QSAR based modeling on a series of lactam fused chroman derivatives as selective 5-HT transporters

One of the most prevalent disorders in the present society is depression. The development of treatments for this disorder, beginning with the tricyclic antidepressants and leading to the development of selective serotonin re-uptake inhibitors, has focused on compounds that block the function of the serotonin transporter (SERT). Quantitative structure–activity relationship has been performed on a series of lactam fused chroman derivatives as selective 5-HT transporters, using different physicochemical parameters along with appropriate indicator variables. It has been found that physicochemical parameters, such as connectivity indices ⁰χ and ²χ, molecular weight (MW), Parachor (Pc), Balaban index (J), Wiener index (W) along with indicator variables are significantly correlated with activity. In this paper best results were obtained by using multiple regression analysis. Different models were generated with high values of R² and low values of PRESS/SSY ratio. The significant equations were statistically tested by using leave one out (LOO) technique and cross-validation methods.     

酪氨酸蛋白激酶抑制剂:亚苄基丙二腈类衍生物定量构效关系的量子化学研究

用量子化学从头算方法,对亚苄丙二腈衍生物的定量构效关系(QSAR)进行了研究,结果显示:指示变量I,偶极矩Dipole和最低空轨道的能量ELUMO对亚苄丙二腈衍生物的抑制活性有很大影响,回归分析得到了相关性好的相关模型(R=0.95).I=0时,亚苄基丙二腈类衍生物的抑制作用由其化学反应性决定;I=1时其抑制作用由其静电性决定.     

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.     

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus.     

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.     

Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors

Summary Inhibition of aromatase, a cytochrome P450 that converts androgens to estrogens, is relevant in the therapeutic control of breast cancer. We investigate this inhibition using a three-dimensional quantitative structure-activity relationship (3D QSAR) method known as Comparative Molecular Field Analysis, CoMFA [Cramer III, R.D. et al., J. Am. Chem. Soc., 110 (1988) 5959]. We analyzed the data for 50 steroid inhibitors [Numazawa, M. et al., J. Med. Chem., 37 (1994) 2198, and references cited therein] assayed against androstenedione on human placental microsomes. An initial CoMFA resulted in a three-component model for log(1/K_i), with an explained variance r² of 0.885, and a cross-validated q² of 0.673. Chemometric studies were performed using GOLPE [Baroni, M. et al., Quant. Struct.-Act. Relatsh., 12 (1993) 9]. The CoMFA/GOLPE model is discussed in terms of robustness, predictivity, explanatory power and simplicity. After randomized exclusion of 25 or 10 compounds (repeated 25 times), the q² for one component was 0.62 and 0.61, respectively, while r² was 0.674. We demonstrate that the predictive r² based on the mean activity (Y_m) of the training set is misleading, while the test set Y_m-based predictive r² index gives a more accurate estimate of external predictivity. Using CoMFA, the observed differences in aromatase inhibition among C6-substituted steroids are rationalized at the atomic level. The CoMFA fields are consistent with known, potent inhibitors of aromatase, not included in the model. When positioned in the same alignment, these compounds have distinct features that overlap with the steric and electrostatic fields obtained in the CoMFA model. The presence of two hydrophobic binding pockets near the aromatase active site is discussed: a steric bulk tolerant one, common for C4, C6-alpha and C7-alpha substitutents, and a smaller one at the C6-beta region.     

A comparative QSAR analysis and molecular docking studies of phenyl piperidine derivatives as potent dual NK1R antagonists/serotonin transporter (SERT) inhibitors

Depression is a critical mood disorder that affects millions of patients. Available therapeutic antidepressant agents are associated with several undesirable side effects. Recently, it has been shown that Neurokinin 1 receptor (NK₁R) antagonists can potentiate the antidepressant effects of serotonin-selective reuptake inhibitors (SSRIs). In this study, a series of phenyl piperidine derivatives as potent dual NK₁R antagonists/serotonin transporter (SERT) inhibitors were applied to quantitative structure–activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis–based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and NK₁R antagonism/SERT inhibitory of these compounds. The best multiple linear regression equation was obtained from GA-PLS and MLR for NK₁R and SERT, respectively. Based on the resulted model, an in silico-screening study was also conducted and new potent lead compounds based on new structural patterns were designed for both targets. Molecular docking studies of these compounds on both targets were also conducted and encouraging results were acquired. There was a good correlation between QSAR and docking results. The results obtained from validated docking studies indicate that the important amino acids inside the active site of the cavity that are responsible for essential interactions are Glu33, Asp395 and Arg26 for SERT and Ala30, Lys7, Asp31, Phe5 and Tyr82 for NK₁R receptors.     

PDK1的吲哚酮类抑制剂定量构效关系研究

3'磷酸肌醇依赖的激酶1(3'-phosphoinositide-dependent kinase1,PDK1)是--个63kDa的丝氨酸/苏氨酸(Ser/Thr)蛋白酶,它是Akt1的上游活化激酶~([1,2]).PDK1可在磷酸化的Akt1的Thr308位点使Akt1的活性增加30倍以上.但这种活化以依赖PIP3或PIP2的方式完成,PDK1也就因此而得名~([3]).     

