A genetic algorithm for flexible molecular overlay and pharmacophore elucidation

CoMFA Study of Piperidine Analogues of Cocaine at the Dopamine Transporter: Exploring the Binding Mode of the 3α-Substituent of the Piperidine Ring Using Pharmacophore-Based Flexible Alignment

A 3D-QSAR CoMFA study of piperidine-based analogues of cocaine with flexible 3 alpha-substituents is described. A series of pharmacophore models were generated based on three representative compounds 1p, 2i, and 3c using the Genetic Algorithm Similarity Program (GASP) method. The flexible superposition of all studied compounds was performed for each pharmacophore model using the FlexS algorithm and the three-dimensional structure of 2i as a template. All sets of the overlaid structures with the top-ranked conformers were used for CoMFA modeling. Two best initial CoMFA models were selected and further optimized by identifying the best-fitting conformer of each compound. Compared with the initial models, the conventional correlation coefficients r(2) for the optimized models 1 and 2 were improved from 0.90 and 0.837 to 0.997 and 0.993, respectively. The leave-one-out cross-validated coefficients q(2) for the optimized models 1 and 2 were improved from 0.515 and 0.296 to 0.828 and 0.849, respectively. The results of the two CoMFA models suggest that both steric and electrostatic interactions play important roles in the binding of the 3 alpha-substituents of the piperidine-based analogues of cocaine. The contributions from steric and electrostatic fields for model 1 were 0.621 and 0.379, respectively. The contributions from steric and electrostatic fields for model 2 were 0.493 and 0.507, respectively. The two highly predictive CoMFA models indicate that the 3 alpha-substituent has two possible binding modes at the DAT. The CoMFA contour maps provide a visual representation of prospective binding modes of the 3 alpha-substituent of the piperidine-based analogues of cocaine and can be used to design novel DAT inhibitors that may be useful for the treatment of cocaine abuse and certain neurological disorders.

Synthesis, Biological Evaluation, and Molecular Modeling Studies of a Novel, Peripherally Selective Inhibitor of Catechol-O-methyltransferase

A novel series of potent, peripherally selective, and long-acting inhibitors of catechol-O-methyltransferase (COMT) has been synthesized. The introduction and nature of heteroatom-containing substituents to the side-chain of the nitrocatechol pharmacophore was found to have a profound effect on both peripheral selectivity and duration of COMT inhibition in the mouse. This approach led to the discovery of 1-(3,4-dihydroxy-5-nitrophenyl)-3-[4-[3-(trifluoromethyl)phenyl]-1-piperazinyl]-1-propanone hydrochloride 35 (BIA 3-335), which was found to possess a superior inhibitory profile in vivo over both the nonselective inhibitor tolcapone 1 and the peripherally selective but short-acting entacapone 2. In this model, 35 retained 75% inhibition of peripheral COMT at 6 h after oral administration, yet significantly, only a minor reduction of central (cerebral) COMT activity was observed. Molecular modeling techniques were applied to review the analysis of the ternary enzyme-inhibitor complex previously determined by X-ray crystallography and to provide a deeper understanding of the structure-activity relationships within this novel series. Furthermore, a computational approach was applied in an effort to elucidate the particular structural factors relevant to the poor blood-brain permeability of 35. In conclusion, the improved biological properties herein reported reveal 35 as a candidate for clinical studies as an adjunct to L-DOPA therapy for Parkinson's disease.

Alignment of three-dimensional molecules using an image recognition algorithm

This paper describes a novel approach, based on image recognition in two dimensions, for the atom-based alignment of two rigid molecules in three dimensions. The atoms are characterised by their partial charges and their positions relative to the remaining atoms in the molecule. Based on this information, a cost of matching a pair of atoms, one from each molecule, is assigned to all possible pairs. A preliminary set of intermolecular atom equivalences that minimises the total atom matching cost is then determined using an algorithm for solving the linear assignment problem. Several geometric heuristics are described that aim to reduce the number of atom equivalences that are inconsistent with the 3D structures. Those that remain are used to calculate an alignment transformation that achieves an optimal superposition of atoms that have a similar local geometry and partial charge. This alignment is then refined by calculating a new set of equivalences consisting of atom pairs that are approximately overlaid, irrespective of partial charge. A range of examples is provided to demonstrate the efficiency and effectiveness of the method.

A virtual screening approach to finding novel and potent antagonists at the melanin-concentrating hormone 1 receptor

Melanin-concentrating hormone (MCH) has been known to be an appetite-stimulating peptide for a number of years. However, it is only recently that MCH has been discovered to be the natural ligand for a previously "orphan" G-protein-coupled receptor, now designated MCH-1R. This receptor has been shown to mediate the effects of MCH on appetite and body weight, and consequently, drug discovery programs have begun to exploit this information in the search for MCH-1R antagonists for the treatment of obesity. In this paper, we report the rapid discovery of multiple, structurally distinct series of MCH-1R antagonists using a variety of virtual screening techniques. The most potent of these compounds (12) demonstrated an IC(50) value of 55 nM in the primary screen and exhibited antagonist properties in a functional cellular assay measuring Ca(2+) release. More potent compounds were identified by follow-up searches around the initial hit. A proposed binding mode for compound 12 in a homology model of the MCH-1R is also presented.

