Formulation of 3D pharmacophore models for bradykinin B2-receptor antagonists

Summary In order to make a further contribution to the elucidation of the essential structural features for bradykinin (BK) antagonism, we extracted 3D pharmacophore models from a training set consisting of nine relatively rigid, small organic, non-peptide molecules, reported to be more or less active, competitive BK B₂-receptor antagonists. This was accomplished by means of the expert system Catalyst^TM. The information contained in one of these models was then used to identify relevant structural features and perform consensus molecular dynamics simulations including, in addition to the non-peptide antagonist set, four prototypical linear and cyclic peptide antagonists, and BK itself. this combined approach allowed us to identify regions of the conformational space shared by this series of compounds, which includes highly flexible, and, hence, otherwise almost inaccessible for conventional conformational sampling techniques, peptide molecules. As a result, we obtained a relatively small number of extended pharmacophore models, whose average, together with the original Catalyst model, could be used to search proprietary 3D databases for potential candidates. The results of such a search are also reported.     

Discovery of potent inhibitors for interleukin-2-inducible T-cell kinase: structure-based virtual screening and molecular dynamics simulation approaches

In our study, a structure-based virtual screening study was conducted to identify potent ITK inhibitors, as ITK is considered to play an important role in the treatment of inflammatory diseases. We developed a structure-based pharmacophore model using the crystal structure (PDB ID: 3MJ2) of ITK complexed with BMS-50944. The most predictive model, SB-Hypo1, consisted of six features: three hydrogen-bond acceptors (HBA), one hydrogen-bond donor (HBD), one ring aromatic (RA), and one hydrophobic (HY). The statistical significance of SB-Hypo1 was validated using wide range of test set molecules and a decoy set. The resulting well-validated model could then be confidently used as a 3D query to screen for drug-like molecules in a database, in order to retrieve new chemical scaffolds that may be potent ITK inhibitors. The hits retrieved from this search were filtered based on the maximum fit value, drug-likeness, and ADMET properties, and the hits that were retained were used in a molecular docking study to find the binding mode and molecular interactions with crucial residues at the active site of the protein. These hits were then fed into a molecular dynamics simulation to study the flexibility of the activation loop of ITK upon ligand binding. This combination of methodologies is a valuable tool for identifying structurally diverse molecules with desired biological activities, and for designing new classes of selective ITK inhibitors.

Three-dimensional Pharmacophore Hypotheses for the Locust Neuronal Octopamine Receptor (OAR3): 1. Antagonists

Three-dimensional pharmacophore hypotheses were built from a set of 17 mianserin-like antagonists against octopamine receptor class 3 (OAR3) in locust nervous tissue. Among the ten chemical-featured models generated by program Catalyst/Hypo, three hypotheses were considered to be important and predictive in evaluating OAR3 antagonists. Predictions were fairly precise for all molecules but the three outliners including eresepine, metoclopramide and yohimbine. While the ideal and null hypotheses had a cost of 66.50 and 124.97, respectively, the ten resulting hypotheses possessed costs from 78.96 to 92.04. The best hypothesis that was confirmed to have a 95% chance of true correlation yielded a low RMS of 1.05 and high regression r of 0.934. Active antagonists mapped well onto all the features of the hypothesis such as hydrophobic, aromatic ring or positive ionizable features. On the other hand, inactive compounds lack of binding affinity were shown to be poorly capable of achieving an energetically favorable conformation shared by the active molecules in order to fit the 3D chemical feature pharmacophore models. In addition, from the comparison and conformation analysis it was proposed that positive ionizable feature contained a lower weight than hydrophobic or an aromatic ring one. Further research on the comparison of models from agonists and antagonists may help elucidate the mechanisms of OAR3 and other types of octopamine receptor-ligand interactions.     

Effects of two novel non-peptide antagonists at the rabbit bradykinin B2 receptor

Large species differences have been previously observed in the pharmacology of bradykinin (BK) B2 receptor antagonists. We investigated the effect of two novel non-peptide antagonists, compound 9 (a benzodiazepine peptidomimetic related to icatibant) and the thiosemicarbazide bradyzide on the rabbit B2 receptor (contractility of the jugular vein, competition of [3H]BK binding to a B2 receptor-green fluorescent protein (B2R-GFP) conjugate, subcellular distribution of B2R-GFP). While compound 9 is about 9000-fold less potent than icatibant, it shares with the latter peptide drug a selective, insurmountable and largely irreversible antagonist behavior against BK and the capacity to translocate B2R-GFP from the membrane into the cells. Bradyzide, reportedly very potent at rodent B2 receptors, was a competitive and reversible antagonist of moderate potency at the rabbit B2 receptor (contractility pA2 6.84, binding competition IC50 5 nM). The C-terminal region of icatibant, reproduced by compound 9, is likely to be important in the non-equilibrium behavior of icatibant. Bradyzide, a non-peptide antagonist developed on different structural grounds, is competitive at the rabbit B2 receptor.     

