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PubMed2002

Modeling of binding modes and inhibition mechanism of some natural ligands of farnesyl transferase using molecular docking.

Several natural inhibitors of farnesyl transferase have been reported in the literature: some compounds are competitive with farnesyl pyrophosphate (FPP), whereas other ones are competitive with Ras proteins, even though it is usually hard to highlight their inhibition mechanism, which is still unknown for several natural compounds. The aim of this work is to show that the molecular docking analysis can be successfully used to underline the inhibition mechanism of these natural compounds. First, the selected compounds were subjected to a detailed docking analysis, by means of BioDock, a program able to reveal the most likely binding mode for each ligand. By comparing these results with the binding sites for the natural substrates, earlier determined, it was possible to highlight the site specificity and the inhibition mechanism of the selected compounds. In addition, it is possible to relate the binding mode of these molecules with their lipole values, which is appreciably less for peptidomimetics than for FPP mimetic and reveals a straightforward method to predict and to understand the inhibition mechanism of these natural derivatives.

Alkyl and Aryl Transferases↗
PubMed2002

Molecular docking and 3D-QSAR studies on gag peptide analogue inhibitors interacting with human cyclophilin A.

The interaction of a series gag peptide analogues with human cyclophilin A (hCypA) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) and divide-and-conquer methods were applied to locate the binding orientations and conformations of the inhibitors interacting with hCypA. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. A novel interaction model was identified for inhibitors 11, 15, and 17 whose N-termini were modified by addition of the deaminovaline (Dav) group and the C-termini of 15 and 17 were modified by addition of a benzyl group. Accordingly, two new binding sites (sites A and D in Figure 1) were revealed, which show a strong correlation with inhibitor potency and thus can be used as a starting point for new inhibitor design. In addition, two predictive 3D-QSAR models were obtained by CoMFA and CoMSIA analyses based on the binding conformations derived from the molecular docking calculations. The reasonable r(cross)(2) (cross-validated) values 0.738 and 0.762 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four peptide analogues test set. The CoMFA and CoMSIA field distributions are in general agreement with the structural characteristics of the binding groove of hCypA. This indicates the reasonableness of the binding model of the inhibitors with hCypA. Considering all these results together with the valuable clues of binding from references published recently, reasonable pharmacophore elements have been suggested, demonstrating that the 3D-QSAR models about peptide analogue inhibitors are expected to be further employed in predicting activities of the novel compounds for inhibiting hCypA.

Binding Sites↗
PubMed2003

Comparative evaluation of 11 scoring functions for molecular docking.

Eleven popular scoring functions have been tested on 100 protein-ligand complexes to evaluate their abilities to reproduce experimentally determined structures and binding affinities. They include four scoring functions implemented in the LigFit module in Cerius2 (LigScore, PLP, PMF, and LUDI), four scoring functions implemented in the CScore module in SYBYL (F-Score, G-Score, D-Score, and ChemScore), the scoring function implemented in the AutoDock program, and two stand-alone scoring functions (DrugScore and X-Score). These scoring functions are not tested in the context of a particular docking program. Instead, conformational sampling and scoring are separated into two consecutive steps. First, an exhaustive conformational sampling is performed by using the AutoDock program to generate an ensemble of docked conformations for each ligand molecule. This conformational ensemble is required to cover the entire conformational space as much as possible rather than to focus on a few energy minima. Then, each scoring function is applied to score this conformational ensemble to see if it can identify the experimentally observed conformation from all of the other decoys. Among all of the scoring functions under test, six of them, i.e., PLP, F-Score, LigScore, DrugScore, LUDI, and X-Score, yield success rates higher than the AutoDock scoring function. The success rates of these six scoring functions range from 66% to 76% if using root-mean-square deviation < or =2.0 A as the criterion. Combining any two or three of these six scoring functions into a consensus scoring scheme further improves the success rate to nearly 80% or even higher. However, when applied to reproduce the experimentally determined binding affinities of the 100 protein-ligand complexes, only X-Score, PLP, DrugScore, and G-Score are able to give correlation coefficients over 0.50. All of the 11 scoring functions are further inspected by their abilities to construct a descriptive, funnel-shaped energy surface for protein-ligand complexation. The results indicate that X-Score and DrugScore perform better than the other ones at this aspect.

Algorithms↗
PubMed2003

Kinases, homology models, and high throughput docking.