Sequence divergence of Entamoeba histolytica tubulin is responsible for its altered tertiary structure

Atypical microtubular structures of the protozoan parasite Entamoeba histolytica (Eh) have been attributed to amino acid sequence divergence of Eh tubulin. To investigate if this sequence divergence leads to significant differences in the tertiary structure of the Eh alphabeta-tubulin heterodimer, we have modeled alphabeta-tubulin heterodimer of Eh based on the crystal structure of mammalian tubulin. The predicted 3D homology model exhibits an overall resemblance with the known crystal structure of mammalian tubulin except for the 16 residue long carboxy terminal region of Eh beta-tubulin. We propose that this C-terminal region may provide steric hindrance in the polymerization of Eh alphabeta-tubulin for microtubule formation. Using docking studies, we have identified the binding sites for different microtubule specific drugs on Eh beta-tubulin. Our model provides a rational framework, both for understanding the contribution of Eh beta-tubulin C-terminal region to alphabeta-tubulin polymerization and design of new anti-protozoan drugs in order to control amoebiasis.

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.

Superimposition evaluation of ecdysteroid agonist chemotypes through multidimensional QSAR

The EC50 values for a training set of 66 ecdysteroids and 97 diacylhydrazines were measured in the ecdysteroid-responsive Drosophila melanogaster BII cell line, a prototypical homologous inducible gene expression system. Each of eight superimposition hypotheses for the folded diacylhydrazine conformation was evaluated and ranked on the basis of CoMFA and 4D-QSAR Q2 values for the training set and R2 values for a 52-member test set comprising randomly-chosen diacylhydrazines and chronologically-chosen ecdysteroids for which data became available after model construction. Both 4D-QSAR and CoMFA rate a common superimposition as the preferred one. Two additional superimpositions, with somewhat weaker 4D-QSAR and CoMFA consensus, nonetheless share several important topological features. The resultant QSAR models address the question of relative binding orientation of the two ligand families and can be useful as a virtual screen for new chemotypes.

Novel technologies for virtual screening

There are several methods for virtual screening of databases of small organic compounds to find tight binders to a given protein target. Recent reviews in Drug Discovery Today have concentrated on screening by docking and by pharmacophore searching. Here, we complement these reviews by focusing on virtual screening methods that are based on analyzing ligand similarity on a structural level. Specifically, we concentrate on methods that exploit structural properties of the complete ligand molecules, as opposed to using just partial structural templates, such as pharmacophores. The in silico procedure of virtual screening (VS) and its relationship to the experimental procedure, HTS, is discussed, new developments in the field are summarized and perspectives on future research are offered.

Detailed analysis of grid-based molecular docking: A case study of CDOCKER-A CHARMm-based MD docking algorithm

The influence of various factors on the accuracy of protein-ligand docking is examined. The factors investigated include the role of a grid representation of protein-ligand interactions, the initial ligand conformation and orientation, the sampling rate of the energy hyper-surface, and the final minimization. A representative docking method is used to study these factors, namely, CDOCKER, a molecular dynamics (MD) simulated-annealing-based algorithm. A major emphasis in these studies is to compare the relative performance and accuracy of various grid-based approximations to explicit all-atom force field calculations. In these docking studies, the protein is kept rigid while the ligands are treated as fully flexible and a final minimization step is used to refine the docked poses. A docking success rate of 74% is observed when an explicit all-atom representation of the protein (full force field) is used, while a lower accuracy of 66-76% is observed for grid-based methods. All docking experiments considered a 41-member protein-ligand validation set. A significant improvement in accuracy (76 vs. 66%) for the grid-based docking is achieved if the explicit all-atom force field is used in a final minimization step to refine the docking poses. Statistical analysis shows that even lower-accuracy grid-based energy representations can be effectively used when followed with full force field minimization. The results of these grid-based protocols are statistically indistinguishable from the detailed atomic dockings and provide up to a sixfold reduction in computation time. For the test case examined here, improving the docking accuracy did not necessarily enhance the ability to estimate binding affinities using the docked structures.

Using Ensembles to Classify Compounds for Drug Discovery

This paper introduces Signal, a novel method for classifying activity against a small molecule drug target. Signal creates an ensemble, or collection, of meaningful descriptors chosen from a much larger property space. The method works with a variety of descriptor types, including fingerprints that represent four-point pharmacophores or shape descriptors. It also exploits information from both active and inactive compounds and generates predictive models suitable for high throughput screening data analysis. Given the fingerprints and activity data for a set of compounds, Signal is a two step process. The first step is to Evaluate the Descriptors: for each descriptor in the fingerprint, quantify and rank the correlation between the activity of the compounds and the presence of that descriptor. The second step is to Create an Ensemble Model: use the high ranking descriptors to create a model of activity against the biological target. For the first step, two possible ranking strategies were investigated: mutual information and chi-square. For the second step, two types of ensemble models were investigated: high ranking and a novel method called high ranking set cover. Of the four possible pairings, the combination of chi-square and high ranking set cover performed the best on a Thrombin data set.

