CN105808973A - Staged multi-strategy-based group conformation space sampling method - Google Patents

Abstract

The invention discloses a staged multi-strategy-based group conformation space sampling method. The method comprises the following steps: dividing a whole algorithm process into a plurality of stages under the framework of a differential evolution algorithm, setting a group of strategy pools for each stage, and when the algorithm achieves a certain stage, randomly selecting a strategy from the corresponding strategy pool to generate a new test conformation individual on the basis of a fragment assembling technology, so as to improve the conformation sampling ability and the convergence rate of the algorithm; introducing distance spectrum constraint in the conformation selection link, when the energy of the tested conformation is higher than a target conformation, comparing the distance differences of the tested conformation and of the target conformation, and if the distance difference of the test individual is relatively small, receiving the tested conformation at a certain probability, so as to guide the algorithm sampling to obtain a conformation with lower energy and a more reasonable structure and then improve the prediction precision of the algorithm.

Description

A kind of based on the interim shifty colony conformational space method of sampling

Technical field

The present invention relates to bioinformatics, computer application field, in particular a kind of based on the interim shifty colony conformational space method of sampling.

Background technology

Having numerous protein (long-chain formed by 2 several amino acids) in biological cell, these macromole play an important role in organism, most important for completing biological function.Protein molecule has reacted the important relationship between its structure and function on a molecular scale, and different protein plays a different role in organism.The space structure of protein often determines its function, therefore, protein structure prediction to the design of new albumen, drug design, protein stability prediction and protein between interaction modeling most important.

The structure of protein is generally divided into four levels: primary structure (aminoacid sequence), secondary structure (partial structurtes formed that interact between skeletal atom), tertiary structure (secondary structure piles up the space structure formed on a large scale) and quarternary structure (describing the interaction between different subunit).Especially, the three dimensional structure (native state structure) of protein is the key of the biological function understanding protein.Protein three-dimensional structure can be obtained by experimental techniques such as nuclear magnetic resonance, NMR and X-ray crystal diffractions, but these experimental determining methods are not only consuming time but also extremely expensive, for inapplicable the protein of some not easily crystallization.Therefore, according to the thermodynamics hypothesis (conformation with minimum energy is considered as native state structure) of Anfinsen, a lot of computational algorithms are proposed for protein structure prediction.

Carrying out protein tertiary structure by computing technique and be usually directed to an energy function evaluating very expensive, its energy function curved surface is generally of thousands of degree of freedom and substantial amounts of locally optimal solution.So huge higher-dimension conformational space carries out sampling extremely difficult.In order to carry out conformational space search, first ab initio prediction method generally obtains the Global optimal solution of conformational space according to Knowledge based engineering coarseness energy model, then the conformation of its correspondence is carried out refine, thus obtaining pre-geodesic structure.Therefore, ab initio prediction method need solve two problems: 1. set up suitable energy function to weigh in protein molecule not homoatomic between interaction；2. propose effective conformational space searching method and search for energy Global optimal solution.

Differential evolution algorithm (DE) has proved to be Stochastic Global Optimization Algorithms simple and the most powerful in evolution algorithm.Due to its simple in construction, it is easy to accomplish, the advantage such as strong robustness and fast convergence rate has been successfully applied to protein tertiary structure.But, along with the growth of aminoacid sequence, protein molecule system degree of freedom also increases, and utilizes the Global optimal solution that the algorithm sampling of tradition colony obtains large-scale protein matter conformational space to become a challenging job；Tradition Swarm Evolution algorithm, when conformational space is sampled, can quickly navigate to the region at minimal solution place, but the later stage is more weak due to local enhancement ability in early stage, and convergence rate is relatively slow, and is easily ensnared into local optimum, it is impossible to obtain Global optimal solution.

Therefore, existing colony conformational space adopts method Shortcomings in ability in sampling and convergence rate, it is necessary to improve.

Summary of the invention

In order to overcome the deficiency in ability in sampling and convergence rate of the existing colony conformational space method of sampling, the present invention provide a kind of promote ability in sampling, improve convergence rate, improve precision of prediction based on the interim shifty colony conformational space method of sampling.

