A Model Binding Site for Testing Scoring Functions in Molecular Docking

Wei, BinQing; Baase, W.A.; Weaver, L.H.; Matthews, Brian W.; Shoichet, Brian K.

doi:10.1016/s0022-2836(02)00777-5

Cited by 216 publications

(349 citation statements)

References 68 publications

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“…Formed in the hydrophobic core of the protein, the resulting 150-Å 3 cavity is sequestered from solvent and is almost entirely apolar. Seminal studies by Matthews and colleagues demonstrated that this cavity can bind aryl hydrocarbons (20,21), and since then the cavity and related mutants have become model systems for ligand recognition (22)(23)(24)(25)(26)(27)(28)(29). Contributing to this status has been the commercial availability of thousands of likely ligands, many closely related to one another.…”

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confidence: 99%

Homologous ligands accommodated by discrete conformations of a buried cavity

Merski

Fischer

Balius

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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114

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Conformational change in protein–ligand complexes is widely modeled, but the protein accommodation expected on binding a congeneric series of ligands has received less attention. Given their use in medicinal chemistry, there are surprisingly few substantial series of congeneric ligand complexes in the Protein Data Bank (PDB). Here we determine the structures of eight alkyl benzenes, in single-methylene increases from benzene to n-hexylbenzene, bound to an enclosed cavity in T4 lysozyme. The volume of the apo cavity suffices to accommodate benzene but, even with toluene, larger cavity conformations become observable in the electron density, and over the series two other major conformations are observed. These involve discrete changes in main-chain conformation, expanding the site; few continuous changes in the site are observed. In most structures, two discrete protein conformations are observed simultaneously, and energetic considerations suggest that these conformations are low in energy relative to the ground state. An analysis of 121 lysozyme cavity structures in the PDB finds that these three conformations dominate the previously determined structures, largely modeled in a single conformation. An investigation of the few congeneric series in the PDB suggests that discrete changes are common adaptations to a series of growing ligands. The discrete, but relatively few, conformational states observed here, and their energetic accessibility, may have implications for anticipating protein conformational change in ligand design.

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confidence: 99%

Homologous ligands accommodated by discrete conformations of a buried cavity

Merski

Fischer

Balius

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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114

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“…The time of calculation was 3.9 h on 468 CPUs. The molecules were scored for receptor complementarity based on the sum of their van der Waals [using the AMBER potential (12)] and electrostatic interaction energies [using ligand probe charges in an electrostatic potential calculated by DelPhi (13,21,22)], corrected for ligand desolvation (adapted from ref. 14).…”

Section: Resultsmentioning

confidence: 99%

Structure-based discovery of β ₂ -adrenergic receptor ligands

Kolb

Rosenbaum

Irwin

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

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Aminergic G protein-coupled receptors (GPCRs) have been a major focus of pharmaceutical research for many years. Due partly to the lack of reliable receptor structures, drug discovery efforts have been largely ligand-based. The recently determined X-ray structure of the ␤2-adrenergic receptor offers an opportunity to investigate the advantages and limitations inherent in a structure-based approach to ligand discovery against this and related GPCR targets. Approximately 1 million commercially available, ''lead-like'' molecules were docked against the ␤2-adrenergic receptor structure. On testing of 25 high-ranking molecules, 6 were active with binding affinities <4 M, with the best molecule binding with a Ki of 9 nM (95% confidence interval 7-10 nM). Five of these molecules were inverse agonists. The high hit rate, the high affinity of the most potent molecule, the discovery of unprecedented chemotypes among the new inhibitors, and the apparent bias toward inverse agonists among the docking hits, have implications for structure-based approaches against GPCRs that recognize small organic molecules.docking ͉ GPCR ͉ inverse agonists ͉ library bias ͉ ligand design

