Complex Molecules Research Articles

Retention of α-pinene oxidation products and nitro-aromatic compounds during riming

Abstract. Riming is an important growth process of graupel and hailstones in the mixed-phase zones of clouds, during which supercooled liquid droplets freeze on the surface of ice particles by contact. Compounds dissolved in the supercooled cloud droplets can remain in the ice or be released to the gas phase during freezing, which might play an important role in the vertical redistribution of these compounds in the atmosphere by convective cloud processes. This is important for estimating the availability of these compounds in the upper troposphere, where organic matter can promote new particle formation and growth. The amount of organic material remaining in the ice phase can be described by the retention coefficient. Experiments were performed in the Mainz vertical wind tunnel under dry and wet growth conditions (temperature from −12 to −3 °C and a liquid water content (LWC) of 0.9±0.2 g m−3 and 2.2±0.2 g m−3) as well as with different pH values (4 and 5.6) to obtain the retention coefficients of α-pinene oxidation products and nitro-aromatic compounds. For cis-pinic acid, cis-pinonic acid, and (−)-pinanediol, mean retention coefficients of 0.96±0.07, 0.92±0.11, and 0.98±0.08 were obtained. 4-Nitrophenol, 4-nitrocatechol, 2-nitrobenzoic acid, and 2-nitrophenol showed mean retention coefficients of 1.01±0.07, 1.01±0.14, 0.99±0.04, and 0.21±0.12. Only the retention coefficient of 2-nitrophenol showed a dependence on temperature, growth regime, and pH. This is in accordance with previous studies, which showed a dependence between the dimensionless effective Henry's law constant H* and the retention coefficient for inorganic and small organic molecules. Our results reveal that this correlation can also be applied to more complex organic molecules and that retention under these conditions is not a significant factor for molecules with H* below 103, while retention close to 1 can be expected for compounds with H* above 108.

Comprehensive molecular docking and molecular dynamics simulation study of unmodified and modified cyclodextrins: erlotinib inclusion complexes

ABSTRACT The goal of this study is to evaluate the effectiveness of cyclodextrins (CDs) in enhancing the stability and bioavailability of Erlotinib (Erl), while also minimising its side effects, in the treatment of metastatic pancreatic and lung cancers. Molecular docking and molecular dynamics (MD) simulations were employed to investigate the effectiveness of various pure CDs (Alpha, Beta, and Gamma Cyclodextrins) and modified CDs (hydroxypropyl, methyl, and amino Beta Cyclodextrins) in forming stable inclusion complexes (ICs) with Erl. Molecular docking results indicated that Erl displayed favourable binding affinities with all CDs, exhibiting the highest affinity with Gamma Cyclodextrin (GCD) due to its larger cavity, with a binding energy of −25.86 KJ/mol. MD simulations revealed a reduction in hydrogen bonds with solvent molecules in CD complexes compared to free CDs, indicating the successful inclusion of Erl into CD cavities. GCD exhibited the highest EVdw and ECoul values, indicating strong binding affinity and the ability to form more hydrogen bonds and Vdw interactions with Erl. In contrast, HPB displayed the lowest van der Waals and Coulomb interactions with Erl. Moreover, the HPB: Erl IC system demonstrated superior vdW and Coulomb interactions in Erl-Solvent, while the GCD: Erl complex exhibited the lowest overall Erl-SOL interactions.

Abstract A001: Navigating the future of therapeutic development: innovations in safety and efficacy through advanced research methodologies and nanotechnology

