Predicting virus-receptor mutant binding by molecular dynamics simulation
Author and article information
Abstract
Existing computational methods to predict protein–protein interaction affinity often perform poorly in important test cases. In particular, the effects of multiple mutations, non-alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here a new method to interrogate affinity differences resulting from mutations in a host-virus protein–protein interface. Our method is based on extensive non-equilibrium all atom simulations: We computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1) and estimate affinity using the max imum applied force during a pulling simulation and the area under the force-versus-distance curve. We find that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our method provides an elegant framework to compare the effects of multi ple mutations, individually and jointly, on protein–protein interactions.
Cite this as
2013. Predicting virus-receptor mutant binding by molecular dynamics simulation. PeerJ PrePrints 1:e138v1 https://doi.org/10.7287/peerj.preprints.138v1Author comment
This manuscript was submitted for review with PeerJ.
Sections
Supplemental Information
Example of the weak binding Y211A mutant being separated from the reduced transferrin receptor.
Additional Information
Competing Interests
The authors declare no competing financial interests.
Author Contributions
Austin G Meyer conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper.
Sara L Sawyer conceived and designed the experiments, contributed reagents/materials/analysis tools.
Andrew D Ellington conceived and designed the experiments, contributed reagents/materials/analysis tools.
Claus O Wilke conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper.
Grant Disclosures
The following grant information was disclosed by the authors:
Defense Threat Reduction Agency (HDTRA1-12-C-0007), National Science Foundation (MCB-0943383), Welch Foundation (F-1654), National Institutes of Health (R01-GM088344), National Institutes of Health (R01-GM093086)
Funding
This work was supported by the Defense Threat Reduction Agency (HDTRA1-12-C-0007) to A.D.E., S.L.S., and C.O.W., the National Science Foundation (MCB-0943383) and the Welch Foundation (F-1654) to A.D.E., the National Institutes of Health (R01-GM088344) to C.O.W., and the National Institutes of Health (R01-GM093086) to S.L.S. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
