A successful structure-based design of a class of non-peptide small-molecule MDM2 inhibitors targeting the p53-MDM2 protein-protein interaction is reported. The most potent compound 1d binds to MDM2 protein with a Ki value of 86 nM and is 18 times more potent than a natural p53 peptide (residues 16-27). Compound 1d is potent in inhibition of cell growth in LNCaP prostate cancer cells with wild-type p53 and shows only a weak activity in PC-3 prostate cancer cells with a deleted p53. Importantly, 1d has a minimal toxicity to normal prostate epithelial cells. Our studies provide a convincing example that structure-based strategy can be employed to design highly potent, non-peptide, cell-permeable, small-molecule inhibitors to target protein-protein interaction, which remains a very challenging area in chemical biology and drug design.
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ACS Med Chem Lett
January 2025
Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Facultat de Farmàcia i Ciències de l'Alimentació - Campus Torribera, Universitat de Barcelona, Prat de la Riba 171, 08921 Santa Coloma de Gramenet, Spain.
Assessing the binding mode of drug-like compounds is key in structure-based drug design. However, this may be challenged by factors such as the structural flexibility of the target protein. In this case, state-of-the-art computational methods can be valuable to explore the linkages between structural and pharmacological data.
View Article and Find Full Text PDFACS Med Chem Lett
January 2025
Bristol Myers Squibb Research & Development, 700 Bay Road, Redwood City, California 94063, United States.
Dual activation of the TLR7 and TLR8 pathways leads to the production of type I interferon and proinflammatory cytokines, resulting in efficient antigen presentation by dendritic cells to promote T-cell priming and antitumor immunity. We developed a novel series of TLR7/8 dual agonists with varying ratios of TLR7 and TLR8 activity for use as payloads for an antibody-drug conjugate approach. The agonist-induced production of several cytokines in human whole blood confirmed their functional activity.
View Article and Find Full Text PDFRecent advancements in 3D structure-based molecular generative models have shown promise in expediting the hit discovery process in drug design. Despite their potential, efficiently generating a focused library of candidate molecules that exhibit both effective interactions and structural diversity at a large scale remains a significant challenge. Moreover, current studies often lack comprehensive comparisons to high-throughput virtual screening methods, resulting in insufficient evaluation of their effectiveness.
View Article and Find Full Text PDFCurr Drug Discov Technol
December 2024
Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University, PushpViharSector-3, M-B Road, New Delhi, 110017, India.
Background: Computer-Aided Drug Design (CADD) approaches are essential in the drug discovery and development process. Both academic institutions and pharmaceutical and biotechnology corporations utilize them to enhance the efficacy of bioactive compounds.
Objective: This study aims to entice researchers by investigating the benefits of Computer-Aided Drug and Design (CADD) and its fundamental principles.
Sci Rep
January 2025
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China.
This research presents a method based on deep learning for the reverse design of sound-absorbing structures. Traditional methods require time-consuming individual numerical simulations followed by cumbersome calculations, whereas the deep learning design method significantly simplifies the design process, achieving efficient and rapid design objectives. By utilizing deep neural networks, a mapping relationship between structural parameters and the sound absorption coefficient curve is established.
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