From Modeling to Medicinal Chemistry: Automatic Generation of Two‐Dimensional Complex Diagrams

As a result of the increasing application of structure‐based drug design, the visualization of protein–ligand complexes has become an important feature in medicinal chemistry. The large number of experimentally resolved complex structures and the further development of computer‐aided methods like docking or de novo design establishes new possibilities in this field. During lead finding and optimization, a manual investigation of many complexes and their interaction patterns is typically performed. We present an algorithm that automatically generates 2D‐protein–ligand diagrams as a possible solution for a transparent visualization of the contact partners in a complex and as a support for scientists in the evaluation of structure‐based design results. Running the software on representative test data sets, it generates collision free layouts for ∼76 % of the cases in the range of tenths of a second per complex. The success rate for complexes with ligands which have a molecular weight <500 Da is 87 %.

[1]  K. Diederichs,et al.  Crystal structure of oxidized flavodoxin, an essential protein in Helicobacter pylori , 2002, Protein science : a publication of the Protein Society.

[2]  Structural Aspects of Kinases and Their Inhibitors , 2005 .

[3]  PatrickY.-S. Lam,et al.  Rational design of potent, bioavailable, nonpeptide cyclic ureas as HIV protease inhibitors. , 1994, Science.

[4]  Thomas Lengauer,et al.  Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking , 1999, Proteins.

[5]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[6]  Ronald L. Graham,et al.  An Efficient Algorithm for Determining the Convex Hull of a Finite Planar Set , 1972, Inf. Process. Lett..

[7]  Robin Taylor,et al.  A new test set for validating predictions of protein–ligand interaction , 2002, Proteins.

[8]  Matthias Rarey,et al.  Automated Drawing of Structural Molecular Formulas under Constraints , 2004, J. Chem. Inf. Model..

[9]  J M Thornton,et al.  LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. , 1995, Protein engineering.

[10]  A. McCarthy,et al.  Modulation of the redox potentials of FMN in Desulfovibrio vulgaris flavodoxin: thermodynamic properties and crystal structures of glycine-61 mutants. , 1998, Biochemistry.

[11]  G. Farber,et al.  A STRUCTURAL EXPLANATION FOR ENZYME MEMORY IN NONAQUEOUS SOLVENTS. , 1995 .

[12]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings , 1997 .

[13]  E. L. Lawler,et al.  Branch-and-Bound Methods: A Survey , 1966, Oper. Res..

[14]  Renxiao Wang,et al.  The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. , 2004, Journal of medicinal chemistry.

[15]  Katrin Stierand,et al.  Molecular complexes at a glance: automated generation of two-dimensional complex diagrams , 2006, Bioinform..

[16]  David A. Agard,et al.  The Structural Basis of Estrogen Receptor/Coactivator Recognition and the Antagonism of This Interaction by Tamoxifen , 1998, Cell.

[17]  Hans-Joachim Böhm,et al.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure , 1994, J. Comput. Aided Mol. Des..

[18]  A H Calvert,et al.  Identification of novel purine and pyrimidine cyclin-dependent kinase inhibitors with distinct molecular interactions and tumor cell growth inhibition profiles. , 2000, Journal of medicinal chemistry.

[19]  Jane A. Endicott,et al.  Structure-based design of a potent purine-based cyclin-dependent kinase inhibitor , 2002, Nature Structural Biology.

[20]  Thomas Lengauer,et al.  A fast flexible docking method using an incremental construction algorithm. , 1996, Journal of molecular biology.