Field interaction and geometrical overlap: a new simplex and experimental design based computational procedure for superposing small ligand molecules

Alignment of molecules is a crucial and time-consuming step in any 3D-QSAR study. For this reason, the field interaction and geometrical overlap (FIGO) procedure presented in this paper is particularly relevant because it can provide an objective and automatic superposition of ligands through the computation of an appropriate alignment index (AI). Ligand overlay takes place via a simplex optimization of the AI function. Experimental design strategies (full factorial design, D-optimal design) are used to define the starting positions of the superposing molecules. Overlay experiments are carried out to test the performance of the method. Comparison between the results obtained with FIGO and known ligand-receptor X-ray crystallographic data (Protein Data Bank) suggests that FIGO is an effective and reliable computational procedure.

Ligand-based computer-aided pesticide design. A review of applications of the CoMFA and CoMSIA methodologies

An overview is given of the CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methodologies that are established ligand-based molecular design tools widely used by medicinal and pesticide chemists. In the absence of a three-dimensional structure of the target biopolymer, CoMFA and CoMSIA often provide a practical solution to an otherwise intractable problem of proper characterization of ligand-receptor interactions. These techniques are especially important in agrochemistry, where the number of known molecular structures of pesticide targets is limited. The use of CoMFA and CoMSIA in the agrochemical field for modelling the interactions of insecticides, fungicides, herbicides and herbicide safeners with their target binding sites is illustrated by using some selected published work. The CoMFA and CoMSIA models developed have been used successfully to map the properties of unknown receptors, construct hypotheses for ligand-receptor interactions, optimize lead structures, design novel active compounds, and predict biological activities. The application of CoMFA by the present authors for deriving a binding site hypothesis for dichloroacetamide-type herbicide safeners is described in somewhat more detail.

Molecular modeling and metabolic studies of the interaction of catechol-O-methyltransferase and a new nitrocatechol inhibitor

Catechol-O-methyltransferase (COMT, EC 2.1.1.6) plays a central role in the metabolic inactivation of neurotransmitters and neuroactive xenobiotics possessing a catechol motif. 1-(3,4-Dihydroxy-5-nitrophenyl)-2-phenyl-ethanone (BIA 3-202) is a novel nitrocatechol-type inhibitor of COMT, the potential clinical benefit of which is currently being evaluated in the treatment of Parkinson's disease. In the present work we characterize the molecular interactions of BIA 3-202 within the active site of COMT and discuss their implication on the regioselectivity of metabolic O-methylation. Unrestrained flexible-docking simulations suggest that the solution structure of this complex is better described as an ensemble of alternative binding modes, in contrast to the well defined bound configuration revealed by the X-ray structures of related nitrocatechol inhibitors, co-crystallized with COMT. The docking results wherein presented are well supported by experimental evidence, where the pattern of in vitro enzymatic O-methylation and O-demethylation reactions are analyzed. We propose a plausible explanation for the paradoxical in vivo regioselectivity of O-methylation of BIA 3-202, as well as of its related COMT inhibitor tolcapone. Both compounds undergo in vivo O-methylation by COMT at either meta or para catechol hydroxyl groups. However, results herein presented suggest that, in a subsequent step, the p-O-methyl derivatives are selectively demethylated by a microsomal enzyme system. The overall balance is the accumulation of the m-O-methylated metabolites over the para-regioisomers. The implications for the general recognition of nitrocatechol-type inhibitors by COMT and the regioselectivity of their metabolic O-methylation are discussed.

3D QSAR investigations on antimalarial naphthylisoquinoline alkaloids by comparative molecular similarity indices analysis (CoMSIA), based on different alignment approaches

3D QSAR models based on the CoMSIA descriptor fields were established using a diverse data set of 53 antimalarial biaryl compounds (tested in vitro against a chloroquine-resistant strain of Plasmodium falciparum), consisting mainly of naphthylisoquinoline alkaloids, but also including phenylanthraquinone structures and naphthylindenes. For the alignment, two commercially available automated approaches, FLEXS and GASP, were compared; initially none of them succeeded in treating the important phenomenon of axial chirality correctly, but after some manual refinement of the alignments initially obtained, the best overall model, based on a modified FLEXS alignment, showed a q(2) (cross-validated r(2)) of 0.818 (eight components), using only the hydrophobic and the H-bond donor and acceptor fields. Using a test set of five compounds the model showed a squared multiple correlation coefficient for the test set (predictive r(2)) of 0.578. The analysis of the 3D contour maps permitted interesting conclusions about the effects of particular functional groups on the biological activity and will now guide the design of novel, hopefully even more active compounds.

Pharmacophore model of drugs involved in P-glycoprotein multidrug resistance: explanation of structural variety (hypothesis)

A general pharmacophore model of P-glycoprotein (P-gp) drugs is proposed that is based on a highly diverse data set and relates to the verapamil binding site of the protein. It is derived from structurally different drugs using the program GASP. The pharmacophore model consists of two hydrophobic points, three hydrogen bond (HB) acceptor points, and one HB donor point. Pharmacophore patterns of various drugs are obtained, and different binding modes are presumed for some of them. It is concluded that the binding affinity of the drugs depends on the number of the pharmacophore points simultaneously involved in the interaction with P-gp. On the basis of the obtained results, a hypothesis is proposed to explain the broad structural variety of the P-gp substrates and inhibitors: (i) the verapamil binding site of P-gp has several points that can participate in hydrophobic and HB interactions; (ii) different drugs can interact with different receptor points in different binding modes.

