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Incorporating Ab Initio energy into threading approaches for protein structure prediction.

Shao M, Wang S, Wang C, Yuan X, Li SC, Zheng W, Bu D - BMC Bioinformatics (2011)

Bottom Line: Subsequently, a local search algorithm is utilized to optimize the scoring function.Experimental results demonstrate that with distant interaction items, the quality of generated alignments are improved on 68 out of 127 query-template pairs in Prosup benchmark.In addition, compared with state-to-art threading methods, our method performs better on alignment accuracy comparison.Incorporating Ab Initio energy functions into threading can greatly improve alignment accuracy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. shaomingfu@ict.ac.cn

ABSTRACT

Background: Native structures of proteins are formed essentially due to the combining effects of local and distant (in the sense of sequence) interactions among residues. These interaction information are, explicitly or implicitly, encoded into the scoring function in protein structure prediction approaches--threading approaches usually measure an alignment in the sense that how well a sequence adopts an existing structure; while the energy functions in Ab Initio methods are designed to measure how likely a conformation is near-native. Encouraging progress has been observed in structure refinement where knowledge-based or physics-based potentials are designed to capture distant interactions. Thus, it is interesting to investigate whether distant interaction information captured by the Ab Initio energy function can be used to improve threading, especially for the weakly/distant homologous templates.

Results: In this paper, we investigate the possibility to improve alignment-generating through incorporating distant interaction information into the alignment scoring function in a nontrivial approach. Specifically, the distant interaction information is introduced through employing an Ab Initio energy function to evaluate the "partial" decoy built from an alignment. Subsequently, a local search algorithm is utilized to optimize the scoring function.Experimental results demonstrate that with distant interaction items, the quality of generated alignments are improved on 68 out of 127 query-template pairs in Prosup benchmark. In addition, compared with state-to-art threading methods, our method performs better on alignment accuracy comparison.

Conclusions: Incorporating Ab Initio energy functions into threading can greatly improve alignment accuracy.

Show MeSH
Effect of global score to distinguish AR from AL. All points lies to the right of x = 0, and 52 of 56 points appear above y = 0.
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Figure 4: Effect of global score to distinguish AR from AL. All points lies to the right of x = 0, and 52 of 56 points appear above y = 0.

Mentions: The 200 query-template pairs in SALIGN [18] dataset are categorized into two classes according to the quality of AL: (i) TM(AR) – TM(AL) < 0.1, 144 pairs in total; and (ii) TM(AR) – TM(AL) ≥ 0.1, 56 pairs in total. Intuitively, class 1 contains the pairs for which a scoring function with local score item alone is sufficient; and class 2 contains the pairs for which local score alone failed. For pairs in class 2, we expect global items can help to distinguish the reference alignment. We verify this by comparing the global score of AL and AR : only for pairs satisfying AL – AR > 0, it is likely to distinguish the reference alignment. Fig.4 and 5 suggest that for the pairs that local item alone cannot separate AL from AR (L(AL) ≤ L(AR) because of AL = argminAL(A)), global item of our scoring function can effectively measure the quality of alignments. Specifically, we observed that G(AR) <G(AL) on 52 of 56 pairs. In contrast, the contact-preference-based score does not help improve this situation, only on 20 of 56 pairs, C(AR) <C(AL).


Incorporating Ab Initio energy into threading approaches for protein structure prediction.

Shao M, Wang S, Wang C, Yuan X, Li SC, Zheng W, Bu D - BMC Bioinformatics (2011)

Effect of global score to distinguish AR from AL. All points lies to the right of x = 0, and 52 of 56 points appear above y = 0.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3044312&req=5

Figure 4: Effect of global score to distinguish AR from AL. All points lies to the right of x = 0, and 52 of 56 points appear above y = 0.
Mentions: The 200 query-template pairs in SALIGN [18] dataset are categorized into two classes according to the quality of AL: (i) TM(AR) – TM(AL) < 0.1, 144 pairs in total; and (ii) TM(AR) – TM(AL) ≥ 0.1, 56 pairs in total. Intuitively, class 1 contains the pairs for which a scoring function with local score item alone is sufficient; and class 2 contains the pairs for which local score alone failed. For pairs in class 2, we expect global items can help to distinguish the reference alignment. We verify this by comparing the global score of AL and AR : only for pairs satisfying AL – AR > 0, it is likely to distinguish the reference alignment. Fig.4 and 5 suggest that for the pairs that local item alone cannot separate AL from AR (L(AL) ≤ L(AR) because of AL = argminAL(A)), global item of our scoring function can effectively measure the quality of alignments. Specifically, we observed that G(AR) <G(AL) on 52 of 56 pairs. In contrast, the contact-preference-based score does not help improve this situation, only on 20 of 56 pairs, C(AR) <C(AL).

Bottom Line: Subsequently, a local search algorithm is utilized to optimize the scoring function.Experimental results demonstrate that with distant interaction items, the quality of generated alignments are improved on 68 out of 127 query-template pairs in Prosup benchmark.In addition, compared with state-to-art threading methods, our method performs better on alignment accuracy comparison.Incorporating Ab Initio energy functions into threading can greatly improve alignment accuracy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. shaomingfu@ict.ac.cn

ABSTRACT

Background: Native structures of proteins are formed essentially due to the combining effects of local and distant (in the sense of sequence) interactions among residues. These interaction information are, explicitly or implicitly, encoded into the scoring function in protein structure prediction approaches--threading approaches usually measure an alignment in the sense that how well a sequence adopts an existing structure; while the energy functions in Ab Initio methods are designed to measure how likely a conformation is near-native. Encouraging progress has been observed in structure refinement where knowledge-based or physics-based potentials are designed to capture distant interactions. Thus, it is interesting to investigate whether distant interaction information captured by the Ab Initio energy function can be used to improve threading, especially for the weakly/distant homologous templates.

Results: In this paper, we investigate the possibility to improve alignment-generating through incorporating distant interaction information into the alignment scoring function in a nontrivial approach. Specifically, the distant interaction information is introduced through employing an Ab Initio energy function to evaluate the "partial" decoy built from an alignment. Subsequently, a local search algorithm is utilized to optimize the scoring function.Experimental results demonstrate that with distant interaction items, the quality of generated alignments are improved on 68 out of 127 query-template pairs in Prosup benchmark. In addition, compared with state-to-art threading methods, our method performs better on alignment accuracy comparison.

Conclusions: Incorporating Ab Initio energy functions into threading can greatly improve alignment accuracy.

Show MeSH