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PubMed2002

Computer-aided design of selective COX-2 inhibitors: comparative molecular field analysis, comparative molecular similarity indices analysis, and docking studies of some 1,2-diarylimidazole derivatives.

Comparative molecular field analysis and comparative molecular similarity indices analysis were performed on 114 analogues of 1,2-diarylimidazole to optimize their cyclooxygenase-2 (COX-2) selective antiinflammatory activities. These studies produced models with high correlation coefficients and good predictive abilities. Docking studies were also carried out wherein these analogues were docked into the active sites of both COX-1 and COX-2 to analyze the receptor ligand interactions that confer selectivity for COX-2. The most active molecule in the series (53) adopts an orientation similar to that of SC-558 (4-[5-(4-bromophenyl)-3-trifluoromethyl-1H-1-pyrozolyl]-1-benzenesulfonamide) inside the COX-2 active site while the least active molecule (101) optimizes in a different orientation. In the active site, there are some strong hydrogen-bonding interactions observed between residues His90, Arg513, and Phe518 and the ligands. Additionally, a correlation of the quantitative structure-activity relationship data and the docking results is found to validate each other and suggests the importance of the binding step in overall drug action.

Binding Sites↗
PubMed2003

Rational design of an indolebutanoic acid derivative as a novel aldose reductase inhibitor based on docking and 3D QSAR studies of phenethylamine derivatives.

A series of 45 phenethylamine derivatives were synthesized and evaluated for their inhibitory activity against pig kidney aldose reductase (ALR2, EC 1.1.1.21). Their IC(50) values ranged from 400 microM to 24 microM. The binding modes of compounds at the active site of ALR2 were examined using flexible docking. The results indicated that phenethylamine derivatives nicely fit into the active pocket of ALR2 by forming various hydrogen bonding and hydrophobic interactions. 3D-QSAR analysis was also conducted using FlexX-docked alignment of the compounds. The best prediction was obtained by CoMSIA combined with hydrophobic and hydrogen bond donor/acceptor field (q(2) = 0.557, r(2) = 0.934). A new derivative, 4-oxo-4-(4-hydroxyindole)butanoic acid, was designed, taking into account the CoMSIA field and the binding mode derived by FlexX docking. This rationally designed compound exhibits an ALR2 inhibition with an IC(50) value of 7.4 microM, which compares favorably to that of a well-known ALR2 inhibitor, tolrestat (IC(50) = 16 microM) and represents a potency approximately 240-fold higher than that of an original phenethylamine lead compound, YUA001.

Aldehyde Reductase↗
PubMed2002

Docking of flexible molecules using multiscale ligand representations.

Structural genomics will yield an immense number of protein three-dimensional structures in the near future. Automated theoretical methodologies are needed to exploit this information and are likely to play a pivotal role in drug discovery. Here, we present a fully automated, efficient docking methodology that does not require any a priori knowledge about the location of the binding site or function of the protein. The method relies on a multiscale concept where we deal with a hierarchy of models generated for the potential ligand. The models are created using the k-means clustering algorithm. The method was tested on seven protein-ligand complexes. In the largest complex, human immunodeficiency virus reverse transcriptase/nevirapin, the root mean square deviation value when comparing our results to the crystal structure was 0.29 A. We demonstrate on an additional 25 protein-ligand complexes that the methodology may be applicable to high throughput docking. This work reveals three striking results. First, a ligand can be docked using a very small number of feature points. Second, when using a multiscale concept, the number of conformers that require to be generated can be significantly reduced. Third, fully flexible ligands can be treated as a small set of rigid k-means clusters.

Algorithms↗
PubMed2002

Docking into knowledge-based potential fields: a comparative evaluation of DrugScore.

A new application of DrugScore is reported in which the knowledge-based pair potentials serve as objective function in docking optimizations. The Lamarckian genetic algorithm of AutoDock is used to search for favorable ligand binding modes guided by DrugScore grids as representations of the protein binding site. The approach is found to be successful in many cases where DrugScore-based re-ranking of already docked ligand conformations does not yield satisfactory results. Compared to the AutoDock scoring function, DrugScore yields slightly superior results in flexible docking.

Algorithms↗
PubMed2004

Finding more needles in the haystack: A simple and efficient method for improving high-throughput docking results.

