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Propellane-Free Access to Bicyclo[1.1.1]pentanes
No full textBicyclo[1.1.1]pentane (BCP) has emerged as a valuable three-dimensional bioisostere of benzene, attracting considerable interest from the pharmaceutical industry due to its potential to enhance drug-like properties. While [1.1.1]propellane has traditionally served as the key precursor to mono- and 1,3-di-substituted BCPs, the rising demand for multisubstituted and bridge-functionalized BCP derivatives has driven the development of alternative, propellane-free synthetic strategies. To access such strain and hindered system, recent advances in this area can be broadly classified into three mechanistic categories: (1) intramolecular diradical couplings, (2) carbene-mediated ring expansions, and (3) 2-electron polar disconnections. This perspective highlights these emerging methodologies, critically examining their scope and limitations, and provides an outlook on the synthetic challenges and their potential impact in medicinal chemistry
Machine learning, docking, or physics for structure prediction of ligand-induced ternary complexes.
No full textProteolysis-targeting chimeras (PROTACs) and molecular glues promote targeted protein degradation by recruiting an E3 ligase to proteins of interest (POIs). An accurate 3D structure of the ternary complex formed by E3 ligase, ligand, and POI is central to the rational design of degraders. Elucidating this structure with crystallography or cryo-EM can be challenging due to conformational flexibility, dynamic protein-protein interactions, and high-dimensional binding landscapes. To facilitate structure-based design in the absence of an experimental structure, computational approaches have been proposed: (i) multistep methods involving traditional docking pipelines, and (ii) single-step methods with deep learning models to directly predict the complex structure. Multistep methods are limited by sampling complexity, accurate input structures, scoring accuracy, and computational cost, while single-step methods are faster but are constrained by training-data scarcity. Here, we examine recent advances and emerging tools in modeling ternary complexes, critically discuss their predictive power and limitations, and highlight remaining challenges
Metadata Assessment of Preclinical Non-Human Primate Studies of AAV9 Uncovers Potential Tissue Specific Variation in Expression Efficiency
No full textAdeno-associated virus (AAV)-based gene therapies have garnered significant attention and investment in recent years due to their clinical success and their potential to address underlying causes of many diseases. These AAV vectors can provide effective delivery of therapeutic genetic material to disease relevant tissues. When evaluating safety and efficacy of recombinant AAV vectors, the biodistribution profile plays a critical role in novel therapy development. Herein, a biodistribution metadata analysis was performed on eight preclinical studies involving 49 cynomolgus macaques (Macaca fascicularis). The macaques were administered a self-complementary or single-stranded AAV9 capsid vector containing chicken ß-actin (CBA) or cytomegalovirus (CMV173) promoters expressing fluorescent reporters or a human SMN1 gene. These studies cover various routes of administration (ROA) including intravenous (IV), intracisternal magna (ICM), and lumbar puncture intrathecal (IT) injection. Through metadata analysis of AAV9 biodistribution we show relatively uniform vector genome delivery throughout spinal cord tissues over multiple timepoints and ROA. In addition, distinct trends emerge that showcase decreased expression efficiency of viral DNA in liver regardless of the ROA, NHP age, or viral constructs used. To understand the observed difference in transcriptional productivity in liver versus other tissues, epigenetic profiling of tissue-localized AAV9 vector genome DNA was performed. Experimental evidence supports potential partial silencing/repression of transgene expression in liver. These findings point to plausible strategies to consider in preclinical development of AAV9 mediated gene therapies
Uncertainty Quantification in Molecular Machine Learning for Property Predictions under Data Shifts.
No full textDrug discovery and medicinal chemistry efforts are increasingly influenced by machine learning (ML), with compound property prediction as a central application. ML models have demonstrated strong performance in predicting various compound properties from chemical structure. However, these models can exhibit varying levels of prediction error, making uncertainty quantification (UQ) essential for informed decisions. Standard UQ metrics include the distance to the molecules in the training set and prediction variance, obtained through methods such as model ensembles or Bayesian modeling. Although several UQ methodologies have been developed in recent years, no single approach consistently outperformed others. Herein, we present a comprehensive benchmark of UQ strategies for ML-based prediction of absorption, distribution, metabolism, and excretion (ADME) properties, using both in-house and public data sets. We employed the recently introduced UNIQUE (UNcertaInty QUantification bEnchmarking) framework and evaluated UQ method performance under data shifts. Our findings indicate data-based UQ metrics (e.g., chemical distance), and model-based UQ metrics (e.g., predicted value and variance) may capture complementary aspects of uncertainty. Their combination through error models, designed to predict the original ML model's error, yielded higher-quality uncertainty estimates. These error models emerged as a promising strategy for enhancing UQ, showing robustness in under various degrees and types of data shift. Taken together, our work highlights the potential of combining diverse UQ metrics and error modeling to improve reliability in molecular property prediction. By establishing standardized evaluation setups and assessing UQ under data shifts, we provide a foundation for future UQ method development and benchmarking in the field
Characterization of VitE-TPGS Micelles linked to Poorly Soluble Compounds for Pharmaceutical Applications exploiting the Pair Distribution Function’s Moments
No full textno final abstract yet.
Draft:
We introduce an innovative theoretical framework tailored for the analysis of Pair Distri�bution Function (PDF) data derived from Small-Angle X-ray Scattering (SAXS) measurements of
core-shell micelles. The new approach involves the exploitation of the first derivative of the PDF and
the derivation of analytical equations to solve the core-shell micelle structure under the hypothesis
of a spheroidal shape. These analytical equations enable us to determine the micelle’s aggregation
number, degree of ellipticity, and contrast in electron density between the core-shell and shell-buffer
regions after having determined the whole micelle size and its shell size from the analysis of the first
derivative of the PDF
Metadata assessment of non-human primate studies of AAV9 uncovers potential tissue specific variation in expression efficiency.
