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PubMed2005

Inhibitory mode of N-phenyl-4-pyrazolo[1,5-b] pyridazin-3-ylpyrimidin-2-amine series derivatives against GSK-3: molecular docking and 3D-QSAR analyses.

Glycogen synthase kinase 3 (GSK-3) inhibition is an important research topic because of its wide range of associated health implications. The interaction mode of a series of N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amine compounds with human GSK-3 has been studied using molecular docking and 3D-QSAR approaches. In the 3D-QSAR studies, the molecular alignment and conformation determination are so important that they affect the success of a model. Flexible docking (AutoDock3.0.5) was used for the determination of 'active' conformation and molecular alignment. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to develop 3D-QSAR models of 80 N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amine compounds. The r(2) values were 0.870 and 0.861 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by 10 compounds of the test set. Mapping these models back to the topology of the active site of GSK-3 led to a better understanding of the vital N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amines-GSK-3 interactions. The results demonstrate that combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models. The interaction mode from this study may be helpful for the design of a novel inhibitor and guide the selection of candidate sites for further experimental studies on site-directed mutagenesis.

Catalytic Domain↗

PubMed1997

A comparison of heuristic search algorithms for molecular docking.

This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone.

Algorithms↗

PubMed2004

Inhibitory mode of indole-2-carboxamide derivatives against HLGPa: molecular docking and 3D-QSAR analyses.

The interaction of a series of indole-2-carboxamide compounds with human liver glycogen phosphorylase a (HLGPa) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) of AutoDock 3.0 was employed to locate the binding orientations and conformations of the inhibitors interacting with HLGPa. The binding models were demonstrated in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding. The very similar binding conformations of these inhibitors show that they interact with HLGPa in a very similar way. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. The structural and energetic differences in inhibitory potencies of indole-2-carboxamide compounds were reasonably explored. Using the binding conformations of indole-2-carboxamides, consistent and highly predictive 3D-QSAR models were developed by CoMFA and CoMSIA analyses. The q2 values are 0.697 and 0.622 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four compounds that were not included in the training set. Mapping these models back to the topology of the active site of HLGPa leads to a better understanding of the vital indole-2-carboxamide-HLGPa interactions. Structure-based investigations and the final 3D-QSAR results provide clear guidelines and accurate activity predictions for novel inhibitor design.

Binding Sites↗

PubMed2006

Indol-1-yl acetic acids as peroxisome proliferator-activated receptor agonists: design, synthesis, structural biology, and molecular docking studies.

A series of novel indole-based PPAR agonists is described leading to discovery of 10k, a highly potent PPAR pan-agonist. The structural biology and molecular docking studies revealed that the distances between the acidic group and the linker, when a ligand was complexed with PPARgamma protein, were important for the potent activity. The hydrophobic tail part of 10k makes intensive hydrophobic interaction with the PPARgamma protein resulting in potent activity.

Binding Sites↗

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↗

PubMed2005

Ligand selectivity for the acetylcholine binding site of the rat alpha4beta2 and alpha3beta4 nicotinic subtypes investigated by molecular docking.

The homology models of the extracellular domains of the neuronal alpha4beta2 (pdb code: 1ole) and ganglionic alpha3beta4 (pdb code: 1olf) rat nicotinic acetylcholine receptor (nAChR) subtypes were refined and energetically minimized. In this work, a series of nAChR ligands (1-15) were docked into the modeled binding cavity of both receptors. High-affinity, toxic ligands such as epibatidine (1) and dechloroepibatidine (2) docked into cluster 1 with the charged tertiary amino group, forming a pi-cation interaction with Trp 147 on the (+) side of the alpha4 subunit and establishing a characteristic H-bond with the Lys 77 on the (-) side of the beta2 subunit. The nontoxic ligands such as 33bMet (3), (S)-A-85380 (4), and acetylcholine (6) docked into cluster 2 with the same pi-cation interaction but with the rest of the molecule occupying a different moiety of the binding pocket. Molecular docking into the alpha3beta4 subtype showed that both enantiomers of 1 (1a and 1b) are representative templates for ligands with affinity toward this ganglionic nAChR subtype. The ranking scores of the docked molecules confirm the existence of structure-dependent subtype selectivity and shed light on the design of specific and selective alpha4beta2 nAChR subtype ligands.