With the many protein sequences coming from the genome sequencing projects, it is unlikely that we will ever have an atomic resolution structure of every relevant protein. With high throughput crystallography, however, we will soon have representative structures for the vast majority of protein families. Thus the drug discovery and design process will rely heavily on protein modeling to address issues such as designing combinatorial libraries for an entire class of targets and engineering genome-wide selectivity over a target class. In this study we assess the value of high throughput docking into homology models. To do this we dock a database of random compounds seeded with known inhibitors into homology models of six different kinases. In five of the six cases the known inhibitors were found to be enriched by factors of 4-5 in the top 5% of the overall scored and ranked compounds. Furthermore, in the same five cases the known inhibitors were found to be enriched by factors of 2-3 in the top 5% of the scored and ranked known kinase inhibitors, thus showing that the homology models can pick up some of the crucial selectivity information.

Catalytic Domain↗
PubMed2003

Docking studies on alphavbeta3 integrin ligands: pharmacophore refinement and implications for drug design.

Starting from the first crystal structure of the extracellular segment of the alpha(v)beta(3) integrin receptor with a cyclic RGD ligand bound to the active site, structural models for the interactions of known ligands with the alpha(v)beta(3) integrin receptor were generated by automated computational docking. The obtained complexes were evaluated for their consistency with structure-activity relationships and site-directed mutagenesis data. A comparison between the calculated interaction free energies and the experimental biological activities was also made. All the possible interactions of the investigated compounds at the active site and the probable ligand binding conformations provide an improved basis for structure-based rational ligand design. Additionally, our docking results allow a further validation and refinement of the pharmacophore model previously postulated by us.

Algorithms↗
PubMed2003

3-(4-Aroyl-1-methyl-1H-2-pyrrolyl)-N-hydroxy-2-alkylamides as a new class of synthetic histone deacetylase inhibitors. 1. Design, synthesis, biological evaluation, and binding mode studies performed through three different docking procedures.

Recently we reported a novel series of hydroxamates, called 3-(4-aroyl-1H-2-pyrrolyl)-N-hydroxy-2-propenamides (APHAs), acting as HDAC inhibitors (Massa, S.; et al. J. Med. Chem. 2001, 44, 2069-2072). Among them, 3-(4-benzoyl-1-methyl-1H-2-pyrrolyl)-N-hydroxy-2-propenamide 1 was chosen as lead compound, and its binding mode into the modeled HDAC1 catalytic core together with its histone hyperacetylation, antiproliferative, and cytodifferentiating properties in cell-based assays were investigated (Mai, A.; et al. J. Med. Chem. 2002, 45, 1778-1784). Here we report the results of some chemical manipulations performed on (i) the aroyl portion at the C4-pyrrole position, (ii) the N(1)-pyrrole substituent, and (iii) the hydroxamate moiety of 1 to determine structure-activity relationships and to improve enzyme inhibitory activity of APHAs. In the 1 structure, pyrrole N(1)-substitution with groups larger than methyl gave a reduction in HDAC inhibiting activity, and replacement of hydroxamate function with various non-hydroxamate, metal ion-complexing groups yielded poorly active or totally inactive compounds. On the contrary, proper substitution at the C4-position favorably affected enzyme inhibiting potency, leading to 8 (IC50 = 0.1 micro M) and 9 (IC50 = 1.0 micro M) which were 38- and 3.8-fold more potent than 1 in in vitro anti-HD2 assay. Against mouse HDAC1, 8 showed an IC50 = 0.5 micro M (IC50 of 1 = 4.9 micro M), and also in cell-based assay, 8 was endowed with higher histone hyperacetylating activity than 1, although it was less potent than TSA and SAHA. Such enhancement of inhibitory activity can be explained by the higher flexibility of the pyrrole C4-substituent of 8 which accounts for a considerably better fitting into the HDAC1 pocket and a more favorable enthalpy ligand receptor energy compared to 1. The enhanced fit allows a closer positioning of 8 hydroxamate moiety to the zinc ion. These findings were supported by extensive docking studies (SAD, DOCK, and Autodock) performed on both APHAs and reference drugs (TSA and SAHA).

Acetylation↗
PubMed2004

Performance of 3D-database molecular docking studies into homology models.

The performance of docking studies into protein active sites constructed by homology model building was investigated using CDK2 and factor VIIa screening data sets. When the sequence identity between model and template near the binding site area is greater than approximately 50%, roughly 5 times more active compounds are identified than would be found randomly. This performance is comparable to docking to crystal structures.

