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

By P. Hawkins, A. Skillman, G. Warren, Benjamin A. Ellingson, Matthew T. Stahl. 2010

1,522 citations recorded by the source corpus.

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.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Molecular Biology

In Pharmacology

Citations in the corpus

Torsional Diffusion for Molecular Conformer Generation (2022, methodology): “Among cheminfor-matics methods, we evaluate RDKit ETKDG [Riniker and Landrum, 2015], the most established open-source package, and OMEGA [Hawkins et al., 2010, Hawkins and Nicholls, 2012], a commercial software in continuous development.”
Cloud-based simulations on Google Exacycle reveal ligand-modulation of GPCR activation pathways (2013, methodology): “Ligands were prepared with Surflex protonation tools, and OpenEye Omega(38) was used to enumerate stereoisomers for compounds with up to 4 chiral centers.”
PubChem3D: conformer ensemble accuracy (2013, methodology): “[18] [The ComboT CT-opt accuracy is identical to the Tanimoto Combo in their study].”
ROCS-derived features for virtual screening (2016, methodology): “Note that 12/102 datasets from the original DUD-E publication were not used in this report since their crystal ligands failed OMEGA expansion: aa2ar, andr, aofb, bace1, braf, dyr, esr2, fkb1a, kif11, rxra, sahh, and urok.”
Ligand placement based on prior structures: the guided ligand-replacement method (2013, methodology): “The SGX pipeline used OMEGA (OpenEye Scientific Software, Santa Fe, New Mexico, USA; Hawkins et al., 2010) to create sets of distinct conformers and then used two approaches to fit ligands (Badger, Hanson et al., 2005): (i) an evolutionary algorithm to explore torsional space and score against elect”
Blind prediction of solvation free energies from the SAMPL4 challenge (2014, methodology): “from the ZINC processing pipeline [24] for hydration free energy predictions, with conformations predicted by OpenEye’s Omega [8, 25, 26].”