Elucidating the structure-activity relationship of Cu-Ag bimetallic catalysts for electrochemical CO_(2) reduction

Developing bimetallic catalysts is an effective strategy for enhancing the activity and selectivity of electrochemical CO_(2) reduction reactions,where understanding the structure-activity relationship is essential for catalyst design.Herein,we prepared two Cu-Ag bimetallic catalysts with Ag nanoparticles attached to the top or the bottom of Cu nanowires.When tested in a flow cell,the Cu-Ag catalyst with Ag nanoparticles on the bottom achieved a faradaic efficiency of 54%for ethylene production,much higher than the catalyst with Ag nanoparticles on the top.The catalysts were further studied in the H-cell and zero-gap MEA cell.It was found that placing the two metals in the intensified reaction zone is crucial to triggering the tandem reaction of bimetallic catalysts.Our work elucidates the structure-activity relationship of bimetallic catalysts for CO_(2) reduction and demonstrates the importance of considering both catalyst structures and cell characteristics to achieve high activity and selectivity.

Review on mechanisms and structure-activity relationship of hypoglycemic effects of polysaccharides from natural resources

Diabetes mellitus(DM)is a common multifactorial disease,causing various complications,such as chronic metabolism.The current therapies for diabetes mellitus are commercial diabetic drugs that have different definite side effect.However,polysaccharides mainly extracted from natural resources,have advantages of safety,accessibility,and anti-diabetic potential.We have summarized recent research of natural polysaccharides with hypoglycemic activities,focusing on different pharmacological mechanisms in various cell and animal models.The relationships of structure-hypoglycemic effect are also discussed in detail.This review could provide a comprehensive perspective for better understanding on development and mechanism of natural polysaccharides against diabetes mellitus,which have been required by clinical studies yet.

Advances in Research of Biological Activity,Action Mechanism and Structure-Activity Relationship of Lentinan

Lentinula edodes is the second largest edible mushroom in the world and is widely used as food and medicine.Modern research shows that lentinan(LNT)is the main active component of L.edodes.It has anti-cancer,treatment of diabetes,intestinal protection,anti-inflammatory,anti-oxidation,anti-aging,hepatoprotective,immune-regulating effects.In this review,the biological activity,action mechanism and structure-activity relationship of LNT in recent years are reviewed.On this basis,the existing problems were discussed,and the future research and application of LNT were prospected.Finally,it is hoped that this review will promote the in-depth study of LNT and provide a reference for its development as a drug and functional food.

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.

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(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.

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）.

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.

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.

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.

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.

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.

Development and structure-activity relationships of tanshinones as selective 11β-hydroxysteroid dehydrogenase 1 inhibitors

11β-Hydroxysteroid dehydrogenase 1(11β-HSD1)represents a promising drug target for metabolic syndrome,includ-ing obesity and type 2 diabetes.Our initial screen of a collection of natural products from Danshen led to the identi-fication of tanshinones as the potent and selective 11β-HSD1 inhibitors.To improve the druggability and explore the structure-activity relationships(SARs),more than 40 derivatives have been designed and synthesized using tanshinone IIA and cryptotanshinone as the starting materials.More than 10 derivatives exhibited potent in vitro 11β-HSD1 inhibitory activity and good selectivity over 11β-HSD2 across human and mouse species.Based on the biological results,SARs were further discussed,which was also partially rationalized by a molecular docking model of 1 bound to the 11β-HSD1.Remarkably,compounds 1,17 and 30 significantly inhibited 11β-HSD1 in 3T3-L1 adipocyte and in livers of ob/ob mice,which merits further investigations as anti-diabetic agents.This study not only provides a series of novel selective 11β-HSD1 inhibitors with promising therapeutic potentials in metabolic syndromes,but also expands the boundaries of the chemical and biological spaces of tanshinones.

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.