Binding Sites↗
PubMed2004

Application of CoMFA and CoMSIA 3D-QSAR and docking studies in optimization of mercaptobenzenesulfonamides as HIV-1 integrase inhibitors.

An essential step in the HIV life cycle is integration of the viral DNA into the host chromosome. This step is catalyzed by a 32-kDa viral enzyme HIV integrase (IN). HIV-1 IN is an important and validated target, and the drugs that selectively inhibit this enzyme, when used in combination with reverse transcriptase (RT) and protease (PR) inhibitors, are believed to be highly effective in suppressing the viral replication. IN catalyzes two discrete enzymatic processes referred to as 3' processing and DNA strand transfer. As a part of a study to optimize new lead molecules we previously identified from a series of 2-mercaptobenzenesulfonamides (MBSAs), we applied three-dimensional quantitative structure-activity relationship methods, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) to training sets of up to 66 compounds. Two different conformational templates were used: Conf-d, obtained from docking into the HIV-1 IN active site and Conf-s obtained by a systematic conformational search, using lead compounds 1 and 14, respectively. Reliable models of good predictive power were obtained after removal of compounds with high residuals. The Conf-s models tended to perform better than the Conf-d models. Cross-validated coefficients (q(2)) of up to 0.719 (strand transfer CoMSIA, Conf-s) regression coefficients (r(2)) of up to 0.932 (strand transfer CoMSIA, Conf-d) were obtained, with the number of partial least squares (PLS) components varying from 3 to 6, and the number of outliers being 4 in most of the models. Because all biological data were determined under exactly the same conditions using the same enzyme preparation, our predictive models are promising for drug optimization. Therefore, these results combined with docking studies were used to guide the rational design of new inhibitors. Further synthesis of 12 new analogues was undertaken, and these were used as a test set for validation of the quantitative structure-activity relationship (QSAR) models. For compounds with closely related structures, binding energies given by the FlexX scoring function correlated with HIV-1 IN inhibitory activity.

HIV Integrase↗
PubMed2003

Docking and database screening reveal new classes of Plasmodium falciparum dihydrofolate reductase inhibitors.

Plasmodium falciparum dihydrofolate reductase (PfDHFR) is an important target for antimalarial chemotherapy. Unfortunately, the emergence of resistant parasites has significantly reduced the efficiency of classical antifolate drugs such as cycloguanil and pyrimethamine. In this study, an approach toward molecular docking of the structures contained in the Available Chemicals Directory (ACD) database to search for novel inhibitors of PfDHFR is described. Instead of docking the whole ACD database, specific 3D pharmacophores were used to reduce the number of molecules in the database by excluding a priori molecules lacking essential requisites for the interaction with the enzyme and potentially unable to bind to resistant mutant PfDHFRs. The molecules in the resulting "focused" database were then evaluated with regard to their fit into the PfDHFR active site. Twelve new compounds whose structures are completely unrelated to known antifolates were identified and found to inhibit, at the micromolar level, the wild-type and resistant mutant PfDHFRs harboring A16V, S108T, A16V + S108T, C59R + S108N + I164L, and N51I + C59R + S108N + I164L mutations. Depending on the functional groups interacting with key active site residues of the enzyme, these inhibitors were classified as N-hydroxyamidine, hydrazine, urea, and thiourea derivatives. The structures of the complexes of the most active inhibitors, as refined by molecular mechanics and molecular dynamics, provided insight into how these inhibitors bind to the enzyme and suggested prospects for these novel derivatives as potential leads for antimalarial development.

Animals↗
PubMed2004

3-(4-Aroyl-1-methyl-1H-pyrrol-2-yl)-N-hydroxy-2-propenamides as a new class of synthetic histone deacetylase inhibitors. 3. Discovery of novel lead compounds through structure-based drug design and docking studies.

Aroyl-pyrrole-hydroxy-amides (APHAs) are a new class of synthetic HDAC inhibitors recently described by us. Through three different docking procedures we designed, synthesized, and tested two new isomers of APHA lead compound 3-(4-benzoyl-1-methyl-1H-pyrrol-2-yl)-N-hydroxy-2-propenamide (1), compounds 3 and 4, characterized by different insertions of benzoyl and propenoylhydroxamate groups onto the pyrrole ring. Biological activities of 3 and 4 were predicted by computational tools up to 617-fold more potent than that of 1 against HDAC1; thus, 3 and 4 were synthesized and tested against both mouse HDAC1 and maize HD2 enzymes. Predictions of biological affinities (K(i) values) of 3 and 4, performed by a VALIDATE model (applied on either SAD or automatic DOCK or Autodock results) and by the Autodock internal scoring function, were in good agreement with experimental activities. Ligand/receptor positive interactions made by 3 and 4 into the catalytic pocket, in addition to those showed by 1, could at least in part account for their higher HDAC1 inhibitory activities. In particular, in mouse HDAC1 inhibitory assay 3 and 4 were 19- and 6-times more potent than 1, respectively, and 3 and 4 antimaize HD2 activities were 16- and 76-times higher than that of 1, 4 being as potent as SAHA in this assay. Compound 4, tested as antiproliferative and cytodifferentiating agent on MEL cells, showed dose-dependent growth inhibition and hemoglobin accumulation effects.

