Aprotinin (APR) was discovered in 1930. APR is an effective pan-protease inhibitor, a typical “magic shotgun”. Until 2007, APR was widely used as an antithrombotic and anti-inflammatory drug in cardiac and noncardiac surgeries for reduction of bleeding and thus limiting the need for blood transfusion. The ability of APR to inhibit proteolytic activation of some viruses leads to its use as an antiviral drug for the prevention and treatment of acute respiratory virus infections. However, due to incompetent interpretation of several clinical trials followed by incredible controversy in the literature, the usage of APR was nearly stopped for a decade worldwide. In 2015–2020, after re-analysis of these clinical trials’ data the restrictions in APR usage were lifted worldwide. This review discusses antiviral mechanisms of APR action and summarizes current knowledge and prospective regarding the use of APR treatment for diseases caused by RNA-containing viruses, including influenza and SARS-CoV-2 viruses, or as a part of combination antiviral treatment.

In the realm of predictive toxicology for small molecules, the applicability domain of QSAR models is often limited by the coverage of the chemical space in the training set. Consequently, classical models fail to provide reliable predictions for wide classes of molecules. However, the emergence of innovative data collection methods such as intensive hackathons have promise to quickly expand the available chemical space for model construction. Combined with algorithmic refinement methods, these tools can address the challenges of toxicity prediction, enhancing both the robustness and applicability of the corresponding models. This study aimed to investigate the roles of gradient boosting and strategic data aggregation in enhancing the predictivity ability of models for the toxicity of small organic molecules. We focused on evaluating the impact of incorporating fragment features and expanding the chemical space, facilitated by a comprehensive dataset procured in an open hackathon. We used gradient boosting techniques, accounting for critical features such as the structural fragments or functional groups often associated with manifestations of toxicity.

Galvanic displacement of electrodeposited lead by palladium fails to produce Pd shells. The anomalous ratio between formic acid electrooxidation reaction (FAOR) rates on Pd⁰(Pb) observed in HClO₄ and H₂SO₄ solutions is associated with the reduction of ClO₄⁻ anions to chloride ones which inhibit the FAOR.

Selective inhibition of poly(ADP-ribose) polymerase 1 (PARP1) may reduce the hematologic toxicity associated with dual PARP1/PARP2 inhibition. We performed molecular dynamics simulations for five selective inhibitors in complexes with PARP1 and PARP2, using three independent 50 ns runs per complex after docking and equilibration, followed by protein–ligand interaction fingerprint and statistical analyses. All complexes remained dynamically stable, with ligand root-mean-square deviation values generally within 0.3 nm. Comparative analysis identified three αF-helix residue pairs with nominally reduced interaction frequencies in PARP2: Asn767/Ala336, Leu769/Gly338, and Asp770/Asp339 (p < 0.05). After Benjamini–Hochberg correction for multiple comparisons, Leu769/Gly338 remained significant (q < 0.05), indicating that this pair represents the most statistically robust interaction difference within this region. Using palacaparib as the most selective inhibitor, these differences were associated with weakened or lost hydrophobic, van der Waals, and cation–π interactions in PARP2. Selective binding of modern PARP1 inhibitors appears to be associated with αF-helix-dependent interaction patterns, providing a mechanistic basis for the rational design of next-generation selective inhibitors with improved selectivity and potentially reduced toxicity.