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PubMed2005

Differential docking of high-affinity peptide ligands to type A and B cholecystokinin receptors demonstrated by photoaffinity labeling.

Type A and B cholecystokinin (CCK) receptors are highly homologous members of the class-I family of G protein-coupled receptors that bind CCK with high affinity. However, they have divergent structural specificities, with the type A receptor requiring seven carboxyl-terminal residues including a sulfated tyrosine and the type B receptor requiring only the carboxyl-terminal tetrapeptide. The aim of this work was to utilize affinity labeling to determine spatial approximations with photolabile p-benzoyl-l-phenylalanine (Bpa) residues sited at each end of CCK as docked at the type B CCK receptor, contrasting this with analogous work using similar probes docked at the type A receptor. Both probes were fully efficacious, potent agonists that stimulated intracellular calcium in receptor-bearing CHO-CCKBR cells (EC(50) values: Bpa(24) probe, 41 +/- 9 pM; Bpa(33) probe, 15 +/- 3.3 pM). They bound specifically, with high affinity (K(i) values: Bpa(24) probe, 0.60 +/- 0.17 nM; Bpa(33) probe, 0.58 +/- 0.11 nM). Cyanogen bromide cleavage of the covalently labeled receptor suggested the first extracellular loop as the region of labeling by each probe, distinct from the type A CCK receptor regions labeled using the same probes (third loop and amino-terminal tail, respectively). This was confirmed by subsequent enzymatic and chemical cleavage of labeled wild-type and mutant receptors. Sequential cycles of Edman degradation of labeled receptor fragments identified the specific residues within loop one labeled by each probe (Bpa(24) probe labeled Phe(122); Bpa(33) probe labeled Thr(119)). This provides a direct demonstration of distinct modes of docking the same high-affinity ligand to highly homologous receptors.

Amino Acid Sequence↗
PubMed2005

Experimental validation of the docking orientation of Cdc25 with its Cdk2-CycA protein substrate.

Cdc25 phosphatases are key activators of the eukaryotic cell cycle and compelling anticancer targets because their overexpression has been associated with numerous cancers. However, drug discovery targeting these phosphatases has been hampered by the lack of structural information about how Cdc25s interact with their native protein substrates, the cyclin-dependent kinases. Herein, we predict a docked orientation for Cdc25B with its Cdk2-pTpY-CycA protein substrate by a rigid-body docking method and refine the docked models with full-scale molecular dynamics simulations and minimization. We validate the stable ensemble structure experimentally by a variety of in vitro and in vivo techniques. Specifically, we compare our model with a crystal structure of the substrate-trapping mutant of Cdc25B. We identify and validate in vivo a novel hot-spot residue on Cdc25B (Arg492) that plays a central role in protein substrate recognition. We identify a hot-spot residue on the substrate Cdk2 (Asp206) and confirm its interaction with hot-spot residues on Cdc25 using hot-spot swapping and double mutant cycles to derive interaction energies. Our experimentally validated model is consistent with previous studies of Cdk2 and its interaction partners and initiates the opportunity for drug discovery of inhibitors that target the remote binding sites of this protein-protein interaction.

Binding Sites↗
PubMedDate not supplied

Application of machine learning to improve the results of high-throughput docking against the HIV-1 protease.

We have previously reported that the application of a Laplacian-modified naive Bayesian (NB) classifier may be used to improve the ranking of known inhibitors from a random database of compounds after High-Throughput Docking (HTD). The method relies upon the frequency of substructural features among the active and inactive compounds from 2D fingerprint information of the compounds. Here we present an investigation of the role of extended connectivity fingerprints in training the NB classifier against HTD studies on the HIV-1 protease using three docking programs: Glide, FlexX, and GOLD. The results show that the performance of the NB classifier is due to the presence of a large number of features common to the set of known active compounds rather than a single structural or substructural scaffold. We demonstrate that the Laplacian-modified naive Bayesian classifier trained with data from high-throughput docking is superior at identifying active compounds from a target database in comparison to conventional two-dimensional substructure search methods alone.

Algorithms↗
PubMedDate not supplied

Expanded interaction fingerprint method for analyzing ligand binding modes in docking and structure-based drug design.

An expanded interaction fingerprint method has been developed for analyzing the binding modes of ligands in docking and structure-based design methods. Taking the basic premise of representing a ligand in terms of a binary string that denotes its interactions with a target protein, we have expanded the method to include additional interaction-specific information. By considering the hydrogen-bonding strength and/or accessibility of the hydrogen bonding groups within a binding site as well as their geometric arrangement we aim to provide a better representation of a ligand-protein interaction. These expanded methods have been applied to the postprocessing of binding poses generated in a docking study for 220 different proteins and to the analysis of ligands generated by an automated ligand-generation algorithm for the anthrax oedema factor. In the docking study, the application of the interaction fingerprint method as a postprocessing tool resulted in an increased success rate in identifying the crystallographic binding mode. In the analysis of the ligands generated for the anthrax oedema factor, the incorporation of additional interaction-specific information resulted in a more intuitive and comprehensive analysis of automated ligand-generation output.

Journal Article↗
PubMedDate not supplied

CoMFA 3D-QSAR analysis of HIV-1 RT nonnucleoside inhibitors, TIBO derivatives based on docking conformation and alignment.

HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as nonnucleoside RT inhibitors (NNRTIs) and nucleoside analogues. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTI category, there is a set of inhibitors commonly referred to as TIBO inhibitors. Fifty TIBO inhibitors were used in the work to build 3-D QSAR models. The two known crystal structures of complexes are used to investigate and validate the docking protocol. The results show that the docking simulations reproduce the crystal complexes very well with RMSDs of approximately 1 A and approximately 0.6 A for 1REV and 1COU, respectively. The alignment of molecules and "active" conformation selection are the key to a successful 3D-QSAR model by CoMFA. The flexible docking (Autodock3) was used on determination of "active" conformation and molecular alignment, and CoMFA and CoMSIA were used to develop 3D-QSAR models of 50 TIBOs in the work. The 3D-QSAR models demonstrate a good ability to predict the activity of studied compounds (r2 = 0.972, 0.944, q2 = 0.704, 0.776). It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the binding structure of the complex. The results demonstrate that the combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models.

Benzodiazepines↗
PubMedDate not supplied

Assessment of docking poses: interactions-based accuracy classification (IBAC) versus crystal structure deviations.

Six docking programs (FlexX, GOLD, ICM, LigandFit, the Northwestern University version of DOCK, and QXP) were evaluated in terms of their ability to reproduce experimentally observed binding modes (poses) of small-molecule ligands to macromolecular targets. The accuracy of a pose was assessed in two ways: First, the RMS deviation of the predicted pose from the crystal structure was calculated. Second, the predicted pose was compared to the experimentally observed one regarding the presence of key interactions with the protein. The latter assessment is referred to as interactions-based accuracy classification (IBAC). In a number of cases significant discrepancies were found between IBAC and RMSD-based classifications. Despite being more subjective, the IBAC proved to be a more meaningful measure of docking accuracy in all these cases.

Crystallography, X-Ray↗
PubMedDate not supplied

A virtual screening approach for thymidine monophosphate kinase inhibitors as antitubercular agents based on docking and pharmacophore models.

Docking and pharmacophore screening tools were used to examine the binding of ligands in the active site of thymidine monophosphate kinase of Mycobacterium tuberculosis. Docking analysis of deoxythymidine monophosphate (dTMP) analogues suggests the role of hydrogen bonding and other weak interactions in enzyme selectivity. Water-mediated hydrogen-bond networks and a halogen-bond interaction seem to stabilize the molecular recognition. A pharmacophore model was developed using 20 dTMP analogues. The pharmacophoric features were complementary to the active site residues involved in the ligand recognition. On the basis of these studies, a composite screening model that combines the features from both the docking analysis and the pharmacophore model was developed. The composite model was validated by screening a database spiked with 47 known inhibitors. The model picked up 42 of these, giving an enrichment factor of 17. The validated model was used to successfully screen an in-house database of about 500,000 compounds. Subsequent screening with other filters gave 186 hit molecules.

Antitubercular Agents↗
PubMedDate not supplied

On evaluating molecular-docking methods for pose prediction and enrichment factors.

Four of the most well-known, commercially available docking programs, FlexX, GOLD, GLIDE, and ICM, have been examined for their ligand-docking and virtual-screening capabilities. The relative performance of the programs in reproducing the native ligand conformation from starting SMILES strings for 164 high-resolution protein-ligand complexes is presented and compared. Applying only the native scoring functions, the latest versions of these four docking programs were also used to conduct virtual screening for 12 protein targets of therapeutic interest, involving both publicly available structures and AstraZeneca in-house structures. The capability of the four programs to correctly rank-order target-specific active compounds over alternative binders and nonbinders (decoys plus randomly selected compounds) and thereby enrich a small subset of a screening library is compared. Enrichments from the virtual-screening experiments are contrasted with those obtained with alternative 3D shape-matching and 2D similarity database-search methods.

