Comparative Molecular Field Analysis Contour Maps Research Articles

Three-dimensional quantitative structural-activity relationship and molecular dynamics study of multivariate substituted 4-oxyquinazoline HDAC6 inhibitors.

3D-QSAR models were established by collecting 46 multivariate-substituted 4-oxyquinazoline HDAC6 inhibitors. The relationship of molecular structure and inhibitory activity was studied by comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). The results showed the models established by CoMFA (q2 = 0.590, r2 = 0.965) and CoMSIA (q2 = 0.594, r2 = 0.931) had good prediction ability. At the same time, 3D-QSAR models met the internal verification, external verification and AD test. Ten new compounds were designed based on CoMFA and CoMSIA contour maps and their pharmacokinetic/toxic properties (ADME/T) were evaluated. It was found that most compounds have well safety profile and pharmacokinetic property. Then, we explored the interaction between HDAC6 and compounds by molecular docking. The results showed that the binding mode of the new compounds with HDAC6 was the same as the template compound 46, and the hydrogen bond and hydrophobic bond played a vital role in the binding process. Molecular dynamics simulation results showed that residues Ser531, His574 and Tyr745 played key roles in the binding process. All newly designed compounds had lower energy gap and binding energy than compound 46 according to DFT analysis and free energy analysis. This study provided a theoretical reference for designing compounds of higher activity and a new idea for the development of novel HDAC6 inhibitors.

Discovery of 2-(3,4-dialkoxyphenyl)-2-(substituted pyridazin-3-yl)acetonitriles as phosphodiesterase 4 inhibitors with anti-neuroinflammation potential based on three-dimensional quantitative structure-activity relationship study.

Phosphodiesterase 4 (PDE4) inhibitors with potential activities for CNS disorders provide a new therapeutic strategy for depression. To discover PDE4 inhibitors with anti-neuroinflammation activities, reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) models on our previous reported catecholic PDE4 inhibitors was built with a statistically significant cross-validated coefficient (q2 ), conventional coefficient (r2 ), and good predictive capabilities based on the molecular docking results, using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Based on the analysis of CoMFA and CoMSIA contour maps, a series of 2-(3,4-dialkoxyphenyl)-2-(substituted pyridazin-3-yl) acetonitriles 16a-i was designed and synthesized. Among these compounds, compound 16a exhibited good inhibitory activities toward PDE4B1 and PDE4D7 with mid-nanomolar IC50 values and potential anti-neuroinflammation activity in BV-2 cells. Docking simulation of compound 16a in the PDE4 catalytic domain activity pocket revealed that compound 16a maybe assumed a "V-shaped" conformation, extending the side chain to S-pocket.

Design of new CD38 inhibitors based on CoMFA modelling and molecular docking analysis of 4‑amino-8-quinoline carboxamides and 2,4-diamino-8-quinazoline carboxamides

ABSTRACTIn this study, based on molecular docking analysis and comparative molecular field analysis (CoMFA) modelling of a series of 71 CD38 inhibitors including 4‑amino-8-quinoline carboxamides and 2,4-diamino-8-quinazoline carboxamides, new CD38 inhibitors were designed. The interactions of the molecules with the greatest and the lowest activities with the nicotinamide mononucleotide (NMN) binding site were investigated by molecular docking analysis. A CoMFA model with four partial least squares regression (PLSR) components was developed to predict the CD38 inhibitory activity of the molecules. The r2 values for the training and test sets were 0.89 and 0.82, respectively. The Q2 values for leave-one-out cross-validation (LOO-CV) and leave-many-out cross-validation (LMO-CV) tests on the training set were 0.65 and 0.64, respectively. The CoMFA model was validated by calculating several statistical parameters. CoMFA contour maps were interpreted, and structural features that influence the CD38 inhibitory activity of molecules were determined. Finally, seven new CD38 inhibitors with greater activity with respect to the greatest active molecules were designed.

Towards the In-silico Design of New HSP90 Inhibitors: Molecular Docking and 3D-QSAR CoMFA Studies of Tetrahydropyrido [4, 3-d] Pyrimidine Derivatives as HSP90 Inhibitors.

