3D–QSAR studies of orvinol analogs as κ-opioid agonists

Orvinols are potent analgesics that target opioid receptors. However, their analgesic mechanism remains unclear and no significant preference for subtype opioid receptor has been achieved. In order to find new orvinols that target the κ-receptor, comparative 3D–QSAR studies were performed on 26 orvinol analogs using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best predictions for the κ-receptor were obtained with the CoMFA standard model (q ²=0.686, r ²=0.947) and CoMSIA model combined steric, electrostatic, hydrophobic, and hydrogen bond donor/acceptor fields (q ²=0.678, r ²=0.914). The models built were further validated by a test set made up of seven compounds, leading to predictive r ² values of 0.672 for CoMFA and 0.593 for CoMSIA. The study could be helpful for designing and prepare new category κ-agonists from orvinols.      

Comparative QSAR studies on peptide deformylase inhibitors

Comparative quantitative structure–activity relationship (QSAR) analyses of peptide deformylase (PDF) inhibitors were performed with a series of previously published (British Biotech Pharmaceuticals, Oxford, UK) reverse hydroxamate derivatives having antibacterial activity against Escherichia coli PDF, using 2D and 3D QSAR methods, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR). Statistically reliable models with good predictive power were generated from all three methods (CoMFA r ² = 0.957, q ² = 0.569; CoMSIA r ² = 0.924, q ² = 0.520; HQSAR r ² = 0.860, q ² = 0.578). The predictive capability of these models was validated by a set of compounds that were not included in the training set. The models based on CoMFA and CoMSIA gave satisfactory predictive r ² values of 0.687 and 0.505, respectively. The model derived from the HQSAR method showed a low predictability of 0.178 for the test set. In this study, 3D prediction models showed better predictive power than 2D models for the test set. This might be because 3D information is more important in the case of datasets containing compounds with similar skeletons. Superimposition of CoMFA contour maps in the active site of the PDF crystal structure showed a meaningful correlation between receptor–ligand binding and biological activity. The final QSAR models, along with information gathered from 3D contour and 2D contribution maps, could be useful for the design of novel active inhibitors of PDF. Figure Superimposition of comparative molecular field analysis (CoMFA) contour plot in the active site of peptide deformylase (PDF)     

3D-QSAR study of microsomal prostaglandin E<Subscript>2</Subscript> synthase(mPGES-1) inhibitors

Microsomal prostaglandin E₂ synthase (mPGES-1) has been identified recently as a novel target for treating pain and inflammation. The aim of this study is to understand the binding affinities of reported inhibitors for mPGES-1 and further to design potential new mPGES-1 inhibitors. 3D-QSAR-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) - techniques were employed on a series of indole derivatives that act as selective mPGES-1 inhibitors. The lowest energy conformer of the most active compound obtained from systematic conformational search was used as a template for the alignment of 32 compounds. The models obtained were used to predict the activities of the test set of eight compounds, and the predicted values were in good agreement with the experimental results. The 3D-QSAR models derived from the training set of 24 compounds were all statistically significant (CoMFA; q ² = 0.89, r ² = 0.95, , and CoMSIA; q ² = 0.84, r ² = 0.93, , ). Contour plots generated for the CoMFA and CoMSIA models reveal useful clues for improving the activity of mPGES-1 inhibitors. In particular, substitutions of an electronegative fluorine atom or a bulky hydrophilic phenoxy group at the meta or para positions of the biphenyl rings might improve inhibitory activity. A plausible binding mode between the ligands and mPGES-1 is also proposed.     

The platinum-olefin binding energy in series of (PH<Subscript>3</Subscript>)<Subscript>2</Subscript>Pt(olefin) complexes - a theoretical study

Theoretical investigation of Pt(0)-olefin organometallic complexes containing tertiary phosphine ligands was focused on the strength of platinum-olefin electronic interaction. DFT theoretical study of electronic effects in a substantial number of ethylene derivatives was evaluated in terms of the Pt-olefin binding energy using MP2 correlation theory. Organometallics bearing coordinated olefins with general formula (R¹R²C = CR³R⁴)Pt(PH₃)₂ [R = various substituents] had been selected, including olefins containing both electron-donor substituents as well as electron-withdrawing groups. The stability of the corresponding complexes increases with a strengthening electron-withdrawal ability of the olefin substituents. Figure Representation of (CH₂ = CHR)Pt(PPh₃)₂ and the stability chart     

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.     

