Mohamed A. Khamis

Learn More
OBJECTIVE The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of(More)
Software agents are the basic building blocks in many software systems especially those based on artificial intelligence methods, e.g., reinforcement learning based multi-agent systems (MASs). However, testing software agents is considered a challenging problem. This is due to the special characteristics of agents which include its autonomy, distributed(More)
Computational docking is the core process of computer-aided drug design; it aims at predicting the best orientation and conformation of a small molecule (drug ligand) when bound to a target large receptor molecule (protein) in order to form a stable complex molecule. The docking quality is typically measured by a scoring function: a mathematical predictive(More)
  • 1