Residue Preference Mapping of Ligand Fragments in the Protein Data Bank

publication · 9 years ago
by Peter Wipf, Lirong Wang, Zhaojun Xie, Xiang-Qun Xie (University of Pittsburgh)
The interaction between small molecules and proteins is one of the major concerns for structure-based drug design because the principles of protein−ligand interactions and molecular recognition are not thoroughly understood. Fortunately, the analysis of protein−ligand complexes in the Protein Data Bank (PDB) enables unprecedented possibilities for new insights. Herein, we applied molecule-fragmentation algorithms to split the ligands extracted from PDB crystal structures into small fragments. Subsequently, we have developed a ligand fragment and residue preference mapping (LigFrag-RPM) algorithm to map the profiles of the interactions between these fragments and the 20 proteinogenic amino acid residues. A total of 4032 fragments were generated from 71 798 PDB ligands by a ring cleavage (RC) algorithm. Among these ligand fragments, 315 unique fragments were characterized with the corresponding fragment−residue interaction profiles by counting residues close to these fragments. The interaction profiles revealed that these fragments have specific preferences for certain types of residues. The applications of these interaction profiles were also explored and evaluated in case studies, showing great potential for the study of protein−ligand interactions and drug design. Our studies demonstrated that the fragment−residue interaction profiles generated from the PDB ligand fragments can be used to detect whether these fragments are in their favorable or unfavorable environments. The algorithm for a ligand fragment and residue preference mapping (LigFrag-RPM) developed here also has the potential to guide lead chemistry modifications as well as binding residues predictions.
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