Tetrahydroisoquinoline-3-carboxylate based matrix-metalloproteinase inhibitors: design, synthesis and structure-activity relationship

The design, synthesis and structure-activity relationship (SAR) of a series of nonpeptidic 2-arylsulfonyl-1,2,3,4-tetrahydro-isoquinoline-3-carboxylates and-hydroxamates as inhibitors of the matrix metalloproteinase human neutrophil collagenase (MMP-8) is described here. Based on available X-ray structures of MMP-8/inhibitor complexes, our structure-based design strategy was directed to complement major protein-ligand interaction regions mainly in the S1' hydrophobic specificity pocket close to the catalytic zinc ion. Here, the rigid 1,2,3,4-tetrahydroisoquinoline scaffold (Tic) provides ideal geometry to combine hydroxamates and carboxylates as typical zinc complexing functionalities, with a broad variety of S1' directed mono- and biaryl substituents consisting of aromatic rings perfectly accommodated within this more hydrophobic region of the MMP-8 inhibitor binding site. The effect of different S1' directed substituents, zinc-complexing groups, chirality and variations of the tetrahydroisoquinoline ring-system is investigated by systematic studies. X-ray structure analyses in combination with 3D-QSAR studies provided an additional understanding of key determinants for MMP-8 affinity in this series. The hypothetical binding mode for a typical molecule as basis for our inhibitor design was found in good agreement with a 1.7 A X-ray structure of this candidate in complex with the catalytic domain of human MMP-8. After analysis of all systematic variations, 3D-QSAR and X-ray structure analysis, novel S1' directed substituents were designed and synthesized and biologically evaluated. This finally results in inhibitors, which do not only show high biological affinity for MMP-8, but also exhibit good oral bioavailability in several animal species.

Targeting thrombin and factor VIIa: design, synthesis, and inhibitory activity of functionally relevant indolizidinones

Guided by molecular modeling, docking experiments, and available X-ray crystal structure data on the serine protease Factor VIIa and thrombin, a series of indolizidinone derivatives was designed and synthesized having diverse functionality at the P1, P2, and P3 sites.

Differential interactions of nateglinide and repaglinide on the human beta-cell sulphonylurea receptor 1

Repaglinide and nateglinide represent a new class of insulin secretagogues, structurally unrelated to sulphonylureas, that were developed for the treatment of type 2 diabetes. The inhibitory effect of these drugs was investigated on recombinant wild-type and mutant Kir6.2/SUR1 channels expressed in HEK293 cells. Nateglinide and repaglinide dose-dependently inhibited whole-cell Kir6.2/SUR1 currents with half-maximal inhibitory concentration (IC(50)) values of 800 and 21 nmol/l, respectively. Mutation of serine 1237 in SUR1 to tyrosine (S1237Y) abolished tolbutamide and nateglinide block, suggesting that these drugs share a common point of interaction on the SUR1 subunit of the ATP-sensitive K(+) channel. In contrast, repaglinide inhibition was unaffected by the S1237Y mutation (IC(50) = 23 nmol/l). Radioligand binding studies revealed a single high-affinity binding site for [(3)H]repaglinide on membranes prepared from HEK293 cells expressing wild-type (equilibrium dissociation constant [K(D)] = 0.40 nmol/l) or mutant (K(D) = 0.31 nmol/l) Kir6.2/SUR1 channels. Nateglinide and tolbutamide displaced [(3)H]repaglinide binding to wild-type channels with IC(50) values of 0.7 and 26 micro mol/l, respectively, but produced <10% displacement of [(3)H]repaglinide bound to mutant channels. This is consistent with the idea that binding of nateglinide and tolbutamide, but not repaglinide, is abolished by the SUR1[S1237Y] mutation and that the binding site for repaglinide is not identical to that of nateglinde/tolbutamide. These results are discussed in terms of a conformational analysis of the drug molecules.

A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP

Three commercially available pharmacophore generation programs, Catalyst/HipHop, DISCO and GASP, were compared on their ability to generate known pharmacophores deduced from protein-ligand complexes extracted from the Protein Data Bank. Five different protein families were included Thrombin, Cyclin Dependent Kinase 2, Dihydrofolate Reductase, HIV Reverse Transcriptase and Thermolysin. Target pharmacophores were defined through visual analysis of the data sets. The pharmacophore models produced were evaluated qualitatively through visual inspection and according to their ability to generate the target pharmacophores. Our results show that GASP and Catalyst outperformed DISCO at reproducing the five target pharmacophores.