Molecular surface electrostatic potentials and anesthetic activity

General anesthetics apparently act through weak, noncovalent and reversible interactions with certain sites in appropriate brain proteins. As a means of gaining insight into the factors underlying anesthetic potency, we have analyzed the computed electrostatic potentials V _S(r) on the surfaces of 20 molecules with activities that vary between zero and high. Our results are fully consistent with, and help to interpret, what has been observed experimentally. We find that an intermediate level of internal charge separation is required; this is measured by Π, the average absolute deviation of V _S(r), and the approximate window is 7 < Π < 13 kcal mol⁻¹. This fits in well with the fact that anesthetics need to be lipid soluble, but also to have some degree of hydrophilicity. We further show that polyhalogenated alkanes and ethers, which include the most powerful known anesthetics, have strong positive potentials, V _S,max, associated with their hydrogens, chlorines and bromines (but not fluorines). These positive sites may impede the functioning of key brain proteins, for example by disrupting their normal hydrogen-bond patterns. It has indeed been recognized for some time that the most active polyhalogenated alkanes and ethers contain hydrogens usually in combination with chlorines and/or bromines. Figure The computed HF/6-31G* electrostatic potential, in kcal mol⁻¹, on the 0.001 electrons/bohr³ surface of halothane, CF₃CHBrCl. The color ranges are: red, more positive than 25; yellow, between 15 and 25; green between 0 and 15; blue, between −10 and 0. The strongly positive (red) potential is due to the hydrogen; the yellow and green positive regions at the right are on the bromine surface Proceedings of “Modeling Interactions in Biomolecules II”, Prague, September 5th–9th, 2005.     

Elucidation of binding mode and three dimensional quantitative structure–activity relationship studies of a novel series of protein kinase B/Akt inhibitors

Protein kinase B (PKB; also known as Akt kinase) is located downstream in the PI-3 kinase pathway. Overexpression and constitutive activation of PKB/Akt leads to human prostate, breast and ovarian carcinomas. A series of 69 PKB/Akt inhibitors were examined to explore their binding modes using FlexX, and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies based on comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed to provide structural insights into these compounds. CoMFA produced statistically significant results, with cross-validated q ² and non-cross validated correlation r ² coefficients of 0.53 and 0.95, respectively. For CoMSIA, steric, hydrophobic and hydrogen bond acceptor fields jointly yielded ‘leave one out’ q ²  = 0.51 and r ²  = 0.84. The predictive power of CoMFA and CoMSIA was determined using a test set of 13 molecules, which gave correlation coefficients, of 0.58 and 0.62, respectively. Molecular docking revealed that the binding modes of these molecules in the ATP binding sites of the Akt kinase domain were very similar to those of the co-crystallized ligand. The information obtained from 3D contour maps will allow the design of more potent and selective Akt kinase inhibitors.     

Study of a ligand complexed with Cdk2/Cdk4 by computer simulation

Cyclin-dependent kinases (Cdks) play important roles in the regulation of the cell cycle. Their inhibitors have entered clinical trials to treat cancer. Very recently, Davis et al. (Nat Struct Biol 9:745–749, 2002) have found a ligand NU6102, which has a high affinity with cyclin-dependent kinase 2 (K _i =6 nM) but a low affinity with cyclin-dependent kinase 4 (K _i =1,600 nM). To understand the selectivity, we use homology modeling, molecular docking, molecular dynamics and free-energy calculations to analyze the interactions. A rational 3D model of the Cdk4–NU6102 complex is built. Asp86 is a key residue that recognizes NU6102 more effectively with Cdk2 rather than Cdk4. Good binding free energies are obtained. Energetic analysis reveals that van der Waals interaction and nonpolar contributions to solvent are favorable in the formation of complexes and the sulfonamide group of the ligand plays a crucial role for binding selectivity between Cdk2 and Cdk4. Figure Two-dimensional representative for the interacting model of NU6102 complexed with the Cdk4 from a predicted structure by LIGPLOT.      