Abstract In recent years, the field of therapeutic development has experienced a significant paradigm shift driven by strategic scientific innovations that prioritize safety and efficacy in therapeutic agents. This paper explores the intersection of advanced research methodologies, novel material sciences, and biotechnological advancements that are revolutionizing the approach to drug formulation and delivery systems. The integration of precision medicine principles alongside cutting-edge technologies allows for the design of therapeutics that are not only effective in targeting specific diseases but are also engineered to minimize adverse effects associated with conventional therapies. One focal point of this exploration is the application of nanotechnology in drug delivery systems. By utilizing nanoparticles, researchers can enhance the bioavailability of therapeutic agents while reducing systemic toxicity. This targeted approach enables the delivery of higher concentrations of drugs to the affected areas, thereby maximizing therapeutic efficacy and minimizing side effects. Additionally, the paper highlights the role of computational modeling and simulations in predicting the interaction of therapeutic agents at the molecular level, facilitating the identification of safer compounds through virtual screening methods. Another significant aspect addressed in this paper is the development of biologics and biosimilars as safer alternatives to traditional synthetic drugs. The advancement of biomanufacturing processes has made it feasible to produce complex molecules with high specificity and reduced immunogenicity, paving the way for innovative therapies that cater to individual patient profiles. Furthermore, the strategic incorporation of pharmacogenomics in drug development allows for the customization of therapeutic agents, ensuring that treatment regimens are tailored to the genetic makeup of patients, which can drastically improve safety and treatment outcomes. The paper also discusses the regulatory landscape surrounding the introduction of these innovative therapeutic agents. It emphasizes the need for adaptive regulatory frameworks that keep pace with scientific advancements while ensuring patient safety and efficacy. Collaborative efforts between researchers, regulatory bodies, and pharmaceutical companies are essential to facilitate the translation of innovative therapies from the laboratory to clinical practice. In conclusion, this paper underscores the critical importance of strategic scientific innovations in the quest for safer therapeutic agents. By harnessing the potential of advanced technologies, researchers can develop therapeutics that not only meet the growing demand for efficacy but also uphold the highest standards of safety, ultimately improving patient care and health outcomes. The findings presented advocate for continued investment in research and collaboration across disciplines to drive future advancements in therapeutic development. Citation Format: Peter O. David. Navigating the future of therapeutic development: innovations in safety and efficacy through advanced research methodologies and nanotechnology. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr A001

Nickel‐catalyzed Reductive Hydrolysis of Nitriles to Alcohols

Nitriles are an abundant class of compounds that are widely used as versatile feedstocks to produce various chemicals including pharmaceuticals, and agrochemicals as well as materials. Here we report Ni‐catalyzed reductive hydrolysis of nitriles to alcohols in the presence of molecular hydrogen. This conversion likely occurs in a domino reaction sequence that first involves the hydrogenation of nitrile to primary imine, then the hydrolysis of imine, and subsequent deamination to the aldehyde, which is finally hydrogenated to the desired alcohol. Crucial for this reductive hydrolysis process is the commercially available triphos‐ligated Ni‐complex that enables highly efficient and selective transformation of aromatic, heterocyclic, and aliphatic nitriles including fatty nitriles to prepare functionalized primary alcohols. Further, the synthetic applicability of this Ni‐based protocol is presented for the selective conversion of nitrile to alcoholic group in structurally diverse and complex drug molecules as well as agrochemicals. The resulting products, alcohols are indispensable chemicals commonly used in organic synthesis and life sciences as well as material and energy technologies.

Nickel-catalyzed Reductive Hydrolysis of Nitriles to Alcohols.

Nitriles are an abundant class of compounds that are widely used as versatile feedstocks to produce various chemicals including pharmaceuticals, and agrochemicals as well as materials. Here we report Ni-catalyzed reductive hydrolysis of nitriles to alcohols in the presence of molecular hydrogen. This conversion likely occurs in a domino reaction sequence that first involves the hydrogenation of nitrile to primary imine, then the hydrolysis of imine, and subsequent deamination to the aldehyde, which is finally hydrogenated to the desired alcohol. Crucial for this reductive hydrolysis process is the commercially available triphos-ligated Ni-complex that enables highly efficient and selective transformation of aromatic, heterocyclic, and aliphatic nitriles including fatty nitriles to prepare functionalized primary alcohols. Further, the synthetic applicability of this Ni-based protocol is presented for the selective conversion of nitrile to alcoholic group in structurally diverse and complex drug molecules as well as agrochemicals. The resulting products, alcohols are indispensable chemicals commonly used in organic synthesis and life sciences as well as material and energy technologies.

The current socioeconomic and regulatory landscape of immune effector cell therapies.

