Łukasz Szeleszczuk

Photostability is a critical determinant of the performance and safety of light-sensitive compounds, yet the effects of cyclodextrin (CD) complexation are often interpreted as uniformly protective. This review critically examines how native and modified CDs and CD-based supramolecular architectures influence photodegradation and other light-driven processes across pharmaceuticals, natural bioactives, vitamins, sunscreen filters, dyes, photosensitizers, and agrochemicals. Evidence from experimental studies is evaluated in relation to host–guest inclusion geometry, conformational restriction, aggregation, microenvironmental polarity, oxygen accessibility, and excited-state and radical pathways. Direct quantification of intact compounds by stability-indicating chromatography (e.g., HPLC/UPLC) is distinguished from indirect indicators such as spectral changes or retained functional activity. The literature reveals condition-dependent outcomes ranging from substantial photoprotection to negligible effects or accelerated photodegradation, potentially reflecting disruption of protective guest aggregates or differential shielding of hydrolysis- and photolysis-prone regions. We also discuss photoresponsive systems in which CD association is exploited to control, rather than suppress, photochemical reactions. Reliable assessment requires matched irradiation controls, characterized irradiation spectra and doses (using ICH Q1B benchmarks where applicable), and consideration of formulation effects. Overall, cyclodextrins emerge as context-dependent modulators of photochemical behavior, supporting a shift from empirical complexation toward mechanism-guided design of light-stable and photoactive systems.

Background/Objectives: Predicting blood–brain barrier (BBB) permeability from structure remains challenging. We evaluated whether graph neural networks (GNNs) improve experimental logBB prediction over descriptor-based machine learning and whether GNN attention agrees with earlier descriptor-based findings. Methods: Graph Convolutional Network (GCN) and Graph Attention Network (GAT) models were trained on 1058 B3DB compounds and compared with LightGBM using 209 RDKit 2D descriptors under identical random and Murcko scaffold splits. Analyses comprised a primary split, 10 repeated random and scaffold splits with nested hyperparameter optimization and paired tests, descriptor-augmented GNNs, classification, external evaluation on the Martins benchmark, and GAT attention analysis. Results and Discussion: In the primary split, LightGBM achieved the highest R² (random 0.673; scaffold 0.604) versus GCN (0.514; 0.133) and GAT (0.430; 0.310). Across repeated splits with nested hyperparameter optimization, LightGBM outperformed both GNNs under both protocols (paired t-test p < 0.001). GCN and GAT did not differ significantly under scaffold splitting in either the original repeated-split evaluation (p = 0.49) or the optimized comparison (p = 0.184). Descriptor augmentation improved both GNNs (p < 0.001); under scaffold splitting, augmented GCN (R² = 0.463 ± 0.084) was not significantly different from LightGBM (0.494 ± 0.093; p = 0.22). Using thresholded regression predictions, LightGBM had the highest mean AUC in every condition (≈0.87 versus 0.77–0.84). On 1627 compounds from the independently curated Martins benchmark, mean AUC was 0.84 (LightGBM), 0.83 (GCN) and 0.81 (GAT). GAT attention was higher on nitrogen/oxygen than carbon in 82 of 98 eligible molecules, but halogen, sulfur, and phosphorus atoms received even more attention. Conclusions: Under the evaluated conditions, 2D descriptors outperformed basic GCN and GAT models across splits; descriptor augmentation substantially narrowed the gap. GAT attention provides hypothesis-generating, not causal, insight.

This study retrospectively evaluates agreement between target-level molecular-modeling rankings from a previously published coumarin–pyrimidine library and an available cellular dataset for 14 experimentally evaluated compounds with documented structure assignments. Laboratory-reported MDA-MB-231 and MCF-10A IC₅₀ values from multi-concentration MTT testing were compared with published AutoDock Vina scores using rank-based analyses. Compound 5e had the lowest laboratory-reported MDA-MB-231 IC₅₀ (12.4 ± 0.2 µM; n = 2) and the largest descriptive selectivity index (7.75); this ratio is specific to the MDA-MB-231/MCF-10A comparison and is not interpreted as evidence of general tumor selectivity. Docking rankings showed weak correspondence with cellular potency, and no docking–phenotype association remained statistically significant after Benjamini–Hochberg adjustment. No basic 2D descriptor showed a compelling adjusted association. Complete ¹H/¹³C NMR and validated HRMS documentation, quantitative purity measurements, and the complete full-series MTT raw export are not available; structure-dependent and potency claims are therefore interpreted cautiously. Overall, the analysis demonstrates limited cross-endpoint transferability between target-level docking rankings and whole-cell activity in the MDA-MB-231/MCF-10A dataset, without establishing a validated structure–activity relationship, generalized TNBC activity, apoptosis induction, a BCL-2 mechanism, or translational efficacy.

