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

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Journal of Chemical Information and Modeling (Impact Factor: 3.74). 04/2010; 50(4):534-46. DOI: 10.1021/ci100015j
Source: PubMed

ABSTRACT 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.

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Available from: Woody Sherman, Sep 28, 2015
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    • "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. "
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    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
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    • "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. "
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    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
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    • "NCI compounds were prepared for screening using the LigPrep process (Schrodinger Suite 2009, Schrodinger LLC NY). The ligands were parametised using OPLS_2005 force field and tautomers and ionisation states expected to occur between pH 5.0 and 9.0 [18, 19]. Following energy minimisation, the total number of compounds generated was 309,520. "
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    ABSTRACT: Unlabelled: ABCC1 is a member of the ATP-binding Cassette super family of transporters, actively effluxes xenobiotics from cells. Clinically, ABCC1 expression is linked to cancer multidrug resistance. Substrate efflux is energised by ATP binding and hydrolysis at the nucleotide-binding domains (NBDs) and inhibition of these events may help combat drug resistance. The aim of this study is to identify potential inhibitors of ABCC1 through virtual screening of National Cancer Institute (NCI) compounds. A threedimensional model of ABCC1 NBD2 was generated using MODELLER whilst the X-ray crystal structure of ABCC1 NBD1 was retrieved from the Protein Data Bank. A pharmacophore hypothesis was generated based on flavonoids known to bind at the NBDs using PHASE, and used to screen the NCI database. GLIDE was employed in molecular docking studies for all hit compounds identified by pharmacophore screening. The best potential inhibitors were identified as compounds possessing predicted binding affinities greater than ATP. Approximately 5% (13/265) of the hit compounds possessed lower docking scores than ATP in ABCC1 NBD1 (NSC93033, NSC662377, NSC319661, NSC333748, NSC683893, NSC226639, NSC94231, NSC55979, NSC169121, NSC166574, NSC73380, NSC127738, NSC115534), whereas approximately 7% (7/104) of docked NCI compounds were predicted to possess lower docking scores than ATP in ABCC1 NBD2 (NSC91789, NSC529483, NSC211168, NSC318214, NSC116519, NSC372332, NSC526974). Analyses of docking orientations revealed P-loop residues of each NBD and the aromatic amino acids Trp653 (NBD1) and Tyr1302 (NBD2) were key in interacting with high-affinity compounds. On the basis of docked orientation and docking score the compounds identified may be potential inhibitors of ABCC1 and require further pharmacological analysis. Abbreviations: ABC - ATP-binding cassette, DHS - dehydrosilybin, MDR - multidrug resistance, NBD - nucleotide-binding domain, PDB - protein data bank.
    Bioinformation 10/2012; 8(19):907-11. DOI:10.6026/97320630008907 · 0.50 Impact Factor
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