The technology underpinning high-throughput docking (HTD) has developed over the past few years to where it has become a vital tool in modern drug discovery. Although the performance of various docking algorithms is adequate, the ability to accurately and consistently rank compounds using a scoring function remains problematic. We show that by employing a simple machine learning method (naïve Bayes) it is possible to significantly overcome this deficiency. Compounds from the Available Chemical Directory (ACD), along with known active compounds, were docked into two protein targets using three software packages. In cases where HTD alone was able to show some enrichment, the application of naïve Bayes was able to improve upon the enrichment. The application of this methodology to enrich HTD results can be carried out without a priori knowledge of the activity of compounds and results in superior enrichment of known actives compared to the use of scoring methods alone.

Bayes Theorem↗
PubMed2004

Validation of molecular docking calculations involving FGF-1 and FGF-2.

A predictive relationship between calculated and observed binding affinities for the complexation of ligands to the fibroblast growth factors FGF-1 and FGF-2 based on molecular docking calculations is described. The majority of the ligands examined in this study have high conformational flexibility, and to account for this, multiple conformers were generated for each and subsequently used in flexible docking calculations. Two scoring functions, Gscore and Emodel, were used to quantify the protein:ligand interaction of which the Emodel score showed the best correlation with experimental binding energies. Both scoring functions, however, predicted similar locations for the ligand sulfate groups in the binding site. The van der Waals radii of nonpolar atoms of both the protein and ligand, which modify the effective sizes of both the protein binding site and the ligand, were also systematically altered by factors of 1.0, 0.9, and 0.8 in order to optimize the conditions for predictive docking. Least squares analyses of the Emodel scores against experimental binding energies yielded best r(2) values of 0.91 and 0.83 for FGF-1 and FGF-2, respectively, with slightly lower q(2) values. Optimized scale factor combinations in conjunction with the least squares lines of best fit based on the Emodel function were used to define a predictive model that was tested against ligands not included in the original set. Acceptable predictions of binding affinity were obtained for use in the initial screening of potential leadlike molecules for both FGF-1 and FGF-2.

Binding Sites↗
PubMed2004

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

Acetylcholinesterase↗
PubMed2003

Discovery of a potent and selective protein kinase CK2 inhibitor by high-throughput docking.

To assess the potential of protein kinase CK2 as a target for developing new antitumor agents, we have undertaken a search for inhibitors of this enzyme. As part of this effort, we report here the discovery of the potent and selective CK2 inhibitor (5-oxo-5,6-dihydroindolo[1,2-a]quinazolin-7-yl)acetic acid. We identified this inhibitor of a novel structural type by high-throughput docking of our corporate compound collection in the ATP binding site of a homology model of human CK2, using an appropriate protocol. The synthesis of the inhibitor as well as that of related analogues whose CK2 inhibitory activities give support to the binding mode proposed by the docking program is described. The results obtained suggest that virtual screening of a 3D database by molecular docking is a useful approach for lead finding provided that adapted postdocking filtering and reranking procedures are applied to the primary hit list.

Acetates↗
PubMed2005

Optimization and validation of a docking-scoring protocol; application to virtual screening for COX-2 inhibitors.

To exploit available structural information about the cyclooxygenase enzyme for the virtual screening of large chemical libraries, a docking-scoring protocol was tuned and validated. The screening accuracy was assessed using a series of known inhibitors and a set of diverse a priori inactive compounds that was seeded with known active ligands. The major parameters of the DOCK algorithm were investigated. A large improvement of the results was obtained on tweaking some of them. The generated complexes were rescored using six scoring functions. In this way, the striking importance of this step was demonstrated, as well as the good performances of DOCK energy and SCORE for this target. The results were further improved via a consensus approach. As a first application, a subset of a large compound library was screened using this protocol. Among the compounds that were selected for biological testing, a third of them turned out to have a significant enzyme inhibition.

Crystallography, X-Ray↗
PubMed2004

Assessment of multiple binding modes in ligand-protein docking.

Computational ligand-protein docking is routinely used for binding mode prediction. We have quantified the effect of considering multiple docking solutions on the success rate of obtaining the crystallographic binding mode. By selection of a small set of representatives, the experimentally observed binding mode can be predicted with a higher probability after a ligand-protein docking simulation. The proportion of correctly predicted complexes improved from 69% to 87% when five distinct binding modes were considered.

Crystallography, X-Ray↗
PubMed2005

Receptor flexibility in de novo ligand design and docking.

