Abstract
Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.
Highlights
Every protein is involved in various binding processes [1], frequently with another proteins [2,3]
The SAAMBE webserver is based on the SAAMBE algorithm [18], which predicts the changes of binding free energy caused by amino acid substitutions
The SAAMBE algorithm performance was previous reported [18] and it is shown that the algorithm achieves a Pearson correlation coefficient of 0.62 in a benchmark against more than 1300 experimentally-determined changes of binding free energy
Summary
Every protein is involved in various binding processes [1], frequently with another proteins [2,3] Altering such interactions via amino acid substitutions, naturally occurring or engineered, is expected to have significant impact on the wild type characteristics of the cell [4,5]. While such changes can, in principle, be experimentally measured, the cost and the required time are prohibitory for large-scale investigations. The Molecular Mechanical Poisson-Boltzmann (Generalized Born)/Surface Accessible (MM/PB(GB)SA) approach is a method that provides the details of the modeling while requiring reasonable computational time [18,19]. In the MM/PBSA method, the binding free energy change (∆∆∆G) is modeled as a linear combination of several potential energies, including molecular mechanics energy, and polar and non-polar components of solvation energy
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