Quantitative Structure-activity Relationships最新文献_第9页

Multi-conformational Ligand Representation in 4D-QSAR: Reducing the Bias Associated with Ligand Alignment 4D-QSAR中的多构象配体表征:减少与配体对齐相关的偏差

Quantitative Structure-activity Relationships Pub Date : 2000-04-01 DOI: 10.1002/1521-3838(200004)19:2<149::AID-QSAR149>3.0.CO;2-9

A. Vedani, D. McMasters, M. Dobler

{"title":"Multi-conformational Ligand Representation in 4D-QSAR: Reducing the Bias Associated with Ligand Alignment","authors":"A. Vedani, D. McMasters, M. Dobler","doi":"10.1002/1521-3838(200004)19:2<149::AID-QSAR149>3.0.CO;2-9","DOIUrl":"https://doi.org/10.1002/1521-3838(200004)19:2<149::AID-QSAR149>3.0.CO;2-9","url":null,"abstract":"Quantitative structure-activity relationship (QSAR) is an area of computational research which builds mathematical or atomistic models to predict biological activities of molecules. While more powerful approaches make use of a genetic algorithm to reduce the bias with respect to model construction, the predictive power of the resulting surrogate still critically depends on the spatial alignment of the ligand molecules used to construct it. The 4D-QSAR concept Quasar developed at our laboratory not only takes local induced fit and H-bond flip-flop into account but also allows for the representation of the ligand molecules by an ensemble of conformations and/or orientations. The contribution of a single entity within this ensemble to the total ligand-receptor interaction energy is determined by a Boltzmann criterion. The three-dimensional surrogate is represented by a family of receptor-surface models, populated with atomistic properties—hydrogen bonds, salt bridges, hydrophobic particles, and solvent—mapped onto it. \u0000 \u0000 \u0000 \u0000Quasar has been used to establish QSARs for the enzyme dopamine β-hydroxylase and for the aryl hydrocarbon receptor. The surrogates were able to predict free energies of ligand binding, ΔG°, for external sets of 15 and 26 test ligand molecules, respectively, to within 0.7 kcal/mol (rms) of the experimental value, with the largest individual deviation not exceeding 1.3 kcal/mol. The results indicate that the use of a multiple-ligand representation is superior to a single-conformer concept and reduces the user bias associated with the ligand alignment. Moreover, the selection protocol demonstrates that the technique is capable of identifying a small number of active conformations and does not prefer a larger selection of lesser-contributing entities.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80760725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

A QSAR Study on Pneumocystis carinii Topoisomerases of bis‐Benzimidazoles 双苯并咪唑卡氏肺囊虫拓扑异构酶的QSAR研究

Quantitative Structure-activity Relationships Pub Date : 2000-04-01 DOI: 10.1002/1521-3838(200004)19:2<173::AID-QSAR173>3.0.CO;2-L

Roberta de Faria Rodrigues, J. C. Lopes, C. Montanari

引用次数: 0

Application of MS‐WHIM Descriptors: 1. Introduction of New Molecular Surface Properties and 2. Prediction of Binding Affinity Data MS‐WHIM描述符的应用:新分子表面性质介绍及2。绑定亲和数据的预测

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<29::AID-QSAR29>3.0.CO;2-P

G. Bravi, J. Wikel

引用次数: 18

Application of MS-WHIM Descriptors: 3. Prediction of Molecular Properties MS-WHIM描述符的应用:分子性质预测

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<39::AID-QSAR39>3.0.CO;2-N

G. Bravi, J. Wikel

{"title":"Application of MS-WHIM Descriptors: 3. Prediction of Molecular Properties","authors":"G. Bravi, J. Wikel","doi":"10.1002/(SICI)1521-3838(200002)19:1<39::AID-QSAR39>3.0.CO;2-N","DOIUrl":"https://doi.org/10.1002/(SICI)1521-3838(200002)19:1<39::AID-QSAR39>3.0.CO;2-N","url":null,"abstract":"MS-WHIM descriptors were developed in attempt to capture global 3D chemical information at molecular surface level. Initially, they contained information about size, shape and electrostatic distribution of a molecule. More recently they were enriched introducing new molecular surface properties related to hydrogen bonding capacity and hydrophobicity. This paper reports the application of expanded MS-WHIM descriptors to model: i) logP of 268 small organic molecules, ii) Caco-2 cell permeability of 17 heterogeneous compounds, and iii) pKa values of 15 substituted imidazoles. PLS regressions were derived and validated through cross-validation, repeated scrambling of the response variables, and test set predictions. The analysis of PLS models showed that MS-WHIM provided meaningful structure-property correlations: i) q2=0.709, ii) q2=0.797, and iii) q2=0.728. Hydrogen bonding capacity and hydrophobicity played a significant role and considerably improved the results. MS-WHIM descriptors, due to their holistic character, appear to be usefully applicable to a wide variety of chemical and biological problems.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84708851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Exploring the Chemistry of Quinones by Computation 用计算方法探索醌类化合物的化学性质