Enantioselective LC analysis and determination of selective serotonin reuptake inhibitors

LC separation of biologically and pharmaceutically important enantiomers (from racemic or non-racemic mixtures) remains a subject of importance. The present review article deals with the liquid chromatographic enantioseparation of chiral selective serotonin reuptake inhibitors (SSRIs), namely citalopram, paroxetine, sertraline and fluoxetine. It is now known that the enantiomers of numerous psychotropic drugs exhibit distinct pharmacodynamics, pharmacokinetic patterns and receptor binding properties, and psychiatric patients are frequently taking more than one medication. Therefore, monitoring of the levels of these analytes in biological fluids is important to determine the levels of enantiomer concentrations; the present paper may be helpful in understanding the present state of available methods (along with a critical discussion of applicability of the methods) and in developing the new ones for this purpose. Different approaches using LC discussed herein may be applied for determining the enantiomeric composition (and enantiomeric purity) of SSRIs and numerous other racemic drugs, of current/future pharmaceutical importance and utility, using simple separation methods, instrumentation, inexpensive reagents and potentially significant analytical approaches. The contents cover the essential data to understand the various separation techniques and associated issues, if any, with documented examples.     

High‐performance liquid chromatography with diode array detection method for the simultaneous determination of seven selected phosphodiesterase‐5 inhibitors and serotonin reuptake inhibitors used as male sexual enhancers

This work presents a simple, sensitive and generic high‐performance liquid chromatography with diode array detection method for the simultaneous determination of seven drugs prescribed for the treatment of erectile dysfunction and premature ejaculation. Investigated drugs include the phosphodiesterase‐5 inhibitors: sildenafil, tadalafil, and vardenafil, in addition to the selective serotonin reuptake inhibitors: dapoxetine, duloxetine, fluoxetine, and paroxetine. The drugs were separated using a Waters C8 column (4.6 × 250 mm, 5 μm) with the mobile phase consisting of phosphate buffer pH 3, acetonitrile and methanol in the ratio 60:33:7. The flow rate was 1.2 mL/min, and quantification was based on measuring peak areas at 225 nm. Peaks were perfectly resolved with retention times 3.3, 3.9, 6.4, 7.5, 9.5, 10.7, and 13.4 min for vardenafil, sildenafil, paroxetine, duloxetine, dapoxetine, fluoxetine, and tadalafil, respectively. The developed method was validated with respect to system suitability, linearity, ranges, accuracy, precision, robustness, and limits of detection and quantification. The proposed method showed good linearity in the ranges 5–500, 2–200, 2–200, 3–300, 1.5–150, 2–200, and 2–200 μg/mL for sildenafil, tadalafil, vardenafil, dapoxetine, duloxetine fluoxetine, and paroxetine, respectively. The limits of detection were 0.18–0.38 μg/mL for the analyzed compounds. The applicability of the proposed method to real life situations was assessed through the analysis of commercial tablets, and satisfactory results were obtained.     

Method development and validation for the simultaneous determination of five selective serotonin reuptake inhibitors by capillary zone electrophoresis

Summary A capillary zone electrophoresis method is proposed for the separation of five antidepressants. Optimum conditions for the separation were investigated. A background electrolyte solution consisting of 40 mM phosphate buffer adjusted to pH 2.5, hydrodynamic injection, and a 28 kV separation voltage were used. Relative standard deviations (RSD) were <0.9% and <1.7% for migration time and corrected peak area (n=21), respectively. The detection limits for the five antidepressants ranged from 0.3 to 0.7 mg L⁻¹. The stability of the solutions, linearity, accuracy, and precision were examined during validation of the method. The method is rapid and sensitive, when it was tested for the analysis of pharmaceutical formulations the recoveries obtained were between 98 and 103% of the nominal content.     

Sensitive capillary GC-MS-SIM determination of selective serotonin reuptake inhibitors: reliability evaluation by validation and robustness study

A simple, fast, selective and very sensitive capillary GC-MS method for the simultaneous determination of five antidepressant drugs is described. Fluoxetine, fluvoxamine, citalopram, sertraline and paroxetine belong to the newest and most important drug group termed selective serotonin reuptake inhibitors. Imipramine was used in this method as an internal standard for quantification. Optimum parameters for GC separation were investigated, i.e., flow rate, column head pressure, injector temperature, injection splitless conditions and oven temperature program. MS detection was performed in SIM mode to increase the sensitivity. Stability of the solutions, linear concentration range, accuracy, precision, LOD, LOQ (3.6-41.5 mg/L) and specificity were examined in the presence of excipients for checking the reliability of this method. The robustness was evaluated with a matrix of 15 experiments (seven factors and three levels) using Plackett-Burman fractional factorial experimental design, and Youden and Steiner statistical treatment. The method was applied to the analysis of these antidepressants in nearly all their pharmaceutical formulations, obtaining recoveries between 98.1% and 102.7% with regard to the claimed values.     

Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines

Summary One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR) — the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives — has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions.     