HSP90 is necessary for the conformational maturation of proteins, proteins disaggregation, folding newly synthesized peptides and the refolding of denatured proteins. The inhibition of HSP90 leads to proteasomal degradations of client proteins that finally kill cancer cells. In this research, molecular docking and comparative molecular field analysis (CoMFA) were used to investigate the interactions of tetrahydropyrido[4,3-d]pyrimidine derivatives with the N-terminal domain binding site of the HSP90 and predicting their inhibitory activities. A CoMFA model with five components and q2 of 0.81 was developed. R2 for training and test sets were 0.96 and 0.79, respectively. Based on extracted Contour maps for this CoMFA model, three new inhibitors with greater pIC50 with respect to the greatest active molecule in the data-set were designed by modifying molecule m45. Molecule m45 and designed inhibitors were docked to the N-terminal domain binding site of the HSP90. Designed inhibitors obtained lower binding energy with respect to m45. Based on extracted CoMFA contour maps, bulky substituents are favored for the R1 group and in R3 group, short and bulky substituents increase the activity of molecules. Less bulky and longer substituents are favored for R2. The molecular docking analysis of compound m45 with the N-terminal domain binding site of the HSP90 show hydroxyl group on phenyl ring is necessary to form hydrogen bonding with hydrophilic residues in binding site and a conserved water molecule. Molecule m45 has Pi-Sigma interaction with phenyl ring in the side chain of Phenylalanine 138 via isopropyl substituent on meta position of the phenyl ring. Also, Molecule m45 forms carbon-hydrogen bond with oxygen atoms at the side chain of Aspartic acid 54 and Asparagine 51 via its dimethylamine group. Others are Van der Waals interactions.

3D-QSAR, molecular docking, and molecular dynamic simulations for prediction of new Hsp90 inhibitors based on isoxazole scaffold

Heat shock protein 90(Hsp90), as a molecular chaperone, play a crucial role in folding and proper function of many proteins. Hsp90 inhibitors containing isoxazole scaffold are currently being used in the treatment of cancer as tumor suppressers. Here in the present studies, new compounds based on isoxazole scaffold were predicted using a combination of molecular modeling techniques including three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamic (MD) simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were also done. The steric and electrostatic contour map of CoMFA and CoMSIA were created. Hydrophobic, hydrogen bond donor and acceptor of CoMSIA model also were generated, and new compounds were predicted by CoMFA and CoMSIA contour maps. To investigate the binding modes of the predicted compounds in the active site of Hsp90, a molecular docking simulation was carried out. MD simulations were also conducted to evaluate the obtained results on the best predicted compound and the best reported Hsp90 inhibitors in the 3D-QSAR model. Findings indicate that the predicted ligands were stable in the active site of Hsp90.

Theoretical analysis of somatostatin receptor 5 with antagonists and agonists for the treatment of neuroendocrine tumors.

We report on SSTR5 receptor modeling and its interaction with reported antagonist and agonist molecules. Modeling of the SSTR5 receptor was carried out using multiple templates with the aim of improving the precision of the generated models. The selective SSTR5 antagonists, agonists and native somatostatin SRIF-14 were employed to propose the binding site of SSTR5 and to identify the critical residues involved in the interaction of the receptor with other molecules. Residues Q2.63, D3.32, Q3.36, C186, Y7.34 and Y7.42 were found to be highly significant for their strong interaction with the receptor. SSTR5 antagonists were utilized to perform a 3D quantitative structure-activity relationship study. A comparative molecular field analysis (CoMFA) was conducted using two different alignment schemes, namely the ligand-based and receptor-based alignment methods. The best statistical results were obtained for ligand-based ([Formula: see text], [Formula: see text] = 0.988, noc = 4) and receptor-guided methods (docked mode 1:[Formula: see text], [Formula: see text], noc = 5), (docked mode 2:[Formula: see text] = 0.555, [Formula: see text], noc = 5). Based on CoMFA contour maps, an electropositive substitution at [Formula: see text], [Formula: see text] and [Formula: see text] position and bulky group at [Formula: see text] position are important in enhancing molecular activity.

3D-QSAR analysis of a series of S-DABO derivatives as anti-HIV agents by CoMFA and CoMSIA

In this study, we retrieved a series of 59 dihydroalkylthio-benzyloxopyrimidine (S-DABO) derivatives, which is a class of highly potent HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) reported from published articles, and analysed them with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Statistically significant three-dimensional quantitative structure–activity relationship (3D-QSAR) models by CoMFA and CoMSIA were derived from a training set of 46 compounds on the basis of the rigid body alignment. Further, the predictive ability of the QSAR models was validated by a test set of 13 compounds. Based on the information derived from CoMFA and CoMSIA contour maps, we have identified some steric and electrostatic features for improving the activities of these inhibitors, and we validated the 3D-QSAR results by a molecular docking method. On the basis of the obtained results, we designed a new series of S-DABO derivatives with high activities. Therefore, this study could be utilized to design more potent S-DABO analogues as anti-HIV agents.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q2) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825–0.969 (>0.5), the correlation coefficient (r2) obtained was in the range of 0.957–1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070–0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3′-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs.

