Two- and three-dimensional quantitative structure-activity relationships for a series of purine nucleoside phosphorylase inhibitors

Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis, and hologram quantitative structure-activity relationship (HQSAR) studies were conducted on a series of 52 training set inhibitors of calf spleen purine nucleoside phosphorylase (PNP). Significant cross-validated correlation coefficients (CoMFA, q(2)=0.68; CoMSIA, q(2)=0.66; and HQSAR, q(2)=0.70) were obtained, indicating the potential of the models for untested compounds. The models were then used to predict the inhibitory potency of 16 test set compounds that were not included in the training set, and the predicted values were in good agreement with the experimental results. The final QSAR models along with the information gathered from 3D contour and 2D contribution maps should be useful for the design of novel inhibitors of PNP having improved potency.     

Modeling the molecular basis for α4β1 integrin antagonism

We report a 3D QSAR study of almost 300 structurally diverse small molecule antagonists of the integrin α4β1 whose biological activity spans six orders of magnitude. The alignment of the molecules was based on the conformation of a structurally related ligand bound to the αIIBβ3 and αvβ3 integrins in X-ray crystallographic studies. The molecular field method, CoMSIA, was used to generate the 3D QSAR models. The resulting models showed that the lipophilic properties were the most important, with hydrogen bond donor and steric properties less relevant. The models were highly significant (r(2)=0.89, q2(LOO)=0.67, r(2) (test set)=0.76), and could make robust predictions of the data (SEE=0.46, SEP=0.78, SEP (test set)=0.66). We predicted the antagonist activities of a further ten compounds with useful accuracy. The model appears capable of predicting α4β1 integrin antagonist activity to within a factor of five for compounds within its domain of applicability. The implications for design of improved integrin antagonists will be discussed.     

QSAR studies for the inhibition of the transmembrane isozymes XII and XIV of human carbonic anhydrase with a series of sulfonamides

A diverse series of aromatic/heterocyclic sulfonamides possessing inhibitory action against the human transmembrane isoforms XII (cancer-associated) and XIV of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) has been used to develop QSAR models. Including all the 55 investigated sulfonamides in the calibration set, the predictive qualities of the QSAR equations were weak (r(2)=0.1771, F=5.70) for CA XII and good for CA XIV inhibition (r(2)=0.8222, F=57.04 before eliminating the outliers, and r(2)=0.8911, F=67.07 after eliminating them). The obtained models suggest a slightly different inhibition mechanism for the two isoforms. 3-Halogeno-4-amino-benzenesulfonamides were outliers for scaffold hopping for the inhibition of CA XIV. CA XIV inhibitory activity was proportional to the degree of molecular surface rugosity. For compounds of the type X-Ar-SO(2)NH(2) and Ar'-Ar-SO(2)NH(2) type, best inhibitors were detected when Ar/Ar' incorporates a heterocyclic moiety. These studies may be helpful for the design of more specific CA XII/XIV inhibitors, since this is the first QSAR model investigating them.     

Three-dimensional holograph vector of atomic interaction field (3D-HoVAIF): a novel rotation-translation invariant 3D structure descriptor and its applications to peptides.

Quantitative structure-activity relationship (QSAR) study, important in drug design, mainly involves two aspects, molecular structural characterization (MSC) and construction of a statistical model. MSC focuses on transforming molecular structural and property characteristics into a group of numerical codes, dedicated to minimizing information loss during this process. In this context, common atoms in organic compounds are classified according to their families in the periodic table, and hybridization states, and on the basis of these, three nonbonding interactions (i.e. electrostatic, van der Waals and hydrophobic) are calculated, ultimately resulting in a new rotation-translation invariant, 3D-MSC, as a three-dimensional holograph vector of atomic interaction field (3D-HoVAIF). By applying 3D-HoVAIF to QSAR studies on two classical peptides including 58 angiotensin-converting enzyme (ACE) inhibitors and 48 bitter-tasting dipeptides, we get two excellent genetic algorithm-partial least squares (GA-PLS) models, with statistics r(2), q(2), root mean square error (RMSEE), and root mean square error of cross-validation (RMSCV) of 0.857, 0.811, 0.376, and 0.432 for ACE inhibitors and 0.940, 0.892, 0.153 and 0.205 for bitter-tasting dipeptides, respectively. By equally dividing the two datasets into training and test sets by D-optimal, the 3D-HoVAIF approach undergoes rigorous statistical validation. Furthermore, the superior performance of 3D-HoVAIF is confirmed in comparison with two other peptide MSC approaches referring to z-scale and ISA-ECI. For 58 ACE inhibitors, the GA-PLS model yields two principal components, with the following statistics: r(2) = 0.893, q(2) = 0.824, RMSEE = 0.349, RMSCV = 0.425, q2(ext) = 0.739, r2(ext)= 0.784, r2(0.ext) = 0.781, rf2(0.ext) = 0.77, k = 0.962, k' = 1.019, and RMSEP = 0.460; for 48 bitter-tasting dipeptides, three principal components resulted, with the statistics as: r(2) = 0.950, q(2) = 0.893, RMSEE = 0.152, RMSCV = 0.222, q2(ext)= 0.875, r2(ext) = 0.919, r2(0.ext)= 0.919, rf2(0.ext)= 0.919, k = 1.018, k' = 0.974, and RMSEP = 0.198. In addition, the relationship of ACE-inhibiting activities with bitter-tasting thresholds has been investigated by applying the above-constructed models to predictions on 400 theoretically possible dipeptides. Through analysis, the ACE-inhibiting activities are found to be prominently related to bitter-tasting intensities. Thus, it is deemed to be difficult to find such dipeptides that simultaneously satisfy pharmacodynamic action (high ACE-inhibiting activities) and comfortable tastes, suggesting that active components of dipeptides that are served as functional food to lower blood pressure are not very ideal.     

