Improved QSAR models for PARP-1 inhibition using data balancing, interpretable machine learning, and matched molecular pair analysis.

The poly (ADP-ribose) polymerase-1 (PARP-1) enzyme is an important target in the treatment of breast cancer. Currently, treatment options include the drugs Olaparib, Niraparib, Rucaparib, and Talazoparib; however, these drugs can cause severe side effects including hematological toxicity and cardiotoxicity. Although in silico models for the prediction of PARP-1 activity have been developed, the drawbacks of these models include low specificity, a narrow applicability domain, and a lack of interpretability. To address these issues, a comprehensive machine learning (ML)-based quantitative structure-activity relationship (QSAR) approach for the informed prediction of PARP-1 activity is presented. Classification models built using the Synthetic Minority Oversampling Technique (SMOTE) for data balancing gave robust and predictive models based on the K-nearest neighbor algorithm (accuracy 0.86, sensitivity 0.88, specificity 0.80). Regression models were built on structurally congeneric datasets, with the models for the phthalazinone class and fused cyclic compounds giving the best performance. In accordance with the Organization for Economic Cooperation and Development (OECD) guidelines, a mechanistic interpretation is proposed using the Shapley Additive Explanations (SHAP) to identify the important topological features to differentiate between PARP-1 actives and inactives. Moreover, an analysis of the PARP-1 dataset revealed the prevalence of activity cliffs, which possibly negatively impacts the model's predictive performance. Finally, a set of chemical transformation rules were extracted using the matched molecular pair analysis (MMPA) which provided mechanistic insights and can guide medicinal chemists in the design of novel PARP-1 inhibitors.

An overview of compound properties, multiparameter optimization, and computational drug design methods for PARP-1 inhibitor drugs.

Breast cancer treatment with PARP-1 inhibitors remains challenging due to emerging toxicities, drug resistance, and unaffordable costs of treatment options. How do we invent strategies to design better anti-cancer drugs? A part of the answer is in optimized compound properties, desirability functions, and modern computational drug design methods that drive selectivity and toxicity and have not been reviewed for PARP-1 inhibitors. Nonetheless, comparisons of these compound properties for PARP-1 inhibitors are not available in the literature. In this review, we analyze the physchem, PKPD space to identify inherent desirability functions characteristic of approved drugs that can be valuable for the design of better candidates. Recent literature utilizing ligand, structure-based drug design strategies and matched molecular pair analysis (MMPA) for the discovery of novel PARP-1 inhibitors are also reviewed. Thus, this perspective provides valuable insights into the medchem and multiparameter optimization of PARP-1 inhibitors that might be useful to other medicinal chemists.

Isolation of phytochemicals from Dolichandrone atrovirens followed by semisynthetic modification of ixoside via azomethine ylide cycloaddition; computational approach towards chemo-selection.

Aims of the study were the phytochemical investigation and chemical transformation of isolated compounds of medicinal plant listed in 'Ayurveda' like Dolichandrone atrovirens, endemic to Indian subcontinents. From chloroform extract of D. atrovirens four compounds; Ursolic acid (1), Maslinic acid (2), Lupeol (3), ß-sitosterol (4) and from methanol extract five compounds; ß-sitosterol-3-O-ß-D-glucopyranoside (5), 10-O-trans-p-Methoxycinnamoylcatalpol (6), Kaempferol-3-O-ß-D-glucopyranoside (7), 6-O-[6"(S)-hydroxy-2",6"dimethyl-2"(E)-7"-octadienoyl] catalpol (8) and Ixoside (9) were isolated. Ixoside was used for the semi-synthetic modification via azomethine ylide cycloaddition leading to novel spiro-oxindolo-pyrrolizidine adduct. The structures of novel adducts were elucidated by analysis of IR, MS and 1 D/2D NMR data. Furthermore, to confirm the chemo selection of only one double bond, we performed density functional theory (DFT) calculation, which confirms the chemo selectivity. In addition, in-silico ADME studies and atom-additive approach based on SASA was also examined for the molecules which suggest that they may be potential future candidates for drug discovery.

Analytical developments of p-hydroxy prenylamine reference material for dope control research: Characterization and purity assessment.

Prenylamine was initially used for the treatment of angina pectoris and later on withdrawn from the market in 1988 due to cardiac arrhythmias concern. The major phase I metabolite of prenylamine is p-hydroxy prenylamine that has a chiral center in the structure. Even though p-hydroxy prenylamine was synthesized earlier, it lacked complete analytical developments for chiral high-performance liquid chromatography (HPLC) separation. However, p-hydroxy prenylamine reference material is not commercially available. The innovation of this manuscript is the development and validation of a chiral HPLC separation method and more extensive characterization of the reference material than previously reported method. Therefore, it was hypothesized to develop and validate normal phase HPLC method for p-hydroxy prenylamine reference material. p-Hydroxy prenylamine was synthesized in two batches and characterized successfully using 13 C NMR, 1 H NMR, high-resolution mass spectrometry (HRMS), Fourier transform infrared spectroscopy (FT-IR), and thermogravimetric analysis (TGA). A normal phase chiral HPLC method was developed to analyze the p-hydroxy prenylamine purity. Separation of the p-hydroxy prenylamine enantiomers were achieved using ultra-high-performance liquid chromatography (UHPLC) on a ChiralCel ODH column at wavelength of 220 nm. The developed method was validated in terms of its linearity, accuracy, precision, and robustness for purification, purity assessment, and stability studies. Proton and carbon peaks were confirmed by nuclear magnetic resonance (NMR) analysis. Functional groups were confirmed by FT-IR. Loss on drying was 0.3% and 0.6% for Batches 1 and 2, respectively. The purity of the developed reference material for Batches 1 and 2 was found to be 99.59% and 100%, respectively. Therefore, the synthesized batches of p-hydroxy prenylamine can be used in dope testing as reference material.