A preference-based free-energy parameterization of enzyme-inhibitor binding. Applications to HIV-1-protease inhibitor design

Wallqvist, Anders; Jernigan, Robert L.; Covell, David G.

doi:10.1002/pro.5560040923

Cited by 121 publications

(100 citation statements)

References 153 publications

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“…Each of these possible binding arrangements is further refined to determine those positions with the maximum binding strength between ligand and target protein. A previously published model of ligand binding (18) was used to select the best binding geometries. This model is based on the atomic preferences of adjacent surfaces buried within a binding interface (18).…”

Section: Methodsmentioning

confidence: 99%

“…A previously published model of ligand binding (18) was used to select the best binding geometries. This model is based on the atomic preferences of adjacent surfaces buried within a binding interface (18). The model has been shown to predict accurately ligand binding strengths and assess the relative contributions of atomic interactions within a binding interface (17).…”

Section: Methodsmentioning

confidence: 99%

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Mapping the Binding Site of Colchicinoids on β-Tubulin

Bai¹,

Covell²,

Pei³

et al. 2000

Journal of Biological Chemistry

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2-Chloroacetyl-2-demethylthiocolchicine (2CTC) and 3-chloroacetyl-3-demethylthiocolchicine (3CTC) resemble colchicine in binding to tubulin and react covalently with ␤-tubulin, forming adducts with cysteine residues 239 and 354. The adducts at Cys-239 are less stable than those at Cys-354 during formic acid digestion. Extrapolating to zero time, the Cys-239 to Cys-354 adduct ratio is 77:23 for 2CTC and 27:73 for 3CTC. Using energy minimization modeling to dock colchicinoids into the electron crystallographic model of ␤-tubulin in protofilaments (Nogales, E., Wolf, S. G., and Downing, K. H. (1998) Nature 391, 199 -203), we found two potential binding sites. At one, entirely encompassed within ␤-tubulin, the C2-and C3-oxygen atoms of 2CTC and 3CTC overlapped poorly with those of colchicine and thiocolchicine, but distances from the reactive carbon atoms of the analogs to the sulfur atoms of the cysteine residues were qualitatively consistent with reactivity. The other potential binding site was located at the ␣/␤ interface. Here, the oxygen atoms of the analogs overlapped well with those of colchicine, but relative distances of the reactive carbons to the cysteine sulfur atoms did not correlate with the observed reactivity. A significant conformational change must occur in the colchicine binding site of tubulin in the transition from the unpolymerized to the polymerized state.Despite the interaction of tubulin with a large number of drugs that inhibit or promote its assembly into microtubules, precise definition of drug binding sites on the protein has not been possible. This is a consequence of the lack of success in crystallizing the protein, probably because of its sequence and post-translational heterogeneity, its instability, and its tendency to form oligomers and polymers of highly aberrant morphology in the presence of many of these drugs. The recent electron crystallographic determination of a relatively detailed structure for zinc-induced antiparallel tubulin protofilaments has provided insights into the paclitaxel/docetaxel site on these protofilaments, since docetaxel was used to enhance their stability during data accumulation (1), and provided a scaffold on which to model other drug sites (2). A limitation in such analysis, however, is that drugs that inhibit assembly have limited ability to bind to tubulin polymers containing linear protofilaments.Alternative approaches to obtain preliminary information about drug binding sites have included "direct" photoaffinity labeling (e.g. Ref.3), analog photoaffinity labeling (e.g. Ref. 4), and cross-link formation with chemically reactive analogs that retain biological activity (e.g. Ref. 5). In the first method, a drug-tubulin complex is exposed to light of an appropriate wave-length, and ligand-protein cross-link formation is evaluated. In the second, an active drug analog containing a photoreactive moiety is prepared and bound to tubulin, and crosslink formation is induced by exposure of the complex to light of an appropriate wavelength. In the third metho...

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Mapping the Binding Site of Colchicinoids on β-Tubulin

Bai¹,

Covell²,

Pei³

et al. 2000

Journal of Biological Chemistry

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show abstract

“…Docking studies were completed with a computational method developed for placing candidate ligands into possible binding sites. Previous calibration of this procedure found the correct binding position for over 93% of the known crystal complexes studies at the time of analysis (38,39). Docking is achieved in three successive steps, each with increasing demands for scoring acceptable binding positions.…”

Section: Fig 2 Coomassie Blue-stained Membrane (Track A) and Its Aumentioning

confidence: 99%

Direct Photoaffinity Labeling by Dolastatin 10 of the Amino-terminal Peptide of β-Tubulin Containing Cysteine 12

Bai

Covell

Taylor

et al. 2004

Journal of Biological Chemistry

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The subunit protein of microtubules, the ␣␤-tubulin heterodimer, has a number of ligand-binding sites. These include the exchangeable and nonexchangeable GTP-binding sites and at least three reasonably well characterized sites that bind antimitotic drugs. The electron crystallographic model of the tubulin sheet polymer formed in the presence of zinc and paclitaxel and composed of antiparallel protofilaments has provided relatively detailed information about the locations of the nucleotide-binding sites and the paclitaxel site on the ␣␤-dimer (1).

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“…A range of different approaches have been used; for instance FEP [4][5][6], LIEA [7,8] and empirical methods such as QSAR [9], CoMFA [10,11], 'master equation' approaches [12][13][14], total energy correlation [15], 'knowledge-based' methods [16][17][18][19] and methods like CScore [20] and X-Score [21] which combine different approaches. The empirical methods, often called scoring functions, are directly derived from observed inhibition strengths by correlating these strengths to components that are thought to be important for the binding process.…”

Section: Introductionmentioning

confidence: 99%

Inhibition and substrate recognition – a computational approach applied to HIV protease

Vinkers

Jonge

Daeyaert

et al. 2003

J Comput Aided Mol Des

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SummaryWe have developed a computational approach in which an inhibitor's strength is determined from its interaction energy with a limited set of amino acid residues of the inhibited protein. We applied this method to HIV protease. The method uses a consensus structure built from X-ray crystallographic data. All inhibitors are docked into the consensus structure. Given that not every ligand-protein interaction causes inhibition, we implemented a genetic algorithm to determine the relevant set of residues. The algorithm optimizes the q 2 between the sum of interaction energies and the observed inhibition constants. The best possible predictive model resulting has a q 2 of 0.63. External validation by examining the predictivity for compounds not used in derivation of the model leads to a prediction accuracy between 0.9 and 1.5 log 10 unit. Out of 198 residues in the whole protein, the best internally predictive model defines a subset of 20 residues and the best externally predictive model one of 9 residues. These residues are distributed over the subsites of the enzyme. This approach provides insight in which interactions are important for inhibiting HIV protease and it allows for quantitative prediction of inhibitor strength.

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A preference-based free-energy parameterization of enzyme-inhibitor binding. Applications to HIV-1-protease inhibitor design

Cited by 121 publications

References 153 publications

Mapping the Binding Site of Colchicinoids on β-Tubulin

Mapping the Binding Site of Colchicinoids on β-Tubulin

Direct Photoaffinity Labeling by Dolastatin 10 of the Amino-terminal Peptide of β-Tubulin Containing Cysteine 12

Inhibition and substrate recognition – a computational approach applied to HIV protease

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