Relevance of Machine Learning to Predict the Inhibitory Activity of Small Thiazole Chemicals on Estrogen Receptor.

Journal: Current computer-aided drug design
Published Date: Jan 1, 2023

Abstract

BACKGROUND: Drug discovery requires the use of hybrid technologies for the discovery of new chemical substances. One of those interesting strategies is QSAR via applying an artificial intelligence system that effectively predicts how chemical alterations can impact biological activity via in-silico.

Authors

  • Venkatesan Jayaprakash
    Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Ranchi, India.
  • Thangavelu Saravanan
    Department of Anesthesiology, Government Medical College and Hospital, Pudukkottai, 622004, Tamilnadu, India.
  • Karuppaiyan Ravindran
    Department of Anesthesiology, Government Medical College and Hospital, Pudukkottai, 622004, Tamilnadu, India.
  • Thangavelu Prabha
    Department of Pharmaceutical Chemistry, Nandha College of Pharmacy, Erode, 638052, Tamilnadu, India.
  • Jubie Selvaraj
    Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty, Tamilnadu, India.
  • Sudeepan Jayapalan
    Department of Chemical Engineering & Technology, Birla Institute of Technology, Mesra, Ranchi, 835215, Jharkhand, India.
  • M V N L Chaitanya
    Department of Pharmacognosy, School of Pharmacy, Lovely Professional University, Phagwara, Punjab, India.
  • Thangavel Sivakumar
    Department of Pharmaceutical Chemistry, Nandha College of Pharmacy, Erode, 638052, Tamilnadu, India.

Keywords

External Resources

Popular Topics
Recent Journals