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The mechanistic underpinnings of asymmetric catalysis at atomic levels provide shortcuts for developing the potential value of chiral catalysts beyond the current state-of-the-art. In the enantioselective redox transformations, the present intuition-driven studies require a systematic approach to support their intuitive idea. Arguably, the most systematic approach would be based on the reliable quantitative structure-selectivity relationship of diverse and dissimilar chiral scaffolds in an optimal feature space that is universally applied to reactions. Here, we introduce a predictive workflow for the extension of the reaction scope of chiral catalysts across name reactions. For this purpose, whole geometry descriptors were encoded from DFT optimized 3D structures of multiple catalyst scaffolds, 113 catalysts in 9 clusters. The molecular descriptors were verified by the statistical comparison of the enantioselective predictive classification models built from each descriptors of chiral iodoarenes. More notably, capturing the whole molecular geometry through one hot encoding of split three-dimensional molecular fingerprints presented reliable enantioselective predictive regression models for three different name reactions by recycling the data and metadata obtained across reactions. The potential use value of this workflow and the advantages of recyclability, compatibility, and generality proved that the workflow can be applied for name reactions other than the aforementioned name reactions (out of samples). Furthermore, for the consensus prediction of ensemble models, this global descriptor can be compared with sterimol parameters and noncovalent interaction vectors. This study is one case showing how to overcome the sparsity of experimental data in organic reactions, especially asymmetric catalysis., Comment: 73 pages, 27 figures, It described the enantioselective transformational potency of catalysts across reactions and introduced a predictive workflow to extend the reaction scope of chiral catalysts based on whole molecular geometry. Though the work is technically sound & well-presented, it is too focused on the enantioselective prediction of iodoarenes with favorable statistical performance

In the drug repurposing approach, the chemically diverse and potentially safe molecules can be explored as therapeutic potential out of those originally targeted indications. However, the intellectual property rights, and competitive over-heating issue from sharing the same drug pipeline information are drawback of the approach. In current paradigm of drug discovery, despite approval of new chemical entity, the finding of a new ring system for drug discovery have stagnated. In addition, there are still rarely used ring systems from FDA approved drug that can be optimized and used for repurposing purpose. In the present work, these rarely used drug ring system were re-purposed with our bidirectional target and ring screening (TR- dual screening) approach within our defined objectives. The TR-dual screening suggested RARbeta and cyproheptadine as a pair of target and ring system. The selected ring system was virtually grown with predefined criterion, ranking of molecular docking and top score poses made us select test compounds for synthesis and biological proof. Among the tested compounds, 6c proved RARbeta agonist activity. The concept of TR dual optimization can contribute to picking either a compound having acceptable ADMET profile or a target for a selected drug scaffold., Comment: 22 pages, 10 figures, peer-reviewing of the manuscript was refused even though submitted to a journal