CoMFA and CoMSIA studies of angiotensin (AT1) receptor antagonists

Two 3D-QSAR methods--CoMFA and CoMSIA--were applied to a set of 38 angiotensin receptor (AT1) antagonists. The conformation and alignment of molecules were obtained by a novel method - consensus dynamics. The representation of biological activity, partial charge formalism, absolute orientation of the molecules in the grid, and grid spacing were also studied for their effect on the CoMFA models. The models were thoroughly validated through trials using scrambled activities and bootstrapping. The best CoMFA model had a cross-validated correlation coefficient ( q2) of 0.632, which improved with "region focusing" to 0.680. This model had a "predictive" r2 of 0.436 on a test series that was unique and with little representation in the training set. Although the "predictive" r2 of the best CoMSIA model, which included steric, electrostatic, and hydrogen bond acceptor fields was higher than that of the best CoMFA model, the other statistical parameters like q2, r2, F value, and s were unsatisfactory. The contour maps generated using the best CoMFA model were used to identify the structural features important for biological activity in these compounds.     

Novel non-peptide lead structures forBradykinin B2-receptor antagonists

A series of new non-peptide Bradykinin (BK)B₂-receptor antagonists is reported. These newleads belong to a larger set including bothcommercially or otherwise available potentialcandidates found by proprietary database searchesusing 3D-pharmacophore models as query, and severalbis-benzamidino compounds selected from ourtryptase-like protease inhibitor library on thebasis of topological considerations, derived fromthe same models.Some of these compounds show functional competitiveantagonistic activity, inhibiting {in vitro} the BK-induced contraction of isolated guinea-pig ileum(GPI) and rat uterus with a pA₂ up to 5.3 and7.0, respectively. They display also bindingaffinity (IC₅₀ up to 0.56 M) to the BKB₂-receptor in radioligand binding assays onGPI membrane preparations and on human IMR-90 fetallung fibroblast cells expressing this receptor subtype.Furthermore, the results with the commerciallyavailable compounds, in some cases developed astherapeutics, show that the used 3D-pharmacophoremodel allows to predict to some certainty possibleside actions of potential drugs.     

Identification of novel non-peptide CXCR4 antagonists by ligand-based design approach

The design and synthesis of novel non-peptide CXCR4 antagonists is described. The peptide backbone of highly potent cyclic peptide-based CXCR4 antagonists was entirely replaced by an indole framework, which was expected to reproduce the disposition of the key pharmacophores consistent with those of potential bioactive conformations of the original peptides. A structure–activity relationship study on a series of modified indoles identified novel small-molecule antagonists having three pharmacophore functional groups through the appropriate linkers.     

Pharmacophore mapping of a series of pyrrolopyrimidines,indolopyrimidines and their congeners as multidrug-resistance-associated protein (MRP1) modulators

Pharmacophore mapping studies were undertaken for a series of molecules belonging to pyrrolopyrimidines, indolopyrimidines and their congeners as multidrug resistance-associated protein (MRP1) modulators. A five-point pharmacophore with two hydrogen bond acceptors (A), one lipophilic/hydrophobic group (H), one positive ionic feature (P) and one aromatic ring (R) as pharmacophoric features was developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of r ² = 0.799 for training set molecules. The model generated showed excellent predictive power, with a correlation coefficient Q ² = 0.679 for an external test set of 20 molecules. The pharmacophore was further validated using four structurally diverse compounds with MRP1 modulatory activity. These compounds mapped well onto four of the five features of the pharmacophore. The pharmacophore proposed here was then utilised for the successful retrieval of active molecules with diverse chemotypes from database search. The geometry and features of pharmacophore are expected to be useful for the design of selective MRP1 inhibitors. Figure Alignment of multidrug resistance-associated protein (MRP1) inhibitors with the developed pharmacophore. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Comparative conformational analysis of two endothelin-B antagonists

Summary A comparative conformational analysis of two short pseudopeptides with ET_B receptor affinity has been performed by molecular modelling and NMR techniques. This analysis aimed to get insight into probable biorelevant conformations and pharmacophoric patterns necessary for an efficient interaction with the receptor. Thus, it was shown that the two compounds can adopt -turn (or -turn-like) conformations, based on which the synthesis of particular, more rigid analogs might be proposed. The results obtained should prove valuable in a strategy aiming to design new endothelin antagonists following a peptide to non-peptide approach.     

Conformational properties of a cyclic peptide bradykinin B2 receptor antagonist using experimental and theoretical methods.

