QSAR of conformationally flexible molecules: comparative molecular field analysis of protein-tyrosine kinase inhibitors

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

Rigorous treatment of multispecies multimode ligand-receptor interactions in 3D-QSAR: CoMFA analysis of thyroxine analogs binding to transthyretin

For a rigorous analysis of the receptor-ligand binding, speciation of the ligands caused by ionization, tautomerism, covalent hydration, and dynamic stereoisomerism needs to be considered. Each species may bind in several orientations or conformations (modes), especially for flexible ligands and receptors. A thermodynamic description of the multispecies (MS), multimode (MM) binding events shows that the overall association constant is equal to the weighted sum of the sums of microscopic association constants of individual modes for each species, with the weights given by the unbound fractions of individual species. This expression is a prerequisite for a precise quantitative characterization of the ligand-receptor interactions in both structure-based and ligand-based structure-activity analyses. We have implemented the MS-MM correlation expression into the comparative molecular field analysis (CoMFA), which deduces a map of the binding site from structures and binding affinities of a ligand set, in the absence of experimental structural information on the receptor. The MS-MM CoMFA approach was applied to published data for binding to transthyretin of 28 thyroxine analogs, each forming up to four ionization species under physiological conditions. The published X-ray structures of several analogs, exhibiting multiple binding modes, served as templates for the MS-MM superposition of thyroxine analogs. Additional modes were generated for compounds with flexible alkyl substituents, to identify bound conformations. The results demonstrate that the MS-MM modification improved predictive abilities of the CoMFA models, even for the standard procedure with MS-MM selected species and modes. The predicted prevalences of individual modes and the generated receptor site model are in reasonable agreement with the available X-ray data. The calibrated model can help in the design of inhibitors of transthyretin amyloid fibril formation.

On the stability of CoMFA models

Abrupt, smooth, and box methods for the calculation of electrostatic and steric field values in the comparative molecular field analysis (CoMFA) 3D QSAR technique are assessed on three diverse data sets of medicinal chemistry interest. While the standard CoMFA settings are robust to small changes in the position of the lattice, superior results may sometimes be obtained by use of only one field. However, if only the electrostatic field is used, then sometimes large differences between models are apparent. This appears to be due to a lack of column dropping, and these difficulties can be remedied by use of the box method.

Multimode Ligand Binding in Receptor Site Modeling: Implementation in CoMFA

Receptor site modeling methods usually use one binding mode (conformation and/or orientation) for each ligand in a 1:1 complex with receptor. Multiple modes should be considered instead because (1). they have frequently been observed experimentally; (2). in a series, ligands can bind in single yet different modes; and (3). a series may only exhibit one but unknown mode and a few plausible modes must be examined. For multimode binding, the observed ligand/receptor association constant is the sum of the association constants that characterize individual binding modes. This relation, when applied to Comparative Molecular Field Analysis (CoMFA), results in a dependence of the observed binding energy on the probe energies that is nonlinear in optimized parameters. The dependence was linearized to allow parameter optimization by the partial least-squares method that was used iteratively until self-consistency. In addition to the standard CoMFA output, the procedure objectively selects one or a few optimal binding modes out of a dozen or more modes that are considered for each ligand. The approach was applied to published data for binding of 34 polychlorinated dibenzofurans to the aryl hydrocarbon receptor. Descriptive and predictive abilities of the 16-mode model were significantly better than for the one-, two-, and four-mode models. Predominantly, edge-aligned modes were selected that are seldom used in CoMFA. Since inclusion of multimode binding only changes the form of the correlation equation and does not affect the number of optimized parameters, the improvement is believed to be due to a more realistic description.

Structure-activity relationships for 1',1'-dimethylalkyl-Delta8-tetrahydrocannabinols

A series of 1',1'-dimethylalkyl-Delta(8)-tetrahydrocannabinol analogues with C-3 side chains of 2-12 carbon atoms has been synthesized and their in vitro and in vivo pharmacology has been evaluated. The lowest member of the series, 1',1'-dimethylethyl-Delta(8)-THC (8, n=0) has good affinity for the CB(1) receptor, but is inactive in vivo. The dimethylpropyl (8, n=1) through dimethyldecyl (8, n=8) all have high affinity for the CB(1) receptor and are full agonists in vivo. 1',1'-Dimethylundecyl-Delta(8)-THC (8, n=9) has significant affinity for the receptor (K(i)=25.8+/-5.8 nM), but has reduced potency in vivo. The dodecyl analogue (8, n=10) has little affinity for the CB(1) receptor and is inactive in vivo. A quantitative structure-activity relationship study of the side chain region of these compounds is consistent with the concept that for optimum affinity and potency the side chain must be of a length which will permit its terminus to loop back in proximity to the phenolic ring of the cannabinoid.

