Publications by authors named "Nida Kati"
Computational drug discovery on human immunodeficiency virus with a customized long short-term memory variational autoencoder deep-learning architecture.
CPT Pharmacometrics Syst Pharmacol
February 2024
Article Synopsis
- The ongoing fight against HIV is hindered by the lack of an effective vaccine and the virus's ability to develop drug resistance, highlighting the need for new therapies.
- This study utilized a deep-learning method called a long short-term memory (LSTM) variational autoencoder to explore potential new drugs for HIV, training on a dataset of 1,377 SMILES-encoded compounds with a high accuracy of 91%.
- The research generated new drug candidates, evaluated their interactions with HIV using AI models, and confirmed their drug likeliness based on Lipinski's rule of five, showcasing a promising direction for drug discovery against HIV.