One of the major problems in computational drug design is incorporation of the intrinsic flexibility of protein binding sites. This is particularly crucial in ligand binding events, when induced fit can lead to protein structure rearrangements. As a consequence of the huge conformational space available to protein structures, receptor flexibility is rarely considered in ligand design procedures. In this work, we present an algorithm for integrating protein binding-site flexibility into de novo ligand design and docking processes. The approach allows dynamic rearrangement of amino acid side chains during the docking and design simulations. The impact of protein conformational flexibility is investigated in the docking of highly active inhibitors in the binding sites of acetylcholinesterase and human collagenase (matrix metalloproteinase-1) and in the design of ligands in the S1' pocket of MMP-1. The results of corresponding simulations for both rigid and flexible binding sites are compared in order to gauge the influence of receptor flexibility in drug discovery protocols.

Acetylcholinesterase↗
PubMed2005

Design and synthesis of new nonsteroidal glucocorticoid modulators through application of an "agreement docking" method.

Structurally related glucocorticoid receptor (GR) binders were docked into the GR active site to select the binding mode closest to the true docking mode. This process, termed an "agreement docking method", led to the design of tetrahydronaphthalene 9. The method was validated by the syntheses of 9 and related analogues, which are potent binders of GR. 15a is a partial agonist while 9e and 15a are micromolar antagonists in a mouse mammary tumor virus transactivation assay.

Animals↗
PubMed2006

Homology modeling of the serotonin 5-HT1A receptor using automated docking of bioactive compounds with defined geometry.

This paper describes a rhodopsin-based model of 5-HT(1A) serotonin receptor. The flexibility of the receptor was considered by using large number of models for ligand dockings. Rearrangements of the heptahelical bundle were introduced, which resulted in the improvement of correlation between computational results and experimental data. The model was validated by automated docking of conformationally restricted arylpiperazines. Specific interactions, responsible for the recognition of arylpiperazine derivatives, were identified. An ionic bond was formed between the protonated amine of ligands and Asp3.32. The aromatic moiety and its substituents specifically interacted with Phe6.52 and Ser5.42, respectively, while the carbonyl groups of imide part of ligands formed hydrogen bonds with Asn7.39 and Tyr7.43. The model reproduced the binding affinity of the test group of ligands (correlation r = 0.8 between pK(i) and docking score). It also gave the enrichment in virtual screening-like experiment (100 compounds), in which 34 high-affinity compounds were found among 50 top-scored ligands.

Binding Sites↗
PubMed2006

Docking of aminoglycosides to hydrated and flexible RNA.

Although much effort has been devoted to the development of programs suited for the docking of ligands to proteins, much less progress has been achieved in the nucleic acid field. We have developed a unique approach for docking aminoglycosides to RNA considering the flexibility of these macromolecules using conformational ensembles and accounting for the role of the first hydration shell. This concept, successfully implemented in AutoDock, relies on the computation of the intermolecular interaction energy that accounts for the presence of dynamically bound water molecules to the RNA. As an application, a set of 11 aminoglycosides was docked with an average root-mean-square deviation (RMSD) of 1.41 A to be compared with an average RMSD of 3.25 A when the original AutoDock protocol was used.

Aminoglycosides↗
PubMed2006

Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.

A novel scoring function to estimate protein-ligand binding affinities has been developed and implemented as the Glide 4.0 XP scoring function and docking protocol. In addition to unique water desolvation energy terms, protein-ligand structural motifs leading to enhanced binding affinity are included: (1) hydrophobic enclosure where groups of lipophilic ligand atoms are enclosed on opposite faces by lipophilic protein atoms, (2) neutral-neutral single or correlated hydrogen bonds in a hydrophobically enclosed environment, and (3) five categories of charged-charged hydrogen bonds. The XP scoring function and docking protocol have been developed to reproduce experimental binding affinities for a set of 198 complexes (RMSDs of 2.26 and 1.73 kcal/mol over all and well-docked ligands, respectively) and to yield quality enrichments for a set of fifteen screens of pharmaceutical importance. Enrichment results demonstrate the importance of the novel XP molecular recognition and water scoring in separating active and inactive ligands and avoiding false positives.

Algorithms↗
PubMed2006

Construction of human ghrelin receptor (hGHS-R1a) model using a fragmental prediction approach and validation through docking analysis.

