AIMC Topic: Antineoplastic Agents

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Extended dipeptide composition framework for accurate identification of anticancer peptides.

Scientific reports
The identification of anticancer peptides (ACPs) is crucial, especially in the development of peptide-based cancer therapy. The classical models such as Split Amino Acid Composition (SAAC) and Pseudo Amino Acid Composition (PseAAC) lack the incorpora...

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders.

PloS one
Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consumin...

Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy.

The international journal of cardiovascular imaging
Global longitudinal strain (GLS) is an echocardiographic measure to detect chemotherapy-related cardiovascular dysfunction. However, its limited availability and the needed expertise may restrict its generalization. Artificial intelligence (AI)-based...

PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation.

Scientific reports
Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The growing research on ACPs as therapeutic agent is increasing due to its minimal side effects. However, identifying novel ACPs using wet-lab experiments are gener...

Neurological insights into brain-targeted cancer therapy and bioinspired microrobots.

Drug discovery today
Cancer, a multifaceted and pernicious disease, continuously challenges medicine, requiring innovative treatments. Brain cancers pose unique and daunting challenges due to the intricacies of the central nervous system and the blood-brain barrier. In t...

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Medical oncology (Northwood, London, England)
Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth Factor -2 (VEGF-2) and its receptor was identified as a potential anti-cancer target, and it plays a...

Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.

The Lancet. Oncology
BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We ...

Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets.

Journal of chemical information and modeling
In drug discovery, molecular docking methods face challenges in accurately predicting energy. Scoring functions used in molecular docking often fail to simulate complex protein-ligand interactions fully and accurately leading to biases and inaccuraci...

Application of Photoactive Compounds in Cancer Theranostics: Review on Recent Trends from Photoactive Chemistry to Artificial Intelligence.

Molecules (Basel, Switzerland)
According to the World Health Organization (WHO) and the International Agency for Research on Cancer (IARC), the number of cancer cases and deaths worldwide is predicted to nearly double by 2030, reaching 21.7 million cases and 13 million fatalities....