The Role of Serotonin Neurotransmission in Gastrointestinal Tract and Pharmacotherapy

5-Hydroxytryptamine (5-HT, serotonin) is a neurotransmitter in both the central nervous system and peripheral structures, acting also as a hormone in platelets. Although its concentration in the gut covers >90% of all organism resources, serotonin is mainly known as a neurotransmitter that takes part in the pathology of mental diseases. Serotonin modulates not only CNS neurons, but also pain transmission and platelet aggregation. In the periphery, 5-HT influences muscle motility in the gut, bronchi, uterus, and vessels directly and through neurons. Serotonin synthesis starts from hydroxylation of orally delivered tryptophan, followed by decarboxylation. Serotonin acts via numerous types of receptors and clinically plays a role in several neural, mental, and other chronic disorders, such as migraine, carcinoid syndrome, and some dysfunctions of the alimentary system. 5-HT acts as a paracrine hormone and growth factor. 5-HT receptors in both the brain and gut are targets for drugs modifying serotonin neurotransmission. The aim of the present article is to review the 5-HT receptors in the gastrointestinal (GI) tract to determine the role of serotonin in GI physiology and pathology, including known GI diseases and the role of serotonin in GI pharmacotherapy.     

Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines

Summary Neural networks and inductive logic programming (ILP) have been compared to linear regression for modelling the QSAR of the inhibition of E. coli dihydrofolate reductase (DHFR) by 2,4-diamino-5-(substitured benzyl)pyrimidines, and, in the subsequent paper [Hirst, J.D., King, R.D. and Sternberg, M.J.E., J. Comput.-Aided Mol. Design, 8 (1994) 421], the inhibition of rodent DHFR by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazines. Cross-validation trials provide a statistically rigorous assessment of the predictive capabilities of the methods, with training and testing data selected randomly and all the methods developed using identical training data. For the ILP analysis, molecules are represented by attributes other than Hansch parameters. Neural networks and ILP perform better than linear regression using the attribute representation, but the difference is not statistically significant. The major benefit from the ILP analysis is the formulation of understandable rules relating the activity of the inhibitors to their chemical structure.     

Quantitative structure-affinity relationship of 5-HT1A receptor ligands by the classification tree method

The influence of molecular structure of 346 ligands on their affinity for 5-HT_1A receptors was investigated. It was shown that the effectiveness of the proposed novel approach for interpretation of decision tree models compared favourably with the PLS method. In the context of the proposed approach, molecular fragments and their values of the relative influence on the affinity for 5-HT_1A receptors were defined.     

The role of dimension in multivalent binding events: structure-activity relationship of dendritic polyglycerol sulfate binding to L-selectin in correlation with size and surface charge density

L ‐, P ‐, and E ‐Selectin are cell adhesion molecules that play a crucial role in leukocyte recruitment from the blood stream to the afflicted tissue in an acute and chronic inflammatory setting. Since selectins mediate the initial contact of leukocytes to the vascular endothelium, they have evolved as a valuable therapeutic target in diseases related to inflammation by inhibition of the physiological selectin–ligand interactions. In a previous study, it was demonstrated that dPGS, a fully synthetic heparin analogue, works as an efficient inhibitor towards L ‐ and P ‐selectin in vitro as well as in vivo. Herein, the focus is directed towards the effect of size and charge density of the polyanion. The efficiency of L ‐selectin inhibition via an SPR‐based in vitro assay and a cell‐based flow chamber assay is investigated with dPGS ranging from approximately 4 to 2000 kDa. SPR measurements show that the inhibitory potential of highly sulfated dPGS increases with size and charge density. Thereby, IC₅₀ values from the micromolar to the low picomolar range are determined. The same tendency could be observed in a cell‐based flow chamber assay with three representative dPGS samples. This structure–affinity relationship of dPGS suggests that the strong inhibitory potential of dPGS is not only based on the strong electrostatic interaction with areas of cationic surface potential on L ‐selectin but is also due to a steric shielding of the carbohydrate binding site by large, flexible dPGS particles.

     

CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV

Recently, we reported structurally novel PDE4 inhibitors based on 1,4-benzodiazepine derivatives. The main interest in developing bezodiazepine-based PDE4 inhibitors is in their lack of adverse effects of emesis with respect to rolipram-like compounds. A large effort has thus been made toward the structural optimization of this series. In the absence of structural information on the inhibitor binding mode into the PDE4 active site, 2D-QSAR (H-QSAR) and two 3D-QSAR (CoMFA and CoMSIA) methods were applied to improve our understanding of the molecular mechanism controlling the PDE4 affinity of the benzodiazepine derivatives. As expected, the CoMSIA 3D contour maps have provided more information on the benzodiazepine interaction mode with the PDE4 active site whereas CoMFA has built the best tool for activity prediction. The 2D pharmacophoric model derived from CoMSIA fields is consistent with the crystal structure of the PDE4 active site reported recently. The combination of the 2D and 3D-QSAR models was used not only to predict new compounds from the structural optimization process, but also to screen a large library of bezodiazepine derivatives.