3D-QSAR studies of dipeptidyl peptidase-4 inhibitors using various alignment methods

Dipeptidyl peptidase-4 (DPP-4) is one of the most attractive targets in the area of type 2 diabetes treatment. Till date, many structurally diverse DPP-4 inhibitors have been explored and published. To identify essential structural features of these diverse DPP-4 inhibitors responsible for antidiabetic activity, three-dimensional quantitative structure–activity relationship analyses were carried out on 36 reported quinoline and isoquinoline derivatives. The studies include comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) using three different alignment methods. The distill rigid body alignment-based CoMFA and CoMSIA models gave best significant results for 27 training set molecules, with cross-validated coefficients (q 2) of 0.803 and 0.826, respectively, and conventional coefficients (r 2) of 0.991 and 0.983, respectively. Validation by test set of nine molecules gave excellent predicted correlation coefficients (r pred 2 ) of 0.874 and 0.847 for CoMFA and CoMSIA models, respectively. Detailed analysis of CoMFA and CoMSIA contour maps revealed many helpful structural insights to improve the activity of newly designed quinoline and isoquinoline derivatives as DPP-4 inhibitors for the treatment of type-2 diabetes.

Molecular Docking and 3D-QSAR Based Design of Novel Imidazopyridinone Derivatives as Pseudomonas Aeruginosa Thymidylate Kinase Inhibitors

Thymidylate kinase (TMK) is a potential chemotherapeutic target since it is directly involved in the synthesis of deoxythymidine 5'-triphosphate an essential component in DNA replication. Inhibiting the function of TMK blocks DNA synthesis in replicating organisms. We report 3D-QSAR analysis on a series of thymidine mimetics exhibiting potent inhibitory activity against TMK. Molecular docking, Comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) were carried out to determine the requisite 3D structural features required for potent thymidylate kinase inhibitory activity. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the q 2 loo, r 2 ncv and r 2 pred. The models were graphically interpreted using CoMFA and CoMSIA contour maps. The results obtained from this study were used for rational design of potent inhibitors against thymidylate kinase.

P56(lck) kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives.

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on 3D-QSAR (3D-quantitative structure activity relationship) studies were carried out on 97 flavonoid derivatives as potent P56(lck) protein tyrosine kinase inhibitors. The best prediction was obtained with CoMFA standard model (q² = 0.838, r² = 0.948) using steric, electrostatic along with CoMSIA standard model (q² = 0.714, r² = 0.921) using steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. Of the 97 molecules a training set of 76 compounds and the predictive ability of the QSAR model were assessed employing a test set of 21 compounds. The resulting CoMFA and CoMSIA contour maps were used to identify the structural features relevant to the biological activity in this series of flavonoid derivatives, based upon which we identified and designed 10 novel molecules that showed superior inhibitory activity against P56(lck) protein which shed new light on effective therapeutic agents against these classes of enzymes.

A systematic quantitative approach to rational drug design and discovery of novel human carbonic anhydrase IX inhibitors

Drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed for a series of carbonic anhydrase IX inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques with the help of SYBYL 7.1 software. The large set of 36 different aromatic/heterocyclic sulfamates carbonic anhydrase (CA, EC 4.2.1.1) inhibitors, such as hCA IX, was chosen for this study. The conventional ligand-based 3D-QSAR studies were performed based on the low energy conformations employing database alignment rule. The ligand-based model gave q2 values 0.802 and 0.829 and r2 values 1.000 and 0.994 for CoMFA and CoMSIA, respectively, and the predictive ability of the model was validated. The predicted r2 values are 0.999 and 0.502 for CoMFA and CoMSIA, respectively. SEA (steric, electrostatic, hydrogen bond acceptor) of CoMSIA has the significant contribution for the model development. The docking of inhibitors into hCA IX active site using Glide XP (Schrödinger) software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps are well in agreement with the structural characteristics of the binding pocket of hCA IX active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved hCA IX inhibitors as leads for various types of metastatic cancers including those of cervical, renal, breast and head and neck origin.