Structural requirements for inhibition of the neuronal nitric oxide synthase (NOS-I): 3D-QSAR analysis of 4-oxo- and 4-amino-pteridine-based inhibitors

The family of homodimeric nitric oxide synthases (NOS I-III) catalyzes the generation of the cellular messenger nitric oxide (NO) by oxidation of the substrate L-arginine. The rational design of specific NOS inhibitors is of therapeutic interest in regulating pathological NO levels associated with sepsis, inflammatory, and neurodegenerative diseases. The cofactor (6R)-5,6,7,8-tetrahydrobiopterin (H(4)Bip) maximally activates all NOSs and stabilizes enzyme quaternary structure by promoting and stabilizing dimerization. Here, we describe the synthesis and three-dimensional (3D) quantitative structure-activity relationship (QSAR) analysis of 65 novel 4-amino- and 4-oxo-pteridines (antipterins) as inhibitors targeting the H(4)Bip binding site of the neuronal NOS isoform (NOS-I). The experimental binding modes for two inhibitors complexed with the related endothelial NO synthase (NOS-III) reveal requirements of biological affinity and form the basis for ligand alignment. Different alignment rules were derived by building other compounds accordingly using manual superposition or a genetic algorithm for flexible superposition. Those alignments led to 3D-QSAR models (comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)), which were validated using leave-one-out cross-validation, multiple analyses with two and five randomly chosen cross-validation groups, perturbation of biological activities by randomization or progressive scrambling, and external prediction. An iterative realignment procedure based on rigid field fit was used to improve the consistency of the resulting partial least squares models. This led to consistent and highly predictive 3D-QSAR models with good correlation coefficients for both CoMFA and CoMSIA, which correspond to experimentally determined NOS-II and -III H(4)Bip binding site topologies as well as to the NOS-I homology model binding site in terms of steric, electrostatic, and hydrophobic complementarity. These models provide clear guidelines and accurate activity predictions for novel NOS-I inhibitors.

SOFTDOCK: understanding of molecular recognition through a systematic docking study

Molecular recognition and docking are essential to the biological functions of proteins. SOFTDOCK was one of the first molecular docking methods developed for protein-protein docking. Its ability to represent the molecular surface with different shapes and properties and to dock a variety of molecular complexes with certain conformational changes was demonstrated in a previous study. In the present work, we studied the effects of the docking parameters through statistical analysis. Seventy one typical binary complexes of different categories in PDB were also systematically docked for a test; 57 of them produced correct solutions with one set of docking parameters whereas the other 14 complexes required adjustment of the docking parameters, by decreasing the softness of the recognition and hence the background noise. We found that these 14 complexes had special structural features. Our results suggest that a variety of mechanisms may be involved in molecular recognition rather than the shape complementarity only, which is very helpful in developing more powerful methods for predicting molecular recognition.

FLASHFLOOD: a 3D field-based similarity search and alignment method for flexible molecules

A three-dimensional field-based similarity search and alignment method for flexible molecules is introduced. The conformational space of a flexible molecule is represented in terms of fragments and torsional angles of allowed conformations. A user-definable property field is used to compute features of fragment pairs. Features are generalizations of CoMMA descriptors that characterize local regions of the property field by its local moments. The features are invariant under coordinate system transformations. Features taken from a query molecule are used to form alignments with fragment pairs in the database. An assembly algorithm is then used to merge the fragment pairs into full structures, aligned to the query. Key to the method is the use of a context adaptive descriptor scaling procedure as the basis for similarity. This allows the user to tune the weights of the various feature components based on examples relevant to the particular context under investigation. The property fields may range from simple, phenomenological fields, to fields derived from quantum mechanical calculations. We apply the method to the dihydrofolate/methotrexate benchmark system, and show that when one injects relevant contextual information into the descriptor scaling procedure, better results are obtained more efficiently. We also show how the method works and include computer times for a query from a database that represents approximately 23 million conformers of seventeen flexible molecules.

Flexible alignment of small molecules

A method is presented for flexibly aligning small molecules. The method accepts a collection of small molecules with 3D coordinates as input and computes a collection of alignments. Each alignment is given a score, which quantifies the quality of the alignment both in terms of internal strain and overlap of molecular features. The results of several computational experiments on pairs of compounds with known binding conformations are used to systematically and objectively tune the parameters for the method. The results indicate the method's utility for the elucidation of pharmacophores and comparative field analysis.

SLATE: a method for the superposition of flexible ligands

A novel program for the superposition of flexible molecules, SLATE, is presented. It uses simulated annealing to minimise the difference between the distance matrices calculated from the hydrogen-bonding and aromaticring properties of two ligands. A method for generating a molecular stack using multiple pairwise matches is illustrated. These stacks are used by the program DOH to predict the relative positions of receptor atoms that could form hydrogen bonds to two or more ligands in the dataset. The methodology has been applied to ligands binding to dihydrofolate reductase, thermolysin. H3 histamine receptors, alpha2 adrenoceptors and 5-HT1D receptors. When there are sufficient numbers and diversity of molecules in the dataset, the prediction of receptor-atom positions is applicable to compound design.

