From knowledge-based potentials to combinatorial lead design in silico.
Computational methods are becoming increasingly used in the drug discovery process. In this Account, we review a novel computational method for lead discovery. This method, called CombiSMoG for "combinatorial small molecule growth", is based on two components: a fast and accurate knowledge-based scoring function used to predict binding affinities of protein-ligand complexes, and a Monte Carlo combinatorial growth algorithm that generates large numbers of low-free-energy ligands in the binding site of a protein. We illustrate the advantages of the method by describing its application in the design of picomolar inhibitors for human carbonic anhydrase.
Grzybowski
Bartosz A
BA
Concurrent Pharmaceuticals, 1 Broadway, 14th floor, Cambridge, Massachusetts 02142, USA.
Ishchenko
Alexey V
AV
Shimada
Jun
J
Shakhnovich
Eugene I
EI
D000465:Algorithms; D001665:Binding Sites; D020650:Combinatorial Chemistry Techniques; D015195:Drug Design; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry
D011506:Proteins