The protein threading problem with sequence amino acid interaction preferences is NP-complete.
In recent protein structure prediction research there has been a great deal of interest in using amino acid interaction preferences (e.g. contact potentials or potentials of mean force) to align ('thread') a protein sequence to a known structural motif. An important open question is whether a polynomial time algorithm for finding the globally optimal threading is possible. We identify the two critical conditions governing this question: (i) variable-length gaps are admitted into the alignment, and (ii) interactions between amino acids from the sequence are admitted into the score function. We prove that if both these conditions are allowed then the protein threading decision problem (does there exist a threading with a score < or = K?) is NP-complete (in the strong sense, i.e. is not merely a number problem) and the related problem of finding the globally optimal protein threading is NP-hard. Therefore, no polynomial time algorithm is possible (unless P = NP). This result augments existing proofs that the direct protein folding problem is NP-complete by providing the corresponding proof for the 'inverse' protein folding problem. It provides a theoretical basis for understanding algorithms currently in use and indicates that computational strategies from other NP-complete problems may be useful for predictive algorithms.
Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge 02139.
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D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D015394:Molecular Structure; D015202:Protein Engineering / Q000379:methods / Q000706:statistics & numerical data; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000235:genetics
D000596:Amino Acids; D011506:Proteins