Synthesis and structure-activity relationships of amide and hydrazide analogues of the cannabinoid CB(1) receptor antagonist N-(piperidinyl)- 5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (SR141716)

Analogues of the biaryl pyrazole N-(piperidinyl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (SR141716; 5) were synthesized to investigate the structure-activity relationship (SAR) of the aminopiperidine region. The structural modifications include the substitution of alkyl hydrazines, amines, and hydroxyalkylamines of varying lengths for the aminopiperidinyl moiety. Proximity and steric requirements at the aminopiperidine region were probed by the synthesis of analogues that substitute alkyl hydrazines of increasing chain length and branching. The corresponding amide analogues were compared to the hydrazides to determine the effect of the second nitrogen on receptor binding affinity. The N-cyclohexyl amide 14 represents a direct methine for nitrogen substitution for 5, reducing the potential for heteroatom interaction, while the morpholino analogue 15 adds the potential for an additional heteroatom interaction. The series of hydroxyalkyl amides of increasing chain length was synthesized to investigate the existence of additional receptor hydrogen binding sites. In displacement assays using the cannabinoid agonist [(3)H](1R,3R,4R)-3-[2-hydroxy-4-(1,1-dimethylheptyl)phenyl]-4-(3-hydroxypropyl) cyclohexan-1-ol (CP 55 940; 2) or the antagonist [(3)H]5, 14 exhibited the highest CB(1) affinity. In general, increasing the length and bulk of the substituent was associated with increased receptor affinity and efficacy (as measured in a guanosine 5'-triphosphate-gamma-[(35)S] assay). However, in most instances, receptor affinity and efficacy increases were no longer observed after a certain chain length was reached. A quantitative SAR study was carried out to characterize the pharmacophoric requirements of the aminopiperidine region. This model indicates that ligands that exceed 3 A in length would have reduced potency and affinity with respect to 5 and that substituents with a positive charge density in the aminopiperidine region would be predicted to possess increased pharmacological activity.

Derivation of pharmacophore and CoMFA models for leukotriene D(4) receptor antagonists of the quinolinyl(bridged)aryl series

The present work focuses on the study of the three-dimensional (3D) structural requirements for the leukotriene D(4) (LTD(4)) antagonistic activity of compounds having the basic quinolinyl(bridged)aryl framework. An approach combining pharmacophore mapping, molecule alignment, and CoMFA models was used to derive a hypothesis for a series of LTD(4) antagonists having the basic diaryl-bridged framework. In this compound series, the produced pharmacophore hypotheses have shown to yield molecule alignments suitable to derive valuable CoMFA models. Model selection focused on (1) obtention of coherent modeling results, (2) consistency with the available SAR data, and (3) ability to predict the activity of an independent set of congeneric molecules. This approach resulted in a combined pharmacophore and CoMFA model that can generally represent the antagonistic activity within a log unit of the measured value for compounds of the series. The resulting pharmacophore (model C) consists of an acidic or negative ionizable function (AC), a hydrogen-bond acceptor (HBA), and three hydrophobic regions (HY) and produces chemically meaningful alignments with the most active compounds of the series mapping the pharmacophore in a extended energetically favorable conformation.

QSAR analysis of Delta(8)-THC analogues: relationship of side-chain conformation to cannabinoid receptor affinity and pharmacological potency