Quantitative Structure-Activity Relationship Study of Some Antipsychotics by Multiple Linear Regressions

The retention behavior and lipophilicity parameters of some antiphychotics were determined using reversed-phase thin layer chromatography. Quantitative structure-activity relationships studies have been performed to correlate the molecular characteristics of observed compounds with their retention as well as with their chromatographically determinated lipophilicity parameters. The effect of different organic modifiers (acetone, tetrahydrofuran, and methanol) has been studied. The retention of investigated compounds decreases linearly with increasing concentration of organic modifier. The chemical structures of the antipsychotics have been characterized by molecular descriptors which are calculated from the structure and related to chromatographically determinated lipophilicity parameters by multiple linear regression analysis. This approach gives us the possibility to gain insight into factors responsible for the retention as well as lipophilicity of the investigated set of the compounds. The most prominent factors affecting lipophilicity of the investigated substances are Solubility, Energy of the highest occupied molecular orbital, and Energy of the lowest unoccupied molecular orbital. The obtained models were used for interpretation of the lipophilicity of the investigated compounds. The prediction results are in good agreement with the experimental value. This study provides good information about pharmacologically important physico-chemical parameters of observed antipsychotics relevant to variations in molecular lipophilicity and chromatographic behavior. Established QSAR models could be helpful in design of novel multitarget antipsychotic 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.

Some substrates of P-glycoprotein targeting <i>β</i>-amyloid clearance by quantitative structure-activity relationship (QSAR)/membrane-interaction (MI)-QSAR analysis

The pathogenesis of Alzheimer’s disease (AD) putatively involves a compromised blood-brain barrier (BBB). In particular, the importance of brain-to-blood transport of brain-derived metabolites across the BBB has gained increasing attention as a potential mechanism in the pathogenesis of neurodegenerative disorders such as AD, which is characterized by the aberrant polymerization and accumulation of specific misfolded proteins, particularly β-amyloid (Aβ), a neuropathological hallmark of AD. P-glycoprotein (P-gp), a major component of the BBB, plays a role in the etiology of AD through Aβ clearance from the brain. Our QSAR models on a series of purine-type and propafenone-type substrates of P-gp showed that the interaction between P-gp and its modulators depended on Molar Refractivity, LogP, and Shape Attribute of drugs it transports. Meanwhile, another model on BBB partitioning of some compounds revealed that BBB partitioning relied upon the polar surface area, LogP, Balaban Index, the strength of a molecule combined with the membrane-water complex, and the changeability of the structure of a solute-membrane-water complex. The predictive model on BBB partitioning contributes to the discovery of some molecules through BBB as potential AD therapeutic drugs. Moreover, the interaction model of P-gp and modulators for treatment of multidrug resistance (MDR) indicates the discovery of some molecules to increase Aβ clearance from the brain and reduce Aβ brain accumulation by regulating BBB P-gp in the early stages of AD. The mechanism provides a new insight into the therapeutic strategy for AD.

Structure-activity relationships regarding the antioxidant effects of the flavonoids on human erythrocytes

The effects of eleven flavonoids on lipid peroxidation, protein degradation, deformability and osmotic fragility of human erythrocytes exposed in vitro to 10 mM H2O2 for 60 min at 37 oC have been studied. The following flavonoids;quercetin, rutin and morin significantly protected eryt-hrocytes against lipid peroxidation caused by H2O2. This inhibition of lipid peroxidation could be explained by the presence of at least two hydroxyl groups in ring B of the flavonoid structure, regardless of their positions. However, the flavonoids;quercetin, 3,5,7-trihy- droxy-4'-methoxy flavone-7-rutinoside and 3- hydroxy flavone significantly protected eryt-hrocytes against protein degradation. This inhibition could also be explained by the presence of a hydroxyl group at C-3 in ring C of the flavonoid structure. Quercetin and 3,5,7-trihydroxy-4'- methoxy flvone-7-rutinoside significantly protected erythrocytes against loss of deformability and increased osmotic fragility, indicating that the loss of erythrocyte deformability and the increase in osmotic fragility of erythrocytes exposed to H2O2 are related to protein degradation rather than to lipid peroxidation. The other flavonoids (chrysin, 2-carboxy ethyl dihydroxy flavone, apigenin, cirsimaritin, α-naphto flavone and flavanone) failed to protect erythrocytes against the observed oxidative damages. The results demonstrate the importance of the chemical groups substituted on the basic skeleton of the flavonoids in dictating the type of antioxidant activity, and also demonstrate the hemorheological potentials of flavonoids that have particular protein-antioxidant activities.