Amides↗
PubMed2004

Interaction of noncompetitive inhibitors with an immobilized alpha3beta4 nicotinic acetylcholine receptor investigated by affinity chromatography, quantitative-structure activity relationship analysis, and molecular docking.

A large number of drug substances act as noncompetitive inhibitors (NCIs) of the nicotinic acetylcholine receptor (nAChR) by blocking the ion flux through the channel. An affinity chromatography technique has been developed for investigating the interactions between NCIs and the alpha3beta4 subtype of neuronal nAChR. The data obtained from the chromatographic study were used to construct QSAR models of the NCI-nAChR binding with both electronic and steric parameters observed as important descriptors. A molecular model of the transmembrane domain of the alpha3beta4 subtype of nAChR was constructed and used to simulate the docking of a series of NCIs. A key aspect of the model was the discovery of the cleft produced by the incorporation of the bulky phenylalanine moiety into the nonpolar section of the lumen by the beta4 subunit. Quantitatively, the results of docking simulations modeled the experimental affinity data better than QSAR results. The computational approach, combined with the modeling of NCI-nAChR interaction by affinity chromatography, can be used to predict possible toxicities and adverse interactions.

Amino Acid Sequence↗
PubMed2005

Docking and 3-D QSAR studies on indolyl aryl sulfones. Binding mode exploration at the HIV-1 reverse transcriptase non-nucleoside binding site and design of highly active N-(2-hydroxyethyl)carboxamide and N-(2-hydroxyethyl)carbohydrazide derivatives.

Three-dimensional quantitative structure-activity relationship (3-D QSAR) studies and docking simulations were developed on indolyl aryl sulfones (IASs), a class of novel HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (Silvestri, et al. J. Med. Chem. 2003, 46, 2482-2493) highly active against wild type and some clinically relevant resistant strains (Y181C, the double mutant K103N-Y181C, and the K103R-V179D-P225H strain, highly resistant to efavirenz). Predictive 3-D QSAR models using the combination of GRID and GOLPE programs were obtained using a receptor-based alignment by means of docking IASs into the non-nucleoside binding site (NNBS) of RT. The derived 3-D QSAR models showed conventional correlation (r(2)) and cross-validated (q(2)) coefficients values ranging from 0.79 to 0.93 and from 0.59 to 0.84, respectively. All described models were validated by an external test set compiled from previously reported pyrryl aryl sulfones (Artico, et al. J. Med. Chem. 1996, 39, 522-530). The most predictive 3-D QSAR model was then used to predict the activity of novel untested IASs. The synthesis of six designed derivatives (prediction set) allowed disclosure of new IASs endowed with high anti-HIV-1 activities.

Binding Sites↗
PubMed2004

Combination of a naive Bayes classifier with consensus scoring improves enrichment of high-throughput docking results.

We have previously shown that a machine learning technique can improve the enrichment of high-throughput docking (HTD) results. In the previous cases studied, however, the application of a naive Bayes classifier failed to improve enrichment for instances where HTD alone was unable to generate an acceptable enrichment. We present here a protocol to rescue poor docking results a priori using a combination of rank-by-median consensus scoring and naive Bayesian categorization.

Algorithms↗
PubMed2006

A method for induced-fit docking, scoring, and ranking of flexible ligands. Application to peptidic and pseudopeptidic beta-secretase (BACE 1) inhibitors.