Journal Article↗
PubMedDate not supplied

Flexible docking of ligands into synthetic receptors using a two-sided incremental construction algorithm.

We present a new algorithm for the fast and reliable structure prediction of synthetic receptor-ligand complexes. Our method is based on the protein-ligand docking program FlexX and extends our recently introduced docking technique for synthetic receptors, which has been implemented in the program FlexR. To handle the flexibility of the relevant molecules, we apply a novel docking strategy that uses an adaptive two-sided incremental construction algorithm which incorporates the structural flexibility of both the ligand and synthetic receptor. We follow an adaptive strategy, in which one molecule is expanded by attaching its next fragment in all possible torsion angles, whereas the other (partially assembled) molecule serves as a rigid binding partner. Then the roles of the molecules are exchanged. Geometric filters are used to discard partial conformations that cannot realize a targeted interaction pattern derived in a graph-based precomputation phase. The process is repeated until the entire complex is built up. Our algorithm produces promising results on a test data set comprising 10 complexes of synthetic receptors and ligands. The method generated near-native solutions compared to crystal structures in all but one case. It is able to generate solutions within a couple of minutes and has the potential of being used as a virtual screening tool for searching for suitable guest molecules for a given synthetic receptor in large databases of guests and vice versa.

Algorithms↗
PubMedDate not supplied

Molecular modeling studies of human A3 adenosine antagonists: structural homology and receptor docking.

Molecular modeling studies were conducted on various chemically diverse classes of human A3 adenosine receptor antagonists (hA3ANTs), such as adenines, xanthines, triazoloquinazolines, flavonoids, thiazolopyridines, 6-phenyl-1, 4-dihydropyridines, and 6-phenylpyridines. Using a combination of ab initio quantum mechanical calculations, electrostatic potential map comparison, and the steric and electrostatic alignment (SEAL) method, a general pharmacophore map for hA3ANTs has been derived. Based on the proposed pharmacophore map, we hypothesize that the receptor binding properties of different A3 antagonist derivatives are due to recognition at a common region inside the receptor binding site and, consequently, a common electrostatic potential profile. A model of the human A3 receptor, docked with the triazoloquinazoline reference ligand CGS 15953 (9-chloro-2-(2-furyl)[1,2,4]triazolo[1,5-c]quinazolin-5-amine), was built and analyzed to help interpret these results. All other antagonist structures were docked inside the receptor according to the results obtained through the steric and electrostatic alignment (SEAL) approach using the structure of CGS 15953 as a template. The receptor model was derived from primary sequence comparison, secondary structure predictions, and three-dimensional homology building, using rhodopsin as a template. An energetically refined 3D structure of the ligand-receptor complex was obtained using our recently introduced cross-docking procedure (J. Med. Chem. 1998, 41, 1456-1466), which simulates the ligand-induced reorganization of the native receptor structure.

Animals↗
PubMed2001

Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of efavirenz by docking and MM-PBSA.

In this work, a new ansatz is presented that combines molecular dynamics simulations with MM-PBSA (Molecular Mechanics Poisson-Boltzmann/surface area) to rank the binding affinities of 12 TIBO-like HIV-1 RT inhibitors. Encouraging results have been obtained not only for the relative binding free energies, but also for the absolute ones, which have a root-mean-square deviation of 1.0 kcal/mol (the maximum error is 1.89 kcal/mol). Since the root-mean-square error is rather small, this approach can be reliably applied in ranking the ligands from the databases for this important target. Encouraged by the results, we decided to apply MM-PBSA combined with molecular docking to determine the binding mode of efavirenz SUSTIVA(TM) another promising HIV-1 RT inhibitor for which no ligand-protein crystal structure had been published at the time of this work. To proceed, we define the following ansatz: Five hundred picosecond molecular dynamics simulations were first performed for the five binding modes suggested by DOCK 4.0, and then MM-PBSA was carried out for the collected snapshots. MM-PBSA successfully identified the correct binding mode, which has a binding free energy about 7 kcal/mol more favorable than the second best mode. Moreover, the calculated binding free energy (-13.2 kcal/mol) is in reasonable agreement with experiment (-11.6 kcal/mol). In addition, this procedure was also quite successful in modeling the complex and the structure of the last snapshot was quite close to that of the measured 2,3 A resolution crystal (structure the root-mean-square deviation of the 54 C(alpha) around the binding site and the inhibitor is 1.1 A). We want to point out that this result was achieved without prior knowledge of the structure of the efavirenz/RT complex. Therefore, molecular docking combined with MD simulations followed by MM-PBSA analysis is an attractive approach for modeling protein complexes a priori.

