AIMC Topic: Antineoplastic Agents

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ACPScanner: Prediction of Anticancer Peptides by Integrated Machine Learning Methodologies.

Journal of chemical information and modeling
Novel therapeutic alternatives for cancer treatment are increasingly attracting global research attention. Although chemotherapy remains a primary clinical solution, it often results in significant side effects for patients. In recent years, anticanc...

Hollow CoFe Nanozymes Integrated with Oncolytic Peptides Designed via Machine-Learning for Tumor Therapy.

Small (Weinheim an der Bergstrasse, Germany)
Developing novel substances to synergize with nanozymes is a challenging yet indispensable task to enable the nanozyme-based therapeutics to tackle individual variations in tumor physicochemical properties. The advancement of machine learning (ML) ha...

T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Journal of biomolecular structure & dynamics
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug di...

Deep-Learning-Based Nanomechanical Vibration for Rapid and Label-Free Assay of Epithelial Mesenchymal Transition.

ACS nano
Cancer is a profound danger to our life and health. The classification and related studies of epithelial and mesenchymal phenotypes of cancer cells are key scientific questions in cancer research. Here, we investigated cancer cell colonies from a mec...

Mechanism of cytotoxicity induced by the cigarette smoke extract (CSE) of heated tobacco products in vascular smooth muscle cells: A comparative study of the cytotoxic effects of CSE and the ferroptosis inducer, erastin.

Journal of pharmacological sciences
Heated tobacco products (HTPs) are marketed worldwide as less harmful alternatives to combustible cigarettes; however, their cytotoxic mechanisms in vascular smooth muscle cells are poorly understood. Ferroptosis is defined as iron-dependent cell dea...

Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC.

Cancer medicine
BACKGROUND: Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC), has the risk of postoperative recurrence, thus its prognosis is poor and its prognostic markers are usually based on imaging methods, which have the...

Machine learning and experimental screening of chromatin regulator signatures and potential drugs in hepatitis B related hepatocellular carcinoma.

Journal of biomolecular structure & dynamics
Many evidences have confirmed that chromatin regulator factors (CRs) are involved in the progression of cancer, but its potential mechanism of affecting hepatitis B related hepatocellular carcinoma still needs to be studied. Our study detected the CR...

Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis.

Journal of biomolecular structure & dynamics
Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. ...

An interpretable artificial intelligence framework for designing synthetic lethality-based anti-cancer combination therapies.

Journal of advanced research
INTRODUCTION: Synthetic lethality (SL) provides an opportunity to leverage different genetic interactions when designing synergistic combination therapies. To further explore SL-based combination therapies for cancer treatment, it is important to ide...

XGraphCDS: An explainable deep learning model for predicting drug sensitivity from gene pathways and chemical structures.

Computers in biology and medicine
Cancer is a highly complex disease characterized by genetic and phenotypic heterogeneity among individuals. In the era of precision medicine, understanding the genetic basis of these individual differences is crucial for developing new drugs and achi...