Immune cell effector therapies, including chimeric antigen receptor (CAR)-T cells, T-cell receptor (TCR) T cells, natural killer (NK) cells, and macrophage-based therapies, represent a transformative approach to cancer treatment, harnessing the immune system to target and eradicate malignant cells. CAR-T cell therapy, the most established among these, involves engineering T cells to express CARs specific to cancer cell antigens, showing remarkable efficacy in hematologic malignancies like leukemias, B-cell lymphomas, and multiple myeloma. Similarly, TCR-modified therapies, which reprogram T cells to recognize intracellular tumor antigens presented by major histocompatibility complex (MHC) molecules, offer promise for a range of solid tumors. NK-cell therapies leverage NK cells' innate cytotoxicity, providing an allogeneic approach that avoids some of the immune-related complications associated with T-cell-based therapies. Macrophage-based therapies, still in early stages of the development, focus on reprogramming macrophages to stimulate an immune response against cancer cells in the tumor microenvironment. Despite their promise, socioeconomic and regulatory challenges hinder the accessibility and scalability of immune cell effector therapies. These treatments are costly, with CAR-T therapies currently exceeding $400,000 per patient, creating significant disparities in access based on socioeconomic status and geographic location. The high manufacturing costs stem from the personalized, labor-intensive processes of harvesting, modifying, and expanding patients' cells. Moreover, complex logistics for manufacturing and delivering these therapies limit their reach, particularly in low-resource settings. Regulatory pathways further complicate the landscape. In the United States., the Food and Drug Administrations' (FDA) accelerated approval processes for cell-based therapies facilitate innovation but do not address cost-related barriers. In Europe, the European Medicines Agency (EMA) offers adaptive pathways, yet decentralized reimbursement systems create uneven access across member states. Additionally, differing regulatory standards for manufacturing and quality control worldwide pose hurdles for global harmonization and access. To expand the reach of immune effector cell therapies, a multipronged approach is needed-streamlined regulatory frameworks, policies to reduce treatment costs, and international collaborations to standardize manufacturing. Addressing these socioeconomic and regulatory obstacles is essential to make these life-saving therapies accessible to a broader patient population worldwide. We present a literature review on the current landscape of immune effector cell therapies and barriers of access to currently approved standard of care therapy at various levels.

Multimodal Fused Deep Learning for Drug Property Prediction: Integrating Chemical Language and Molecular Graph

Accurately predicting molecular properties is a challenging but essential task in drug discovery. Recently, many mono-modal deep learning methods have been successfully applied to molecular property prediction. However, mono-modal learning is inherently limited as it relies solely on a single modality of molecular representation, which restricts a comprehensive understanding of drug molecules. To overcome the limitations, we propose a multimodal fused deep learning (MMFDL) model to leverage information from different molecular representations. Specifically, we construct a triple-modal learning model by employing Transformer-Encoder, BiGRU, and graph convolutional network (GCN) to process three modalities of information from chemical language and molecular graph: SMILES-encoded vectors, ECFP fingerprints, and molecular graphs, respectively. We evaluate the proposed triple-modal model using five fusion approaches on six molecule datasets including Delaney, Llinas2020, Lipophilicity, SAMPL, BACE, and pKa from DataWarrior. The results show that the MMFDL model achieves the highest Pearson coefficients, and stable distribution of Pearson coefficients in a random splitting test, outperforming mono-modal models in accuracy and reliability. Furthermore, we validate the generalization ability of our model in the prediction of binding constants for protein-ligand complex molecules and assess the resilience capability against noise. Through analysis of feature distributions in chemical space and the assigned contribution of each modal model, we demonstrate that the MMFDL model shows the ability to acquire complementary information by using proper models and suitable fusion approaches. By leveraging diverse sources of bioinformatics information, multimodal deep learning models hold the potential for successful drug discovery.

The Action of Testosterone in Anti-aging, Rejuvenation, and Longevity

Testosterone is an anabolic androgenic steroid hormone, that is, it is a lipid synthesized from cholesterol-steroid, produced by glands and with regulatory action on cellular physiology hormone, whose main actions are to promote masculinization -androgenic effect- and the synthesis of complex molecules from simpler molecules anabolic effect. Our body's three main steroid substances are androgens, estrogens, and corticosteroids. This literature review aims to verify testosterone's action on rejuvenation, anti-aging, and longevity. The integrative literature review is a method that aims to synthesize results obtained in research on a topic or issue, in a systematic, ordered, and comprehensive way. It is called integrative because it provides broader information on a subject/problem, thus constituting a body of knowledge. To carry out the study, a search for scientific articles was carried out through the Virtual Health Library (SCIELO), Latin American and Caribbean Literature in Health Sciences (LILACS), US National Library of Medicine National Center for Biotechnology Information (PUBMED), Social Network for Scientists (ResearchGate) and Virtual Social Network for Academics (Academia.edu) using the terminologies registered in the health sciences descriptors: Anti-aging, hormones, longevity, rejuvenation, and testosterone.

GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts

In this work, inspired by the graph transformer, we presented an improved protocol, termed GT-NMR, which integrates 2D molecular graph representation with Transformer architecture, for accurate yet efficient prediction of NMR chemical shifts. The effectiveness of the GT-NMR was thoroughly examined with the standard nmrshiftdb2 dataset, 37 natural products and structural elucidation of 11 pairs of natural products. Systematical analysis affirms that GT-NMR outperforms traditional graph-based methods in all aspects, achieving state-of-the-art performance, with the mean absolute error of 0.158 and 1.189 ppm in predicting 1H and 13C NMR chemical shifts, respectively, for the standard nmrshiftdb2 dataset. Further scrutiny of its practical applications indicates that GT-NMR's efficacy is closely tied to molecular complexity, as quantified by the size-normalized spatial score (nSPS). For relatively simple molecules (nSPS < = 27.71), GT-NMR performs comparably to the best density functional while its effectiveness significantly diminishes with complex molecules characterized by higher nSPS values (nSPS > = 38.42). This trend is consistent across other graph-based NMR chemical shift prediction methods as well. Therefore, while employing GT-NMR or other graph-based methods for the rapid and routine prediction of NMR chemical shifts, it is advisable to utilize nSPS to assess their suitability. The source codes and trained model of GT-NMR are publicly available at GitHub.Scientific contributionGT-NMR, which combines the 2D molecular graph representation with the Transformer architecture, was implemented for the first time to predict atom-level NMR chemical shifts, achieving state-of-the-art performance. More importantly, the reliability of the GT-NMR and graph-based methods was assessed for the first time in terms of molecular complexity, as quantified by the size-normalized spacial score (nSPS). Systematical scrutiny demonstrated that GT-NMR offer a valuable way for routine application in structural screening and elucidation of relatively simple molecules.

Confinement Effects of Coordination Cages on the Synthesis and Application of Polyoxometalates.

The confinement effects within coordination cages present powerful tools in modern chemistry, particularly for the synthesis and manipulation of complex molecules. This concept article reviews the use of coordination cages to stabilize and tune the properties of polyoxometalates (POMs), a class of nano-sized metallic clusters, expanding the focus beyond traditional organic reactions. The article provides a brief overview of coordination cages, and POM chemistry and discusses the encapsulation of POMs in coordination cages, highlighting how these cages provide a confinement effect that enhances the stability and reactivity of POMs. Additionally, the concept of cavity-directed synthesis is explored as a method for creating labile POMs, which are often unstable in aqueous conditions, underlining its implications for supramolecular catalysis. Future research will focus on expanding the structures and applications of encapsulated POMs, as well as improving cage designs to unlock new cluster architectures.

What to Expect When Switching to a Biosimilar: A US Healthcare Professional’s Perspective

Abstract Biologics are medications made up of large, complex molecules that are manufactured in living tissues or cells and can be used to treat autoimmune conditions such as inflammatory bowel disease. Biosimilars are biologics that are highly similar to an approved biologic medicine. Biosimilars cost less for manufacturers to make than the original biologic (known as the reference product) and can help more people have access to treatment. Insurance companies in the United States may require a patient to switch their treatment from a reference product to a biosimilar to help decrease the cost of treatment. In this article, a physician assistant and a pharmacist discuss the patient experience when a patient is switched to a biosimilar. The most common questions patients have when being switched are around the safety and effectiveness of biosimilars. The authors explain that all biosimilars must go through a rigorous process mandated by the US Food and Drug Administration to prove they have the same side effects and effectiveness as the biologics on which they are based. It is important for healthcare professionals to proactively educate patients who are being switched about biosimilars. Advance practice providers, physicians, and pharmacists should work with patients to answer their questions to enable them to feel comfortable starting or switching to a biosimilar.

Importance of the CuAAC Reaction in the Synthesis of Platinum Complexes with 1,4-Disubstituted-1H-1,2,3-triazoles: A Review of Their Anticancer Activity

Despite multiple advances in treatment and prevention, cancer remains one of the leading causes of death worldwide. Chemotherapy remains the most effective method for cancer treatment. However, commercial chemotherapeutic drugs have limited efficacy, severe side effects, and acquired resistance. Therefore, the scientific community has devoted a great effort to designing new, more effective, and cheaper drugs. In this sense, copper-catalyzed azide-alkyne cycloaddition reactions (CuAAC) provide 1,4-disubstituted 1H-1,2,3-triazoles in high yields without forming by-products. This reaction allows the easy, efficient, functional, ordered, rapid, selective, and specific joining of small molecules, giving rise to more complex molecules. The CuACC reaction simplifies the synthesis processes, accelerating the discovery of new chemotherapeutic agents by allowing the joining of commercial platinum drugs, slightly altering their structure, or creating new molecules with improved properties. This work shows the importance of CuAAC reactions in the search for new metallodrugs with possible anticancer activity.