Insight into the Structural Requirements of Narlaprevir-Type Inhibitors of NS3/NS4A Protease Based on HQSAR and Molecular Field Analyses

In the life cycle of hepatitis C virus (HCV), NS3/NS4A protease has been proved to play a vital role in the replication of the HCV virus. Narlaprevir and its derivatives, the inhibitors of NS3/NS4A, would be potentially developed as important anti-HCV drugs in the future. In this study, quantitative structure-activity relationship (QSAR) analyses for 190 narlaprevir derivatives were conducted using comparative molecular field analysis (CoMFA), comparative molecular indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) techniques. Both of the best CoMFA and HQSAR models showed statistical significance for the training set and good predictive accuracy for the test set, which strongly manifested the robustness of the CoMFA and HQSAR models. The CoMFA contour maps and the HQSAR contribution maps were both presented. Furthermore, based on the essential factors for ligand binding derived from the QSAR models, sixteen new derivatives were designed and some of them showed higher inhibitory activities confirmed by our models and molecular docking studies. General speaking, this study provides useful suggestions for the design of potential anti-HCV drugs.

Computational Insights into the Inhibition of Inosine 5′‐Monophosphate Dehydrogenase by Mycophenolic Acid Analogs: Three‐Dimensional Quantitative Structure–Activity Relationship and Molecular Docking Studies

Inosine 5'-monophosphate dehydrogenase (IMPDH) is a key enzyme in the de novo synthesis of guanosine nucleotides. It is considered as an important target in the quest for drugs in the immunosuppressive, antiviral, antibacterial, and anticancer therapeutic areas. Herein, we report the 3D-QSAR analyses using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking on mycophenolic acid derivates for the first time. We obtained cross-validated q(2) value of 0.805 for CoMFA and 0.620 for CoMSIA, while the non-cross-validated r(2) values for them were 0.969 and 0.935, respectively. Based on the CoMFA and CoMSIA contour maps and docking analyses, some key structural factors responsible for inhibitory activity were revealed. The results obtained from this study could be used for the rational design of potent inhibitors against IMPDH.

2D and 3D QSAR study on amino nicotinic acid and isonicotinic acid derivatives as potential inhibitors of dihydroorotate dehydrogenase (DHODH)

Dihydroorotate dehydrogenase (DHODH) is a central enzyme of pyrimidine biosynthesis which catalyzes oxidation of dihydroorotate (DHO) to orotate (ORO). DHODH inhibitors are considered as promising targets for the development of antiproliferative, antiparasitic, and immunosuppressive drugs. The best 2D QSAR model for the prediction of human dihydroorotate dehydrogenase (hDHODH) inhibitory activity was obtained by applying MLR giving r2 = 0.834 and q2 = 0.756, PCR giving r2 = 0.833 and q2 = 0.756, and PLS giving r2 = 0.864 and q2 = 0.786. 2D QSAR studies reveal the importance of alignment independent descriptors for predicting hDHODH inhibitory activity. The 3D QSAR study was performed by comparative molecular field analysis (CoMFA) to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The best CoMFA model obtained for the training set was statistically significant with cross-validated coefficients (q2) of 0.630 and conventional coefficients (r2) of 0.949. The CoMFA contour maps suggest some important structural features-like electronegative substituents at biphenyl ring system for strong inhibitory activity. We believe that these results are helpful in design of more potent and selective hDHODH inhibitors.

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q (2)=0.696 and r (2)=0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q (2)=0.711 and r (2)=0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r (2) (pred) values of 0.76 and 0.74, respectively. CoMFA and CoMSIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.

Multi-conformation 3D QSAR study of benzenesulfonyl-pyrazol-ester compounds and their analogs as cathepsin B inhibitors

Cathepsin B has been found being responsible for many human diseases. Inhibitors of cathepsin B, a ubiquitous lysosomal cysteine protease, have been developed as a promising treatment for human diseases resulting from malfunction and over-expression of this enzyme. Through a high throughput screening assay, a set of compounds were found able to inhibit the enzymatic activity of cathepsin B. The binding structures of these active compounds were modeled through docking simulation. Three-dimensional (3D) quantitative structure–activity relationship (QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on the docked structures of the compounds. Strong correlations were obtained for both CoMFA and CoMSIA models with cross-validated correlation coefficients ( q 2) of 0.605 and 0.605 and the regression correlation coefficients ( r 2) of 0.999 and 0.997, respectively. The robustness of these models was further validated using leave-one-out (LOO) method and training-test set method. The activities of eight (8) randomly selected compounds were predicted using models built from training set of compounds with prediction errors of less than 1 unit for most compounds in CoMFA and CoMSIA models. Structural features for compounds with improved activity are suggested based on the analysis of the CoMFA and CoMSIA contour maps and the property map of the protein ligand binding site. These results may help to provide better understanding of the structure–activity relationship of cathepsin B inhibitors and to facilitate lead optimization and novel inhibitor design. The multi-conformation method to build 3D QSAR is very effective approach to obtain satisfactory models with high correlation with experimental results and high prediction power for unknown compounds.

