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SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models
- Source :
- Bioinformatics (Oxford, England). 28(20)
- Publication Year :
- 2012
-
Abstract
- Motivation: Empirical models for the prediction of how changes in sequence alter protein–protein binding kinetics and thermodynamics can garner insights into many aspects of molecular biology. However, such models require empirical training data and proper validation before they can be widely applied. Previous databases contained few stabilizing mutations and no discussion of their inherent biases or how this impacts model construction or validation. Results: We present SKEMPI, a database of 3047 binding free energy changes upon mutation assembled from the scientific literature, for protein–protein heterodimeric complexes with experimentally determined structures. This represents over four times more data than previously collected. Changes in 713 association and dissociation rates and 127 enthalpies and entropies were also recorded. The existence of biases towards specific mutations, residues, interfaces, proteins and protein families is discussed in the context of how the data can be used to construct predictive models. Finally, a cross-validation scheme is presented which is capable of estimating the efficacy of derived models on future data in which these biases are not present. Availability: The database is available online at http://life.bsc.es/pid/mutation_database/ Contact: juanf@bsc.es
- Subjects :
- Statistics and Probability
Binding free energy
Protein family
Computer science
Context (language use)
computer.software_genre
medicine.disease_cause
Biochemistry
Mutant protein
Protein Interaction Mapping
medicine
Databases, Protein
Molecular Biology
Mutation
Database
Empirical modelling
Receptor–ligand kinetics
Computer Science Applications
Computational Mathematics
Kinetics
Computational Theory and Mathematics
Models, Chemical
Mutation (genetic algorithm)
Thermodynamics
Mutant Proteins
Construct (philosophy)
computer
Protein Binding
Subjects
Details
- ISSN :
- 13674811
- Volume :
- 28
- Issue :
- 20
- Database :
- OpenAIRE
- Journal :
- Bioinformatics (Oxford, England)
- Accession number :
- edsair.doi.dedup.....4938d54cde252ecc062fcd8c230fe9f8