual-LAO, in combination with the AMOEBA polarizable force field, achieves an unprecedented acceleration factor of 15 to 30 times compared to current state-of-the-art methods on standard drug targets. Crucially, the approach maintains high accuracy and successfully tackles previously prohibitive molecular changes, including scaffold-hopping, buried water displacement, charge changes, ring-opening, and binding pose perturbations. This significant leap in efficiency allows for the widespread, routine integration of predictive molecular simulations into the rapid optimization cycles of drug discovery, enabling chemists to confidently model historically challenging systems in timescales compatible with real-world project deadlines.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Greta Baltušytė, Isaac J D Toleman, James O Jones, Sarah J Welsh, Grant D Stewart, Thomas J Mitchell, Kourosh Saeb-Parsy, Namshik Han
{"title":"A network medicine framework for multi-modal data integration in therapeutic target discovery.","authors":"Greta Baltušytė, Isaac J D Toleman, James O Jones, Sarah J Welsh, Grant D Stewart, Thomas J Mitchell, Kourosh Saeb-Parsy, Namshik Han","doi":"10.1038/s42004-026-02049-9","DOIUrl":"https://doi.org/10.1038/s42004-026-02049-9","url":null,"abstract":"<p><p>The high cost and attrition rate of drug development underscore the need for more effective strategies for therapeutic target discovery. Here, we present a network medicine-based machine learning framework that integrates single-cell transcriptomics, bulk multi-omic profiles, genome-wide CRISPR perturbation screens, and protein-protein interaction networks to systematically prioritise disease-specific targets. Applied to clear cell renal cell carcinoma, the framework successfully recovered established targets and predicted five therapeutic candidates, with subsequent in vitro validation demonstrating that among these, ENO2 inhibition had the strongest anti-tumour effect, followed by LRRK2, a repurposing candidate with phase III Parkinson's disease inhibitors. The proposed approach advances target discovery by moving beyond single-feature, single-modality heuristics to a scalable, machine learning-driven strategy that is generalisable across diseases.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Apostolos Pantousas, Georgios Aprilis, Alena Aslandukova, Ilya Kupenko, Xiang Li, Susanne Müller, Wenju Zhou, Pauline Leveque, Michael Hanfland, Leonid Dubrovinsky, Anna Pakhomova
{"title":"Tetrahedral frameworks and chains in oP32 CaC<sub>2</sub>O<sub>5</sub> and mP80 CaCO<sub>3</sub> calcium carbonates above 100 GPa.","authors":"Apostolos Pantousas, Georgios Aprilis, Alena Aslandukova, Ilya Kupenko, Xiang Li, Susanne Müller, Wenju Zhou, Pauline Leveque, Michael Hanfland, Leonid Dubrovinsky, Anna Pakhomova","doi":"10.1038/s42004-026-02041-3","DOIUrl":"https://doi.org/10.1038/s42004-026-02041-3","url":null,"abstract":"<p><p>Recent advances in the exploration of carbonates have established their high-pressure crystal chemistry as mainly based on carbon in the sp<sup>3</sup> configuration. Such carbonates, built upon isolated or vertex-sharing <math><msubsup><mrow><mi>CO</mi></mrow><mrow><mn>4</mn></mrow><mrow><mn>4</mn><mo>-</mo></mrow></msubsup></math> tetrahedra, exhibit striking structural diversity. Despite extensive research, synthesis of layered or framework carbonates remained a long-standing challenge. Herein we report on the synthesis and full structural characterization of a novel carbonate, oP32 CaC<sub>2</sub>O<sub>5</sub> (Pna2<sub>1</sub>), obtained at 122 GPa and 2800 K in a laser-heated diamond anvil cell, with a structure based on a vertex-sharing tetrahedral framework. In addition, mP80 CaCO<sub>3</sub> (P2<sub>1</sub>/c) was obtained at the same conditions, featuring pyroxene-like chains of vertex-sharing tetrahedra. In contrast to previously reported CaCO<sub>3</sub> phases, we propose a novel racemic model based on both clockwise and counter-clockwise helical chirality of the chains. Ab initio calculations support experimental findings and indicate thermodynamic stability of oP32 CaC<sub>2</sub>O<sub>5</sub> and mP80 CaCO<sub>3</sub> in the megabar pressure range.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Konstantin Stracke, Connor W Edwards, Jack D Evans