Structural determinants of benzodiazepinedione/peptide-based p53-HDM2 inhibitors using 3D-QSAR, docking and molecular dynamics

As a tumor suppressor, p53 protein regulates the cell cycle and is involved in preventing tumorgenesis. The protein level of p53 is under the tight control of its negative regulator human double minute 2 (HDM(2)) via ubiquitination. Therefore, the design of inhibitors of HDM(2) has attracted much interest of research on developing novel anticancer drugs. Presently, two classes of molecules, i.e., the 1,4-benzodiazepine-2,5-diones (BDPs) and N-Acylpolyamine (NAPA) derivatives were studied by three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling approaches including the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) as promising p53-HDM(2) inhibitors. Based on both the ligand-based and receptor-guided (docking) alignments, two optimal 3D-QSAR models were obtained with good predictive power of q(2) = 0.41, r(2)(pred) = 0.60 for BDPs, and q(2) = 0.414, r(2)(pred) = 0.69 for NAPA analogs, respectively. By analysis of the model and its related contour maps, it is revealed that the electrostatic interactions contributed much larger to the compound binding affinity than the steric effects. And the contour maps intuitively suggested where to modify the molecular structures in order to improve the binding affinity. In addition, molecular dynamics simulation (MD) study was also carried out on the dataset with purpose of exploring the detailed binding modes of ligand in the HDM(2) binding pocket. Based on the CoMFA contour maps and MD-based docking analyses, some key structural aspects responsible for inhibitory activity of these two classes of compounds were concluded as follows: For BDPs, the R(1) and R(3) regions should have small electronegativity groups; substituents R(2) and R(4) should be larger, and R(3) substituent mainly involves in H-bonds forming. For NAPA derivatives, bulky and electropositive groups in ring B and ring A, small substituent at region P is favorable for the inhibitory activity. The models and related information, we hope, may provide important insight into the inhibitor-p53-HDM(2) interactions and be helpful for facilitating the design of novel potent inhibitors.

Predicting anti-cancer activity of quinoline derivatives: CoMFA and CoMSIA approach

The 3D quantitative structure-activity relationships of 31 quinoline nuclei containing compounds and their biological activity have been investigated to establish various models. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies resulted in reliable and significant computational models. The obtained CoMFA model showed high predictive ability with q2 = 0.592, r2 = 0.966 and standard error of estimation (SEE) = 0.167, explaining majority of the variance in the data with two principal components. Predictions obtained with CoMSIA steric, electrostatic, hydrophobic, hydrogen-bond acceptor and donor fields (q2 = 0.533, r2 = 0.985) showed high prediction ability with minimum SEE (0.111) and four principal components. The information obtained from the CoMFA and CoMSIA contour maps can be utilized for the design and development of topoisomerase-II inhibitors for synthesis.

Key Features for Designing Phosphodiesterase-5 Inhibitors

Phosphodiesterase superfamily is the key regulator of 3′,5′-cyclic guanosine monophosphate (cGMP) decomposition in human body. Phosphodiesterase-5 (PDE-5) inhibitors, sildenafil, vardenafil and tadalafil, are well known oral treatment for males with erectile dysfunction. To investigate the inhibitory effects of traditional Chinese medicine (TCM) compounds to PDE-5, we performed both ligand-based and structure-based studies on this topic. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted to construct three dimensional quantitative structure-activity relationship (3D-QSAR) models of series of known PDE-5 inhibitors. The predictive models had cross-validated, q2, and non cross-validated coefficient, r2, values of 0.791 and 0.948 for CoMFA and 0.724 and 0.908 for CoMSIA. These two 3D-QSAR models were used to predict activity of TCM compounds. Docking simulations were performed to further analyze the binding mode of training set and TCM compounds. A putative binding model was proposed based on CoMFA and CoMSIA contour maps and docking simulations; formation of pi-stacking, water bridge and specific hydrogen bonding were deemed important interactions between ligands and PDE-5. Of our TCM compounds, engeletin, satisfied our binding model, and hence, emerged as PDE-5 inhibitor candidate. Using this study as an example, we demonstrated that docking should be conducted for qualitative purposes, such as identifying protein characteristics, rather than for quantitative analyses that rank compound efficacy based on results of scoring functions. Prediction of compound activity should be reserved for QSAR analyses, and scoring functions and docking scores should be used for preliminary screening of TCM database (http://tcm.cmu.edu.tw/index.php).