A novel quantitative structure-activity relationship (QSAR) for the side-chain region of Delta(8)-tetrahydrocannabinol (Delta(8)-THC) analogues is reported. A series of 36 side-chain-substituted Delta(8)-THCs with a wide range of pharmacological potency and CB1 receptor affinity was investigated using computational molecular modeling and QSAR analyses. The conformational mobility of each compound's side chain was characterized using a quenched molecular dynamics approach. The QSAR techniques included a modified active analogue approach (MAA), multiple linear regression analyses (MLR), and comparative molecular field analysis (CoMFA) studies. All three approaches yielded consistent results. The MAA approach applied to a set of alkene/alkyne pairs identified the most active conformers as those with conformational mobility constrained within an approximately 8 A radius. MLR analyses (restricted to 15 hydrocarbon side-chain analogues) identified two variables describing side-chain length and terminus position that were able to fit the pharmacological data for receptor affinity with a correlation coefficient for pK(D) of 0.82. While chain length was found to be directly related to receptor affinity, the angle made by the side chain from its attachment point to its terminus (angle defined by C3-C1'-side-chain terminus carbon, see Figure 1) was found to be inversely related to affinity. These results suggest that increased side-chain length and increased side-chain ability to wrap around the ring system are predicted to increase affinity. Therefore, the side chain's conformational mobility must not restrict the chain straight away from the ring system but must allow the chain to wrap back around toward the ring system. Finally, the CoMFA analyses involved all 36 analogues; they also provided data to support the hypothesis that for optimum affinity and potency the side chain must have conformational freedom that allows its terminus to fold back and come into proximity with the phenolic ring.

Three-dimensional quantitative structure-activity relationship of interleukin 1-beta converting enzyme inhibitors: A comparative molecular field analysis study

A three-dimensional quantitative structure-activity relationship (QSAR) study using the comparative molecular field analysis (CoMFA) method was performed on a series of interleukin 1-beta converting enzyme (ICE) inhibitors. The compounds studied have been reported to be time-dependent inhibitors of ICE. This study was performed using 49 compounds, in which the CoMFA models were developed using a training set of 39 compounds. All the compounds were modeled using the X-ray crystal structure of tetrapeptide aldehyde inhibitor/ICE complex. The inhibitor compounds were considered both as neutral species and as P1 carboxylate ionized species. Superimpositions were performed using two alignment rules, namely, an alignment of the structures based on RMS fitting of the backbone heavy atoms of each structure to compound 2 and an alignment based on SYBYL QSAR rigid body field fit of the steric and electrostatic fields of the molecules to the fields of compound 2. Use of LUMO energies or ClogP as additional descriptors in the QSAR table did not improve the significance of the CoMFA models. Steric and electrostatic fields of the inhibitors were found to be the relevant descriptors for structure-activity relationships. The predictive ability of the CoMFA model was evaluated by using a test set of 10 compounds (r2pred as high as 0.859). Further comparison of the coefficient contour maps with the steric and electrostatic properties of the receptor show a high level of compatibility.

Quantitative structure-activity relationship studies of a series of sulfa drugs as inhibitors of Pneumocystis carinii dihydropteroate synthetase

Sulfone and sulfanilamide sulfa drugs have been shown to inhibit dihydropteroate synthetase (DHPS) isolated from Pneumocystis carinii. In order to develop a pharmacophoric model for this inhibition, quantitative structure-activity relationships (QSAR) for sulfa drugs active against DHPS have been studied. Accurate 50% inhibitory concentrations were collected for 44 analogs, and other parameters, such as partition coefficients and molar refractivity, were calculated. Conventional multiple regression analysis of these data did not provide acceptable QSAR. However, three-dimensional QSAR provided by comparative molecular field analysis did give excellent results. Upon removal of poorly correlated analogs, a data set of 36 analogs, all having a common NHSO2 group, provided a cross-validated r2 value of 0.699 and conventional r2 value of 0.964. The resulting pharmacophore model should be useful for understanding and predicting the binding of DHPS by new sulfa drugs.

Alignment of flexible molecules at their receptor site using 3D descriptors and Hi-PCA

Three categories of molecular flexibility are defined. A novel method of aligning partly flexible molecules with each other is described. The binding mode of one of these molecules to its receptor site was already well known from previous crystallographic studies, and this known binding mode was used to predict the binding mode of the other molecules at their receptor. The predictions were checked by comparison with previous observations, and were correct. Two novel methods were combined in this research. It was necessary to take account of the conformational changes which occur when each ligand molecule binds to the protein, and a new release of programme Grid was used for this. It was also necessary to analyse the Grid results in order to distinguish the role of each chemical group at the receptor site. This was done by applying hierarchical principal component analysis (Hi-PCA) methods to the descriptors obtained from Grid.

