Alex MacKerell received a PhD in Biochemistry in 1985 from Rutgers University, which was followed by postdoctoral fellowships in the Department of Medical Biophysics, KarolinskaIntitutet, Stockholm, Sweden and the Department of Chemistry, Harvard University.In 1992 he assumed his faculty position in the School of Pharmacy, University of Maryland where he is currently the Grollman-Glick Professor of Pharmaceutical Sciences and the Director of University of Maryland Computer-Aided Drug Design Center.Heis also co-founder and Chief Scientific Officer of SilcsBio LLC


Computational functional group affinity mapping of proteins is of utility for ligand design in the context of database screening, fragment-based design and lead compound optimization.Affinity maps from the site identification by ligand competitive saturation (SILCS) methodology, termed grid free energy maps (GFE FragMaps), are generated using explicit solvent MD simulations of a collection of representative solutes in the presence of the protein of interest such that the mapsinclude contributions from protein desolvation, ligand desolvation, protein flexibility as well as direct interactions of the ligands with the protein.In a number of studies the GFE FragMaps have been shown to recapitulate the binding orientations of ligands to a range of proteins and be predictive of the relative affinities of ligands binding to the same protein as well as beingutilized in ligand design.However, SILCS simulations of proteins with deep or occluded pockets are challenging due to the need for the solutes and water in the simulations to diffuse into the pockets on the time scale of the simulations.To overcome this we have developed a novel simulation approach allowing for adequate sampling of these challenging pockets as required to obtain accurate GFE FragMaps.An overview of the methodology will be presented along with its application to lysozyme, the adrenal receptor, a GPCR (mu opioid receptor), and the macrolide-binding site of the ribosome.