{"title":"Evaluating mechanical property prediction across material classes using molecular dynamics simulations with universal machine-learned interatomic potentials.","authors":"Konstantin Stracke, Connor W Edwards, Jack D Evans","doi":"10.1038/s42004-026-02057-9","DOIUrl":"https://doi.org/10.1038/s42004-026-02057-9","url":null,"abstract":"<p><p>Simulating the mechanical and thermal properties of materials requires accurate treatment of interatomic interactions, yet quantum-mechanical methods can be computationally prohibitive for the time scales needed. Universal machine-learned interatomic potentials (MLIPs) offer a promising alternative, but their reliability for dynamics across diverse material classes remains largely untested. Here, we assess the accuracy of six universal MLIPs for predicting the temperature and pressure response of 13 diverse materials (nine metal-organic frameworks and four inorganic compounds), computing bulk modulus, thermal expansion, and thermal decomposition. These MLIPs employ three architectures (graph neural networks, graph network simulators, and graph transformers) with varying training datasets. We observe qualitative agreement with experiment, outperforming UFF4MOF, but also systematic underestimation of bulk modulus and overestimation of thermal expansion across all models, consistent with potential energy surface softening. From all tested models, three top performers arise; 'MACE-MP-0a', 'fairchem_OMAT', and 'Orb-v3', with average error across metrics and materials of 41%, 43%, and 43%, respectively. Beyond overall performance, dataset homogeneity and structural representation dominate model accuracy, while certain architectures can compensate for biases, a step closer to truly universal MLIPs.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147833771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jie Liu, Guodong Chen, Shengpeng He, Runjing Guan, Liang Gong, Yongfei Yang, Tao Zhang, Shuyu Sun
{"title":"Machine learning enabled molecular dynamics-Monte Carlo framework for nanoconfined fluid adsorption.","authors":"Jie Liu, Guodong Chen, Shengpeng He, Runjing Guan, Liang Gong, Yongfei Yang, Tao Zhang, Shuyu Sun","doi":"10.1038/s42004-026-02053-z","DOIUrl":"https://doi.org/10.1038/s42004-026-02053-z","url":null,"abstract":"<p><p>Nanoconfined fluid is central to many engineering applications such as shale energy production, carbon sequestration, and molecular separations. While classical molecular dynamics (MD) simulation provides essential atomistic detail, its prohibitive computational cost severely limits accessible time and length scales. Hybrid MD-Monte Carlo (MDMC) methods accelerate sampling but lack generality beyond their trained conditions. In this work, we introduce an AI-assisted MDMC framework that overcomes this limitation by learning local, conditional transition statistics directly from MD trajectories. Our method encodes molecular motion into a compact set of neural network-predicted displacement actions, preserving MD-level accuracy within a drastically reduced dimensionality. This approach enables efficient sampling with robust generality. We systematically demonstrate the framework's accuracy and transferability across diverse thermodynamic conditions (temperature, pressure), spatial scales, and complex nano-scale geometries, establishing a versatile path for simulating confined fluid phenomena relevant to engineering applications.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kerry Y Kao, Matthew Carter Childers, Divya Pathak, Rama Reddy Goluguri, Timothy S McMillen, Joseph D Powers, Kathleen M Ruppel, James A Spudich, Michael Regnier
{"title":"The hypertrophic cardiomyopathy myosin variant G256E prolongs cardiac muscle relaxation via altered nucleotide handling.","authors":"Kerry Y Kao, Matthew Carter Childers, Divya Pathak, Rama Reddy Goluguri, Timothy S McMillen, Joseph D Powers, Kathleen M Ruppel, James A Spudich, Michael Regnier","doi":"10.1038/s42004-026-02048-w","DOIUrl":"https://doi.org/10.1038/s42004-026-02048-w","url":null,"abstract":"<p><p>Mutations in myosin alter its motor functions in diverse ways by affecting different structural and chemo-mechanical events. Multidisciplinary strategies can be used to understand how varying alterations in motor function converge to common phenotypes like hypercontractility and hypertrophic cardiomyopathy (HCM). We combined molecular dynamics (MD) simulations with protein biochemical and myofibril mechanical analyses to study the HCM-causing myosin variant G256E. MD simulations demonstrated that G256E induces structural changes that increase the work required to displace ADP.Mg<sup>2+</sup> from actomyosin. Stopped-flow biochemical analysis demonstrated increased ADP affinity and decreased ADP release rate, and single myofibril mechanics analysis demonstrated increased force generation and reduced ADP sensitivity of the early, slow phase of relaxation. Together, these results demonstrate that slower ADP release from myosin during contraction is a significant contributor to pathological contractile nature of the G256E mutation. This study highlights the importance of detailed chemo-mechanical analysis of mutations associated with hereditary cardiac diseases.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alessandro Agostini, Eduard Elias, Niccolò Cianfarani, Tim J Dalebout, Donatella Carbonera, Roberta Croce
