Predicting stability of Arc repressor mutants with protein stochastic moments
| Autor: | Ronal Ramos de Armas, Humberto González-Díaz, Eugenio Uriarte |
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| Rok vydání: | 2004 |
| Předmět: |
Quantitative structure–activity relationship
Models Statistical Molecular model Chemistry Protein Conformation Organic Chemistry Clinical Biochemistry Static Electricity Pharmaceutical Science Quantitative Structure-Activity Relationship Linear discriminant analysis Biochemistry Stability (probability) Markov Chains Repressor Proteins Protein structure Molar refractivity Molecular descriptor Drug Discovery Mutation Molecular Medicine Thermodynamics Thermal stability Biological system Molecular Biology |
| Zdroj: | Bioorganicmedicinal chemistry. 13(2) |
| ISSN: | 0968-0896 |
| Popis: | As more and more protein structures are determined and applied to drug manufacture, there is increasing interest in studying their stability. In this study, the stochastic moments ( SR π k ) of 53 Arc repressor mutants were introduced as molecular descriptors modeling protein stability. The Linear Discriminant Analysis model developed correctly classified 43 out of 53, 81.13% of proteins according to their thermal stability. More specifically, the model classified 20/28 (71.4%) proteins with near wild-type stability and 23/25 (92%) proteins with reduced stability. Moreover, validation of the model was carried out by re-substitution procedures (81.0%). In addition, the stochastic moments based model compared favorably with respect to others based on physicochemical and geometric parameters such as D-Fire potential, surface area, volume, partition coefficient, and molar refractivity, which presented less than 77% of accuracy. This result illustrates the possibilities of the stochastic moments’ method for the study of bioorganic and medicinal chemistry relevant proteins. |
| Databáze: | OpenAIRE |
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