Application of PCA and HCA to the Structure-Activity Relationship Study of Fluoroquinolones

用密度泛函理论计算了12种具有抗肺炎链球菌的氟诺喹酮类药物分子的分子特性.利用主成分分析和分层聚类分析方法来简化氟诺喹酮类药物数据库的维数.主成分分析法表明,变量 E_(LUMO)、 Q_3、Q_5、Q_A、lgP、MR、VOL、ΔE_(HL)能够有效地对抗肺炎链球菌的氟诺喹酮类药物进行分类.分层聚类方法的结果和主成分分析方法的结果一致.这表明两种方法都能够对新的具有抗肺炎链球菌的氟诺喹酮类药物的分类提供一个可信的规律.利用主成分分析法和分层聚类分析法对其他6个氟诺喹酮类药物分子进行分析,结果都表明有两个药物分子具有较强的抗肺炎链球菌活性.此结果和临床结果相吻合.

Molecular characteristics and structure–activity relationships of food-derived bioactive peptides

Peptides are functional active fragments of proteins which can provide nutrients needed for human growth and development,and they also have unique physiological activity characteristics relative to proteins.Bioactive peptides contain a great deal of development potential.More specifically,food-derived bioactive peptides have the advantages of a wide variety of sources,unique structures,high efficiency and safety,so they have broad development prospects.This review provides an overview of the current advances regarding the preparation,functional characteristics,and structure–activity relationships of food-derived bioactive peptides.Moreover,the prospects for the future development and application of food-derived bioactive peptides are discussed.This review may provide a better understanding of foodderived bioactive peptides,and some constructive inspirations for further research and applications in the food industry.

Quantitative structure-activity relationship study on the biodegradation of acid dyestuffs

Quantitative structure-biodegradability relationships （QSBRs） were established to develop predictive models and mechanistic explanations for acid dyestuffs as well as biological activities. With a total of four descriptors, molecular weight （MW）, energies of the highest occupied molecular orbital （EHOMO）, the lowest unoccupied molecular orbital （ELUMO）, and the excited state （EES）, calculated using quantum chemical semi-empirical methodology, a series of models were analyzed between the dye biodegradability and each descriptor. Results showed that EHOMO and Mw were the dominant parameters controlling the biodegradability of acid dyes. A statistically robust QSBR model was developed for all studied dyes, with the combined application of EHOMO and Mw. The calculated biodegradations fitted well with the experimental data monitored in a facultative-aerobic process, indicative of the reliable prediction and mechanistic character of the developed model.

Determination of structure-activity relationships between fentanyl analogs and human μ-opioid receptors based on active binding site models

Fentanyl is a potent and widely used clinical narcotic analgesic, as well as a highly selective IJ-opioid agonist. The present study established a homologous model of the human μ-opioid receptor; an intercomparison of three types of μ-opioid receptor protein sequence homologous rates was made. The secondary receptor structure was predicted, the model reliability was assessed and verified using the Ramachandran plot and ProTab analysis. The predictive ability of the CoMFA model was further validated using an external test set. Using the Surflex-Dock program, a series of fentanyl analog molecules were docked to the receptor, the calculation results from Biopolymer/SitelD showed that the receptor had a deep binding area situated in the extracellular side of the transmembrane domains （TM） among TM3, TM5, TM6, and TMT. Results suggested that there might be 5 active areas in the receptor. The important residues were Asp147, Tyr148, and Tyr149 in TM3, Trp293, and His297 in TM6, and Trp318, His319, Ile322, and Tyr326 in TM7, which were located at the 5 active areas. The best fentanyl docking orientation position was the piperidine ring, which was nearly perpendicular to the membrane surface in the 7 TM domains. Molecular dynamic simulations were applied to evaluate potential relationships between ligand conformation and fentanyl substitution.

Quantitative Structure-activity Relationship Study on the Antioxidant Activity of Carotenoids

Carotenoids are a family of effective active oxygen scavengers, which can reduce the danger of occurrence of chronic diseases such as cardiovascular disease, cataract, cancer, and so on. The quantitative structure-activity relationship （QSAR） equation between carotenoids and antioxidant activity was established by quantum chemistry AM1, molecular mechanism （MM＋） and stepwise regression analysis methods, and the model was evaluated by leave-one-out approach. The results showed that the significant molecular descriptors related to the antioxidant activity of carotenoids were the energy difference （E_HL） between the lowest unoccupied molecular orbital （LUMO） and the highest occupied molecular orbital （HOMO） and ionization energy （Eiso）. The model showed a good predictive ability （Q^2 〉 0.5）.