Rational design, synthesis, and biological activity of benzoxazinones as novel factor Xa inhibitors

Inappropriate thrombus formation within blood vessels is the leading cause of mortality in the industrialized world. Factor Xa (FXa) is a trypsin-like serine protease that plays a key role in the blood coagulation cascade and represents an attractive target for anticoagulant drug development. From a high-throughput in vitro mass screen of our chemical library, we identified 4-[5-[(2R,6S)-2, 6-dimethyltetrahydro-1(2H)-pyridinyl]pentyl]-2-phenyl-2H-1, 4-benzoxazin-3(4H)-one (1a) as an inhibitor of FXa with an IC(50) of 27 microM. Through a combination of SAR studies and molecular modeling, we synthesized 3-(4-[5-[(2R,6S)-2, 6-dimethyltetrahydro-1(2H)-pyridinyl]pentyl]-3-oxo-3,4-dihydro-2H- 1,4-benzoxazin-2-yl)-1-benzenecarboximidamide (1n) which was a potent FXa inhibitor with an IC(50) of 3 nM. This compound exhibited high selectivity for FXa over other related serine proteases and was efficacious when dosed intravenously in rabbit and dog antithrombotic models.

Synthesis and estrogen receptor binding affinities of novel pyrrolo[2,1,5-cd]indolizine derivatives

A series of pyrrolo[2,1,5-cd]indolizine derivatives has been synthesized and evaluated as ligands for the estrogen receptor. Properly substituted mono- and di-hydroxy derivatives showed binding in the low nanomolar range in accordance with their structural resemblance to estrogen.

Similarity-driven flexible ligand docking

A similarity-driven approach to flexible ligand docking is presented. Given a reference ligand or a pharmacophore positioned in the protein active site, the method allows inclusion of a similarity term during docking. Two different algorithms have been implemented, namely, a similarity-penalized docking (SP-DOCK) and a similarity-guided docking (SG-DOCK). The basic idea is to maximally exploit the structural information about the ligand binding mode present in cases where ligand-bound protein structures are available, information that is usually ignored in standard docking procedures. SP-DOCK and SG-DOCK have been derived as modified versions of the program DOCK 4.0, where the similarity program MIMIC acts as a module for the calculation of similarity indices that correct docking energy scores at certain steps of the calculation. SP-DOCK applies similarity corrections to the set of ligand orientations at the end of the ligand incremental construction process, penalizing the docking energy and, thus, having only an effect on the relative ordering of the final solutions. SG-DOCK applies similarity corrections throughout the entire ligand incremental construction process, thus affecting not only the relative ordering of solutions but also actively guiding the ligand docking. The performance of SP-DOCK and SG-DOCK for binding mode assessment and molecular database screening is discussed. When applied to a set of 32 thrombin ligands for which crystal structures are available, SG-DOCK improves the average RMSD by ca. 1 A when compared with DOCK. When those 32 thrombin ligands are included into a set of 1,000 diverse molecules from the ACD, DIV, and WDI databases, SP-DOCK significantly improves the retrieval of thrombin ligands within the first 10% of each of the three databases with respect to DOCK, with minimal additional computational cost. In all cases, comparison of SP-DOCK and SG-DOCK results with those obtained by DOCK and MIMIC is performed.

A widely applicable set of descriptors

Three sets of molecular descriptors computable from connection table information are defined. These descriptors are based on atomic contributions to van der Waals surface area, log P (octanol/water), molar refractivity, and partial charge. The descriptors are applied to the construction of QSAR/QSPR models for boiling point, vapor pressure, free energy of solvation in water, solubility in water, thrombin/trypsin/factor Xa activity, blood-brain barrier permeability, and compound classification. The wide applicability of these descriptors suggests uses in QSAR/QSPR, combinatorial library design, and molecular diversity work.

Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR

Binding of the Tat protein to TAR RNA is necessary for viral replication of HIV-1. We screened the Available Chemicals Directory (ACD) to identify ligands to bind to a TAR RNA structure using a four-step docking procedure: rigid docking first, followed by three steps of flexible docking using a pseudobrownian Monte Carlo minimization in torsion angle space with progressively more detailed conformational sampling on a progressively smaller list of top-ranking compounds. To validate the procedure, we successfully docked ligands for five RNA complexes of known structure. For ranking ligands according to binding avidity, an empirical binding free energy function was developed which accounts, in particular, for solvation, isomerization free energy, and changes in conformational entropy. System-specific parameters for the function were derived on a training set of RNA/ligand complexes with known structure and affinity. To validate the free energy function, we screened the entire ACD for ligands for an RNA aptamer which binds L-arginine tightly. The native ligand ranked 17 out of ca. 153,000 compounds screened, i.e., the procedure is able to filter out >99.98% of the database and still retain the native ligand. Screening of the ACD for TAR ligands yielded a high rank for all known TAR ligands contained in the ACD and suggested several other potential TAR ligands. Eight of the highest ranking compounds not previously known to be ligands were assayed for inhibition of the Tat-TAR interaction, and two exhibited a CD50 of ca. 1 microM.

Critical point representations of electron density maps for the comparison of benzodiazepine-type ligands

A procedure for the comparison of three-dimensional electron density distributions is proposed for similarity searches between pharmacological ligands at various levels of crystallographic resolution. First, a graph representation of molecular electron density distributions is generated using a critical point analysis approach. Pairwise as well as multiple comparisons between the obtained graphs of critical points are then carried out using a Monte Carlo/simulated annealing technique, and results are compared with genetic algorithm solutions.

