A Computational Fragment Approach by Mining the Protein Data Bank: Library Design and Bioisosterism

摘要

Through database mining of the Protein Data Bank (PDB), protein pocket similarities and 3D structural alignments of similar pockets can be performed. These 3D structural alignments can serve as guides in drug design. The commercial MED-SuMo software performs superimposition of PDB ligands based on the ligand-binding corresponding pockets' and subpockets' 3D similarities. Subpockets are occupied by fragment-like molecules or portion of ligands. The mining of such fragments' interaction with the macromolecule surface serves as both a target-based and fragment-based computational method for PDB mining. In this work, we describe two practical applications: (1) a ligand-based drug design technique for bioisosteric replacement and compound library design and (2) a computational fragment-based drug design protocol for target-based drug design scenarios : ligand design, ligand decoration and compound library design. The bioisosteric approach is based on a database of bioisosteric replacement rules which were dervived from the entire PDB and are applicable to any ligand with a known or predicted 3D bound conformation. We present two successful applications: the design of alkenyldiarylmethane ligands for HIV-RT, and the design of a small compound library for HSP90. A case study using the computational Fragment-Based Drug Design approach, was applied to the design of compounds for three types of protein target: Protein kinase, GPCR and kinesin.