Application of PCA and HCA to the Structure-activity Relationship(SAR) Study of Fluoroquinolones

Density functional theory （DFT） was used to calculate a set of molecular descri ptors （properties） for 14 fluoroquinolones with anti-B.fragilis activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying fluoroquinolones according to their an-B.fragilis activity degree. The PCA shows that the variables of ELUMO, AEHL, μ, Q2, Q3, Q5, Q6, QB, LogP, MR and MP are responsible for the separation between compounds with higher and lower anti-B.fragilis activities. The HCA results are similar to those obtained with PCA. By using the chemometric results, 4 synthetic compounds were analyzed through PCA and HCA, and 2 of them are proposed as active molecules against B.fragilis, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new fluoroquinolones with anti-B.fragilis activity.

New Descriptors of Amino Acids and Its Applications to Peptide Quantitative Structure-activity Relationship

A new set of descriptors, HSEHPCSV （component score vector of hydrophobic, steric, and electronic properties together with hydrogen bonding contributions）, were derived from principal component analyses of 95 physicochemical variables of 20 natural amino acids separately according to different kinds of properties described, namely, hydrophobic, steric, and electronic properties as well as hydrogen bonding contributions. HSEHPCSV scales were then employed to express structures of angiotensin-converting enzyme inhibitors, bitter tasting thresholds and bactericidal 18 peptide, and to construct QSAR models based on partial least square （PLS）. The results obtained are as follows： the multiple correlation coefficient （R2cum） of 0.846, 0.917 and 0.993, leave-one-out cross validated Q2cm of 0.835, 0.865 and 0.899, and root-mean-square error for estimated error （RMSEE） of 0.396, 0.187and 0.22, respectively. Satisfactory results showed that, as new amino acid scales, data of HSEHPCSV may be a useful structural expression methodology＇for the studies on peptide QSAR （quantitative structure-activity relationship） due to many advantages such as plentiful structural information, definite physical and chemical meaning and easy interpretation.

Quantitative Structure-activity Relationship Studies on the Antioxidant Activity and Gap Junctional Communication of Carotenoids

The antioxidant and gap junctional communication（GJC） activities of carotenoids are known to be the two main anticancer mechanisms.Quantitative structure-activity relationship（QSAR） models of the two activities were developed using stepwise regression and multilayer perceptron neural network based on the calculated descriptors of quantum chemistry.The results showed that the significant molecular descriptor related to the antioxidant activity of carotenoids was the HOMO-LUMO energy gap（EHL） and the molecular descriptor related to the GJC was the lowest unoccupied molecular orbital energy（ELUMO）.The two models of antioxidant activity both showed good predictive power,but the predictive power of the neural network QSAR model of antioxidant activity was better.In addition,the two GJC models have similar,moderate predictive power.The possible mechanisms of antioxidant activity and GJC of carotenoids were discussed.

Quantitative Structure-activity Relationship(QSAR) Study of Toxicity of Substituted Aromatic Compounds to Photobacterium Phosphoreum

With the artificial neural network（ANN） method combined with the multiple linear regression（MLR）,based on a series of quantum chemical descriptors and molecular connectivity indexes,quantitative structure-activity relationship（QSAR） models to predict the acute toxicity（-lgEC50） of substituted aromatic compounds to Photobacterium phosphoreum were established.Four molecular descriptors that appear in the MLR model,namely,the second order valence molecular connectivity index（2XV）,the energy of the highest occupied molecular orbital（EHOMO）,the logarithm of n-octyl alcohol/water partition coefficient（logKow） and the Connolly molecular area（MA）,were inputs of the ANN model.The root-mean-square error（RMSE） of the training and validation sets of the ANN model are 0.1359 and 0.2523,and the correlation coefficient（R） is 0.9810 and 0.8681,respectively.The leave-one-out（LOO） cross validated correlation coefficient（Q L2OO） of the MLR and ANN models is 0.6954 and 0.6708,respectively.The result showed that the two methods are complementary in the calculations.The regression method gave support to the neural network with physical explanation,and the neural network method gave a more accurate model for QSAR.In addition,some insights into the structural factors affecting the acute toxicity and toxicity mechanism of substituted aromatic compounds were discussed.

