ConfGen: A Conformational Search Method for Efficient Generation of Bioactive Conformers

Schrodinger, LLC, 101 SW Main Street, Suite 1300, Portland, Oregon 97204, USA.
Journal of Chemical Information and Modeling (Impact Factor: 3.74). 04/2010; 50(4):534-46. DOI: 10.1021/ci100015j
Source: PubMed


We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reasonable amount of computer time. The method combines physics-based force field calculations with empirically derived heuristics designed to achieve efficient searching and prioritization of the ligand's conformational space. While many parameter settings are supported, four modes spanning a range of speed and quality trades-offs are defined and characterized. The validation set used to test the method is composed of ligands from 667 crystal structures covering a broad array of target and ligand classes. With the fastest mode, ConfGen uses an average of 0.5 s per ligand and generates only 14.3 conformers per ligand, at least one of which lies within 2.0 A root-mean-squared deviation of the crystal structure for 96% of the ligands. The most computationally intensive mode raises this recovery rate to 99%, while taking 8 s per ligand. Combining multiple search modes to "fill-in" holes in the conformation space or energy minimizing using an all-atom force field each lead to improvements in the recovery rates at higher resolutions. Overall, ConfGen is at least as good as competing programs at high resolution and demonstrates higher efficiency at resolutions sufficient for many downstream applications, such as pharmacophore modeling.

Download full-text


Available from: Woody Sherman,
  • Source
    • "As a prerequisite to 3D pharmacophore development, conformational models for the compounds were generated using the " best " conformer generation method [16]. The poling algorithm was used, which seeks to provide a broad coverage of conformational space with a maximum conformational energy of 20 kcal/mol above the lowest energy conformation [17]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: For a series of 35 piperazino-phthalimide and piperazino-isoindolinone based urotensin-II receptor (UT) antagonists, a thoroughly validated 3D pharmacophore model has been developed, consisting of four chemical features: one hydrogen bond acceptor lipid (HBA_L), one hydrophobe (HY), and two ring aromatic (RA). Multiple validation techniques like CatScramble, test set prediction, and mapping analysis of advanced known antagonists have been employed to check the predictive power and robustness of the developed model. The results demonstrate that the best model, Hypo 1, shows a correlation (r) of 0.902, a root mean square deviation (RMSD) of 0.886, and the cost difference of 39.69 bits. The model obtained is highly predictive with good correlation values for both internal () as well as external () test set compounds. Moreover, the pharmacophore model has been used as a 3D query for virtual screening which served to detect prospective new lead compounds which can be further optimized as UT antagonists with potential for treatment of cardiovascular diseases.
    01/2014; 2014:1-16. DOI:10.1155/2014/921863
    • "The pharmacophore features like hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic/Non-polar group (H), negatively ionizable (N), positively ionizable (P), and aromatic ring (R) were used to create the pharmacophore sites for the energy-calculated ligands. The following features were assigned using SMART queries [Tables 2a,b].[18–20] Tree-based partition algorithm is used by PHASE for detection of common pharmacophore from a set of variants taking maximum tree depth 3. To find common pharmacophore, PHASE algorithm use an exhaustive analysis of k-point pharmacophore match picked from the conformations of a set of active ligands on the basis of inter site distances,[21] and then find all spatial arrangements of pharmacophore features those are common to at least 8 of 10 active ligands. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Febrifugine and its derivatives are effective against Plasmodium falciparum. Using PHASE algorithm, a five-point pharmacophore model with two hydrogen bond acceptor (A), one positively ionizable (P) and two aromatic rings (R), was developed to derive a predictive ligand-based statistically significant 3D-quantitative structure-activity relationship (QSAR) model (r(2) = 0.972, SD = 0.3, F = 173.4, Q(2) = 0.712, RMSE = 0.3, Person-R = 0.94, and r(2) pred = 0.8) to explicate the structural attributes crucial for antimalarial activity. The developed pharmacophore model and 3D QSAR model can be a substantial tool for virtual screening and related antimalarial drug discovery research.
    03/2013; 4(1):50-60. DOI:10.4103/2231-4040.107501
  • Source
    • "Compounds 1–14 (Table 1) with L-leucine uptake inhibition >50% were assigned as active whereas compounds 23–28 with L-leucine uptake inhibition 0% were considered to be inactive. Multiple conformers were generated for the compounds using ConfGen method (Schrödinger LLC; Watts et al., 2010) and 500 minimization steps. The ligands were superimposed with each other and aligned with respect to alternative feature mappings. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Large neutral amino acid transporter 1 (LAT1) is predominantly expressed at the blood-brain barrier and it has a major role in transporting neutral amino acids into the brain. LAT1 has the potential to function as a drug carrier for improved drug brain delivery which makes it an intriguing target protein for central nervous system disorders e.g., Alzheimer's disease, Parkinson's disease and brain tumors. In this study, a 3D pharmacophore was generated for a set of LAT1 substrates whose binding affinities were studied using competitive inhibition of the brain uptake of [(14)C]-L-leucine with an in situ rat brain perfusion method. The pharmacophore highlights the most important molecular features shared by efficient LAT1-binding compounds and elucidates their 3D-arrangement in detail. This clarifies the structure-activity relationships of LAT1 substrates and provides insights for making a binding hypothesis. The results can be further applied in the design of novel efficient LAT1 substrates.
    European journal of pharmaceutical sciences: official journal of the European Federation for Pharmaceutical Sciences 12/2012; 48(3). DOI:10.1016/j.ejps.2012.11.014 · 3.35 Impact Factor
Show more