Acetylcholine↗

PubMed2004

A molecular docking study of estrogenically active compounds with 1,2-diarylethane and 1,2-diarylethene pharmacophores.

Numerous selective estrogen receptor modulators (SERMs) have been synthesized and assayed in recent years. The focus of this study is to apply coarse-grain molecular docking procedures coupled with fine-grain all-atom force field optimization strategies to shed light on the binding mechanisms of currently available estrogen receptor-active compounds. Although the mechanics of ligand binding in estrogen receptors is generally well understood, there is room for surprises. In this paper computational evidence corroborating the experimentally observed type I agonistic binding mode for estradiol (E2) and diethylstilbesterol (DES) and the type II antagonistic binding mode for 4-hydroxytamoxifen and raloxifen is presented. Included in this type I agonistic mode are the DES derivatives, transstilbene and 1,2-diaryldiaminoethane. In addition, a novel 'type II agonistic' binding mode for 2,3-diarylimidazolines, 4,5-diarylimidazoles, 2,3-diarylpiperazines is introduced. This mode is stabilized by suggesting alternative hydrogen bond anchor points in the ligand binding domain as potential leads for future drug design.

Computer Simulation↗

PubMed2002

Discovery of new inhibitors of aldose reductase from molecular docking and database screening.

Aldose reductase (ALR2) is a target enzyme for the treatment of diabetic complications. Owing to the limited number of currently available drugs for the treatment of diabetic complications, the discovery of new inhibitors of ALR2 that can potentially be optimized as drugs appears highly desirable. In this study, a molecular docking analysis of the structures of more than 127,000 organic compounds contained in the National Cancer Institute database was performed to find and score molecules that are complementary to ALR2. Besides retrieving several carboxylic acid derivatives, which are known to generally inhibit aldose reductase, docking proposed other families of putative inhibitors such as sulfonic acids, nitro-derivatives, sulfonamides and carbonyl derivatives. Twenty-five compounds, chosen as the highest-scoring representatives of each of these families, were tested as aldose reductase inhibitors. Five of them were found to inhibit aldose reductase in the micromolar range. For these active compounds, selectivity with respect to the closely-related aldehyde reductase was determined by measuring the corresponding inhibitory activities. The structures of the complexes between the new lead inhibitors and aldose reductase, here refined with molecular mechanics and molecular dynamics calculations, suggest that new pharmacophoric groups can bind aldose reductase very efficiently. In the case of the family of the nitro-derivative inhibitors, a class of particularly interesting compounds, a round of optimizations was performed with the synthesis and biological evaluation of a series of derivatives aimed at testing the proposed binding mode and at improving interaction with active site residues. Starting from a hit compound having an IC(50) of 42 microM, the most potent compound synthesized showed a 10-fold increase in inhibitory activity and 10-fold selectivity with respect to ALR1, and structure--activity relationships of the designed compounds were in agreement with the proposed mode of binding at the active site.

Aldehyde Reductase↗

PubMed2005

Molecular docking and 3D-QSAR studies on the binding mechanism of statine-based peptidomimetics with beta-secretase.

beta-Secretase is an important protease in the pathogenesis of Alzheimer's disease. Some statine-based peptidomimetics show inhibitory activities to the beta-secretase. To explore the inhibitory mechanism, molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies on these analogues were performed. The Lamarckian Genetic Algorithm (LGA) was applied to locate the binding orientations and conformations of the peptidomimetics with the beta-secretase. A good correlation between the calculated binding free energies and the experimental inhibitory activities suggests that the identified binding conformations of these potential inhibitors are reliable. Based on the binding conformations, highly predictive 3D-QSAR models were developed with q(2) values of 0.582 and 0.622 for CoMFA and CoMSIA, respectively. The predictive abilities of these models were validated by some compounds that were not included in the training set. Furthermore, the 3D-QSAR models were mapped back to the binding site of the beta-secretase, to get a better understanding of vital interactions between the statine-based peptidomimetics and the protease. Both the CoMFA and the CoMSIA field distributions are in well agreement with the structural characteristics of the binding groove of the beta-secretase. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction would be useful in developing new drug leads against Alzheimer's disease.

