AI Article Synopsis
- The study involved predicting the structures of two protein-protein complexes using a genetic algorithm called GAPDOCK, along with several biochemical and human intervention methods.
- Among the models tested, the best prediction for the first target achieved 17 out of 52 correct interprotein contacts, while the second target's best model achieved 27 out of 52 correct contacts.
- Despite the challenges in targeting these complexes, the results are promising but highlight the need for better methods to differentiate truly accurate models from those that are merely plausible.
Article Abstract
As part of the first Critical Assessment of PRotein Interactions, round 1, we predict the structure of two protein-protein complexes, by using a genetic algorithm, GAPDOCK, in combination with surface complementarity, buried surface area, biochemical information, and human intervention. Among the five models submitted for target 1, HPr phosphocarrier protein (B. subtilis) and the hexameric HPr kinase (L. lactis), the best correctly predicts 17 of 52 interprotein contacts, whereas for target 2, bovine rotavirus VP6 protein-monoclonal antibody, the best model predicts 27 of 52 correct contacts. Given the difficult nature of the targets, these predictions are very encouraging and compare well with those obtained by other methods. Nevertheless, it is clear that there is a need for improved methods for distinguishing between "correct" and "plausible but incorrect" complexes.
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| http://dx.doi.org/10.1002/prot.10386 | DOI Listing |
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