The solution conformation of the cyclic peptide J324 (cyclo0,6-[Lys0,Glu6,D-Phe7]BK), an antagonist targeted at the bradykinin (BK) B2 receptor, has been investigated using experimental and theoretical methods. In order to gain insight into the structural requirements essential for BK antagonism, we carried out molecular dynamics (MD) simulations using simulated annealing as the sampling protocol. Following a free MD simulation we performed simulations using nuclear Overhauser enhancement (NOE) distance constraints determined by NMR experiments. The low-energy structures obtained were compared with each other, grouped into families and analyzed with respect to the presence of secondary structural elements in their backbone. We also introduced new ways of plotting structural data for a more comprehensive analysis of large conformational sets. Finally, the relationship between characteristic backbone conformations and the spatial arrangement of specific pharmacophore centers was investigated.     

Computer-aided discovery of novel non-peptide inhibitors against amyloid-beta (Aβ) peptide aggregation for treating Alzheimer's disease

A non-peptide inhibitor that is metabolically stable, orally active and capable of crossing the blood–brain barrier has been a popular option for treating Alzheimer's disease (AD). To identify novel non-peptide inhibitors for AD drug development, a structure-based pharmacophore model (SBPM) was developed using the representative docked conformation of the recently discovered peptide inhibitor PGKLVYA in the potential binding site on the Aβ(17–42) protofibril. The best SBPM, consisting of two hydrophobic, one hydrogen bond donor, and one positive ionisable feature, was further validated using ligand pharmacophore mapping studies. The well-validated SBPM was then used as the 3D query in virtual screening to identify potential hits from the National Cancer Institute database. These hits were subsequently filtered by toxicity prediction and molecular docking, and their binding stabilities and affinities were validated by 20-ns molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area analysis, respectively. Finally, two Hits (NSC35984 and NSC102747) were identified as potential leads, which exhibited higher binding stability and affinity towards Aβ compared with PGKVYA. Our results also suggest that these two Hits have the ability to prevent Aβ adopting toxic β-sheet structures, and can be easily synthesised and have structural novelty, indicating that they are promising candidates for treating AD.     

Bioactive conformations of peptides and mimetics as milestones in drug design: Investigation of NK1 receptor antagonists

Summary Nine potent and selective substance P receptor antagonists (NK₁ ^-) were analyzed with respect to their conformational space, with the aim to suggest probable conformations adopted at the receptor site and superposition rules for each structure (pharmacophore mapping). Key atoms within the ligands as well as receptor site points were considered in order to identify acceptable solutions (DISCO program). The results obtained allowed the suggestion or probable peptidic pharmacophores based on the structure of 1 (FK888). This knowledge was used to search commercial databases. The number and diversity of known retrieved NK₁ antagonists allowed a general evaluation of the proposed pharmacophores. Moreover, a search in our proprietary database detected a short peptide with modest affinity but high selectivity for the NK₁ receptor. The combination of molecular modeling with database searches is useful in a strategy aiming to develop new NK₁ antagonists starting from existing knowledge.     

CYP isoform specificity toward drug metabolism: analysis using common feature hypothesis

Three dimensional pharmacophoric maps were generated for each isoforms of CYP2C9, CYP2D6 and CYP3A4 separately using independent training sets consist of highly potent substrates (seven substrates for each isoform). HipHop module of CATALYST software was used in the generation of pharmacophore models. The best pharmacophore model was chosen out of the several models on the basis of (i) highest ranking score, (ii) better fit value among training set, (iii) capability to screen substrates from data set and (iv) efficiency to identify the isoform specificity. The individual pharmacophore models (CYP2C9-hypo1, CYP2D6-hypo1 and CYP3A4-hypo1) are characterized by the pharmacophoric features XZDH, RPZH and XYZHH for the CYP2C9, CYP2D6 and CYP3A4 respectively. Each of the chosen models was validated by using data sets of CYP substrates. This comparative study of CYP substrates demonstrates the importance of acidic character along with HBD and HBAl features for CYP2C9, basic character with ring aromatic features for CYP2D6 and hydrophobic features for CYP3A4. Acidity, basicity and hydrophobicity features arising from the functional groups of the substrates are also responsible for demonstrating CYP isoform specificity. Hence, these chemical features are incorporated in the decision tree along with pharmacophore maps. Finally, a decision tree based on chemical features and pharmacophore features was generated to identify the isoform specificity of novel query molecule toward the three isoforms.     