Algorithms↗

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↗

PubMed2006

Molecular docking simulations of steroid substrates into human cytosolic hydroxysteroid dehydrogenases (AKR1C1 and AKR1C2): insights into positional and stereochemical preferences.

AKR1C1 and AKR1C2 are human cytosolic hydroxysteroid dehydrogenases, which play pivotal roles in the metabolism and action of natural and synthetic steroid hormones. The two enzymes are highly homologous, and have distinct positional and stereochemical preferences with various substrates. We performed molecular docking simulations of three steroid substrates, including an androgen (5alpha-dihydrotestosterone, DHT), a progestin (progesterone, PRO), and a synthetic hormone ([7alpha,17alpha]-17-hydroxy-7-methyl-19-norpregn-5(10)-en-20-yn-3-one or tibolone, TIB), into the active sites of the two enzymes. For each substrate and enzyme pair, the activity inferred by the "productive" docking models (in which the spatial arrangement of the steroid and the cofactor would permit a reaction) matched the experimentally observed positional and stereochemical outcome. These productive conformations were energetically and statistically favored except for TIB and PRO with AKR1C2, where experimentally strong substrate inhibition and low activity were observed, respectively. Results showed that (i) a 3-ketosteroid (DHT) and a 20-ketosteroid (PRO) were reduced by AKR1C1 since the carbonyl groups could occupy the same position by "backwards" binding of steroids; (ii) 3alpha-reduced (DHT) and 3beta-reduced (TIB) products were formed by AKR1C2 since the angular methyl groups of the steroids were inverted by "upside-down" binding of steroids; and (iii) the 3beta- and 3alpha-reduction of DHT by AKR1C1 and AKR1C2, respectively occurred since the steroids employed a "swinging" motion to present opposite faces to the cofactor. Favorable nonproductive modes were observed with all substrates in both enzymes in which the steroid was bound at a "near-entry" position and/or an "in-middle" position, which may influence the reaction coordinate.

20-Hydroxysteroid Dehydrogenases↗

PubMed2002

A model binding site for testing scoring functions in molecular docking.

Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized experimental systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of atomic charges and solvation energies affects molecular docking. Atomic charges and solvation energies were calculated for 172,118 molecules in the Available Chemicals Directory using a semi-empirical quantum mechanical approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99Ala and Met102Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4A RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.

Algorithms↗

PubMed2005

A molecular docking model of SARS-CoV S1 protein in complex with its receptor, human ACE2.

The exact residues within severe acute respiratory syndrome coronavirus (SARS-CoV) S1 protein and its receptor, human ACE2, involved in their interaction still remain largely undetermined. Identification of exact amino acid residues that are crucial for the interaction of S1 with ACE2 could provide working hypotheses for experimental studies and might be helpful for the development of antiviral inhibitor. In this paper, a molecular docking model of SARS-CoV S1 protein in complex with human ACE2 was constructed. The interacting residue pairs within this complex model and their contact types were also identified. Our model, supported by significant biochemical evidence, suggested receptor-binding residues were concentrated in two segments of S1 protein. In contrast, the interfacial residues in ACE2, though close to each other in tertiary structure, were found to be widely scattered in the primary sequence. In particular, the S1 residue ARG453 and ACE2 residue LYS341 might be the key residues in the complex formation.

Amino Acid Sequence↗

PubMed1999

Ligand solvation in molecular docking.

Solvation plays an important role in ligand-protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure-based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non-polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non-polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand-receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes.

Aniline Compounds↗

PubMed2005

Design, synthesis, biological evaluation and molecular docking of curcumin analogues as antioxidant, cyclooxygenase inhibitory and anti-inflammatory agents.

