AIMC Topic: Drug Screening Assays, Antitumor

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Anticancer and anti-inflammatory activities of girinimbine isolated from .

Drug design, development and therapy
Therapy that directly targets apoptosis and/or inflammation could be highly effective for the treatment of cancer. is an edible herb that has been traditionally used for cancer treatment as well as inflammation. Here, we describe that girinimbine, a...

Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner.

BMC medical genomics
BACKGROUND: Phenotype-based high-throughput screening is a useful technique for identifying drug candidate compounds that have a desired phenotype. However, the molecular mechanisms of the hit compounds remain unknown, and substantial effort is requi...

Low-cost robotic manipulation of live microtissues for cancer drug testing.

Science advances
The scarcity of human biopsies available for drug testing is a paramount challenge for developing therapeutics, disease models, and personalized treatments. Microtechnologies that combine the microscale manipulation of tissues and fluids offer the ex...

A Novel Effective Models for Identifying BRCA Patients and Optimizing Clinical Treatments.

Anti-cancer agents in medicinal chemistry
OBJECTIVE: This study aimed to develop an effective model that identifies high-risk breast cancer (BRCA) patients and optimizes clinical treatments.

PySmash: Python package and individual executable program for representative substructure generation and application.

Briefings in bioinformatics
BACKGROUND: Substructure screening is widely applied to evaluate the molecular potency and ADMET properties of compounds in drug discovery pipelines, and it can also be used to interpret QSAR models for the design of new compounds with desirable phys...

Anticancer drug synergy prediction in understudied tissues using transfer learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Drug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies...

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model.

Journal of enzyme inhibition and medicinal chemistry
Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLI...

Volatile constituents and in vitro activity of Syzygium aromaticum flower buds (clove) against human cancer cell lines.

Pakistan journal of pharmaceutical sciences
The methanolic extract (SA-EXT) of Syzygium aromaticum flower buds and its fractions tested against three human cancer cell lines viz uterine cervix (HeLa), breast (MCF-7) and lung NCI (H-460) using sulforhodamine-B assay. The ethyl acetate soluble s...

Assessing the Anti-cancer Therapeutic Mechanism of a Herbal Combination for Breast Cancer on System-level by a Network Pharmacological Approach.

Anticancer research
BACKGROUND/AIM: Accumulating evidence has shown therapeutic effects of herbals on breast cancer, a commonly diagnosed malignancy in women worldwide. However, their underlying mechanisms remain unclear. We aimed to explore the mode of action of a rece...

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.

Oncotarget
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first applic...