3D-QSAR CoMFA on cyclin-dependent kinase inhibitors

Discovery of novel antifungal resorcylate aminopyrazole Hsp90 inhibitors based on structural optimization by molecular simulations

Novel antifungal resorcylate aminopyrazole Hsp90 inhibitors were discovered by 3D-QSAR, molecular docking and molecular dynamics simulations.

Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor

Endocrine-disrupting chemicals (EDCs) can interact with nuclear receptors, including estrogen receptor α (ERα) and androgen receptor (AR), to affect the normal endocrine system function, causing severe symptoms. Limited studies queried the EDC mechanisms, focusing on limited chemicals or a set of structurally similar compounds. It remained uncertain how hundreds of diverse EDCs could bind to ERα and AR and cause distinct functional consequences. Here, we employed a series of computational methodologies to investigate the structural features of EDCs that bind to and activate ERα and AR based on more than 4000 compounds. We used molecular docking and molecular dynamics simulations to elucidate the functional consequences and validated structure-function correlations experimentally using a time-resolved fluorescence resonance energy-transfer assay. We found that EDCs share three levels of key fragments. Primary (20 for ERα and 18 for AR) and secondary fragments (38 for ERα and 29 for AR) are responsible for the binding to receptors, and tertiary fragments determine the activity type (agonist, antagonist, or mixed). In summary, our study provides a general mechanism for the EDC function. Discovering the three levels of key fragments may drive fast screening and evaluation of potential EDCs from large sets of commercially used synthetic compounds.

Yeast as a model system to screen purine derivatives against human CDK1 and CDK2 kinases

Cyclin-dependent kinases (Cdk) play crucial roles in cell cycle progression. Aberrant activation of Cdk1 has been observed in a number of primary tumors and Cdk2 is deregulated in various malignancies. The therapeutic value of targeting Cdk1 and Cdk2 has been explored in a number of experimental systems. In the present study, taking advantage of the fact that deletion of the yeast CDC28 gene is functionally complemented by human CDK1 or CDK2, we set up an in vivo screen system to evaluate the inhibitory potency of purine derivatives against these two human Cdks. We constructed three isogenic strains highly sensitive to small molecules and harboring genes CDK1, CDK2 or CDC28, under the control of the CDC28 promoter. In a proof of principle assay, we determined the inhibitory effect of 82 purine derivatives on the growth rate of these strains. Thirty-three of them were revealed to be able to inhibit the Cdk1- or Cdk2-harboring strains but not the Cdc28-harboring strain, suggesting a specific inhibitory effect on human Cdks. Our data demonstrate that the yeast-based assay is an efficient system to identify potential specific inhibitors that should be preferentially selected for further investigation in cultured human cell lines.

Synthesis and biological evaluation of metabolites of 2-n-butyl-9-methyl-8-[1,2,3]triazol-2-yl-9H-purin-6-ylamine (ST1535), a potent antagonist of the A2A adenosine receptor for the treatment of Parkinson's disease

The synthesis and preliminary in vitro evaluation of five metabolites of the A2A antagonist ST1535 (1) are reported. The metabolites, originating in vivo from enzymatic oxidation of the 2-butyl group of the parent compound, were synthesized from 6-chloro-2-iodo-9-methyl-9H-purine (2) by selective C-C bond formation via halogen/magnesium exchange reaction and/or palladium-catalyzed reactions. The metabolites behaved in vitro as antagonist ligands of cloned human A2A receptor with affinities (Ki 7.5-53 nM) comparable to that of compound 1 (Ki 10.7 nM), thus showing that the long duration of action of 1 could be in part due to its metabolites. General behavior after oral administration in mice was also analyzed.

Effect of steric molecular field settings on CoMFA predictivity

Steric molecular field can be represented in a number of ways in comparative molecular field analysis (CoMFA). This study aimed to investigate whether the choice of steric molecular field settings significantly influences the predictive performance of CoMFA and, if so, which is the best. The three-dimensional quantitative structure activity relationship (3D-QSAR) models based on Lennard-Jones, indicator, parabolic and Gaussian steric fields were compared using 28 datasets taken from the literature. The analysis of the predictive ability of these models (cross validated R(2)) indicates that steric fields in which the value drops off quickly with distance (i.e. Lennard-Jones and indicator fields) tend to perform better than the Gaussian version, which has a slower and smoother decrease. Furthermore, depending on the steric field type used, the field sampling density (i.e. grid spacing) has a variable influence on the predictive ability of the models generated.