The Neural Palette of Heme: Altered Heme Homeostasis Underlies Defective Neurotransmission, Increased Oxidative Stress, and Disease Pathogenesis

Heme, a complex iron-containing molecule, is traditionally recognized for its pivotal role in oxygen transport and cellular respiration. However, emerging research has illuminated its multifaceted functions in the nervous system, extending beyond its canonical roles. This review delves into the diverse roles of heme in the nervous system, highlighting its involvement in neural development, neurotransmission, and neuroprotection. We discuss the molecular mechanisms by which heme modulates neuronal activity and synaptic plasticity, emphasizing its influence on ion channels and neurotransmitter receptors. Additionally, the review explores the potential neuroprotective properties of heme, examining its role in mitigating oxidative stress, including mitochondrial oxidative stress, and its implications in neurodegenerative diseases. Furthermore, we address the pathological consequences of heme dysregulation, linking it to conditions such as Alzheimer’s disease, Parkinson’s disease, and traumatic brain injuries. By providing a comprehensive overview of heme’s multifunctional roles in the nervous system, this review underscores its significance as a potential therapeutic target and diagnostic biomarker for various neurological disorders.

3T-VASP: fast ab-initio electrochemical reactor via multi-scale gradient energy minimization

Ab-initio methods such as density functional theory (DFT) is useful for fundamental atomistic-level study and is widely used across many scientific fields, including for the discovery of electrochemical reaction byproducts. However, many DFT steps may be needed to discover rare electrochemical reaction byproducts, which limits DFT’s scalability. In this work, we demonstrate that it is possible to generate many elementary electrochemical reaction byproducts in-silico using just a small number of ab-initio energy minimization steps if it is done in a multi-scale manner, such as via previously reported tiered tensor transform (3T) method. We first demonstrate the algorithm through a simple example of a complex floppy organic molecule passivator binding onto perovskite solar cell surface defect site. We then demonstrate more complex examples by generating hundreds of electrochemical reaction byproducts in lithium-ion battery liquid electrolyte (many are verified in previous experimental studies), with most trajectories completed within 50–100 DFT steps as opposed to more than 10,000 steps typically utilized in an ab-initio molecular dynamics trajectory. This approach requires no machine learning training data generation and can be directly applied on any new chemistries, making it suitable for ab-initio elementary chemical reaction byproduct investigation when temperature dependence is not required.

Deep Learning for Generating Phase-Conditioned Infrared Spectra.

Infrared (IR) spectroscopy is an efficient method for identifying unknown chemical compounds. To accelerate IR spectrum analysis, various calculation and machine learning methods for simulating IR spectra of molecules have been studied in chemical science. However, existing calculation and machine learning methods assumed a rigid constraint that all molecules are in the gas phase, i.e., they overlooked the phase dependency of the IR spectra. In this paper, we propose an efficient phase-aware machine learning method to generate phase-conditioned IR spectra from 2D molecular structures. To this end, we devised a phase-aware graph neural network and combined it with a transformer decoder. To the best of our knowledge, the proposed method is the first IR spectrum generator that can generate the phase-conditioned IR spectra of real-world complex molecules. The proposed method outperformed state-of-the-art methods in the tasks of generating IR spectra on a benchmark dataset containing experimentally measured 11,546 IR spectra of 10,288 unique molecules. All implementations of the proposed method are publicly available at https://github.com/ngs00/PASGeN.

Feedstock chemical dichloromethane as the C1 source for the chemoselective multicomponent synthesis of valuable 1,4,2-dioxazoles

The development of mild and practical strategies to produce value-added fine chemicals directly from inexpensive and readily available commodity chemicals is actively pursued by chemists. However, the application of feedstock chemical dichloromethane (DCM) as the C1 source in organic synthesis is still in its infancy. Herein, we describe a multicomponent strategy for the chemoselective synthesis of valuable 1,4,2-dioxazoles by using DCM as a C1 source. Critical to the success of this process is tuning of the type of nucleophiles to inhibit the easily-occurring side reactions. This approach features mild and simple conditions, excellent chemoselectivity, metal free, and broad substrate scope covering different types of nucleophiles. Furthermore, its synthetic utility is further demonstrated by the preparation of deuterated 1,4,2-dioxazoles, the late-stage functionalization of complex molecules and large-scale synthesis. Preliminary mechanistic studies indicate the dual roles of 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) as both a proton scavenger and a nucleophilic catalyst. This work provides not only a platform for DCM application, but also an excellent complementary strategy to the established 1,4,2-dioxazoles synthesis.

