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Functional antitumor vaccine constructs are the basis for active tumor immunotherapy, which is useful in the treatment of many types of cancers. MUC1 is one key glycoprotein for targeting and designing new strategies for multicomponent vaccines. Two self-adjuvant tetravalent vaccine candidates were prepared by clustering four or eight PDTRP MUC1 core epitope sequences on calixarene scaffolds. In this work, the different activities of two molecules with calix[4]arene and calix[8]arene skeleton are rationalized. Quantum mechanics, docking, and molecular dynamics structural optimization were first carried out followed by metadynamics to calculate the energy profiles. Further insights were obtained by complementarity studies of molecular fields. The molecular modeling results are in strong agreement with the experimental immunogenicity data. In conclusion, the overall data shows that, in the designing of anticancer vaccines, scaffold flexibility has a pivotal role in obtaining a suitable electrostatic, hydrophobic, and steric complementarity with the biological target.
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http://dx.doi.org/10.1021/acs.jcim.9b00989 | DOI Listing |
Nano Lett
September 2025
School of Chemistry and Materials Science, Hunan Agricultural University, Changsha 410128, China.
Passivating detrimental defects is essential for improving perovskite solar cells (PSCs) performance. While hydrogen interstitials are often considered harmful, their role in defect passivation remains unclear. Using nonadiabatic molecular dynamics, we uncover a self-passivation mechanism between hydrogen (H) and bromine (Br) interstitials in all-inorganic CsPbBr perovskites.
View Article and Find Full Text PDFAutophagy
September 2025
Department of Biochemistry and Molecular Biology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Macroautophagy/autophagy is an evolutionarily conserved process through which cells degrade cytoplasmic substances via autophagosomes. During the initiation of autophagosome formation, the ULK/Atg1 complex serves as a scaffold that recruits and regulates downstream ATG/Atg proteins and ATG9/Atg9-containing vesicles. Despite the essential role of the ULK/Atg1 complex, its components have changed during evolution; the ULK complex in mammals consists of ULK1 (or ULK2), RB1CC1, ATG13, and ATG101, whereas the Atg1 complex in the yeast lacks Atg101 but instead has Atg29 and Atg31 along with Atg17.
View Article and Find Full Text PDFNano Lett
September 2025
Department of Physics, Columbia University, New York, New York 10027, United States.
Graphene-based photonic structures have emerged as fertile ground for the controlled manipulation of surface plasmon polaritons (SPPs), providing a two-dimensional platform with low optoelectronic losses. In principle, nanostructuring graphene can enable further confinement of nanolight─enhancing light-matter interactions in the form of SPP cavity modes. In this study, we engineer nanoscale plasmonic cavities composed of self-assembled C arrays on graphene.
View Article and Find Full Text PDFAnal Chem
September 2025
Institute of Biological Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria.
The discovery of solute precursors of crystalline materials, such as biominerals, recently challenged the classical nucleation theory (CNT). One emerging method for investigating these early-stage intermediates in solution is dissolution dynamic nuclear polarization (dDNP)-enhanced nuclear magnetic resonance (NMR) spectroscopy. Recent applications of dDNP to calcium carbonate (CaC) and calcium phosphate (CaP) mineralization have demonstrated the feasibility of identifying and tracing very early-stage prenucleation clusters (PNCs).
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Dipartimento di Chimica, Università di Pavia, Via Taramelli 12, Pavia 27100, Italy.
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' predictions. Indeed, we previously demonstrated that combining molecular dynamics (MD)-derived descriptors with ML models allows to effectively classify kinase ligands as allosteric or orthosteric.
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