AIMC Topic: Antineoplastic Agents

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AntiCP 2.0: an updated model for predicting anticancer peptides.

Briefings in bioinformatics
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides...

Prediction of Chemosensitivity in Multiple Primary Cancer Patients Using Machine Learning.

Anticancer research
BACKGROUND/AIM: Many cancer patients face multiple primary cancers. It is challenging to find an anticancer therapy that covers both cancer types in such patients. In personalized medicine, drug response is predicted using genomic information, which ...

Artificial Intelligence in Cancer Research and Precision Medicine.

Cancer discovery
Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical care. Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has...

Machine learning approaches for elucidating the biological effects of natural products.

Natural product reports
Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural pr...

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...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is the largest, public, freely available, integrative translational research and drug discovery knowledgebase for oncology. canSAR integrates vast multidisciplinary data from across genomic, protein, pharmacological, ...

Open Targets Platform: supporting systematic drug-target identification and prioritisation.

Nucleic acids research
The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicl...

Chemotherapy Knowledge Base Management in the Era of Precision Oncology.

JCO clinical cancer informatics
Cancer medicine has grown increasingly complex in recent years with the advent of precision oncology and wide utilization of multidrug regimens. Representing this increasingly granular knowledge is a significant challenge. As users and managers of a ...

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...

Synthesis and evaluation of a novel nanosized anionic linear globular dendrimer G2-ciprofloxacin conjugate against prostate cancer.

Pakistan journal of pharmaceutical sciences
Prostate cancer is the second most common cancer in the world and the fifth cause of cancer deaths in men. Ciprofloxacin enables the inhabitation of the development of prostate cancer. In this regard, we plan to improve the anticancer effect of cipro...