Alkynes↗
PubMed2003

HADDOCK: a protein-protein docking approach based on biochemical or biophysical information.

The structure determination of protein-protein complexes is a rather tedious and lengthy process, by both NMR and X-ray crystallography. Several methods based on docking to study protein complexes have also been well developed over the past few years. Most of these approaches are not driven by experimental data but are based on a combination of energetics and shape complementarity. Here, we present an approach called HADDOCK (High Ambiguity Driven protein-protein Docking) that makes use of biochemical and/or biophysical interaction data such as chemical shift perturbation data resulting from NMR titration experiments or mutagenesis data. This information is introduced as Ambiguous Interaction Restraints (AIRs) to drive the docking process. An AIR is defined as an ambiguous distance between all residues shown to be involved in the interaction. The accuracy of our approach is demonstrated with three molecular complexes. For two of these complexes, for which both the complex and the free protein structures have been solved, NMR titration data were available. Mutagenesis data were used in the last example. In all cases, the best structures generated by HADDOCK, that is, the structures with the lowest intermolecular energies, were the closest to the published structure of the respective complexes (within 2.0 A backbone RMSD).

Bacterial Proteins↗
PubMed2004

Antibody-catalyzed oxy-cope rearrangement: mechanism and origins of catalysis and stereoselectivity from DFT quantum mechanics and flexible docking.

Density functional theory using B3LYP and flexible ligand docking methods were used to investigate the complete potential surface for the uncatalyzed and the AZ28 antibody-catalyzed oxy-Cope reaction of 2,5-diaryl-1,5-hexadien-3-ol derivatives. The reaction mechanism is stepwise, involving a cyclohexane diyl intermediate. Theoretical deuterium isotope effects match well with those from experiment. Gas-phase transition structures show mixed preferences for the axial vs equatorial hydroxyl group, while solvation favors the axial isomer. Specific phenyl group conformations are shown to be critical to transition-state stabilization (by up to 15 kcal/mol), and the effective conformation is not that found in the hapten used to generate the germline and affinity-matured AZ28 catalytic antibodies. Docking studies support greater transition-state binding than reactant binding. Docking studies also predict the S stereoselectivity of mature AZ28 and suggest that binding modes quite different from those of the hapten might play a role in catalysis, with specific focus on ligand hydrogen bonding to Asp(H101).

Alcohols↗
PubMed2005

Picosecond dynamics of ligand interconversion in the primary docking site of heme proteins.

We have used femtosecond IR spectroscopy to probe interconversion dynamics of ligand in the primary docking site of heme proteins under physiological conditions. The docking site, fashioned with highly conserved amino acid residues, modulates ligand-binding activity by mediating the passage of ligand to and from the active binding site. Ligands in two states of the docking site interconvert on the picosecond time scale, and the rates are about 4 times slower in hemoglobin than that in myoglobin. The accurate interconversion rates on the time scale readily accessible by MD simulations can be used to refine computer simulations, which could in turn provide a detailed mechanistic picture of ligand binding in heme proteins.

Animals↗
PubMed2006

Docking of photosystem I subunit C using a constrained geometric simulation.

The elucidation of assembly pathways of multi-subunit protein complexes is a problem of great interest in structural biology and biomolecular modeling. In this study, we use a new computer algorithm for the simulation of large-scale motion in proteins to dock the subunit PsaC onto Photosystem I. We find that a complicated docking pathway involving multiple conformational changes can be quickly simulated by actively targeting only a few residues at a time to their target positions. Simulations for two possible docking scenarios are explored, and experimental approaches to distinguish between them are discussed.

Algorithms↗
PubMed1994

Docking analysis of a series of benzylamino acetylcholinesterase inhibitors with a phthalimide, benzoyl, or indanone moiety.