Comparative molecular field analysis of flavonoid inhibitors of the PIM-1 kinase

The PIM-1 protein, the product of the pim-1 oncogene, is a serine/threonine kinase. Dysregulation of the PIM-1 kinase has been implicated in the development of human malignancies including lymphomas, leukemias, and prostate cancer. Comparative molecular field analysis (CoMFA) is a 3-D QSAR technique that has been widely used, with notable success, to correlate biological activity with the steric and electrostatic properties of ligands. We have used a set of 15 flavonoid inhibitors of the PIM-1 kinase, aligned de novo by common substructure, to generate a CoMFA model for the purpose of elucidating the steric and electrostatic properties involved in flavonoid binding to the PIM-1 kinase. Partial least squares correlation between observed and predicted inhibitor potency (expressed as -logIC50), using a non-cross-validated partial least squares analysis, generated a non-cross-validated q2=0.805 for the training set (n=15) of flavonoids. The CoMFA generated steric map indicated that the PIM-1-binding site was sterically hindered, leading to more efficient binding of planar molecules over (R) or (S) compounds. The electrostatic map identified that positive charges near the flavonoid atom C8 and negative charges near C4' increased flavonoid binding. The CoMFA model accurately predicted the potency of a test set of flavonoids (n=6), generating a correlation between observed and predicted potency of q2=0.825. CoMFA models generated from additional alignment rules, which were guided by co-crystal structure ligand orientations, did not improve the correlative value of the model. Superimposing the PIM-1 kinase crystal structure onto the CoMFA contours validated the steric and electrostatic maps, elucidating the amino acid residues that potentially contribute to the CoMFA fields. Thus we have generated the first predictive model that may be used for the rational design of small-molecule inhibitors of the PIM-1 kinase.

Novel structural features of CDK inhibition revealed by an ab initio computational method combined with dynamic simulations

The rational development of specific inhibitors for the approximately 500 protein kinases encoded in the human genome is impeded by a poor understanding of the structural basis for the activity and selectivity of small molecules that compete for ATP binding. Combining classical dynamic simulations with a novel ab initio computational approach linear-scalable to molecular interactions involving thousands of atoms, we have investigated the binding of five distinct inhibitors to the cyclin-dependent kinase CDK2. We report here that polarization and dynamic hydrogen bonding effects, so far undetected by crystallography, affect both their activity and selectivity. The effects arise from the specific solvation patterns of water molecules in the ATP binding pocket or the intermittent formation of hydrogen bonds during the dynamics of CDK/inhibitor interactions and explain the unexpectedly high potency of certain inhibitors such as 3-(3H-imidazol-4-ylmethylene)-5-methoxy-1,3-dihydro-indol-2-one (SU9516). The Lys89 residue in the ATP-binding pocket of CDK2 is observed to form temporary hydrogen bonds with the three most potent inhibitors. This residue is replaced in CDK4 by Thr89, whose shorter side-chain cannot form similar bonds, explaining the relative selectivity of the inhibitors for CDK2. Our results provide a generally applicable computational method for the analysis of biomolecular structures and reveal hitherto unrecognized features of the interaction between protein kinases and their inhibitors.

QSAR studies on 1-phenylbenzimidazoles as inhibitors of the platelet-derived growth factor

This work is devoted to the development of quantitative structure-activity relationship (QSAR) models of the biological activity of 123 1-phenylbenzimidazoles as inhibitors of the PDGF receptor. The molecular features are represented by chemical descriptors that have been calculated on geometrical, topological, quantum mechanical, and electronic basis by using CODESSA PRO. The obtained models, linear (multilinear regression) and nonlinear (artificial neural network), are aimed to link the structures to their reported activity log 1/IC50. The former model can be used for physico-chemical interpretation, while the latter possesses a superior predictive ability.

Preparation of a Fully Substituted Purine Library

A library of tetra-substituted purine analogues was readily prepared via parallel synthesis. This strategy relies on a key cyclization of a 4,5-diaminopyrimidine with either a carboxylic acid or its derivative to construct the 2,8,9-trisubstituted 6-chloropurine core. Further elaborations of this core allow the introduction of other diversity points. This methodology is demonstrated through the preparation of a 135-membered library of tetra-substituted purines in good yields and high purity.