{"title":"A design principle for tuning far-red absorption of chlorophyll a in light-harvesting complexes.","authors":"Alessandro Agostini, Eduard Elias, Niccolò Cianfarani, Tim J Dalebout, Donatella Carbonera, Roberta Croce","doi":"10.1038/s42004-026-02052-0","DOIUrl":"https://doi.org/10.1038/s42004-026-02052-0","url":null,"abstract":"<p><p>Far-red absorption in eukaryotic light-harvesting complexes (LHCs) has been associated with strongly excitonically coupled chlorophyll a clusters exhibiting mixing with charge-transfer states, yet the structural rules enabling this spectral tuning remain unclear. Previous studies have highlighted the importance of the amino acid ligating Chl a603 in providing the pigment orientation required for the formation of a red-shifted Chl a603-a609 cluster. More recently, it has been suggested that the steric properties of the residue at the i-4 position from the ligand may also play a crucial role.Here, we test this hypothesis through targeted mutagenesis of two light-harvesting complexes, Lhca4 and CP29, which host the Chl a603-a609 pair, but differ in their protein environment and spectral properties. In Lhca4, introduction of steric constraints at the i-4 position relative to the Chl a603 ligand (A43L) abolishes far-red absorption, indicating that steric crowding at this position destabilizes the strongly coupled pigment configuration. In CP29, substitution of the Chl a603 ligand (H111N) is required for far-red absorption, while the additional mutation at i-4 position (H111N/C107A) modulates the magnitude of the red-shift. Together these results highlight the importance of both axial ligand identity and local protein environment in controlling far-red absorption in Chl a clusters.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147834632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasunori Minami, Shunsuke Tsuyuki, Ryota Watanabe, Nobuyasu Itoh, Masaru Yoshida
{"title":"Amination-degradation of super engineering plastics for the construction of surface emissive resin materials.","authors":"Yasunori Minami, Shunsuke Tsuyuki, Ryota Watanabe, Nobuyasu Itoh, Masaru Yoshida","doi":"10.1038/s42004-026-02051-1","DOIUrl":"https://doi.org/10.1038/s42004-026-02051-1","url":null,"abstract":"<p><p>The advent of effective use of carbon resources has demanded for the future society. This importance is evident from the recent evolution of the \"R\" framework such as \"10 R\" including \"Repurpose\". In this context, super engineering plastics such as polyetheretherketone (PEEK) are considered as promising plastic materials because they can be used as monomaterials, i.e., without additives, by virtue of their high stability, which also renders them suitable to be converted to functionalized recyclable plastics. Herein, we report a degradation methodology for PEEK and polysulfone (PSU) resins using aza-aromatic compounds such as phenothiazine. This amination-degradation reaction cleaves the polymer main chains to form donor-acceptor-donor-type molecules, which allow functionalizing only the resin surface to produce luminescent PEEK powder and plates. These surface-functionalized PEEK materials maintain high thermal stability and are applicable as photoredox catalysts, demonstrating the \"Repurpose\" of PEEK into value-added products.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147811762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kirklin L McWhorter, Benjamin D Dratch, Brandon M Colella, Katherine M Davis
{"title":"Expanding the paradigm of glycopeptide antibiotic recognition through molecular dynamics simulations.","authors":"Kirklin L McWhorter, Benjamin D Dratch, Brandon M Colella, Katherine M Davis","doi":"10.1038/s42004-026-02040-4","DOIUrl":"https://doi.org/10.1038/s42004-026-02040-4","url":null,"abstract":"<p><p>Glycopeptide antibiotics (GPAs) canonically bind the terminus of peptidoglycan precursors. However, recent work suggests they can engage other targets. Keratinicyclin B (KCB), for example, is believed to bind the wall teichoic acid polysaccharide II (PSII). Although GPA-peptidoglycan interactions are well studied, the molecular determinants of KCB specificity remain unclear. Herein, we employ molecular dynamics and free-energy analysis to probe how scaffold variations, glycosylation patterns, and functional group modifications govern GPA recognition of canonical (peptidoglycan) and noncanonical (PSII) ligands. Our results demonstrate that features beyond the characteristic hydrogen bonding network, including steric preorganization, electrostatics, and binding site solvation, collectively shape the energetic landscape. Simulations of KCB-PSII variants reveal a layered recognition strategy in which PSII is stabilized by a secondary interface when the primary interface is disrupted. Together, these findings expand the paradigm of GPA recognition and provide a mechanistic framework for designing next-generation antibiotics.</p>","PeriodicalId":10529,"journal":{"name":"Communications Chemistry","volume":" ","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147811787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}