The development of multifunctional hybrid electrode materials with high-performance energy storage and electrocatalytic activity is highly desirable for advanced energy technologies. Herein, a MIL-88A/NiCo₂O₄@N-CNT ternary composite was prepared through ultrasonic-assisted assembly of porous MIL-88A, redox-active NiCo₂O₄, and conductive nitrogen-doped carbon nanotubes (N-CNTs). The synergistic interaction among these components provides abundant active sites, improved electrolyte accessibility, and enhanced charge transfer pathways. An increase in the BET surface area was observed in the case of hybrid composite (176.43 m² g⁻¹), compared to MIL-88A (99.35 m² g⁻¹) and NiCo₂O₄ (145.52 m² g⁻¹). The electrode based on MIL-88A/NiCo₂O₄@N-CNT was obtained with a specific capacity of 2036 C g⁻¹ at 10 mV s⁻¹ and 2209 C g⁻¹ at 2.0 A g⁻¹ in a three-electrode cell system. The specific capacity for asymmetric supercapacitors with the MIL-88A/NiCo₂O₄@N-CNT//AC structure was found to be 412 C g⁻¹ from cyclic voltammetry (CV) and 432 C g⁻¹ from galvanostatic charge–discharge (GCD), and the energy density was 98.6 Wh kg⁻¹, and the power density was 1727 W kg⁻¹. The electrochemical stability was also confirmed, as after 10,000 charge–discharge cycles, the hybrid supercapacitor still maintained 87.66% capacity with a coulombic efficiency of 93.60%. Moreover, the fabricated material proved to be a suitable catalyst for the hydrogen evolution reaction (HER) process, showing low overpotential (98 mV at 10 mA cm⁻²), a Tafel slope of 46.20 mV dec⁻¹, and current retention of 95.3% after 20 h. This synergistic effect between the porous framework of MOF, multivalent active NiCo₂O₄ centers, and conducting N-CNT structure provides the above improved properties, which are effective in providing electrons.

An integrated computational workflow was developed to prioritize piperazinylanthranilamide factor Xa (FXa) inhibitor candidates. Twenty literature compounds were geometry-optimized and described using alvaDesc to construct a constrained additive multivariate adaptive regression splines model. Internal validation and an assessment of the applicability domain guided the evaluation of 20 prospective analogs. Ten selected analogs and two same-series references were docked to FXa, with apixaban as the crystallographic comparator. Thirteen initial 100 ns molecular dynamics simulations were supplemented by two independent runs for each of PAX-M09, PAX-M15, and PAX-M18. Binding energetics were assessed using molecular mechanics/generalized Born surface area (MM/GBSA), alongside in silico developability profiling. The model achieved R² = 0.904 and an internal leave-one-out Q² of 0.846. PAX-M09 was the strongest strict in-domain prediction, whereas PAX-M15 was borderline. Apixaban redocking yielded a root-mean-square deviation (RMSD) of 0.953 Å. Although PAX-M17 and PAX-M19 ranked highest in docking, subsequent analyses prioritized PAX-M15, PAX-M09, and PAX-M18. PAX-M15 showed the most consistent positional behavior across replicates and consistently favorable run-specific MM/GBSA estimates (−68.76, −70.11, and −69.42 kcal/mol). PAX-M09 and PAX-M18 showed greater between-run heterogeneity. Solubility, metabolic, and toxicity liabilities remained important. The results support experimental investigation of the three candidates without changing their applicability-domain classifications or establishing superior experimental potency.

Crystalline chlorobenzofuroxan (ClBF) exhibits persistent positional isomeric disorder, with 5-ClBF and 6-ClBF sharing the same crystallographic sites. Periodic density functional theory was used to investigate the associated configurational energetics and solid-state interconversion pathways. All 256 starting arrangements constructed from four local models—5-ClBF, 6-ClBF, and two atom-mapped representations of the same open-dinitroso structural model—over four molecular sites were optimized at fixed experimental lattice parameters. Among the 254 structures retaining the predefined molecular connectivity, the fully 5-ClBF configuration had the lowest electronic energy. Mixed cyclic configurations remained comparatively low in energy and showed non-additive, arrangement-dependent energy penalties. Ring-opened configurations and an alternative ordered model containing four-membered N–O–N–O rings were substantially less favorable. Eight representative one-site transformations yielded non-spin-polarized electronic barrier estimates of 170.1–217.7 kJ mol⁻¹, compared with 745.5 kJ mol⁻¹ for the investigated four-molecule transformation, for the complete four-molecule crystallographic unit cell. Three sequential branches differed in their intermediate barrier estimates but reached the same maximum electronic-energy level within the investigated model. The separation between modest configurational energy differences and substantially larger barrier estimates is consistent with kinetically hindered redistribution after a mixed isomeric population has been incorporated into the crystal, without quantitatively predicting the experimental populations or their origin.