Evaluation and Comparison of 3D-QSAR CoMSIA Models for CDK1, CDK5, and GSK-3 Inhibition by Paullones

With a view to the rational design of selective GSK-3beta inhibitors, 3D-QSAR CoMSIA models were developed for the inhibition of the three serine/threonine kinases CDK1/cyclin B, CDK5/p25, and GSK-3beta by compounds from the paullone inhibitor family. The models are based on the kinase inhibition data of 52 paullone entities, which were aligned by a docking routine into the ATP-binding cleft of a CDK1/cyclin B homology model. Variation of grid spacing and column filtering were used during the optimization of the models. The predictive ability of the models was shown by a leave-one-out cross-validation and the prediction of an independent set of test compounds, which were synthesized especially for this purpose. Besides paullones with the basic indolo[3,2-d][1]benzazepine core, the test set comprised novel thieno[3',2':2,3]azepino[4,5-b]indoles, pyrido[2',3':2,3]azepino[4,5-b]indoles, and a pyrido[3',2':4,5]pyrrolo[3,2-d][1]benzazepine. The best statistical values for the CoMSIA were obtained for the CDK1-models (r(2)() = 0.929 and q(2)() = 0.699), which were clearly superior to the models for CDK5 (r(2)() = 0.874 and q(2)() = 0.652) and GSK-3 (r(2)() = 0.871 and q(2)() = 0.554).

Aryl[ a ]pyrrolo[3,4- c ]carbazoles as selective cyclin D1-CDK4 inhibitors

The synthesis of new analogues of Arcyriaflavin A in which one indole ring is replaced by an aryl or heteroaryl ring is described. These new series of aryl[a]pyrrolo[3,4-c]carbazoles were evaluated as inhibitors of Cyclin D1-CDK4. A potent and selective D1-CDK4 inhibitor, 7a (D1-CDK4 IC(50)=45 nM), has been identified. The potency, selectivity profile against other kinases, and structure-activity relationship (SAR) trends of this class of compounds are discussed.

Quantitative structure–activity relationships (QSAR): studies of inhibitors of tyrosine kinase

A quantitative structure-activity relationship (QSAR) study of the 1-phenylbenzimidazoles as inhibitors of the platelet-derived growth factor receptor (PDGFR) was performed. Some new electronic parameters Q(o), Q(m) and Q(p) are suggested for characterizing the effect of substituents. Many other descriptors are also used which are selected by evolution algorithm (EA) using modified Cp as objective function proposed by the present authors. The descriptor Q(m) is shown to be an important variable to express effect of substituents. The variable selection shows that spatial descriptors are most important variables revealing important properties of the inhibitors. Electron-releasing substitutes at 5-position and the absence of bulky groups at 4,7-positions of the parent structure can enhance inhibitor activity. Principal component analysis is performed to classify this series of compounds.

Synthesis of quinolinyl/isoquinolinyl[a]pyrrolo [3,4-c] carbazoles as cyclin D1/CDK4 inhibitors

A novel series of pyrrolo[3,4-c] carbazoles fused with a quinolinyl/isoquinolinyl moiety were synthesized and their D1/CDK4 inhibitory and antiproliferative activity were evaluated. Compound 8H, 14H-isoquinolinyl[6,5-a]-pyrrolo[3,4-c]carbazole-7,9-dione (1d) was found to be a highly potent D1/CDK4 inhibitor with an IC(50) of 69 nM. Compound 1d also inhibited tumor cell growth, arrested tumor cells in G1 phase and inhibited pRb phosphorylation.

Synthesis and evaluation of indenopyrazoles as cyclin-dependent kinase inhibitors. 2. Probing the indeno ring substituent pattern

We disclose a novel series of indenopyrazole-based cyclin-dependent kinase (CDK) inhibitors. Kinetic experiments confirmed our initial molecular modeling studies that the compounds are competitive with respect to adenosine 5'-triphosphate (ATP) and bind in the kinase ATP pocket. A unique combination of active pharmacophores led us to a series of semicarbazide-based inhibitors that are highly potent against CDK2 and CDK4 while maintaining selectivity against other relevant serine/threonine kinases. These compounds were active against a transformed human colon cancer cell line (HCT116) while maintaining an acceptable margin of activity against a normal fibroblast cell line. The compounds were found to be highly protein bound in our cell-based assay with the exception of 11k, which maintained a reasonable level of activity in the presence of human plasma proteins.