Arylamide inhibitors of HIV-1 integrase

Based on data derived from a large number of HIV-1 integrase inhibitors, similar structural features can be observed, which consist of two aryl units separated by a central linker. For many inhibitors fitting this pattern, at least one aryl ring also requires ortho bis-hydroxylation for significant inhibitory potency. The ability of such catechol species to undergo in situ oxidation to reactive quinones presents one potential limitation to their utility. In an effort to address this problem, a series of inhibitors were prepared which did not contain ortho bishydroxyls. None of these analogues exhibited significant inhibition. Therefore an alternate approach was taken, whose aim was to increase potency rather than eliminate catechol substructures. In this latter study, naphthyl nuclei were utilized as aryl components, since a previous report had indicated that fused bicyclic rings may afford higher affinity relative to monocyclic phenyl-based systems. In preliminary work with monomeric units, it was found that the 6,7-dihydroxy-2-naphthoic acid (17) (IC50 = 4.7 microM) was approximately 10-fold more potent than its 5,6-dihydroxy isomer 19 (IC50 = 62.4 microM). Of particular note was the dramatic difference in potency between free acid 17 and its methyl ester 21 (IC50 > 200 microM). The nearly total loss of activity induced by esterification strongly indicates that the free carboxylic -OH is important for high potency of this compound. This contrasts with the isomeric 5,6-dihydroxy species 19, where esterification had no effect on inhibitory potency (23, IC50 = 52.7 microM). These data provide evidence that the monomeric 6,7- and 5,6-dihydroxynaphthalenes may be interacting with the enzyme in markedly different fashions. However, when these naphthyl nuclei were incorporated into dimeric structures, significant enhancements in potencies each relative to the monomeric acids were observed, with bis-6,7-dihydroxy analogue 49 and bis-5,6-dihydroxy analogue 51 both exhibiting approximately equal potencies (IC50 values of 0.81 and 0.11 microM, respectively).

Structure-activity correlation study of HIV-1 inhibitors: electronic and molecular parameters

Quantitative structure-activity relationships (QSARs) for 40 HIV-1 inhibitors, 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine and its derivatives, were studied. Fully optimized geometries, based on the semiempirical AMl method, were used to calculate electronic and molecular properties of all compounds. In order to examine the relation between biological activities and structural properties, multiple linear regression models were employed. A suitable QSAR model was obtained, showing not only statistical significance, but also predictive ability. The significant molecular descriptors used were atomic charges of two substituted carbon atoms in the thymine ring, hydration energies and molar refractivities of the molecules. These descriptors allowed a physical explanation of electronic and molecular properties contributing to HIV-1 inhibitory potency.

A comparative molecular field analysis study of N-benzylpiperidines as acetylcholinesterase inhibitors

A series of 1-benzyl-4-[2-(N-benzoylamino)ethyl]piperidine derivatives and of N-benzylpiperidine benzisoxazoles has been investigated using the comparative molecular field analysis (CoMFA) approach. These compounds have been found to inhibit the metabolic breakdown of the neurotransmitter acetylcholine (ACh) by the enzyme acetylcholinesterase (AChE) and hence alleviate memory deficits in patients with Alzheimer's Disease by potentiating cholinergic transmission. Development of the CoMFA model considered two separate alignments: (i) alignment I which emphasized the electrostatic fitting of the subject compounds and (ii) alignment II which emphasized their steric fitting. In addition, the inhibitor compounds were considered both as neutral species and as N-piperidine-protonated species. The resulting 3D-QSAR indicates a strong correlation between the inhibitory activity of these N-benzylpiperidines and the steric and electronic factors which modulate their biochemical activity. A CoMFA model with considerable predictive ability was obtained.

A new procedure for improving the predictiveness of CoMFA models and its application to a set of dihydrofolate reductase inhibitors

A new automated procedure to improve the predictive quality of CoMFA models for both training and test sets is described. A model of greater consistency is generated by performing small reorientations of the underlying molecules for which too low activities are calculated. In order to predict activities of test compounds, the most similar molecules in the previously optimized model are identified and used as a basis for the prediction. This method has been applied to two independent sets of dihydrofolate reductase inhibitors (80 compounds each, serving as training sets), resulting in a significant increase of the cross-validated r2 value. For both models, the predictive r2 value for a test set consisting of 70 compounds was improved substantially.