Curcuminoids were isolated from Curcuma longa and their pyrazole and isoxazole analogues were synthesized and evaluated for antioxidant, COX-1/COX-2 inhibitory and anti-inflammatory activities. The designed analogues significantly enhance COX-2/COX-1 selectivity and possess significant anti-inflammatory activity in carrageenan induced rat paw edema assay. Pyrazole, isoxazole analogues of curcumin (4 and 7) exhibited higher antioxidant activity than trolox. Molecular docking study revealed the binding orientations of curcumin analogues in the active sites of COX and thereby helps to design novel potent inhibitors.

Animals↗

PubMed2006

Molecular docking approach on the Topoisomerase I inhibitors series included in the NCI anti-cancer agents mechanism database.

Topoisomerase I (Top1) is an essential enzyme participating to all those processes associated with separation of DNA strands. It manages superhelical tensions through the transient breakage of one strand of duplex DNA, followed by the unwinding of supercoiled DNA. Camptothecins, a class of alkaloids extracted from the wood of a Chinese tree, were found to be potent inhibitors of Topoisomerase I. The National Cancer Institute (NCI) Anti-cancer Agents Mechanism Database contains several camptothecins derivatives, classified as selective Top1 inhibitors. In this work we performed molecular docking studies on 24 camptothecin-like inhibitors present in this database (using Autodock 3.0.5). In order to consider the different orientations of the active site residues, docking was performed using four different structures of a Top1-DNA complex. The results obtained allowed us to analyze some conformations adopted by the inhibitors during active site binding, confirming the role of hydrogen bond and contributed to clarify the loss of activity due to single point mutations.

Antineoplastic Agents↗

PubMed2006

Anti-SARS drug screening by molecular docking.

Starting from a collection of 1386 druggable compounds obtained from the 3D pharmacophore search, we performed a similarity search to narrow down the scope of docking studies. The template molecule is KZ7088 (Chou et al., 2003, Biochem Biophys Res Commun 308: 148-151). The MDL MACCS keys were used to fingerprint the molecules. The Tanimoto coefficient is taken as the metric to compare fingerprints. If the similarity threshold was 0.8, a set of 50 unique hits and 103 conformers were retrieved as a result of similarity search. The AutoDock 3.011 was used to carry out molecular docking of 50 ligands to their macromolecular protein receptors. Three compounds, i.e., C(28)H(34)O(4)N(7)Cl, C(21)H(36)O(5)N(6), and C(21)H(36)O(5)N(6), were found that may be promising candidates for further investigation. The main feature shared by these three potential inhibitors as well as the information of the involved side chains of SARS Cov Mpro may provide useful insights for the development of potent inhibitors against SARS enzyme.

Antiviral Agents↗

PubMedDate not supplied

Ionization state and molecular docking studies for the macrophage migration inhibitory factor: the role of lysine 32 in the catalytic mechanism.

The macrophage migration inhibitory factor (MIF) is a cytokine that is structurally similar to certain isomerases and for which multiple immune and catalytic roles have been proposed. Different catalytic activities have been reported for MIF, yet the exact mechanism by which MIF acts is not completely known. As a tautomerase, the enzyme uses a general acid-base mechanism of proton transfer in which the amino-terminal proline has been shown to function as the catalytic base. We report the results of molecular docking simulations of macrophage migration inhibitory factor with three substrates, D-dopachrome, L-dopachrome methyl ester and p-(hydroxyphenyl)pyruvate. Electrostatic pK(a) predictions were also performed for the free and complexed forms of the enzyme. The predicted binding mode of p-(hydroxyphenyl)pyruvate is in agreement with the recently published X-ray structure. A model for the binding mode of D-dopachrome and L-dopachrome methyl ester to MIF is proposed which offers insights into the catalytic mechanism of D-dopachrome tautomerase activity of MIF. The proposed catalytic mechanism is further supported by the pK(a) predictions, which suggest that residue Lys32 acts as the general acid for the enzymatic catalysis of D-dopachrome.

Catalysis↗