The enzyme-binding mode of a series of acetylcholinesterase inhibitors has been analyzed on the basis of the crystal structure of the Torpedo enzyme using docking programs DOCK and directed-DOCK. The inhibitors have a benzyl group connected to tertiary ammonium nitrogen at one end and a phthalimide, benzoyl, or indanone moiety at the other. Our modeling results have indicated that the benzyl group interacts with Trp 84, which is located near the bottom of the binding pocket and is postulated to be the quaternary ammonium binding site for acetylcholine. The other aromatic ring has been found to interact with Trp 279 at the peripheral hydrophobic site. In addition, the hydrogen-bonding interaction between a carbonyl group of the inhibitor and Tyr 121 OH seems to play an important role. Our active-orientation model is, at least qualitatively, consistent with structure-activity data for more than 50 compounds and should be useful for the design of more potent inhibitors.

Acetylcholinesterase↗
PubMed2001

Homology modeling using multiple molecular dynamics simulations and docking studies of the human androgen receptor ligand binding domain bound to testosterone and nonsteroidal ligands.

To facilitate the rational design of novel and more potent androgen receptor ligands, three-dimensional models for the human androgen receptor ligand binding domain bound to testosterone have been developed. These models of the androgen receptor were based on the crystal structure of the highly homologous human progesterone receptor ligand binding domain. The homology modeled androgen receptor was refined using unrestrained multiple molecular dynamics simulations in explicit solvent. Key H-bonding partners with the 17-hydroxy group and 3-keto group of testosterone are Asn705 and Thr877, and Gln711 and Arg752, respectively. These models show the presence of a unique unoccupied cavity within the androgen receptor binding pocket which may be valuable in the development of novel selective androgen receptor ligands. A qualitative analysis of amino acid mutations within the hAR binding pocket that affect ligand binding are consistent with these androgen receptor models. In addition to testosterone, the binding modes of several hydroxyflutamide-like nonsteroidal ligands for the androgen receptor are investigated using flexible docking with FlexX followed by refinement of the initial complexes with molecular dynamics simulations. These docking studies indicate that Asn705 is an important determinant in binding hydroxyflutamide and its derivatives by participating in H-bond interactions with the alpha-hydroxy moiety of these ligands. In addition, the nitro functionality mimics the 3-keto group of the natural ligand testosterone and is involved in H-bonding interactions with Gln711 and Arg752. From these docking studies, we suggest a mechanism for the enantioselective binding of chiral hydroxyflutamide derivatives and expand upon the previously reported structure-activity relationship for hydroxyflutamide and its derivatives.

Amino Acid Substitution↗
PubMed2002

CoMFA and CoMSIA 3D QSAR and docking studies on conformationally-restrained cinnamoyl HIV-1 integrase inhibitors: exploration of a binding mode at the active site.

Anti-HIV (human immunodeficiency virus) drug discovery has been increasingly focusing on HIV integrase (IN) as a potential therapeutic target. This enzyme is required for the integration of reverse transcribed proviral DNA into the host cell's genome and is essential for the propagation of the HIV life cycle. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) three-dimensional quantitative structure-activity relationship (3D QSAR) studies and docking simulations were conducted on a series of potent conformationally restrained cinnamoyl inhibitors of HIV-1 IN (Artico; et al. J. Med. Chem. 1998, 41, 3948-3960). Predictive 3D QSAR models were established using SYBYL multifit molecular alignment rule, which had conventional r(2) and cross-validated coeffiecient (q(2)) values up to 0.981 and 0.721 for CoMFA and 0.975 and 0.804 for CoMSIA, respectively. These models were validated by an external test set (Burke; et al. J. Med. Chem. 1995, 38, 4171-4178). CoMFA and CoMSIA 3D QSAR models were also derived using a molecular alignment obtained by docking the compounds into the active site of HIV IN. These latter models were comparable to multifit-derived models in terms of relative descriptor field contributions and the partial least squares (PLS) contour maps. The CoMSIA 3D QSAR models performed better than the CoMFA models. The superior performance of CoMSIA was attributed to the large contribution of hydrogen-bonding interactions to the inhibitory activity differences among the compounds. This was supported by FlexX binding energy scores that correlated well with the inhibitory activity differences between hydroxylated compounds and their corresponding methoxy or deoxy counterparts. The CoMFA and CoMSIA PLS contour maps and MOLCAD-generated active site electrostatic, lipophilicity, and hydrogen-bonding potential surface maps, as well as the docking results, were integrated to propose a binding mode for the cinnamoyl inhibitors at the active site of HIV-1 IN.

Binding Sites↗