Synthesis of Polysubstituted Vinyl Sulfones by Direct C-S Cross-Coupling.

Vinyl sulfones are valued for their unique chemical properties and bioactivity, but creating a wide range of different analogs remains a challenge. To address this limitation, we have developed a novel approach that facilitates the synthesis of polysubstituted vinyl sulfones. This method utilizes the dual functionality of NIS as a promoter that enables sulfonation and elimination in the synthesis of vinyl sulfones. We used the broad applicability, efficiency, selectivity, and functional group tolerance of this approach to synthesize more than 70 examples. Additionally, competition experiments have provided insights into the reactivity and selectivity of the transient sulfonyl radical towards various C-C multiple bonds. Herein, we describe using this mild protocol in the late-stage vinyl sulfonation of complex molecules to simplify the synthesis of specific targets and enable the modification of complex natural products and advanced materials.

Association of HLA-G Expression, Its Genetic Variants and Related Neuro-Immunomodulation with Characteristics of Bladder Carcinoma.

Human leukocyte antigen G (HLA-G) is an immune checkpoint molecule with immunosuppressive and anti-inflammatory activities. It belongs to class I non-classical major histocompatibility complex molecules and has been upregulated in various cancer types. In bladder cancer (BC) tumors, the association of HLA-G with cancer progression has to be explained. A total of 89 BC patients and 74 control subjects were genotyped for the HLA-G 14 bp ins/del polymorphism. In urine cell samples, HLA-G mRNA expression was analyzed using real-time PCR. Soluble HLA-G (sHLA-G) serum levels were measured by ELISA. The associations between the HLA-G 14 bp ins/del polymorphism, HLA-G mRNA expression, and/or sHLA-G levels and selected variables including tumor grade, disease stage, body mass index, and heart rate variability (HRV) parameters were evaluated. The protective HLA-G 14 bp ins/ins genotype under the recessive genetic model was associated with lower HLA-G mRNA expression in the BC group (p = 0.049). Significantly higher HLA-G mRNA expression was detected in patients with pT2 + pT3 as compared to those with pTa + pT1 stages (p = 0.0436). Furthermore, higher HLA-G mRNA expression was observed in high-grade muscle-infiltrating BC (MIBC) than in the low-grade non-MIBC group (p = 0.0365). Patients with a level of sHLA-G above 29 U/mL had shorter disease-free survival than patients with lower sHLA-G levels. Furthermore, the opposite HRV correlations with sHLA-G levels in BC patients as compared to controls probably reflect the different roles of HLA-G in health and cancer. Our results suggest the impact of the HLA-G 14 bp ins/del variant, HLA-G expression, and autonomic nervous system imbalance on advanced stages of BC.

Iron-Catalyzed Cross-Electrophile Coupling for the Formation of All-Carbon Quaternary Centers.

Quaternary carbon centers are desirable targets for drug discovery and complex molecule synthesis, yet the synthesis of these motifs within traditional cross-coupling paradigms remains a significant challenge due to competing β-hydride elimination pathways. In contrast, the bimolecular homolytic substitution (SH2) mechanism offers a unique and attractive alternative pathway. Metal porphyrin complexes have emerged as privileged catalysts owing to their ability to selectively form primary metal-alkyl complexes, thereby eliminating the challenges associated with tertiary alkyl complexation with a metal center. Herein, we report an iron-catalyzed cross-electrophile coupling of tertiary bromides and primary alkyl electrophiles for the formation of all-carbon quaternary centers through a biomimetic SH2 mechanism.

Siloxyflavylium Triflates as Organic Photocatalysts

Photocatalysis is a promising tool for complex molecule construction. Inspired by the potential of photocatalysis, the investigations herein describe on the development of siloxyflavium triflates as a new family of organic photocatalysts for synthetic chemistry. In this report, the utility of siloxyflavium triflate photocatalysis is demonstrated in the α‐C‐H activation of ethers in the presence of chromenones to generate valuable, biologically relevant C(sp3)‐C(sp3) linkages. The scope of the bond‐forming event is demonstrated with 20 substrates.