Toward the identification of a reliable 3D QSAR pharmacophore model for the CCK2 receptor antagonism

The present study describes application of computational approaches to identify a validated and reliable 3D QSAR pharmacophore model for the CCK-2R antagonism through integrated ligand and structure based studies using anthranilic sulfonamide and 1,3,4-benzotriazepine based CCK-2R antagonists. The best hypothesis consisted five features viz. two aliphatic hydrophobic, one aromatic hydrophobic, one H-bond acceptor, and one ring aromatic feature with an excellent correlation for 34 training set (r2(training) = 0.83) and 58 test set compounds (r2(test) = 0.74). This model was validated through F-test and docking studies at the active site of the plausible CCK-2R where the 99% significance and well corroboration with the pharmacophore model respectively describes the model's reliability. The model also predicts well to other known clinically effective CCK-2R antagonists. Therefore, the developed model may useful in finding new scaffolds that may aid in design and develop new chemical entities (NCEs) as potent CCK-2R antagonists before their synthesis.     

Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of −OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.     

3D QSAR analyses of novel tyrosine kinase inhibitors based on pharmacophore alignment

In an effort to develop a quantitative ligand-binding model for the receptor tyrosine kinases, a pharmacophore search was first used to identify structural features that are common in two novel sets of 12 molecules of the 3-substituted indolin-2-ones and 19 compounds of the benzylidene malononitriles with low-to-high affinity for HER2, a kind of receptor tyrosine kinase. The common pharmacophore model based on these 31 compounds was used as a template to obtain the aligned molecular aggregate, which provided a good starting point for 3D-QSAR analysis of only the 19 benzylidene malononitriles. Two molecular field analysis (MFA) techniques, including CoMFA and CoMSIA, were used to derive the quantitative structure-activity relationships of the studied molecules. From the studied results, it was obvious that the 3D-QSAR models based on the pharmacophore alignment were superior to those based on the simple atom-by-atom fits. Considering the flexibility of the studied molecules and the difference between the active conformers and the energy-lowest conformers, the pharmacophore model can usually provide the common features for the flexible regions. Moreover, the best CoMSIA model based on the pharmacophore hypothesis gave good statistical measure from partial least-squares analysis (PLS) (q(2) = 0.71), which was slightly better than the CoMFA one. Our study demonstrated that pharmacophore modeling and CoMSIA research could be effectively combined. Results obtained from both methods helped with understanding the specific activity of some compounds and designing new specific HER2 inhibitors.     

Joint QSAR analysis using the Free-Wilson approach and quantum chemical parameters

A new quantitative structure-activity relationship (QSAR) technique combining the Free-Wilson method and constructed quantum chemical parameters was used to simulate the aqueous solubility (Sw), 1-octanol/water partition coefficient (Kow) of 14 new synthesized benzanilide derivatives and their 96 h acute toxicity (EC50) to Daphnia magna. The mode of action of the 14 selected compounds to Daphnia magna was shown to be a complex process involving a physical partition stage and a bio-chemical reaction stage. The results also indicated that the joint (QSAR) analysis was much effective than the original Free-Wilson method and Hansch method not only in predicting properties/toxicity, but also in investigating the mode of action of chemicals.     

PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results

We introduce PHASE, a highly flexible system for common pharmacophore identification and assessment, 3D QSAR model development, and 3D database creation and searching. The primary workflows and tasks supported by PHASE are described, and details of the underlying scientific methodologies are provided. Using results from previously published investigations, PHASE is compared directly to other ligand-based software for its ability to identify target pharmacophores, rationalize structure-activity data, and predict activities of external compounds.     