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<22::AID-QSAR22>3.0.CO;2-U

P. S. Magee

引用次数: 7

Three-Dimensional Structure-Activity Relationships of Synthetic Pyrethroids: 1. Similarity in Bioactive Conformations and Their Structure-Activity Pattern 合成拟除虫菊酯的三维构效关系:1。生物活性构象的相似性及其构效模式

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<10::AID-QSAR10>3.0.CO;2-7

H. Chuman, S. Goto, M. Karasawa, M. Sasaki, U. Nagashima, K. Nishimura, T. Fujita

引用次数: 3

QSAR Studies of Compounds Acting by Polar and Non-polar Narcosis: an Examination of the Role of Polarisability and Hydrogen Bonding 极性和非极性麻醉作用化合物的QSAR研究:极性和氢键作用的检验

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<3::AID-QSAR3>3.0.CO;2-N

J. Dearden, M. Cronin, Yuanhui Zhao, O. Raevsky

引用次数: 41

Theoretical Investigation on Free Radical Scavenging Activity of 6,7‐Dihydroxyflavone 6,7‐二羟黄酮清除自由基活性的理论研究

Quantitative Structure-activity Relationships Pub Date : 2000-02-01 DOI: 10.1002/(SICI)1521-3838(200002)19:1<50::AID-QSAR50>3.0.CO;2-#

Hong-yu Zhang

引用次数: 16

QSAR Study of the Fungicidal Activity of Thiophosphorylglycinamide Derivatives. Comparison of Principal Component Analysis and Spectral Mapping Technique 硫代磷酰甘氨酸酰胺衍生物杀菌活性的QSAR研究。主成分分析与光谱映射技术的比较

Quantitative Structure-activity Relationships Pub Date : 1999-12-01 DOI: 10.1002/(SICI)1521-3838(199912)18:6<584::AID-QSAR584>3.0.CO;2-B

Gyula Oros, T. Cserháti

{"title":"QSAR Study of the Fungicidal Activity of Thiophosphorylglycinamide Derivatives. Comparison of Principal Component Analysis and Spectral Mapping Technique","authors":"Gyula Oros, T. Cserháti","doi":"10.1002/(SICI)1521-3838(199912)18:6<584::AID-QSAR584>3.0.CO;2-B","DOIUrl":"https://doi.org/10.1002/(SICI)1521-3838(199912)18:6<584::AID-QSAR584>3.0.CO;2-B","url":null,"abstract":"The growth inhibitory effect of 38 thiophosphorylglycinamide (TPGA) derivatives against 25 fungal species (test organisms) belonging to various taxonomic groups was determined. Principal component analysis (PCA) was used for the elucidation of similarities and dissimilarities between TPGAs and between fungi. The strength (potency) and selectivity of the fungicidal effect were separated by the spectral mapping technique (SPM). The dimensionality of the matrices of PC loadings and variables and the selectivity maps were reduced to two by the nonlinear mapping technique. PCA and SPM were compared by calculating linear relationships between the potency values and the corresponding coordinates of maps calculated by PCA and SPM. The relationship between fungicidal effect and molecular structure was elucidated by stepwise regression analysis. It was established that the coordinates of maps are orthogonal and the results of PCA and SPM are similar but not identical. The advantage of SPM is the separation of the strength and selectivity of fungicidal effect facilitating the rational design of new TPGA derivatives. Stepwise regression analysis indicated that the position of substituents in the TPGA molecule, its bulkiness and hydrophobicity exert the highest impact on both the strength and selectivity of fungicidal effect. No relationship was found between sensitivity of fungal species towards TPGAs and their taxonomic position.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73193965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Predicting Ecotoxicology of Organophosphorous Insecticides: Successful Parameter Selection with the Genetic Function Algorithm 有机磷杀虫剂生态毒理学预测:遗传函数算法的成功参数选择

Quantitative Structure-activity Relationships Pub Date : 1999-12-01 DOI: 10.1002/(SICI)1521-3838(199912)18:6<573::AID-QSAR573>3.0.CO;2-J

M. Drew, J. Lumley, N. Price

引用次数: 8