Quadratic shape descriptors. 1. Rapid superposition of dissimilar molecules using geometrically invariant surface descriptors

In this paper, we present a novel approach to shape-based molecular similarity searching. The method that we introduce is able to superimpose dissimilar molecules by using geometrically invariant molecular surface descriptors. The shape descriptors are calculated by least-squares fitting of a quadratic function to small sections of the molecular surface of a ligand. Invariant geometric properties of the approximated surface patch are then extracted from the fitted quadratic function. The extracted properties are used to quantify the shape and to obtain a canonical orientation for this section of surface. The superimposition algorithm uses these geometric invariants to recognize similar regions of surface shape existing on two molecules and to bring these regions (and consequently the molecules) into registration. Because these geometric descriptors are based upon local surface shape, the superimposing algorithm is insensitive to the connectivity and the relative sizes of the molecules being matched. The capabilities of our algorithm are demonstrated by superimposing dissimilar ligands known to inhibit the same enzyme system. In all cases examined the algorithm generates superpositions that are in agreement with crystallographic results. The algorithm is also applied to align the two different proteins on the basis of the shape of their active sites.

Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.

Multiple flexible alignment with SEAL: a study of molecules acting on the colchicine binding site

An extension of the steric and electrostatic alignment alignment (SEAL) method (MultiSEAL) is described that allows the overlay of multiple molecules and conformations. The method is well-suited for the systematic study of possible alignments, also revealing information about the conformational energies associated with a given overlay. It has been tested on three examples: angiotensin II antagonists, 5-HT3 antagonists, and dopaminergic compounds. The utility of the method is further demonstrated in an analysis of molecules that putatively bind to the colchicine site of tubulin. On the basis of its overlay with colchicine, allocolchicine, 2-methoxy-5-(2',3',4'-trimethoxyphenyl)tropone, and combretastatin A-4, it appears that 2-methoxyestradiol (2-ME) is unlikely to fit the colchine site properly. The weak antimitotic activity of 2-ME may be explained by its partial fit in the site.

Partial molecular alignment via local structure analysis

Molecular alignment remains as one of the most problematic aspects of molecular design. A technique is introduced that facilitates the alignment of a range of structures that could not be handled easily using existing alignment procedures. The flexibility of the method is illustrated with a series of test sets. First, an alignment is performed on a series of molecules from a typical 3D-quantitative structure-activity relationship data set. The results of this test show the technique to outperform many existing alignment methodologies based upon the optimization of molecular similarity of molecular overlaps. This test set is then extended to consider the alignment of more structurally diverse inhibitors of HIV-1 reverse transcriptase and HIV-1 protease. Finally, in the most challenging test, a large protein-based inhibitor is matched with a small-molecule mimic. It is believed that the existence of such a versatile alignment technique will prove invaluable in the fields of molecular design and chemical information handling.

Design and biological evaluation of non-peptide analogues of omega-conotoxin MVIIA

Omega-conotoxin MVIIA, a highly potent antagonist of the N-type voltage sensitive calcium channel, has shown utility in several models of pain and ischemia. We report a series of three alkylphenyl ether based analogues which mimic three key amino acids of the toxin. Two of the compounds have been found to exhibit IC50 values of 2.7 and 3.3 microM at the human N-type voltage sensitive calcium channel.

DREAM++: flexible docking program for virtual combinatorial libraries

We present a set of programs, DREAM+2 (Docking and Reaction programs using Efficient seArch Methods written in C++), for docking computationally generated ligands into macromolecular binding sites. DREAM++ is composed of three programs: ORIENT++, REACT++ and SEARCH++. The program ORIENT++ positions molecules in a binding site with the DOCK algorithm. Its output can be used as input to REACT++ and SEARCH+2. The program REACT++ performs user-specific chemical reactions on a docked molecule, so that reaction products can be evaluated for three dimensional complementarity with the macromolecular site. The program SEARCH++ performs an efficient conformation search on the reaction products using a hybrid backtrack and incremental construction algorithm. We have applied the programs to HIV protease-inhibitor complexes as test systems. We found that we can differentiate high-affinity ligands based on several measures: interaction energies, occupancy of protein subsites and the number of successfully docked conformations for each product. Encouraged by the results in the test case, we applied the programs to propose novel inhibitors of HIV protease. These inhibitors can be generated by organic reactions using commercially available reagents. They are alternatives to the inhibitors synthesized by Glaxo.