A Systematic Review of Uric Acid Transporter 1(URAT1) Inhibitors for the Treatment of Hyperuricemia and Gout and an Insight into the Structure-activity Relationship(SAR)

Gout is caused by the deposition of uric acid as monosodium urate（MSU）. Chronic hyperuricemia is the necessary condition for MSU deposition, which arises from over-production and/or under-excretion of uric acid. Renal under-excretion of uric acid accounts for greater than 90% of the patients with hyperuricemia, making URAT1 inhibitors, which act through uricosuric effect a promising class of urate-lowering therapy（ULT）. This review aims at the summary and discussion of the latest development of URAT1 inhibitors for the treatment of hyperuricemia and gout and providing an insight into their structure-activity relationship（SAR）, which will be helpful to the design of URAT1 inhibitors for both academic research and pharmaceutical industry. The current development pipeline of URAT1 inhibitors is promising and encouraging.

On quantitative structure-activity relationships between hydrazine derivatives and β irradiation

In this study, solutions of hydrazine and its derivatives were irradiated using a pulsed electron beam to determine the half-reaction time of radiolysis. 3 D structures of the hydrazine derivatives were optimized, and their energies were calculated using density functional theory with the B3 LYP method and 6-311 +(3 d, 3 p) basis set.For the first time, the 3 D quantitative structure-activity relationship(QSAR) equation describing the relationship between the hydrazine derivative structures and rate of radiolysis has been established using SPSS software.Pearson correlation analysis revealed a close correlation between the total energies of the molecules and half-reaction times. In the QSAR equation, Y =-7583.464 +54.687 X_1+94333.586 X_2,Y,X_1,and X_2 are the half-reaction time, total energy of the molecule, and orbital transition energy, respectively. The significance levels of the regression coefficients were 0.006 and 0.031, i.e., both less than 0.05. Thus, this model fully explains the relationship between hydrazine derivatives and β radiolysis stability.The results show that the total energy of the molecule and orbital transition energy are the main factors that influence the β radiolysis stability of these hydrazine derivatives.

Studies on the Structure-Activity Relationship of p-Substituted Thiobenzanilides as Extractant for Pd( Ⅱ )

Introduction The metal extraction is a process of complex formation by organic ligands with metal ions or corresponding ionic groups, that is to say, it is a multicomponent coordination process in the heterogeneous phase system. The property of extraction is chiefly dependent on the stability of metal complexes, which is closely related to both the structure of ligands and the nature of metal ions. Therefore, the physicochemical behaviour of the substituent in the ligand will influence the extractive ability of the extractant for a certain

Quantitative Structure-activity Relationship of TIBO HIV-1 Inhibitors

Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for 14 TIBO derivatives with anti-HIV activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying TIBO derivatives according to their degree of anti-HIV activity. The PCA showed that the EHOMO, μ, LogP, QA, QB and MR variables are responsible for the separation between compounds with higher and lower anti-HIV activity. The HCA results are similar to those obtained with PCA. By using the chemometric results, four synthetic compounds were analyzed through PCA and HCA and three of them are proposed as active molecules against HIV, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new TIBO derivatives with anti-HIV activity. The model obtained showed not only statistical significance but also predictive ability.

A Structure-activity Relationship (SAR) Study of Fluoroquinolones with Biological Activity against Anti-S.pneumoniae

Structure-activity relationship techniques were employed to classify fluoroquinolones against S.pneumoniae. Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for eighteen fluoroquinolones. The descriptors were further analyzed using the principal component analysis （PCA）, hierarchical cluster analysis （HCA） and K-nearest neighbor （KNN） chemometeric method. The PCA and HCA methods are quite efficient to classify the eighteen compounds into two groups （active and inactive） according to their degrees of anti- S.pneumoniae activity. The classified result is consistent with the clinic experimental result. The PCA shows that the variables Q3 （net charge on atom 3）, QA （net charge on ring A）, QB （net charge on ring B）, VOL （molecular volume） and A （surface area） are found to be responsible for the separation between compounds with higher and lower anti-S.pneumoniae.

