Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins

✍ Scribed by Kim T. Simons; Ingo Ruczinski; Charles Kooperberg; Brian A. Fox; Chris Bystroff; David Baker

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 313 KB
• Volume: 34
• Category: Article
• ISSN: 0887-3585
• DOI: 10.1002/(sici)1097-0134(19990101)34:1<82::aid-prot7>3.0.co;2-a

✦ Synopsis

We describe the development of a scoring function based on the decomposition P(structure 0 sequence) ϰ P(sequence 0 structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of ␤-strands into ␤-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of D30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence 0 structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (