Chemometric methods and correlation of spectroscopic or spectrometric data with bioactivity results are known to improve dereplication in classical bio-guided isolation approaches. However, in drug discovery from natural sources the isolation of bioactive constituents from a crude extract containing close structural analogues remains a significant challenge. This study is a H NMR-MS workflow named ELINA (Eliciting Nature's Activities) which is based on statistical heterocovariance analysis (HetCA) of H NMR spectra detecting chemical features that are positively ("hot") or negatively ("cold") correlated with bioactivity prior to any isolation. ELINA is exemplified in the discovery of steroid sulfatase (STS) inhibiting lanostane triterpenes (LTTs) from a complex extract of the polypore fungus Fomitopsis pinicola.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668471 | PMC |
http://dx.doi.org/10.1038/s41598-019-47434-8 | DOI Listing |
Int J Geriatr Psychiatry
January 2025
Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Background: Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30-90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal "Perturbation-based" transcranial Alternating Current Stimulation-Electroencephalography (tACS)-EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype.
View Article and Find Full Text PDFExp Hematol Oncol
January 2025
Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430300, China.
Immune checkpoint therapies have spearheaded drug innovation over the last decade, propelling cancer treatments toward a new era of precision therapies. Nonetheless, the challenges of low response rates and prevalent drug resistance underscore the imperative for a deeper understanding of the tumor microenvironment (TME) and the pursuit of novel targets. Recent findings have revealed the profound impacts of biomechanical forces within the tumor microenvironment on immune surveillance and tumor progression in both murine models and clinical settings.
View Article and Find Full Text PDFMol Cancer
January 2025
Department of Medical Oncology and Radiation Sickness, Peking University Third Hospital, Beijing, 100191, China.
The Kirsten rat sarcoma viral oncogene homolog (KRAS) protein plays a key pathogenic role in oncogenesis, cancer progression, and metastasis. Numerous studies have explored the role of metabolic alterations in KRAS-driven cancers, providing a scientific rationale for targeting metabolism in cancer treatment. The development of KRAS-specific inhibitors has also garnered considerable attention, partly due to the challenge of acquired treatment resistance.
View Article and Find Full Text PDFMol Divers
January 2025
School of Sciences, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, 211198, People's Republic of China.
The p53 protein is regarded as the "Guardian of the Genome," but its mutation is tumor progression and present in more than half of malignant tumors. The pro-metastatic property of mutant p53 makes a strong argument for targeting mutant p53 with new therapeutic strategies. However, mutant p53 was considered as a challenging target for drug discovery due to the lack of small molecular binding pockets.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Institute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.
Nuclear receptors (NRs) are a class of essential proteins that regulate the expression of specific genes and are associated with multiple diseases. In silico methods for prescreening potential NR binders with predictive binding ability are highly desired for NR-related drug development but are rarely reported. Here, we present the PbsNRs (Predicting binders and scaffolds for Nuclear Receptors), a user-friendly web server designed to predict the potential NR binders and scaffolds through proteochemometric modeling.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!