Protein docking with predicted constraints
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RESEARCH
Open Access
Protein docking with predicted constraints Ludwig Krippahl* and Pedro Barahona
Abstract This paper presents a constraint-based method for improving protein docking results. Efficient constraint propagation cuts over 95% of the search time for finding the configurations with the largest contact surface, provided a contact is specified between two amino acid residues. This makes it possible to scan a large number of potentially correct constraints, lowering the requirements for useful contact predictions. While other approaches are very dependent on accurate contact predictions, ours requires only that at least one correct contact be retained in a set of, for example, one hundred constraints to test. It is this feature that makes it feasible to use readily available sequence data to predict specific potential contacts. Although such prediction is too inaccurate for most purposes, we demonstrate with a Naïve Bayes Classifier that it is accurate enough to more than double the average number of acceptable models retained during the crucial filtering stage of protein docking when combined with our constrained docking algorithm. All software developed in this work is freely available as part of the Open Chemera Library. Keywords: Docking, Constraints
Background Proteins are large molecules formed by long chains of amino acid residues, often hundreds of residues long. The sequence of residues in each chain is determined by the DNA sequence of its corresponding gene, where each nucleotide triplet specifies which of 20 different amino acids will be covalently bound at that position of the chain, releasing one water molecule in the peptide bond reaction and leaving behind the amino acid residue, the remaining molecule, bound to the growing chain. Thousands of millions of years of evolution ensured that the proteins thus formed have a well defined structure and were selected for playing important roles in the biochemistry of the organism. In many cases, these roles involve specific interactions with other proteins and understanding which partners interact and the structure of the complexes formed by these protein interactions is a fundamental part not only of current fundamental research in molecular biology but also in applied fields such as drug design or metabolic engineering. Docking
Protein docking is the prediction of these protein-protein complexes from the known structures of the protein targets [1]. This is not an easy task, as demonstrated by *Correspondence: [email protected] CENTRIA, Dept. Informática, FCT, UNL, 2829-516 Caparica, Portugal
the results of the Critical Assessment of PRediction of Interactions experiment, ongoing since 2001 [2]. According to the 2010 report for rounds 13-19, out of a total of 4420 submissions by 64 groups and 12 web servers, for six out of the thirteen target complexes there were no predictions considered highly accurate and only 16 models of at least acceptable quality in total, considering all submissions. Furthermore, one third of the participants failed to
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