Structure-based 3D-QSAR studies on thiazoles as 5-HT<Subscript>3</Subscript> receptor antagonists

Structure-based 3D-QSAR studies were performed on 20 thiazoles against their binding affinities to the 5-HT₃ receptor with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The thiazoles were initially docked into the binding pocket of a human 5-HT_3A receptor homology model, constructed on the basis of the crystal structure of the snail acetylcholine binding protein (AChBP), using the GOLD program. The docked conformations were then extracted and used to build the 3D-QSAR models, with cross-validated values 0.785 and 0.744 for CoMFA and CoMSIA, respectively. An additional five molecules were used to validate the models further, giving satisfactory predictive values of 0.582 and 0.804 for CoMFA and CoMSIA, respectively. The results would be helpful for the discovery of new potent and selective 5-HT₃ receptor antagonists.      

3D-QSAR studies on caspase-mediated apoptosis activity of phenolic analogues

Phenols and its analogues are known to induce caspase-mediated apoptosis activity and cytotoxicity on various cancer cell lines. In the current work, two types of molecular field analysis techniques were used to perform the three dimension quantitative structure activity relationship (3D-QSAR) modeling between structural characters and anticancer activity of two sets of phenolic compounds, which are comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Then two 3D-QSAR models for two sets of phenolic analogues were obtained with good results. The first QSAR model, which was derived from CoMFA for phenols with caspase-mediated apoptosis activity against L1210 cells, had good predictability (q ² = 0.874, r ² = 0.930), and the other one was derived from CoMSIA for electron-attracting phenols with cytotoxicity in L1210 cell (q ² = 0.836, r ² = 0.950). In addition, the CoMFA and CoMSIA contour maps provide valuable guidance for designing highly active phenolic compounds.     

Theoretical study of [ XN5 ]− (X=O, S, Se, Te) systems

A series of [XN₅]⁻ (X=O, S, Se, Te) compounds has been examined with ab initio and Density Functional Theory (DFT) methods. The five-membered nitrogen ring series of structures are global minima and may exist or be characterized due to their significant dissociation barriers (29.7–32.7 kcal mol⁻¹). Nucleus-independent chemical shifts (NICS) criteria and the presence of (4n+2) π-electrons confirmed that the five-membered nitrogen ring in their structures exhibits characteristics of aromaticity. Thus, the strong stability of the five-membered nitrogen ring structures may be attributed partially to their aromaticity.      

Molecular modeling studies of poly lactic acid initiation mechanisms

The two possible routes to synthesize poly (lactic acid) are polycondensation of the lactic acid and ring opening polymerization (ROP) of the lactide. This work involves molecular modeling of the polymerization initiation mechanisms using different initiators a) H₂SO₄ for polycondensation b) aluminum isopropoxide for coordination-insertion ROP c)methyl triflate for cationic ROP, and d) potassium methoxide for anionic ROP. For molecular modeling of PLA, we have benchmarked our approach using Ryner’s work on ROP of L-lactide using stannous (II) 2-ethylhexanoate (Sn(Oct)₂) and methanol as initiators. Our values of -15.2 kcal mol^-1 and -14.1 kcal mol^-1 for enthalpy changes in the two steps of activated complex formation match with Ryner’s. Geometric and frequency optimizations have been done on Gaussian’03 using B3LYP density functional theory along with the basis sets LANL2DZ for metal atoms and 6–31G* and 6–31G** for non metal atoms. The kinetic rate constant for each mechanism has been calculated using the values of energy of activation, change in enthalpy, Gibbs free energy, entropy and the partition functions from the Gaussian’03 output. Our polycondensation rate constant value of 1.07 × 10^–4 se^-1 compares well with 1.51 × 10^–4 se^-1 as reported by Wang. However, ROP rate constants could not be validated due to lack of experimental data. Figure Cationic Ring Opening Polymerization of L-Lactide

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Why are dimethyl sulfoxide and dimethyl sulfone such good solvents?