Pharmacophore mapping and in silico screening to identify new potent leads for A2A adenosine receptor as antagonists

A_2A adenosine receptor (AR) antagonists play an important role in neurodegenerative diseases like Parkinson’s disease. A 3D-QSAR study of A_2A AR antagonists, was taken up to design best pharmacophore model. The pharmacophoric features (ADHRR) containing a hydrogen bond acceptor (A), a hydrogen bond donor (D), a hydrophobic group (H) and two aromatic rings (R), is projected as the best predictive pharmacophore model. The QSAR model was further treated as a template for in silico search of databases to identify new scaffolds. The binding patterns of the leads with A_2A AR are analysed using docking studies and novel potent ligands of A_2A AR are projected.     

Identification of structural motifs in the E2 glycoprotein of Chikungunya involved in virus–host interaction

Chikungunya fever is one of the reemerging vector-borne diseases. It has become a major global health problem especially in the developing countries. There are no vaccines or specific antiviral drugs available to date. This study reports small molecule inhibitors of envelope glycoprotein 2 (E2 glycoprotein) which are predicted based on Chikungunya virus–host interactions. E2 glycoprotein of Chikungunya virus interacts at 216 residue of the host receptor protein which plays a vital role in initiating infection. Understanding the structural aspects of E2 glycoprotein is crucial to develop specific inhibitors to prevent the virus binding from host receptors. In silico method was adopted to predict the sequence motifs of envelope protein, as the method like yeast two hybrid system is laborious, time consuming, and costly. The E2 glycoprotein structure of the Indian isolate was modeled using two templates (2XFC and 3JOC) and then validated. The class III PDZ domain binding motif was found to be identified at 213–216 amino acids. The corresponding peptide structures which recognize the PDZ domain binding motif were identified by the literature search and were used for generating five point pharmacophore model (ADDDR) containing acceptor, donor and aromatic ring features. Databases such as Asinex, TosLab and Maybridge were searched for the matches for the predicted pharmacophore model. Two compounds were identified as lead molecules as their glide score is?>?5?kcal/mol. Since the pharmacophore model is developed based on Chikungunya virus–host interaction, it can be used for designing promising antiviral lead compounds for the treatment of Chikungunya fever.An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:21     

Pharmacophore-based molecular docking to account for ligand flexibility

Rapid computational mining of large 3D molecular databases is central to generating new drug leads. Accurate virtual screening of large 3D molecular databases requires consideration of the conformational flexibility of the ligand molecules. Ligand flexibility can be included without prohibitively increasing the search time by docking ensembles of precomputed conformers from a conformationally expanded database. A pharmacophore-based docking method whereby conformers of the same or different molecules are overlaid by their largest 3D pharmacophore and simultaneously docked by partial matches to that pharmacophore is presented. The method is implemented in DOCK 4.0.     

A proposed bioactive form of peptide T and the design of peptidomimetics

Peptide T is a non-natural octapeptide of sequence Ala-Ser-Thr-Thr-Thr-Asn-Tyr-Thr, taken from the sequence of the protein gp120 of HIV. The peptide has been shown to bind competitively to the CD4 receptors of the helper/inducer lymphocytes T. The peptide is presently used for the treatment of AIDS-associated dementia and has been proven useful for the treatment of psoriasis. Using molecular modeling procedures, we studied the conformational profile of this peptide as well as those of several active and inactive analogs. The analysis of these results gave rise to the proposal of a bioactive conformation of the peptide, which can be described as a pseudo -turn structure, involving the last four residues at the C-terminus of the peptide. The secondary structure is stabilized by a hydrogen bond between the hydroxyl hydrogen of the side chain of Thr⁵ and the carbonyl oxygen of Tyr⁷. From the bioactive form and different structure–activity relationship studies, a pharmacophore was proposed. This hypothesis was used to search on several 3D data bases. One of the hits obtained was the natural compound amigdalin, which was tested and exhibited moderate activity.     

Exploring the binding features of rimonabant analogues and acyclic CB<Subscript>1</Subscript> antagonists: docking studies and QSAR analysis

In order to elucidate the structural requirements for human CB₁ receptor antagonism, 78 antagonists belonging to five different chemical classes were selected from the literature and docked into the receptor binding site, built by homology modeling techniques. To further explore the structure-activity relationships within the considered chemical classes, a pharmacophore model and a QSAR analysis were developed. In a first step five alignments, one for each group of compounds were generated. All of them were then submitted to a MOE pharmacophore search in order to obtain a final pharmacophore model representative of the whole dataset which was used to elaborate the following 3D-QSAR analysis, by means of the CoMFA methodology. The results of these investigations are expected to be useful in the process of design and development of new potent CB₁ antagonists. Figure Compounds 1-78 are aligned into the putative CB1 receptor binding site. The three key features shared by all of them are reported in coloured spheres. The hydrophobic/aromatic ones are depicted in purple while the acceptor functions are coloured in blue.