Quantum Chemical Study on Structure-activity Relationship of Several Kinds of Drugs

The structure-activity relationship of several drugs with similar structure has been investigated by using ab initio method. The relation between the dipole moments and biological activities of these drugs was judged after comparing their geometric structures, dipole moments and inhibitory concentrations. In principle, new drug molecule could be reasonably designed by altering the place of groups and ultimately, the potential drug could be screened by comparing the dipole moments of obtained molecules.

Quantitative structure-activity relationship of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives with AT1 receptor antagonistic activity

The quantitative structure-activity relationship(QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied.Three different alignment methods were used to get the models of the comparative molecular field analysis(CoMFA),the comparative molecular similarity indices analysis(CoMSIA),and the hologram quantitative structure?activity relationship(HQSAR).The statistical results from the established models show believable predictivity based on the cross-validated value(q2>0.5) and the non-validated value(r2>0.9),The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields,The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.

Support vector classification for structure-activity-relationship of 1-（ 1H- 1,2,4-triazole- 1-yl）- 2-（ 2,4-difluorophenyl）-3-substituted-2- propanols

The support vector classification （SVC） was employed to make a model for classification of antifungal activities of 1-（1H-1,2,4-triazole-l-yl）-2-（2,4-difluorophenyl）-3-substituted-2-propanols triazole derivatives. The compounds with high antifungal activities and those with low antifungal activities were compared on the basis of the following molecular descriptors： net atomic charge on the atom N connecting with R, dipole moment and heat of formation, By using the SVC, a mathematical model was constructed, which can predict the antifungal activities of the triazole derivatives, with an accuracy of 91% on the basis of the leave-one-out cross-validation （LOOCV） test, The results indicate that the performance of the SVC model can exceed that of the principal component analysis （PCA） and K-Nearest Neighbor （KNN） models for this real world data set.

Predicting quantitative structure-activity relationship of substituted 17α-acetoxyprogesterones by molecular hybridization electronegativity-distance vector

A set of novel structural descriptors (molecular hybridization electronegativity-distance vector, VMEDh) was put forward, and the quantitative structure–activity relationship (QSAR) of a series of 17α-Acetoxyprogesterones (APs) was investigated. Taking into account the effect of various hybridized orbits on atomic electronegativities, we developed the structure descriptors with amended electronegativities to build a QSAR model. The 10-parameter model based on VMEDh yields a correlation coefficient R=0.972 and standard deviation SD=0.262, which are more desirable than those of the previous molecular electonegativity-distance vector (MEDV-4) (R=0.969, SD=0.275). By stepwise multiple linear regression, several parameters are selected to construct optimal models. The 7-parameter model based on VMEDh has R=0.960 and SD=0.276; its correlation coefficient (RCV) and standard deviation (SDCV) for leave-one-out procedure crossvalidation are respectively RCV=0.890 and SDCV=0.445. The 6-parameter MEDV-4 model has R=0.946, SD=0.304, RCV=0.903 and SDCV=0.406. It is demonstrated that VMEDh has desirable estimation performance and good predictive capability for this series of chemical compounds.

Quantitative Structure-activity Relationship Models of Monomer Reactivity

The reactivity parameters,Q and e,in the Q-e scheme reflect the reactivities of a monomer(or a radical)in free-radical copolymerizations.By applying multiple linear regression(MLR)analysis,the optimal quantitative structure-activity relationship(QSAR)model for the reactivity parameter lnQ was developed based on five descriptors(NAF,NOF,EαLUMO,EβHOMO,and EβLUMO)and 69 monomers with the root mean square(rms)error of 0.61.The optimal MLR model of the parameter e obtained from five descriptors(TOcl,NpN,NSO,EαHOMO and DH)and 68 monomers produced rms error of 0.42.Compared with previous models,the two optimal MLR models in this paper show satisfactory statistical characteristics.The feasibility of combining 2D descriptors obtained from the monomers and 3D descriptors calculated from the radical structures(formed from monomers+H )to predict parameters Q and e has been demonstrated.