Inhibition of beta-secretase (BACE 1) has recently been investigated as a promising therapeutic approach in the treatment of Alzheimer's disease, and a growing number of BACE 1 inhibitors and crystal structures of BACE 1/inhibitors complexes have been reported. We report herein a predictive computational method and its application to potential BACE 1 inhibitors. Using a training set of 50 known highly flexible inhibitors, we developed a docking method that accounts for the flexibility of both the protein and the inhibitors. Protein flexibility is accounted for using a specifically designed genetic algorithm. We next developed a scoring function consisting of force field evaluation of the inhibitor/protein interactions and two additional terms for hydrogen bonding and entropy change upon binding. Discarding three outliers from the training set, our protocol was found to perform well with an rmsd of 1.19 kcal/mol. Evaluation of the predictive power was next carried out by virtual screening of 80 synthetic compounds. The significant enrichment at the top of the ranking list in active compounds demonstrated the ability of the docking and scoring protocol to rank the compounds relative to their activities.

Algorithms↗
PubMed2005

Fast structure-based virtual ligand screening combining FRED, DOCK, and Surflex.

A protocol was devised in which FRED, DOCK, and Surflex were combined in a multistep virtual ligand screening (VLS) procedure to screen the pocket of four different proteins. One goal was to evaluate the impact of chaining "freely available packages to academic users" on docking/scoring accuracy and CPU time consumption. A bank of 65 660 compounds including 49 known actives was generated. Our procedure is successful because docking/scoring parameters are tuned according to the nature of the binding pocket and because a shape-based filtering tool is applied prior to flexible docking. The obtained enrichment factors are in line with those reported in recent studies. We suggest that consensus docking/scoring could be valuable to some drug discovery projects. The present protocol could process the entire bank for one receptor in less than a week on one processor, suggesting that VLS experiments could be performed even without large computer resources.

Binding Sites↗
PubMed2005

Toward selective histone deacetylase inhibitor design: homology modeling, docking studies, and molecular dynamics simulations of human class I histone deacetylases.

Histone deacetylases (HDACs) play an important role in gene transcription. Inhibitors of HDACs induce cell differentiation and suppress cell proliferation in tumor cells. Although many HDAC inhibitors have been designed and synthesized, selective inhibition for class I HDAC isoforms is a goal that has yet to be achieved. To understand the difference between class I HDAC isoforms that could be exploited for the design of isoform-specific HDAC inhibitors, we have built three-dimensional models of four class I histone deacetylases, HDAC1, HDAC2, HDAC3, and HDAC8. Comparison of the homology model of HDAC8 with the recently published X-ray structure shows excellent agreement and validates the approach. A series of HDAC inhibitors were docked to the homology models to understand the similarities and differences between the binding modes. Molecular dynamic simulations of these HDAC-inhibitor complexes indicate that the interaction between the protein surface and inhibitor is playing an important role; also some active site residues show some flexibility, which is usually not included in routine docking protocols. The implications of these results for the design of isoform-selective HDAC inhibitors are discussed.

Amino Acid Sequence↗
PubMed2005

Docking studies and ligand recognition in folylpolyglutamate synthetase.

Folylpolyglutamate synthetase (FPGS) catalyzes the sequential addition of several glutamates to folate, forming gamma-linked polyglutamate folates of varying lengths. To understand how this protein is capable of accommodating ligands of different length and net charge, we have performed docking studies for folate substrates and glutamate based on the ternary crystal structure of Lactobacillus casei FPGS. Our results suggest two locations for folate binding, the one seen in the crystal structure and another distinct cavity. According to our model and experimental data, it is highly probable that folate can bind in both sites, and we suggest that the new pocket is especially important for the initial addition of the first glutamate residue. Docking longer substrates, di- and triglutamylated folates, showed how these molecules bind in the same sites. The longer folates also adopted transition-state-like conformations that may help us to understand the ligation reaction in FPGS and influence the design of mechanism-based inhibitors for anticancer or antimicrobial therapy.

Binding Sites↗
PubMed2006

Cannabinoid CB2/CB1 selectivity. Receptor modeling and automated docking analysis.

Three-dimensional models of the CB1 and CB2 cannabinoid receptors were constructed by means of a molecular modeling procedure, using the X-ray structure of bovine rhodopsin as the initial template, and taking into account the available site-directed mutagenesis data. The cannabinoid system was studied by means of docking techniques. An analysis of the interaction of WIN55212-2 with both receptors showed that CB2/CB1 selectivity is mainly determined by the interaction in the CB2 with the nonconserved residues S3.31 and F5.46, whose importance was suggested by site-directed mutagenesis data. We also carried out an automated docking of several ligands into the CB2 model, using the AUTODOCK 3.0 program; the good correlation obtained between the estimated free energy binding and the experimental binding data confirmed our binding hypothesis and the reliability of the model.

Amino Acid Sequence↗