Starting with the molecular scaffold of the DA(2)/β(2) dual agonist sibenadet (Viozan™), a number of molecular changes were incorporated, which were designed to increase the potency and selectivity of the target molecule, and improve its pharmacokinetics. Through this process a novel, high potency, full β(2)-agonist with high selectivity and long duration capable of being dosed once daily has been discovered.
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http://dx.doi.org/10.1016/j.bmcl.2011.05.097 | DOI Listing |
Angew Chem Int Ed Engl
August 2024
Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom, CB2 1EW.
Alkyl chlorides are a class of versatile building blocks widely used to generate C(sp)-rich scaffolds through transformation such as nucleophilic substitution, radical addition reactions and metal-catalyzed cross-coupling processes. Despite their utility in the synthesis of high-value functional molecules, distinct methods for the preparation of alkyl chlorides are underrepresented. Here, we report a visible-light-mediated dual catalysis strategy for the modular synthesis of highly functionalized and structurally diverse arylated chloroalkanes via the coupling of diaryliodonium salts, alkenes and potassium chloride.
View Article and Find Full Text PDFComput Biol Med
June 2024
Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No.22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, PR China. Electronic address:
Background And Objective: Complete denture is a common restorative treatment in dental patients and the design of the core components (major connector and retentive mesh) of complete denture metal base (CDMB) is the basis of successful restoration. However, the automated design process of CDMB has become a challenging task primarily due to the complexity of manual interaction, low personalization, and low design accuracy.
Methods: To solve the existing problems, we develop a computer-aided Segmentation Network-driven CDMB design framework, called CDMB-SegNet, to automatically generate personalized digital design boundaries for complete dentures of edentulous patients.
Brief Bioinform
November 2023
Institute of Chinese Medical Sciences (ICMS), State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau, China.
Today, pharmaceutical industry faces great pressure to employ more efficient and systematic ways in drug discovery and development process. However, conventional formulation studies still strongly rely on personal experiences by trial-and-error experiments, resulting in a labor-consuming, tedious and costly pipeline. Thus, it is highly required to develop intelligent and efficient methods for formulation development to keep pace with the progress of the pharmaceutical industry.
View Article and Find Full Text PDFACS Med Chem Lett
July 2022
Epizyme Inc., 50 Hampshire Street, Sixth Floor, Cambridge, Massachusetts 02139, United States.
SETD2, a lysine -methyltransferase, is a histone methyltransferase that plays an important role in various cellular processes and was identified as a target of interest in multiple myeloma that features a t(4,14) translocation. We recently reported the discovery of a novel small-molecule SETD2 inhibitor tool compound that is suitable for preclinical studies. Herein we describe the conformational-design-driven evolution of the advanced chemistry lead, which resulted in compounds appropriate for clinical evaluation.
View Article and Find Full Text PDFExpert Opin Drug Discov
January 2022
Computational Drug Design and Biomedical Informatics Laboratory, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina.
Introduction: The implementation of Artificial Intelligence (AI) methodologies to drug discovery (DD) are on the rise. Several applications have been developed for structure-based DD, where AI methods provide an alternative framework for the identification of ligands for validated therapeutic targets, as well as the design of ligands through generative models.
Areas Covered: Herein, the authors review the contributions between the 2019 to present period regarding the application of AI methods to structure-based virtual screening (SBVS) which encompasses mainly molecular docking applications - binding pose prediction and binary classification for ligand or hit identification-, as well as drug design driven by machine learning (ML) generative models, and the validation of AI models in structure-based screening.
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