The objective of this study was to investigate the reliability of a fragmental approach to build a full-length model of the human ghrelin receptor (hGHS-R1a) in its open state. The soundness of the model was verified by docking the tetrapeptide Gly-Ser-Ser(n-octanoyl)-Phe-NH2, which represents the ghrelin active core, and a dataset of 35 peptidomimetic GH secretagogues taken from literature. Docking results confirm the relevance of two distinct subpockets: a polar cavity bearing the key residues involved in receptor activation and an aromatic/apolar subpocket, which plays a crucial role in determining the high constitutive activity of hGHS-R1a. The docking scores of both subpockets are in remarkable agreement with biological data, emphasizing that the model can be used to predict the activity of novel ligands. Moreover, the subpocket selectivity of peptidomimetic GHSs suggests a cooperative role of the aromatic/apolar subpocket. Taken globally, the results highlight the potential of the fragmental approach to build improved models for any GPCR.

Binding Sites↗
PubMed1997

A new approach to docking in the beta 2-adrenergic receptor that exploits the domain structure of G-protein-coupled receptors.

A novel technique for docking ligands to the beta 2-adrenergic receptor is described which exploits the domain structure of this class of receptors. The ligands (norepinephrine, an agonist; pindolol, a partial agonist; and propranolol, an antagonist) were docked into the receptor using the key conserved aspartate on helix 3 (D113) as an initial guide to the placement of the amino group and GRID maps (Goodford, P. J. J. Med. Chem, 1985, 28, 849) to identify the likely binding regions of the hydrophobic (and hydroxyl) moieties on the A domain (comprising of helices 1-5). The essence of the new approach involved pulling the B domain, which includes helices 6 and 7, away from the other domain by 5-7 A. During the subsequent minimization and molecular dynamics, the receptor ligand complex reformed to yield structures which were very well supported by site-directed mutagenesis data. In particular, the model predicted a number of important interactions between the antagonist and key residues on helix 7 (notably Leu311 and Asn312) which have not been described in many previous computer simulation studies. The justification for this new approach is discussed in terms of (a) phase space sampling and (b) mimicking the natural domain dynamics which may include domain swapping and dimerization to form a 5,6-domain-swapped dimer. The observed structural changes in the receptor when pindolol, the partial agonist, was docked were midway between those observed for propranolol and norepinephrine. These structural changes, particularly the changes in helix-helix interactions at the dimer interface, support the idea that the receptors have a very dynamic structure and may shed some light on the activation process. The receptor model used in these studies is well supported by experiment, including site-directed mutagenesis (helices 1-7), zinc binding studies (helices 2, 3, 5, and 6), the substituted cysteine accessibility method (helices 3, 5, and 7), and site-directed spin-labeling studies (helices 3-6).

Amino Acid Sequence↗
PubMed1999

Docking of cationic antibiotics to negatively charged pockets in RNA folds.

The binding of aminoglycosides to RNA provides a paradigm system for the analysis of RNA-drug interactions. The electrostatic field around three-dimensional RNA folds creates localized and defined negatively charged regions which are potential docking sites for the cationic ammonium groups of aminoglycosides. To explore in RNA folds the electronegative pockets suitable for aminoglycoside binding, we used calculations of the electrostatic field and Brownian dynamics simulations of cation diffusion. We applied the technique on those RNA molecules experimentally known to bind aminoglycosides, namely, two tobramycin aptamers (Wang, Y.; Rando, R. R. Chem. Biol. 1995, 2, 281-290): the aminoglycoside-binding region in 16S ribosomal RNA (Moazed, S.; Noller, H. F. Nature 1987, 327, 389-394) and the TAR RNA from human immunodeficiency virus (Mei, H.-Y.; et al. Bioorg. Med. Chem. Lett. 1995, 5, 2755-2760). For the aptamers and ribosomal RNA, for which the binding sites of the aminoglycosides are known, a good agreement between negatively charged pockets and the binding positions of the drugs was found. On the basis of variations between neomycin-like and kanamycin-like aminoglycosides in the interaction with the electrostatic field of ribosomal RNA, we propose a model for the different binding specificities of these two classes of drugs. The spatial congruence between the electronegative pockets in RNA folds and binding positions of aminoglycosides was used to dock aminoglycosides to ribosomal and TAR RNAs. Molecular dynamics simulations were used to analyze possible RNA-drug interactions. Aminoglycosides inhibit the binding of the viral Tat protein to TAR RNA; however, the drug-binding sites are still unknown. Thus, our docking approach provides first structural models for TAR-aminoglycoside complexes. The RNA-drug interactions observed in the modeled complexes support the view that the antibiotics might lock TAR in a conformation with low affinity for the Tat protein, explaining the experimentally found aminoglycoside inhibition of the Tat-TAR interaction (Mei, H.-Y.; et al. Bioorg. Med. Chem. Lett. 1995, 5, 2755-2760).

Anti-Bacterial Agents↗