Desirability-Based Methods of Multiobjective Optimization and Ranking for Global QSAR Studies. Filtering Safe and Potent Drug Candidates from Combinatorial Libraries

Article

作者: Cagide Fajin, J. Luis ; Cañizares-Carmenate, Yudith ; Dominguez, Elena Rosa ; Ruiz, Reinaldo Molina ; Borges, Fernanda ; Morell, Carlos ; Cordeiro, M. Natália D. S. ; Cruz-Monteagudo, Maykel

Up to now, very few applications of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies have been reported in the literature. However, none of them report the optimization of objectives related directly to the final pharmaceutical profile of a drug. In this paper, a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies, simultaneously considering the potency, bioavailability, and safety of a set of drug candidates, is introduced. The results of the desirability-based MOOP (the levels of the predictor variables concurrently producing the best possible compromise between the properties determining an optimal drug candidate) are used for the implementation of a ranking method that is also based on the application of desirability functions. This method allows ranking drug candidates with unknown pharmaceutical properties from combinatorial libraries according to the degree of similarity with the previously determined optimal candidate. Application of this method will make it possible to filter the most promising drug candidates of a library (the best-ranked candidates), which should have the best pharmaceutical profile (the best compromise between potency, safety and bioavailability). In addition, a validation method of the ranking process, as well as a quantitative measure of the quality of a ranking, the ranking quality index (Psi), is proposed. The usefulness of the desirability-based methods of MOOP and ranking is demonstrated by its application to a library of 95 fluoroquinolones, reporting their gram-negative antibacterial activity and mammalian cell cytotoxicity. Finally, the combined use of the desirability-based methods of MOOP and ranking proposed here seems to be a valuable tool for rational drug discovery and development.

2007-06-01·CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

The application of rough sets in SAR analysis of N1-site substituted fluoroquinolones

作者: Hao Liu ; Lingbo Qu ; Bingren Xiang

The 3 dimension structure-activity relationships (3D-SAR) for N1-site substituted fluoroquinolones that used as antibiotics were performed with RS (rough sets) method.The process of RS is a concise nonlinear process, it has broad application foreground in the data mining of nonlinear life course.In this paper, initially the parameters of N1-site substituted quinolones were computed with the semi-empirical method: AM1 (Austin model) and MNDO3 (modified neglect diat. overlap), and the information table is composed of the parameters (condition attributes) and biol. activity (decision attributes).According to the anal. of rough sets method, the core and reduction of attributes set were obtained, then the decision rules were extractedThe results indicate that LUMO, A5, A3 and dipole, etc. have the great contribution to the activity of N1-site substituted fluoroquinolones.Integrating the related biol. research of fluoroquinolones resistance, the binary hydrogen bond mechanism of fluoroquinolones is brought forward.It implies that fluoroquinolones realize their function as electron donors as well as electron acceptors in its function process, and the process is finished by the formation of two hydrogen bonds (6-site F and 3-site OH).The mutation of bacteria makes it hard to form hydrogen bonds, then cause the fluoroquinolones resistance.The result also indicates that moderate dipole and ΔH_f are helpful to fluoroquinolones to be absorbed by the human body and act on bacteria.As a nonlinear system, RS theory can extract the special relation in the database, it has nonlinear character compared with PCA (Principal Component Anal.), PLS (Partial Least Square), etc., and the result has unambiguous phys. meaning compared with ANN (Artificial Neuron Network), etc.The result is very succinct and pointed, it is instructive to the study of pharmacody function process, resistance mechanism of fluoroquinolones and development of new fluoroquinolones.

2000-03-01·Journal of medicinal chemistry1区 · 医学

Artificial Neural Network Applied to Prediction of Fluorquinolone Antibacterial Activity by Topological Methods

1区 · 医学

Article

作者: Jaén-Oltra, José ; Salabert-Salvador, M Teresa ; García-March, Francisco J. ; Pérez-Giménez, Facundo ; Tomás-Vert, Francisco

A new topological method that makes it possible to predict the properties of molecules on the basis of their chemical structures is applied in the present study to quinolone antimicrobial agents. This method uses neural networks in which training algorithms are used as well as different concepts and methods of artificial intelligence with a suitable set of topological descriptors. This makes it possible to determine the minimal inhibitory concentration (MIC) of quinolones. Analysis of the results shows that the experimental and calculated values are highly similar. It is possible to obtain a QSAR interpretation of the information contained in the network after the training has been carried out.

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