No full textAdeno-associated virus (AAV)-based gene therapies have garnered significant attention and investment due to their clinical success and potential to address underlying causes of many diseases. AAV vectors provide effective delivery of therapeutic genetic material to disease-relevant tissues. When evaluating safety and efficacy of recombinant AAV vectors, biodistribution profiles play a critical role in novel therapy development. Herein, a biodistribution metadata analysis was performed on ten studies involving 51 cynomolgus macaques (Macaca fascicularis). The macaques received a self-complementary or single-stranded AAV9 vector containing chicken ß-actin (CBA) or cytomegalovirus (CMV173) promoters expressing fluorescent reporters or a human SMN1 gene. These studies covered various routes of administration (ROA) including intravenous (IV), intracisternal magna (ICM), and lumbar puncture intrathecal (IT) injection. Metadata analysis of AAV9 biodistribution showed relatively uniform vector genome delivery throughout spinal cord tissues over multiple timepoints and ROAs. Moreover, decreased expression efficiency of viral DNA in liver was observed regardless of the ROA, macaque age, or viral construct used. To understand this trend, epigenetic profiling of tissue-localized AAV9 vector genome DNA was performed. Experimental evidence supports partial silencing and repression of transgene expression in macaque liver. These findings point to plausible strategies to consider in preclinical development of AAV9 mediated gene therapies
Editorial for "Associations Between Hippocampal Transverse Relaxation Time and Amyloid PET in Cognitively Normal Aging Adults".
No full textNo abstrac
Minute-scale Alkylation of Heteroarenes via Photo-Fenton Mechanism in Continuous Flow
No full textThe development of cost-effective, operationally simple, and rapid late-stage alkylation of heteroarenes is pivotal to both medicinal and process chemistry. Inspired by the facile hydroxyl radical (•OH) generation via Fenton chemistry broadly used in environmental wastewater remediation, we developed a visible-light photo-Fenton flow protocol that converts inexpensive H2O2 into •OH for downstream hydrogen atom transfer (HAT) with a ferrocenyl diphenylphosphine-oxide photocatalyst. The transient •OH executes selective C-H abstraction from unactivated alcohols, alkanes, ethers, and aldehydes, furnishing carbon-centered radicals that engage N-heteroarenes in Minisci coupling to give alkylated products in up to 93% yield. More importantly, continuous-flow intensification enabled minute-level synthesis, achieving a productivity of 8.6 mol/(h•L). Despite the aggressive nature of •OH as the HAT mediator, this method tolerates sensitive motifs and enables multigram-scale functionalization of biologically active compounds, including voriconazole and quinine, with <10 min residence time
Supplementary Information: Metadata Assessment of Preclinical Non-Human Primate Studies of AAV9 Uncovers Potential Tissue Specific Variation in Expression Efficiency
No full textAdeno-associated virus (AAV)-based gene therapies have garnered significant attention and investment in recent years due to their clinical success and their potential to address underlying causes of many diseases. When evaluating safety and efficacy of recombinant AAV vectors, the biodistribution profile plays a critical role in novel therapy development. Herein, a biodistribution metadata analysis was performed on eight preclinical studies involving 49 cynomolgus macaques (Macaca fascicularis). The macaques were administered a self-complementary or single-stranded AAV9 capsid vector containing chicken ß-actin (CBA) or cytomegalovirus (CMV173) promoters expressing fluorescent reporters or a human SMN1 gene. These studies cover various routes of administration (ROA) including intravenous (IV), intracisternal magna (ICM), and lumbar puncture intrathecal (IT) injection. Through metadata analysis of AAV9 biodistribution we show relatively uniform vector genome delivery throughout spinal cord tissues over multiple timepoints and ROA. In addition, distinct trends emerge showcasing decreased expression efficiency of viral DNA in liver regardless of the ROA, NHP age, or viral constructs used. Epigenetic evaluation of tissue-localized AAV9 vector genome DNA was performed. Experimental evidence supports potential partial silencing/repression of transgene expression in liver. These findings point to plausible strategies to consider in preclinical development of AAV9 mediated gene therapies
Discovery of EGT710, an Oral Nonpeptidomimetic Reversible Covalent SARS-CoV-2 Main Protease Inhibitor.
No full textThe coronavirus main protease (3CLpro, Mpro, nsp5) is a highly conserved cysteine protease unique to the Coronaviridae family, including SARS-CoV-2, and is a validated target for the treatment of COVID-19. Our efforts focused on the identification of a nonpeptidomimetic Mpro inhibitor, due to the potential for superior pharmacological properties. Herein, we report our efforts leveraging virtual screening and X-ray crystallography that enabled a structure-based drug design approach, leading to the discovery of series of quinazoline-2,4(1H,3H)-dione and oxoimidazolidine-4-carbonitrile compounds with potent inhibition of SARS-CoV-2 Mpro as well as other coronaviruses main proteases. Extensive lead optimization focusing on pharmacokinetic properties, developability, and breadth of activity across coronaviruses, led to the identification of EGT710. EGT710 demonstrates excellent potency against SARS-CoV-2 infection in a primary differentiated normal human bronchial epithelial (dNHBE) cellular assay, as well as a favorable pharmacology profile that supported advancement into preclinical and clinical studies