A three-dimensional chemical phase pharmacophore mapping,QSAR modelling and electronic feature analysis of benzofuran salicylic acid derivatives as LYP inhibitors

Lymphoid tyrosine phosphatase (LYP), encoded by the PTPN22 gene, has a critical negative regulatory role in T-cell antigen receptor (TCR) and emerged as a promising drug target for human autoimmune diseases. A five-point pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and two aromatic ring features was generated for a series of benzofuran salicylic acid derivatives as LYP inhibitors in order to elucidate their anti-autoimmune activity. The generated pharmacophore yielded a significant 3D-QSAR model with r² of 0.9146 for a training set of 27 compounds. The model also showed excellent predictive power with Q² of 0.7068 for a test set of eight compounds. The investigation of the 3D-QSAR model has revealed the structural insights which could lead to more potent analogues. The most active and inactive compounds were further subjected to electronic structure analysis using density functional theory (DFT) at B3LYP/3?21^?G level to support the 3D-QSAR predictions. The results obtained from this study are expected to be useful in the proficient design and development of benzofuran salicylic acid derivatives as inhibitors of LYP.     

3D QSAR investigation of the blood-brain barrier penetration of chemical compounds

In the present study, we investigated structure-permeability relationships for the blood-brain barrier (BBB) of 16 imipramine and phenothiazine derivatives. The compounds belong to structurally related chemical classes of catamphiphiles, representatives of which have previously been investigated for membrane activity and ability to overcome multidrug resistance (MDR) in tumour cells. These studies show that phenothiazines and structurally related drugs (imipramines, thioxanthenes, acridines) interact with membrane phospholipids, and additionally inhibit the MDR transport P-glycoprotein. This study aimed to identify common 3D structural characteristics of these compounds related to their mechanism of transport across the BBB. For this purpose Genetic Algorithm Similarity Programme (GASP), Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) were applied. The results demonstrate the importance of the spatial distribution of molecular hydrophobicity for the BBB penetration of the investigated compounds. It suggests that the compounds should follow a specific profile of two hydrophobic and one hydrophilic centres in a particular space configuration, for optimal BBB penetration.     

Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor

Summary A systematic search has been used to derive a hypothesis for the receptor-bound conformation of A-II antagonists at the AT₁ receptor. The validity of the pharmacophore hypothesis has been tested using CoMFA, which included 50 diverse A-II antagonists, spanning four orders of magnitude in activity. The resulting cross-validated R² of 0.64 (conventional R² of 0.76) is indicative of a good predictive model of activity, and has been used to estimate potency for a variety of non-peptidyl antagonists. The structural model for the non-peptide has been compared with respect to the natural substrate, A-II, by generating peptide to non-peptide overlays.     

QSAR modeling and chemical space analysis of antimalarial compounds

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.     

Sublimation properties of CoF(3): mass spectrometric and quantum chemical studies

The sublimation of cobalt trifluoride was studied using the Knudsen effusion method combined with mass spectrometry. The pressure of F was directly measured for decomposition of CoF(3)(s) into CoF(2)(s). The average kinetic energy of CoF(2)(+), CoF(+) and Co(+) fragment ions was determined and the relative ionisation cross section curves measured from 6 eV to 100 eV. Thermodynamic functions of gaseous CoF(3) and Co(2)F(6), were evaluated from geometrical and vibrational parameters provided from theoretical calculations. Heats of formation of CoF(3)(s), CoF(3)(g), Co(2)F(6)(g) were established as (-784 +/- 6) kJ/mol, (-565 +/- 11) kJ/mol and (-1289 +/- 22) kJ/mol, respectively.     

