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New approach in the characterization of bioactive compounds isolated from Calycotome spinosa (L.) Link leaves by the use of negative electrospray ionization LITMS, LC-ESI-MS/MS, as well as NMR analysis.

Bioorganic chemistry
Two novel compounds were isolated for the first time from Calycotome spinosa (L.) Link, an alkaloid 5-Hydroxy-1H-indole (4) and a cyclitol D-pinitol (5), together with the three well-known flavonoids; Chrysin-7-O-(β-D-glucopyranoside) (1), Chrysin-7-...

Drug response prediction by ensemble learning and drug-induced gene expression signatures.

Genomics
Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental information one requires to design anti-cancer drugs. Recently, considerable amount of drug-induced gene expression data has become publicly available, in ad...

Novel indolizine derivatives lowers blood glucose levels in streptozotocin-induced diabetic rats: A histopathological approach.

Pharmacological reports : PR
BACKGROUND: Diabetes mellitus is a deadly disorder in human which induce chronic complications. The streptozotocin (STZ)-induced diabetes in rat is the most common animal model of human diabetes. The present study investigated the effects of novel in...

Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.

BMC bioinformatics
BACKGROUND: Understanding the phenotypic drug response on cancer cell lines plays a vital role in anti-cancer drug discovery and re-purposing. The Genomics of Drug Sensitivity in Cancer (GDSC) database provides open data for researchers in phenotypic...

Artificial Intelligence Approach To Investigate the Longevity Drug.

The journal of physical chemistry letters
Longevity is a very important and interesting topic, and has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Re...

All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration ICs for 8558 Novartis Assays.

Journal of chemical information and modeling
Profile-quantitative structure-activity relationship (pQSAR) is a massively multitask, two-step machine learning method with unprecedented scope, accuracy, and applicability domain. In step one, a "profile" of conventional single-assay random forest ...

Elucidating Compound Mechanism of Action and Predicting Cytotoxicity Using Machine Learning Approaches, Taking Prediction Confidence into Account.

Current protocols in chemical biology
The modes of action (MoAs) of drugs frequently are unknown, because many are small molecules initially identified from phenotypic screens, giving rise to the need to elucidate their MoAs. In addition, the high attrition rate for candidate drugs in pr...

A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients.

International journal of molecular sciences
Heterogeneity in intratumoral cancers leads to discrepancies in drug responsiveness, due to diverse genomics profiles. Thus, prediction of drug responsiveness is critical in precision medicine. So far, in drug responsiveness prediction, drugs' molecu...

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

Scientific reports
It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a ...