Cholesteryl ester transfer protein gene haplotypes, plasma high-density lipoprotein levels and the risk of coronary heart disease

High-density lipoprotein cholesterol (HDL-C) is a known inverse predictor of coronary heart disease (CHD) and is thus a potential therapeutic target. Cholesteryl ester transfer protein (CETP) is a key protein in HDL-C metabolism such that elevated CETP activity is associated with lower HDL-C. Currently available HDL-C raising drugs are relatively ineffective and evidence suggesting the role of CETP in HDL-C levels has promoted the development of CETP inhibitors as potential therapeutic agents for CHD. We investigated three SNPs in the CETP gene in two cross-sectional community-based populations (n = 1,574 and 1,109) and a population of 556 CHD patients to determine if reduced CETP activity due to genetic variations in the CETP gene would increase HDL-C levels and reduce the risk of CHD. CETP genotypes and haplotypes were tested for association with lipid levels, CETP activity and risk of CHD. Multivariate analysis showed the common AAB2 haplotype defined by the G-2708A, C-629A and TaqIB polymorphisms, was consistently associated with reduced CETP activity and increased HDL-C levels. A mean increase in HDL-C levels of 0.16–0.24 mmol/l was observed in individuals with two copies of the AAB2 haplotype relative to non AAB2 carriers across all three populations (P < 0.001). A case-control study of males indicated no association between single SNPs or haplotypes and the risk of CHD. These results suggest that raising HDL-C via CETP inhibition may not alter risk of CHD. Randomized control trials are needed to determine whether CETP inhibition will in reality reduce risk of CHD by raising HDL-C. Pamela A. McCaskie and John P. Beilby contributed equally to this work.     

Cholesteryl Ester Transfer Protein (CETP) Deficiency and CETP Inhibitors

Epidemiologic studies have shown that low-density lipoprotein cholesterol (LDL-C) is a strong risk factor, whilst high-density lipoprotein cholesterol (HDL-C) reduces the risk of coronary heart disease (CHD). Therefore, strategies to manage dyslipidemia in an effort to prevent or treat CHD have primarily attempted at decreasing LDL-C and raising HDL-C levels. Cholesteryl ester transfer protein (CETP) mediates the exchange of cholesteryl ester for triglycerides between HDL and VLDL and LDL. We have published the first report indicating that a group of Japanese patients who were lacking CETP had extremely high HDL-C levels, low LDL-C levels and a low incidence of CHD. Animal studies, as well as clinical and epidemiologic evidences, have suggested that inhibition of CETP provides an effective strategy to raise HDL-C and reduce LDL-C levels. Four CETP inhibitors have substantially increased HDL-C levels in dyslipidemic patients. This review will discuss the current status and future prospects of CETP inhibitors in the treatment of CHD. At present anacetrapib by Merck and evacetrapib by Eli Lilly are under development. By 100mg of anacetrapib HDL-C increased by 138%, and LDL-C decreased by 40%. Evacetrapib 500 mg also showed dramatic 132% increase of HDL-C, while LDL-C decreased by 40%. If larger, long-term, randomized, clinical end point trials could corroborate other findings in reducing atherosclerosis, CETP inhibitors could have a significant impact in the management of dyslipidemic CHD patients. Inhibition of CETP synthesis by antisense oligonucleotide or small molecules will produce more similar conditions to human CETP deficiency and may be effective in reducing atherosclerosis and cardiovascular events. We are expecting the final data of prospective clinical trials by CETP inhibitors in 2015.     

