Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database

Abstract

Here, we present the algorithm and validation for OMEGA, a systematic, knowledge-based conformer generator. The algorithm consists of three phases: assembly of an initial 3D structure from a library of fragments; exhaustive enumeration of all rotatable torsions using values drawn from a knowledge-based list of angles, thereby generating a large set of conformations; and sampling of this set by geometric and energy criteria. Validation of conformer generators like OMEGA has often been undertaken by comparing computed conformer sets to experimental molecular conformations from crystallography, usually from the Protein Databank (PDB). Such an approach is fraught with difficulty due to the systematic problems with small molecule structures in the PDB. Methods are presented to identify a diverse set of small molecule structures from cocomplexes in the PDB that has maximal reliability. A challenging set of 197 high quality, carefully selected ligand structures from well-solved models was obtained using these methods. This set will provide a sound basis for comparison and validation of conformer generators in the future. Validation results from this set are compared to the results using structures of a set of druglike molecules extracted from the Cambridge Structural Database (CSD). OMEGA is found to perform very well in reproducing the crystallographic conformations from both these data sets using two complementary metrics of success.

Reliability analysis and optimization of the consensus docking approach for the development of virtual screening studies

“…The conformers were generated by OMEGA2 [56][57][58] . We applied the following modifications to the default settings of OMEGA2: the energy window was set at 50.0, the maximum number of output conformers was set at 10000, the time limit was set at 1200, and the root mean square deviation (RMSD) value below which two conformations were considered to be similar was set at 0.3 Å .…”

Mutant cycle analysis with modified saxitoxins reveals specific interactions critical to attaining high-affinity inhibition of hNa V 1.7

“…Docking experiments were performed using homology models of the pore structure for WT rNa V 1.4 and M1240T/D1241I doublepoint mutants previously reported by Walker et al (6). Computational ligand preparation was accomplished using OMEGA version 2.5.1 and docking was performed with the FRED prediction tool in the OEDocking (version 3.0.1) suite (OpenEye Scientific Software) (47,48).…”

Andrographolide and Its Derivative - A Story of Antimalarial Drug Design and Synthesis

“…Before molecular docking, every ligand was fixed to pKa = 7.0 and their tautomers assigned by QUACPAC 1.6.3.1 [23,24]. Then, the derivative was filtered for drug-likenesses and its conformations generated by OMEGA 2.5.1.4 [25] using default parameters.…”