AI Medical Compendium Journal:
Current medicinal chemistry

Showing 1 to 10 of 30 articles

iACVP-MR: Accurate Identification of Anti-coronavirus Peptide based on Multiple Features Information and Recurrent Neural Network.

Current medicinal chemistry
BACKGROUND: Over the years, viruses have caused human illness and threatened human health. Therefore, it is pressing to develop anti-coronavirus infection drugs with clear function, low cost, and high safety. Anti-coronavirus peptide (ACVP) is a key ...

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

Current medicinal chemistry
BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe acute respiratory syndrome (SARS-CoV) and SARS-CoV-2. Many peptides in the host defense system have an...

Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives.

Current medicinal chemistry
Gastric cancer (GC) represents a significant global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide. Despite recent advancements in GC treatment, the five-year survival rate fo...

Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction.

Current medicinal chemistry
Currently, the main therapeutic methods for cancer include surgery, radiation therapy, and chemotherapy. However, chemotherapy still plays an important role in tumor therapy. Due to the variety of pathogenic factors, the development process of tumors...

Prediction of Human Microbe-Drug Association based on Layer Attention Graph Convolutional Network.

Current medicinal chemistry
UNLABELLED: Human microbes are closely associated with a variety of complex diseases and have emerged as drug targets. Identification of microbe-related drugs is becoming a key issue in drug development and precision medicine. It can also provide gui...

Graph Neural Networks with Multi-features for Predicting Cocrystals using APIs and Coformers Interactions.

Current medicinal chemistry
INTRODUCTION: Active pharmaceutical ingredients (APIs) have gained direct pharmaceutical interest, along with their in vitro properties, and thus utilized as auxiliary solid dosage forms upon FDA guidance and approval on pharmaceutical cocrystals whe...

Multiomics Analysis of Disulfidptosis Patterns and Integrated Machine Learning to Predict Immunotherapy Response in Lung Adenocarcinoma.

Current medicinal chemistry
BACKGROUND: Recent studies have unveiled disulfidptosis as a phenomenon intimately associated with cellular damage, heralding new avenues for exploring tumor cell dynamics. We aimed to explore the impact of disulfide cell death on the tumor immune mi...

Identifying Hub Genes for Glaucoma based on Bulk RNA Sequencing Data and Multi-machine Learning Models.

Current medicinal chemistry
AIMS: The aims of this study were to determine hub genes in glaucoma through multiple machine learning algorithms.

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.

Current medicinal chemistry
Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics...