Nonnucleoside reverse transcriptase inhibitors (NNRTIs) nowadays represent very potent and most promising anti-AIDS agents that specifically target the HIV-1 reverse transcriptase (RT). However, the effectiveness of NNRTI drugs can be hampered by rapid emergence of drug-resistant viruses and severe side effects upon long-term use. Therefore, there is an urgent need to develop novel, highly potent NNRTIs with broad spectrum antiviral activity and improved pharmacokinetic properties, and more efficient strategies that facilitate and shorten the drug discovery process would be extremely beneficial. Fortunately, the structural diversity of NNRTIs provided a wide space for novel lead discovery, and the pharmacophore similarity of NNRTIs gave valuable hints for lead discovery and optimization. More importantly, with the continued efforts in the development of computational tools and increased crystallographic information on RT/NNRTI complexes, structure-based approaches using a combination of traditional medicinal chemistry, structural biology, and computational chemistry are being used increasingly in the design of NNRTIs. First, this review covers two decades of research and development for various NNRTI families based on their chemical scaffolds, and then describes the structural similarity of NNRTIs. We have attempted to assemble a comprehensive overview of the general approaches in NNRTI lead discovery and optimization reported in the literature during the last decade. The successful applications of medicinal chemistry strategies, crystallography, and computational tools for designing novel NNRTIs are highlighted. Future directions for research are also outlined.
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http://dx.doi.org/10.1002/med.20241 | DOI Listing |
Nat Commun
January 2025
School of Mathematical Sciences, Queen Mary University of London, London, UK.
Studying how we explore the world in search of novelties is key to understand the mechanisms that can lead to new discoveries. Previous studies analyzed novelties in various exploration processes, defining them as the first appearance of an element. However, novelties can also be generated by combining what is already known.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs & Fisheries college, Jimei University, Xiamen, Fujian, People's Republic of China.
Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms.
View Article and Find Full Text PDFGlob Chang Biol
January 2025
School of Biological Sciences, The University of Hong Kong, Hong Kong, China.
Land use change threatens global biodiversity and compromises ecosystem functions, including pollination and food production. Reduced taxonomic α-diversity is often reported under land use change, yet the impacts could be different at larger spatial scales (i.e.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin, 300350, China.
Histone lysine-specific demethylase 1 (LSD1) is overexpressed in various solid and hematological tumors, suggesting its potential as a therapeutic target, but there are currently no LSD1 inhibitors available on the market. In this study we employed a computer-guided approach to identify novel LSD1/EGFR dual inhibitors as a potential therapeutic agent for non-small cell lung cancer. Through a multi-stage virtual screening approach, we found L-1 and L-6, two compounds with unique scaffolds that effectively inhibit LSD1 with IC values of 6.
View Article and Find Full Text PDFBioorg Chem
December 2024
Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, China. Electronic address:
Membranes that destroy anticancer peptides can bind to negatively charged cancer cell membranes through electrostatic interactions, destroying their functions and leading to cancer cell necrosis. Temporin-1CEa, obtained from the skin secretions of the Chinese frog Rana chensinensis, is an anticancer peptide with 17 amino acid residues that exhibits concentration-dependent cytotoxicity against a variety of cancer cell lines, although it has no obvious cytotoxicity to normal HUVECs. In this work, we designed and synthesized 12 derivative peptides through double-cysteine scanning of temporin-1CEa-truncated peptides.
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