Physicochemical explanation of peptide binding to HLA-A*0201 major histocompatibility complex: a three-dimensional quantitative structure-activity relationship study

A three-dimensional quantitative structure-activity relationship method for the prediction of peptide binding affinities to the MHC class I molecule HLA-A*0201 was developed by applying the CoMSIA technique on a set of 266 peptides. To increase the self consistency of the initial CoMSIA model, the poorly predicted peptides were excluded from the training set in a stepwise manner and then included in the study as a test set. The final model, based on 236 peptides and considering the steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor fields, had q2 = 0.683 and r2 = 0.891. The stability of this model was proven by cross-validations in two and five groups and by a bootstrap analysis of the non-cross-validated model. The residuals between the experimental pIC50 (-logIC50) values and those calculated by "leave-one-out" cross-validation were analyzed. According to the best model, 63.2% of the peptides were predicted with /residuals/ < or = 0.5 log unit; 29.3% with 1.0 < or = /residuals/ < 0.5; and 7.5% with /residuals/ > 1.0 log unit. The mean /residual/ value was 0.489. The coefficient contour maps identify the physicochemical property requirements at each position in the peptide molecule and suggest amino acid sequences for high-affinity binding to the HLA-A*0201 molecule.

Quantitative approaches to computational vaccinology

This article reviews the newly released JenPep database and two new powerful techniques for T-cell epitope prediction: (i) the additive method; and (ii) a 3D-Quantitative Structure Activity Relationships (3D-QSAR) method, based on Comparative Molecular Similarity Indices Analysis (CoMSIA). The JenPep database is a family of relational databases supporting the growing need of immunoinformaticians for quantitative data on peptide binding to major histocompatibility complexes and to the Transporters associated with Antigen Processing (TAP). It also contains an annotated list of T-cell epitopes. The database is available free via the Internet (http://www.jenner.ac.uk/JenPep). The additive prediction method is based on the assumption that the binding affinity of a peptide depends on the contributions from each amino acid as well as on the interactions between the adjacent and every second side-chain. In the 3D-QSAR approach, the influence of five physicochemical properties (steric bulk, electrostatic potential, local hydrophobicity, hydrogen-bond donor and hydrogen-bond acceptor abilities) on the affinity of peptides binding to MHC molecules were considered. Both methods were exemplified through their application to the well-studied problem of peptides binding to the human class I MHC molecule HLA-A*0201.

Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201

A method has been developed for prediction of binding affinities between proteins and peptides. We exemplify the method through its application to binding predictions of peptides with affinity to major histocompatibility complex class I molecule HLA-A*0201. The method is named "additive" because it is based on the assumption that the binding affinity of a peptide could be presented as a sum of the contributions of the amino acids at each position and the interactions between them. The amino acid contributions and the contributions of the interactions between adjacent side chains and every second side chain were derived using a partial least squares (PLS) statistical methodology using a training set of 420 experimental IC50 values. The predictive power of the method was assessed using rigorous cross-validation and using an independent test set of 89 peptides. The mean value of the residuals between the experimental and predicted pIC50 values was 0.508 for this test set. The additive method was implemented in a program for rapid T-cell epitope search. It is universal and can be applied to any peptide-protein interaction where binding data is known.

Three-dimensional quantitative structure-activity relationships of cyclo-oxygenase-2 (COX-2) inhibitors: a comparative molecular field analysis

The three-dimensional quantitative structure-activity relationship (3D-QSAR) approach using comparative molecular field analysis (CoMFA) was applied to an extensive series of 305 varied diarylheterocyclic derivatives known as COX-2 selective inhibitors. X-ray crystal structure of COX-2 bound with SC-558, a selective COX-2 inhibitor, was used to derive the putative bioactive conformation of these inhibitors. Five statistically significant models were obtained from the randomly constituted training sets (229 compounds) and subsequently validated with the corresponding test sets (76 compounds). The best predictive model (n = 229, q(2) = 0.714, N = 8, r(2) = 0.905, s = 0.291, F = 261.545) was selected for further comparison of the CoMFA contour maps obtained for steric, electrostatic, and lipophilic fields with the enzyme structure. The high level of compatibility with the COX-2 enzyme topology shows the great accuracy of this model that can predict inhibitory activities for a wide range of compounds and offers important structural insight into designing novel antiinflammatory drugs prior to their synthesis.