Mutagenesis data in the automated prediction of transmembrane helix dimers.
We present a molecular modeling protocol that selects modeled protein structures based on experimental mutagenesis results. The computed effect of a point mutation should be consistent with its experimental effect for correct models; mutations that do not affect protein stability and function should not affect the computed energy of a correct model while destabilizing mutations should have unfavorable computed energies. On the other hand, an incorrect model will likely display computed energies that are inconsistent with experimental results. We added terms to our energy function which penalize models that are inconsistent with experimental results. This creates a selective advantage for models that are consistent with experimental results in the Monte Carlo simulated annealing protocol we use to search conformational space. We calibrated our protocol to predict the structure of transmembrane helix dimers using glycophorin A as a model system. Inclusion of mutational data in this protocol compensates for the limitations of our force field and the limitations of our conformational search. We demonstrate an application of this structure prediction protocol by modeling the transmembrane region of the BNIP3 apoptosis factor.
Metcalf
Douglas G
DG
Department of Biochemistry and Biophysics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA.
Law
Peter B
PB
DeGrado
William F
WF
D019295:Computational Biology / Q000379:methods; D019281:Dimerization; D006021:Glycophorins / Q000737:chemistry; D006801:Humans; D008565:Membrane Proteins / Q000737:chemistry* / Q000235:genetics*; D008958:Models, Molecular; D016296:Mutagenesis; D010802:Phylogeny; D017354:Point Mutation; D017433:Protein Structure, Secondary; D011518:Proto-Oncogene Proteins / Q000737:chemistry
C090121:BNIP3 protein, human; D006021:Glycophorins; D008565:Membrane Proteins; D011518:Proto-Oncogene Proteins