QSAR studies and pharmacophore identification for arylsubstituted cycloalkenecarboxylic acid methyl esters with affinity for the human dopamine transporter

Data from a series of 29 monoamine transport inhibitors were used to generate 2D and 3D QSAR models for their binding affinity to the human dopamine transporter (hDAT). Among the inhibitors were many non-nitrogen containing compounds. The 2D QSAR analysis resulted in the equation -logK(i)=4.00-3.93E(LUMO)-0.67E(HOMO)-3.24sigma(p), which predicted the importance of electron withdrawing groups in the aromatic moiety. However, the model failed to predict the observed poor binding of nitro-substituted compounds. In contrast, a derived 3D QSAR model was capable of predicting these more correctly.     

Human protein tyrosine phosphatase 1B inhibitors: QSAR by genetic function approximation

Protein tyrosine phosphatase 1B (PTP 1B), a negative regulator of insulin receptor signaling system, has emerged as a highly validated, attractive target for the treatment of non-insulin dependent diabetes mellitus (NIDDM) and obesity. As a result there is a growing interest in the development of potent and specific inhibitors for this enzyme. This quantitative structure-activity relationship (QSAR) study for a series of formylchromone derivatives as PTP lB inhibitors was performed using genetic function approximation (GFA) technique. The QSAR models were developed using a training set of 29 compounds and the predictive ability of the QSAR model was evaluated against a test set of 7 compounds. The internal and external consistency of the final QSAR model was 0.766 and 0.785. The statistical quality of QSAR models was assessed by statistical parameters r2, r2 (crossvalidated r2), r2pred (predictive r2) and lack of fit (LOF) measure. The results indicate that PTP lB inhibitory activity of the formylchromone derivatives is strongly dependent on electronic, thermodynamic and shape related parameters.     

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r2, q2(loo) and r2(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r2(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.     

Resveratrol analogues as selective cyclooxygenase-2 inhibitors: synthesis and structure-activity relationship

Resveratrol (3,5,4'-trihydroxy-trans-stilbene) is found in grapes and various medical plants. Among cytotoxic, antifungal, antibacterial cardioprotective activity resveratrol also demonstrates non-selective cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) inhibition. In order to find more selective COX-2 inhibitors a series of methoxylated and hydroxylated resveratrol derivatives were synthesized and evaluated for their ability to inhibit both enzymes using in vitro inhibition assays for COX-1 and COX-2 by measuring PGE(2) production. Hydroxylated but not methoxylated resveratrol derivatives showed a high rate of inhibition. The most potent resveratrol compounds were 3,3',4',5-tetra-trans-hydroxystilbene (COX-1: IC(50)=4.713, COX-2: IC(50)=0.0113 microM, selectivity index=417.08) and 3,3',4,4',5,5'-hexa-hydroxy-trans-stilbene (COX-1: IC(50)=0.748, COX-2: IC(50)=0.00104 microM, selectivity index=719.23). Their selectivity index was in part higher than celecoxib, a selective COX-2 inhibitor already established on the market (COX-1: IC(50)=19.026, COX-2: IC(50)=0.03482 microM, selectivity index=546.41). Effect of structural parameters on COX-2 inhibition was evaluated by quantitative structure-activity relationship (QSAR) analysis and a high correlation was found with the topological surface area TPSA (r=0.93). Docking studies on both COX-1 and COX-2 protein structures also revealed that hydroxylated but not methoxylated resveratrol analogues are able to bind to the previously identified binding sites of the enzymes. Hydroxylated resveratrol analogues therefore represent a novel class of highly selective COX-2 inhibitors and promising candidates for in vivo studies.     

Predicting anti-HIV activity of PETT derivatives: CoMFA approach

HIV-1 (Human Immunodeficiency Virus Type-1) is the pathogenic retrovirus and causative agent of AIDS. HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as NNRTIs and NRTIs. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTIs category, there is a set of inhibitors commonly referred to as phenyl ethyl thiazolyl thiourea (PETT) derivatives. The present 3D QSAR study attempts to explore the structural requirements of phenyl ethyl thiazolyl thiourea (PETT) derivatives for anti-HIV activity. Based on the structures and biodata of previous PETT analogs, 3D-QSAR (CoMFA) study has been performed with a training set consisting of 60 molecules, which resulted in a reliable computational model with q(2)=0.657, S(PRESS)=0.957, r(2)=0.938, and standard error of estimation (SEE)=0.270 with the number of partial least square (PLS) components being 5. It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the anti-HIV activity. The predictive ability of the resultant model was evaluated using a test set comprised of 11 molecules and the predicted r(2)=0.893. This model is a more significant guide to trace the features that really matter especially with respect to the design of novel compounds.     

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.