We have carried out B3PW91 and MP2-FC computational studies of dimethyl sulfoxide, (CH₃)₂SO, and dimethyl sulfone, (CH₃)₂SO₂. The objective was to establish quantitatively the basis for their high polarities and boiling points, and their strong solvent powers for a variety of solutes. Natural bond order analyses show that the sulfur–oxygen linkages are not double bonds, as widely believed, but rather are coordinate covalent single S⁺→O⁻ bonds. The calculated electrostatic potentials on the molecular surfaces reveal several strongly positive and negative sites (the former including σ-holes on the sulfurs) through which a variety of simultaneous intermolecular electrostatic interactions can occur. A series of examples is given. In terms of these features the striking properties of dimethyl sulfoxide and dimethyl sulfone, their large dipole moments and dielectric constants, their high boiling points and why they are such good solvents, can readily be understood. Figure Dimers of dimethyl sulfoxide (DMSO; left) and dimethyl sulfone (DMSO2; right) showing O S—O -hole bonding and C H—O hydrogen bonding. Sulfur atoms are yellow, oxygens are red, carbons are gray and hydrogens are white     

Identification of novel 5-hydroxy-1<Emphasis Type="Italic">H</Emphasis>-indole-3-carboxylates with anti-HBV activities based on 3D QSAR studies

Infection with hepatitis B virus (HBV) is a major cause of liver diseases such as cirrhosis and hepatocellular carcinoma. In our previous studies, we identified indole derivatives that have anti-HBV activities. In this study, we optimize a series of 5-hydroxy-1H-indole-3-carboxylates, which exhibited potent anti-HBV activities, using three-dimensional quantitative structure-activity relationship (3D QSAR) studies with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The lowest energy conformation of compound 3, which exhibited the most potent anti-HBV activity, obtained from systematic search was used as the template for alignment. The best predictions were obtained with the CoMFA standard model (q ² = 0.689, r ² = 0.965, SEE = 0.082, F = 148.751) and with CoMSIA combined steric, electrostatic, hydrophobic and H-bond acceptor fields (q ² = 0.578, r ² = 0.973, SEE = 0.078, F = 100.342). Both models were validated by an external test set of six compounds giving satisfactory prediction. Based on the clues derived from CoMFA and CoMSIA models and their contour maps, another three compounds were designed and synthesized. Pharmacological assay demonstrated that the newly synthesized compounds possessed more potent anti-HBV activities than before (IC₅₀: compound 35a is 3.1 μmol/l, compound 3 is 4.1 μmol/l). Combining the clues derived from the 3D QSAR studies and from further validation of the 3D QSAR models, the activities of the newly synthesized indole derivatives were well accounted for. Furthermore, this showed that the CoMFA and CoMSIA models proved to have good predictive ability.     

Hologram and 3D-quantitative structure toxicity relationship studies of azo dyes

Amino azobenzenes are important dyes in the food and textile industry but their application is limited due to their mutagenicity. Computational modeling techniques were used to help understand the factors responsible for mutagenicity, and several quantitative structure toxicity relationship (QSTR) models have been derived. HQSTR (hologram QSTR) analyses indicated that different substituents at sites on both rings contribute to mutagenicity. Fragment parameters such as bond (B) and connectivity(C), as well as donor-acceptor (DA)-based model provide significant results (q² = 0.59, r² = 0.92, ) explaining these harmful effect. HQSTR results indicated that a bulky group at ring “Y” and small group at ring “X” might help to decrease mutagenicity. 3D-QSTR based on comparative molecular field analyses (CoMFA) and comparative molecular similarity index analyses (CoMSIA) are also in agreement with HQSTR. The 3D QSTR studies reveal that steric and electrostatic field effects have a strong relationship with mutagenicity (for CoMFA: q² = 0.51, r² = 0.95, and for CoMSIA: q² = 0.51, r² = 0.93 and ). In summary, negative groups and steric bulk at ring “Y” and small groups at carbon-3 of ring “X” might be helpful in reducing the mutagenicity of azo dyes.