Taking a Respite from Representation Learning for Molecular Property Prediction

Artificial intelligence (AI) has been widely applied in drug discovery with a major task as molecular property prediction. Despite the boom of AI techniques in molecular representation learning, some key aspects underlying molecular property prediction haven't been carefully examined yet. In this study, we conducted a systematic comparison on three representative models, random forest, MolBERT and GROVER, which utilize three major molecular representations, extended-connectivity fingerprints, SMILES strings and molecular graphs, respectively. Notably, MolBERT and GROVER, are pretrained on large-scale unlabelled molecule corpuses in a self-supervised manner. In addition to the commonly used MoleculeNet benchmark datasets, we also assembled a suite of opioids-related datasets for downstream prediction evaluation. We first conducted dataset profiling on label distribution and structural analyses; we also examined the activity cliffs issue in the opioids-related datasets. Then, we trained 4,320 predictive models and evaluated the usefulness of the learned representations. Furthermore, we explored into the model evaluation by studying the effect of statistical tests, evaluation metrics and task settings. Finally, we dissected the chemical space generalization into inter-scaffold and intra-scaffold generalization and measured prediction performance to evaluate model generalizbility under both settings. By taking this respite, we reflected on the key aspects underlying molecular property prediction, the awareness of which can, hopefully, bring better AI techniques in this field

Drug Targeting Mini-Symposium of the Division for Medicinal Chemistry (DMC) of the Swiss Chemical Society (SCS), at the Department of Chemistry, University of Basel, May 29, 2008: Conference Report

Specific targeting of drugs to their respective target organs or tissues is challenging. Substantial research efforts have been undertaken in the recent past to develop target specific drugs or drug conjugates. Such concepts are most relevant in rather severe diseases like cancer since it helps to reduce the concentration of frequently rather toxic drugs outside the tumor tissue. Various techniques can be used to specifically direct a drug or a drug conjugate to a specific tumor tissue such as using antibodies directed against tumor specific proteins, as nanoparticles or nano-sized polymer conjugates carrying tumor-specific recognition elements or by applying the active drug principle in a prodrug form designed to be liberated specifically in tumor tissue. Three speakers from the academia and one speaker from industry described different approaches and their respective potentials from various perspectives in the lectures entitled: 'Polymer Therapeutics and other Nanomedicines as Targetable Cancer Therapies', 'Design, Application, and Chemical Biology of Tumor-Targeting Drug Conjugates', 'Antibody-Based Vascular Tumor Targeting: From the Bench to the Clinic', and 'Discovery of Capecitabine, a Rationally Designed and Tumor-Activated Oral Prodrug of 5-FU, and Beyond'

Prostate Cancer Stem Cell-Targeted Efficacy of a New-Generation Taxoid, SBT-1214 and Novel Polyenolic Zinc-Binding Curcuminoid, CMC2.24

Background Prostate cancer is the second leading cause of cancer death among men. Multiple evidence suggests that a population of tumor-initiating, or cancer stem cells (CSCs) is responsible for cancer development and exceptional drug resistance, representing a highly important therapeutic target. The present study evaluated CSC-specific alterations induced by new-generation taxoid SBT-1214 and a novel polyenolic zinc-binding curcuminoid, CMC2.24, in prostate CSCs. Principal Findings The CD133high/CD44high phenotype was isolated from spontaneously immortalized patient-derived PPT2 cells and highly metastatic PC3MM2 cells. Weekly treatment of the NOD/SCID mice bearing PPT2- and PC3MM3-induced tumors with the SBT-1214 led to dramatic suppression of tumor growth. Four of six PPT2 and 3 of 6 PC3MM2 tumors have shown the absence of viable cells in residual tumors. In vitro, SBT-1214 (100nM-1µM; for 72 hr) induced about 60% cell death in CD133high/CD44+/high cells cultured on collagen I in stem cell medium (in contrast, the same doses of paclitaxel increased proliferation of these cells). The cytotoxic effects were increased when SBT-1214 was combined with the CMC2.24. A stem cell-specific PCR array assay revealed that this drug combination mediated massive inhibition of multiple constitutively up-regulated stem cell-related genes, including key pluripotency transcription factors. Importantly, this drug combination induced expression of p21 and p53, which were absent in CD133high/CD44high cells. Viable cells that survived this treatment regimen were no longer able to induce secondary spheroids, exhibited significant morphological abnormalities and died in 2-5 days. Conclusions We report here that the SBT-1214 alone, or in combination with CMC2.24, possesses significant activity against prostate CD133high/CD44+/high tumor-initiating cells. This drug combination efficiently inhibits expression of the majority of stem cell-related genes and pluripotency transcription factors. In addition, it induces a previously absent expression of p21 and p53 (“gene wake-up”), which can potentially reverse drug resistance by increasing sensitivity to anti-cancer drugs

Inhibition of Fatty Acid Binding Proteins Elevates Brain Anandamide Levels and Produces Analgesia

The endocannabinoid anandamide (AEA) is an antinociceptive lipid that is inactivated through cellular uptake and subsequent catabolism by fatty acid amide hydrolase (FAAH). Fatty acid binding proteins (FABPs) are intracellular carriers that deliver AEA and related N-acylethanolamines (NAEs) to FAAH for hydrolysis. The mammalian brain expresses three FABP subtypes: FABP3, FABP5, and FABP7. Recent work from our group has revealed that pharmacological inhibition of FABPs reduces inflammatory pain in mice. The goal of the current work was to explore the effects of FABP inhibition upon nociception in diverse models of pain. We developed inhibitors with differential affinities for FABPs to elucidate the subtype(s) that contributes to the antinociceptive effects of FABP inhibitors. Inhibition of FABPs reduced nociception associated with inflammatory, visceral, and neuropathic pain. The antinociceptive effects of FABP inhibitors mirrored their affinities for FABP5, while binding to FABP3 and FABP7 was not a predictor of in vivo efficacy. The antinociceptive effects of FABP inhibitors were mediated by cannabinoid receptor 1 (CB1) and peroxisome proliferator-activated receptor alpha (PPARα) and FABP inhibition elevated brain levels of AEA, providing the first direct evidence that FABPs regulate brain endocannabinoid tone. These results highlight FABPs as novel targets for the development of analgesic and anti-inflammatory therapeutics

Catalytic asymmetric synthesis

xiv, 864 p. : ill. ; 25 cm