The encapsulation of a single water molecule inside C₆₀ has established H₂O@C₆₀ as a benchmark system for investigating molecular behavior under precisely defined subnanometer confinement. This review integrates advances in the synthesis, experimental characterization, theoretical description, and emerging applications of H₂O@C₆₀ and selected related water-containing fullerenes. Particular attention is given to molecular-surgery strategies, in which the fullerene cage is opened, loaded with water, and subsequently reconstructed, as well as to improvements that have increased encapsulation and cage-closure efficiencies and enabled isotopically labeled and heterofullerene derivatives. Structural, nuclear magnetic resonance, infrared, terahertz, neutron-scattering, dielectric, photoelectron, and single-molecule transport studies collectively show that the C₆₀ framework remains highly rigid, while the confined water molecule retains pronounced translational, rotational, vibrational, and nuclear-spin dynamics. At the same time, weak but measurable host–guest interactions produce symmetry breaking, rotational-level splitting, electrostatic screening, modified vibrational responses, and environment-dependent ortho–para conversion. Computational studies, ranging from density functional and correlated wave-function methods to multidimensional quantum-dynamical and molecular-dynamics approaches, have been essential for interpreting these observations and defining the underlying potential-energy landscape. Related systems, including H₂O@C₇₀, H₂O@C₅₉N, charged azafullerenes, and isotopically substituted endofullerenes, provide routes to tune cage geometry and electrostatic interactions. Although technological applications remain largely at the proof-of-principle stage, these systems offer promising platforms for quantum spectroscopy, molecular electronics, and the rational design of functional host–guest nanomaterials.

Tuberculosis remains a major global health burden, highlighting the urgent need for new therapeutic agents with improved efficacy and safety. In this study, a series of vanillin-derived biphenyl ether analogues inspired by the nimesulide scaffold was designed and synthesized as multifunctional candidates targeting tuberculosis-associated pathologies. The compounds were prepared via Schiff base formation followed by microwave-assisted Ullmann coupling and were structurally confirmed by FTIR, NMR, and mass spectrometry. In silico evaluation revealed favorable physicochemical and ADME profiles, supporting drug-likeness. Molecular docking against enoyl-acyl carrier protein reductase (InhA, PDB ID: 1P44) demonstrated strong binding affinities, with analogue 3e exhibiting the most favorable docking score (−8.8 kcal/mol). In vitro antitubercular assays showed that compound 3e maintained activity across the full concentration range tested (0.8–100 µg/mL), while compounds 3a and 3c remained active at concentrations where isoniazid was ineffective and compounds 4b and 4d displayed comparable potency to the reference drug. Anti-inflammatory and antioxidant evaluations further identified compounds with pronounced activity, notably compounds 4a, 3b, 4b, and 4d. Overall, these findings indicate that vanillin-based biphenyl ethers—particularly compound 3e—represent promising multifunctional scaffolds for further optimization and preclinical development as next-generation antitubercular agents.

Molecular docking is widely used to predict cyclodextrin host–guest structures, yet its ability to reproduce the directional orientation of asymmetric guests within the β-cyclodextrin (β-CD) cavity has rarely been evaluated systematically. Here, 20 crystallographically characterized 1:1 β-CD complexes containing asymmetric 1,4-disubstituted benzene guests were selected from the Cambridge Structural Database. Each guest was docked into each of 20 experimentally derived β-CD conformations, yielding 7916 retained poses. Poses reproducing the crystallographic direction of inclusion were classified as Up, whereas the opposite orientation was classified as Down. Across the complete dataset, approximately 26% of poses were Up, with guest-dependent frequencies ranging from 5% to 83%. Importantly, only one β-CD conformation generated Up poses for all 20 guests, whereas the complete receptor set sampled at least one crystal-consistent pose for every compound. However, GlideScore-based orientation recovery was 65% for Top-1, 95% for Top-2, and 100% for Top-3, demonstrating that successful sampling does not necessarily ensure correct top-ranked prediction. Selected poses were subsequently optimized using dispersion-corrected DFT. DFT-based energetic ranking did not consistently favour the crystallographic orientation and could either decrease or increase guest heavy-atom RMSD. Overall, the results demonstrate that reliable validation of β-CD docking requires explicit separation of pose generation, pose ranking, energetic refinement, and structural similarity, and support the use of structurally diverse crystal-derived receptor sets to broaden orientational sampling.