3D QSAR (COMFA) of a series of potent and highly selective VLA-4 antagonists

The integrin VLA-4 (41) is involved in the migration of white blood cells to sites of inflammation, and is implicated in the pathology of a variety of diseases including asthma and multiple sclerosis. We report the structure-activity relationships of a series of VLA-4 antagonists that were based upon the integrin-binding sequence of the connecting segment peptide of fibronectin (Leu-Asp-Val), and of VCAM-1 (Ile-Asp-Ser), both natural ligands of VLA-4. We explore variation in the ligand derived peptide portion of these antagonists and also in the novel N-terminal cap, which have discovered through chemical optimization, and which confers high affinity and selectivity. Using the X-ray derived conformation of the Ile-Asp-Ser region of VCAM-1, we rationalize the structure-activity relationships of these antagonists using 3D QSAR (COMFA). The COMFA model was found to be highly predictive with a cross-validated R² _CVof 0.7 and a PRESS of 0.49. The robustness of the model was confirmed by testing the influence of various parameters, including grid size, column filtering, as well as the role of orientation of the aligned molecules. Our results suggest that the VCAM-1 structure is useful in generating highly predictive models of our VLA-4 antagonists. The COMFA model coupled with the knowledge that the peptide amides are tolerant to methylation should prove useful in future peptidomimetic design studies.     

A 3D QSAR study on a set of dopamine D4 receptor antagonists

The molecular alignments obtained from a previously reported pharmacophore model have been employed in a three-dimensional quantitative structure-activity relationship (3D QSAR) study, to obtain a more detailed insight into the structure-activity relationships for D(2) and D(4) receptor antagonists. The frequently applied CoMFA method and the related CoMSIA method were used. Statistically significant models have been derived with these two methods, based on a set of 32 structurally diverse D(2) and D(4) receptor antagonists. The CoMSIA and the CoMFA methods produced equally good models expressed in terms of q(2) values. The predictive power of the derived models were demonstrated to be high. Graphical interpretation of the results, provided by the CoMSIA method, brings to light important structural features of the compounds related to either low- or high-affinity D(2) or D(4) antagonism. The results of the 3D QSAR studies indicate that bulky N-substituents decrease D(2) binding, whereas D(4) binding is enhanced. Electrostatically favorable and unfavorable regions exclusive to D(2) receptor binding were identified. Likewise, certain hydrogen-bond acceptors can be used to lower D(2) affinity. These observations may be exploited for the design of novel dopamine D(4) selective antagonists.     

Mechanisms for NH3 decomposition on Si(100)-(2 x 1) surface: a quantum chemical cluster model study

In this paper, we present a detailed mechanism for the complete decomposition of NH3 to NHx(a) (x = 0-2). Our calculations show that the initial decomposition of NH3 to NH2(a) and H(a) is facile, with a transition-state energy 7.4 kcal mol-1 below the vacuum level. Further decomposition to N(a) or recombination-desorption to NH3(g) is hindered by a large barrier of approximately 46 kcal mol-1. There are two plausible NH2 decomposition pathways: 1) NH2(a) insertion into the surface Si-Si dimer bond, and 2) NH2(a) insertion into the Si-Si backbond. We find that pathway (1) leads to the formation of a surface Si = N unit, similar to a terminal Si = Nt pair in silicon nitride, Si3N4, while pathway (2) leads to the formation of a near-planar, subsurface Si3N unit, in analogy to a central nitrogen atom (Nc) bounded to three silicon atoms in the Si3N4 environment. Based on these results, a plausible microscopic mechanism for the nitridation of the Si(100)-(2 x 1) surface by NH3 is proposed.     

Influence of the conditions in pharmacophore generation, scoring, and 3D database search for chemical feature-based pharmacophore models: one application study of ETA- and ETB-selective antagonists

Using the commercial pharmacophore modeling suite Catalyst, we have studied the influence of the compare.scaledMultiBlobFeatureErrors . Catalyst parameter. The influence of this parameter has been studied in pharmacophore generation, hypothesis scoring, and database searching. This parameter, introduced in Catalyst 4.7, changed its default value in Catalyst 4.8, and it strongly influences the statistical quality of pharmacophore generation, scoring of the hypotheses, and database searching. Two different pharmacophore models have been constructed for the ETA and ETB receptor antagonists. Both models contain one positive ionizable, one negative ionizable, one hydrogen-bond acceptor, one hydrophobic aromatic, and one hydrophobic aliphatic feature. The models have been compared, and some differences in the position of the hydrogen-bond acceptor in the putative binding pocket have been highlighted.