FLEXS: a method for fast flexible ligand superposition

If no structural information about a particular target protein is available, methods of rational drug design try to superimpose putative ligands with a given reference, e.g., an endogenous ligand. The goal of such structural alignments is, on the one hand, to approximate the binding geometry and, on the other hand, to provide a relative ranking of the ligands with respect to their similarity. An accurate superposition is the prerequisite of subsequent exploitation of ligand data by either 3D QSAR analyses, pharmacophore hypotheses, or receptor modeling. We present the automatic method FLEXS for structurally superimposing pairs of ligands, approximating their putative binding site geometry. One of the ligands is treated as flexible, while the other one, used as a reference, is kept rigid. FLEXS is an incremental construction procedure. The molecules to be superimposed are partitioned into fragments. Starting with placements of a selected anchor fragment, computed by two alternative approaches, the remaining fragments are added iteratively. At each step, flexibility is considered by allowing the respective added fragment to adopt a discrete set of conformations. The mean computing time per test case is about 1:30 min on a common-day workstation. FLEXS is fast enough to be used as a tool for virtual ligand screening. A database of typical drug molecules has been screened for potential fibrinogen receptor antagonists. FLEXS is capable of retrieving all ligands assigned to platelet aggregation properties among the first 20 hits. Furthermore, the program suggests additional interesting candidates, likely to be active at the same receptor. FLEXS proves to be superior to commonly used retrieval techniques based on 2D fingerprint similarities. The accuracy of computed superpositions determines the relevance of subsequently performed ligand analyses. In order to validate the quality of FLEXS alignments, we attempted to reproduce a set of 284 mutual superpositions derived from experimental data on 76 protein-ligand complexes of 14 proteins. The ligands considered cover the whole range of drug-size molecules from 18 to 158 atoms (PDB codes: 3ptb, 2er7). The performance of the algorithm critically depends on the sizes of the molecules to be superimposed. The limitations are clearly demonstrated with large peptidic inhibitors in the HIV and the endothiapepsin data set. Problems also occur in the presence of multiple binding modes (e.g., elastase and human rhinovirus). The most convincing results are achieved with small- and medium-sized molecules (as, e.g., the ligands of trypsin, thrombin, and dihydrofolate reductase). In more than half of the entire test set, we achieve rms deviations between computed and observed alignment of below 1.5 A. This underlines the reliability of FLEXS-generated alignments.

Do active site conformations of small ligands correspond to low free-energy solution structures?

We compare the low free energy structures of ten small, polar ligands in solution to their conformations in their respective receptor active sites. The solution conformations are generated by a systematic search and the free energies of representative structures are computed with a continuum solvation model. Based on the values of torsion angles, we find little similarity between low energy solution structures of small ligands and their active site conformations. However, in nine out of ten cases, the positions of 'anchor points' (key atoms responsible for tight binding) in the lowest energy solution structures are very similar to the positions of these atoms in the active site conformations. A metric that more closely captures the essentials of binding supports the basic premise underlying pharmacophore mapping, namely that active site conformations of small flexible ligands correspond to their low energy structures in solution. This work supports the efforts of building pharmacophore models based on the information present in solution structures of small isolated ligands.

Feature trees: a new molecular similarity measure based on tree matching

In this paper we present a new method for evaluating molecular similarity between small organic compounds. Instead of a linear representation like fingerprints, a more complex description, a feature tree, is calculated for a molecule. A feature tree represents hydrophobic fragments and functional groups of the molecule and the way these groups are linked together. Each node in the tree is labeled with a set of features representing chemical properties of the part of the molecule corresponding to the node. The comparison of feature trees is based on matching subtrees of two feature trees onto each other. Two algorithms for tackling the matching problem are described throughout this paper. On a dataset of about 1000 molecules, we demonstrate the ability of our approach to identify molecules belonging to the same class of inhibitors. With a second dataset of 58 molecules with known binding modes taken from the Brookhaven Protein Data Bank, we show that the matchings produced by our algorithms are compatible with the relative orientation of the molecules in the active site in 61% of the test cases. The average computation time for a pair comparison is about 50 ms on a current workstation.

RigFit: a new approach to superimposing ligand molecules

If structural knowledge of a receptor under consideration is lacking, drug design approaches focus on similarity or dissimilarity analysis of putative ligands. In this context the mutual ligand superposition is of utmost importance. Methods that are rapid enough to facilitate interactive usage, that allow to process sets of conformers and that enable database screening are of special interest here. The ability to superpose molecular fragments instead of entire molecules has proven to be helpful too. The RIGFIT approach meets these requirements and has several additional advantages. In three distinct test applications, we evaluated how closely we can approximate the observed relative orientation for a set of known crystal structures, we employed RIGFIT as a fragment placement procedure, and we performed a fragment-based database screening. The run time of RIGFIT can be traded off against its accuracy. To be competitive in accuracy with another state-of-the-art alignment tool, with which we compare our method explicitly, computing times of about 6 s per superposition on a common day workstation are required. If longer run times can be afforded the accuracy increases significantly. RIGFIT is part of the flexible superposition software FLEXS which can be accessed on the WWW [http:/(/)cartan.gmd.de/FlexS].

Superposition of three-dimensional chemical structures allowing for conformational flexibility by a hybrid method

The superposition of three-dimensional structures is the first task in the evaluation of the largest common three-dimensional substructure of a set of molecules. This is an important step in the identification of a pharmacophoric pattern for molecules that bind to the same receptor. The superposition method described here combines a genetic algorithm with a numerical optimization method. A major goal is to adequately address the conformational flexibility of ligand molecules. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the substructures. The geometric fit is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. This directed tweak method is based on a numerical quasi-Newton optimization method. Only one starting conformation per molecule is necessary. Molecules having several rotatable bonds and quite different initial conformations are modified to find large structural similarities. A set of angiotensin II antagonists is investigated to illustrate the performance of the method.