Protein Threading. Bioinformatics 404 DIKU Spring 2006
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1 Protein Threading Bioinformatics 404 DIKU Spring 2006
2 Agenda Protein Threading in general Branch and bound Refresh Protein Threading with B&B Evaluation and optimization Performance Engbo Jørgensen & Leon Jensen 2#28
3 Protein Threading in general Two similar sequences of aminoacids does not necessarily form the same structure Therefore inverse protein folding methods has occurred Engbo Jørgensen & Leon Jensen 3#28
4 Protein Threading in general Method that utilize the secondary structure of a know protein to predict a folding Sequence of amino-acids Database (proteins and their secondary structure) Set of energy functions Engbo Jørgensen & Leon Jensen 4#28
5 Protein Threading in general Engbo Jørgensen & Leon Jensen 5#28
6 Protein Threading in general For each protein in the database Find the alignment with lowest amount of free energy between the current aminoacid and the secondary structure Return the threading with the lowest free energy Engbo Jørgensen & Leon Jensen 6#28
7 Protein Threading in general Different variants Variable length loops Pairwise interactions (the location of two elements influence the scorefunction) NP-hard only if both are present Engbo Jørgensen & Leon Jensen 7#28
8 Protein Threading in general Engbo Jørgensen & Leon Jensen 8#28
9 Protein Threading in general Score function Engbo Jørgensen & Leon Jensen 9#28
10 Protein Threading in general Score function g 1 energy of one core segment g 2 energy between two core segments ( ) ( ) g i, t + g i, j, t, t 1 i i j i j> i min f(t) = min 2 t T t T Engbo Jørgensen & Leon Jensen 10#28
11 Branch and bound Refresh Paradigme, prunes parts of the search space Find s optimal solution If used on NP-hard problems O(n)=a n Engbo Jørgensen & Leon Jensen 11#28
12 Branch and bound Refresh For minimization problems Upperbound Bedst valid solution so far Lowerbound Tight provides more pruning Search strategy Depth-, breadth-, best- and worst-first Branching rule Engbo Jørgensen & Leon Jensen 12#28
13 Branch and bound Refresh Engbo Jørgensen & Leon Jensen 13#28
14 Branch and bound Refresh Engbo Jørgensen & Leon Jensen 14#28
15 Branch and bound Refresh Engbo Jørgensen & Leon Jensen 15#28
16 Protein Threading with B&B Engbo Jørgensen & Leon Jensen 16#28
17 Protein Threading with B&B Finds the k best solutions Exact solution to the threading problem Threading is not exact solution to folding problem Illegal solutions violates either : Spacing constraint Ordering constrant Engbo Jørgensen & Leon Jensen 17#28
18 Protein Threading with B&B Priorityqueue Sorts subproblems (sets of threadings) with increasing lb q=[(set 0,lb 0 ), (set 1,lb 1 ),,(set i,lb i )] When set 0 is a singleton set, it is the optimal solution Engbo Jørgensen & Leon Jensen 18#28
![(set 1,lb 1 ),,(set i,lb i )] When set 0 is a singleton](/docs-images/53/12049926/images/page_18.jpg "set, it is the optimal solution Engbo Jørgensen & Leon")
19 Protein Threading with B&B Representing sets of threadings b o =[,100,106] d o =[,117,120] Engbo Jørgensen & Leon Jensen 19#28
![b o =[,100,106] d o =[,117,120]](/docs-images/53/12049926/images/page_19.jpg "Engbo Jørgensen & Leon Jensen")
20 Protein Threading with B&B Engbo Jørgensen & Leon Jensen 20#28
21 Protein Threading with B&B Search strategy : Best first If bad lb the priorityqueue consumes too much space No upper bound Implicit pruning Engbo Jørgensen & Leon Jensen 21#28
22 Protein Threading with B&B Engbo Jørgensen & Leon Jensen 22#28
23 Engbo Jørgensen & Leon Jensen 23 #28 Protein Threading with B&B Lower bound 1. edt. ( ) ( ) + > i i j d z b d y b d x b z y j i g x i g j j i i I I,,, min, min 2 1
24 Protein Threading with B&B Lower bound 2. edt., tighter bound min t T i g ( i, t ) + ( ) + ( ) i g2 i 1, i, ti 1, ti min ½g2 i, j, ti u j 1, u T max j i > 1 l =+ j Engbo Jørgensen & Leon Jensen 24#28
25 Evaluation and optimization How to measure the quality of the threading? Self-threading Threading of analog and homolog sequences Engbo Jørgensen & Leon Jensen 25#28
26 Performance Engbo Jørgensen & Leon Jensen 26#28
27 Performance Error avoidance Fair scorefunction for all loop lengths Avoiding memorizing a sequence Choosing right structure representatives Penalizing amphipathic shifts (local errors) Engbo Jørgensen & Leon Jensen 27#28
28 Concluding remarks We can find an exact solution, that s not necessarily correct The algorithm is reasonably fast Combination with techniques from sequence based methods yields better results Detects structural similarities between genetically unrelated sequences Better sequence based methods are evolving Engbo Jørgensen & Leon Jensen 28#28
29 Protein Threading Bioinformatics 404 DIKU Spring 2006
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