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“…Docking calculations were judged to be more or less successful based on their ability to enrich known ligands among the topscoring docked molecules. Enrichment was evaluated using four criteria: the maximum "enrichment factor" 13 of the known ligands among the ranked hits (Table 2), the percentage of the docking-ranked MDDR database necessary to look through to find 25% of the known ligands (Table 2), overall profiles of enrichment factors and percentage of ligands found as a function of the percentage of the ranked database (Figures 1 and 2), and the geometry of the docked ligands compared to that observed crystallographically (Figures 3 and 4). The "enrichment factor" is defined as the number of known ligands found, at any given point in the docked-ranked list of compounds, divided by the number of ligands one would expect to find at random.…”

Section: Resultsmentioning

confidence: 99%

“…39 The database used here extends this ligand ensemble by a fully hierarchical organization of ligand conformational information, reducing redundancy throughout the "tree" of ligand conformations and not just in the rigid fragment alone as in the previous implementation. 39 Partial atomic charges, solvation energies, 13 and van der Waals parameters 40 for the ligands were calculated as previously described.…”

Section: Methodsmentioning

confidence: 99%

“…Each energy score was adjusted by an electrostatic and an apolar desolvation term calculated for each ligand by the program AMSOL, as described. 13 This precalculated desolvation penalty from AMSOL calculates the cost of moving the ligand from water to a dielectric of 2. This desolvation cost was based on the orientation adopted by the ligand in the binding site according to how buried any given ligand atom was by the receptor.…”

Section: Methodsmentioning

confidence: 99%

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Information Decay in Molecular Docking Screens against Holo, Apo, and Modeled Conformations of Enzymes

2003

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Molecular docking uses the three-dimensional structure of a receptor to screen a small molecule database for potential ligands. The dependence of docking screens on the conformation of the binding site remains an open question. To evaluate the information loss that occurs as the active site conformation becomes less defined, a small molecule database was docked against the holo (ligand bound), apo, and homology modeled structures of 10 different enzyme binding sites. The holo and apo representations were crystallographic structures taken from the Protein Data Bank (PDB), and the homology-modeled structures were taken from the publicly available resource ModBase. The database docked was the MDL Drug Data Report (MDDR), a functionally annotated database of 95 000 small molecules that contained at least 35 ligands for each of the 10 systems. In all sites, at least 99% of the molecules in the MDDR were treated as nonbinding decoys. For each system, the holo, apo, and modeled structures were used to screen the MDDR, and the ability of each structure to enrich the known ligands for that system over random selection was evaluated. The best overall enrichment was produced by the holo structure in seven systems, the apo structure in two systems, and the modeled structure in one system. These results suggest that the performance of the docking calculation is affected by the particular representation of the receptor used in the screen, and that the holo structure is the one most likely to yield the best discrimination between known ligands and decoy molecules, but important exceptions to this rule also emerge from this study. Although each of the holo, apo, and modeled conformations led to enrichment of known ligands in all systems, the enrichment did not always rise to a level judged to be sufficient to justify the effort of a docking screen. Using a 20-fold enrichment of known ligands over random selection as a rough guideline for what might be enough to justify a docking screen, the holo conformation of the enzyme met this criterion in eight of 10 sites, whereas the apo conformation met this criterion in only two sites and the modeled conformation in three.

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A Model Binding Site for Testing Scoring Functions in Molecular Docking

Cited by 216 publications

References 68 publications

Homologous ligands accommodated by discrete conformations of a buried cavity

Homologous ligands accommodated by discrete conformations of a buried cavity

Structure-based discovery of β ₂ -adrenergic receptor ligands

Information Decay in Molecular Docking Screens against Holo, Apo, and Modeled Conformations of Enzymes

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A Model Binding Site for Testing Scoring Functions in Molecular Docking

Cited by 216 publications

References 68 publications

Homologous ligands accommodated by discrete conformations of a buried cavity

Homologous ligands accommodated by discrete conformations of a buried cavity

Structure-based discovery of β 2 -adrenergic receptor ligands

Information Decay in Molecular Docking Screens against Holo, Apo, and Modeled Conformations of Enzymes

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Product

Resources

About

Structure-based discovery of β ₂ -adrenergic receptor ligands