The technical solution adopted for the present invention to solve the technical problems is:

A kind of based on the interim shifty colony conformational space method of sampling, the described method of sampling comprises the following steps:

1) given list entries information；

2) from QUARK server (http://zhanglab.ccmb.med.umich.edu/QUARK/), distance spectrum file profile, rp are obtained according to sequence information_iFor the residue pair recorded in distance spectrum, D_iFor this residue between distance, wherein i ∈ (1, N), N be in distance spectrum residue to quantity；

3) parameter is set: Population Size NP, the iterations G of algorithm, intersection factor CR, stage factor s, put iteration algebraically g=0；

4) initialization of population: produced NP initial configurations C by list entries_i, i={1 ..., NP}, the individual all position fragments of each conformation are assembled；

5) for each conformation individuality C in population_i, i ∈ 1,2,3 ..., and NP}, make C_target=C_i, C_targetRepresent that target conformation is individual, perform following operation and obtain variation conformation C_mutant:

5.1) stochastic generation positive integer rand1, rand2, rand3 ∈ 1,2,3 ... NP}, and rand1 ≠ rand2 ≠ rand3 ≠ i；Regeneration 4 random integers randrange1, randrange2, randrange3, randrange4；Wherein randrange1 ≠ randrange2, randrange3 ≠ randrange4 ∈ 1,2 ..., L}, L is sequence length；

5.2) a=min (randrange1, randrange2), b=max (randrange1, randrange2), k ∈ [a, b] are made；Make c=min (randrange3, randrange4), d=max (randrange3, randrange4), p ∈ [c, d]；Wherein min represents the minima taking two numbers, and max represents the maximum taking two numbers

5.3) if g is < s G, then following operation is performed:

5.3.1) if randn (1,3)=1, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position, then by gained C_rand1Carry out fragment assembling and obtain variation conformation C_mutant, wherein randn (1,3) represents the integer between stochastic generation [1,3]；

5.3.2) if randn (1,3)=2, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand3Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.3.3) if randn (1,3)=3, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.4) if s is G≤g < 2s G, then following operation is performed:

5.4.1) according to energy, the conformation in whole population is carried out ascending order arrangement, then 0.5NP conformation individuality of the past selects a conformation at random and be designated as C_pbest；

5.4.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.4.3) if randn (1,3)=2, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.4.4) if randn (1,3)=3, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.5) if g >=2s is G, then following operation is performed:

5.5.1) whole population stochastic averagina is divided into three groups, it is judged that current goal conformation C_targetThe group at place, then selects the conformation C of minimum energy from corresponding group_lbest；

5.5.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.5.3) if randn (1,3)=2, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.5.4) if randn (1,3)=3, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

6) to variation conformation C_mutantPerform to intersect and operate:

6.1) random number rand4, rand5, wherein rand4 ∈ (0,1), rand5 ∈ (1, L) are generated；

6.2) basis $C_{trail}=\left\{\begin{array}{cc}{C}_{mu\tan t,rand5}\&LeftArrow;C_{t\arg et,rand5},& if(rand4\&le;CR)\\ C_{mu\tan t,rand5},& otherwise\end{array}\right.$ Perform crossover process: if random number rand4≤CR, make a variation conformation C_mutantFragment rand5 replace with target conformation C_targetThe fragment of middle correspondence, is otherwise directly equal to variation conformation C_mutant；

7) to target conformation C_targetWith test conformation C_trailCarry out selecting operation；

7.1) C is calculated_targetAnd C_trailEnergy: E (C_target) and E (C_trail)；

7.2) if E is (C_target)>E(C_trail), then C_trailReplace C_target, and forward step 8 to), otherwise continue executing with step 7.3)；

7.3) target conformation C is calculated respectively_targetWith test conformation C_trailMiddle residue is to rp_iBetween the distance distance corresponding with distance spectrum between range differenceWith

7.4) judgeWithValue whether more than 6, if more than 6, then make it be equal to 6, remove the abnormal numerical value that some distance difference are bigger；

7.5) calculate respectively all residues in target conformation and test conformation between distance and distance spectrum in the meansigma methods of difference of distance, $\&dtri;D_{t\arg et}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{t\arg et},\&dtri;D_{trail}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{trail};$

7.6) if D_trail> D_target, then step 8 is forwarded to)；

7.7) if D_trail< D_target, then produce the random number rand6 between (0,1), if rand6 is less than 0.2, then use C_trailReplace C_target, otherwise enter step 8)；

8) i=i+1；Judge that whether i is be more than or equal to NP, if it is g=g+1, otherwise enter step 9)；

9) operating procedure 5 of iteration)～7), to meeting end condition.

The technology of the present invention is contemplated that: under differential evolution algorithm framework, whole algorithmic procedure is divided into multiple stage, each stage is arranged a group policy pond, when algorithm reaches certain stage, from the tactful pond of its correspondence, randomly select a strategy, based on fragment package technique, generate new test conformation individual, thus improving conformation ability in sampling and convergence of algorithm speed；Select link to introduce distance spectrum constraint in conformation simultaneously, when the energy testing conformation is higher than target conformation, then compare both range differences, if the range difference of test individuality is less, then with certain probability acceptance test conformation, thus bootstrap algorithm sampling obtains, energy is lower and the conformation of more reasonable structure, improves the precision of prediction of algorithm.

The present invention is under basic differential evolution algorithm framework, based on fragment package technique, in algorithm each stage, different new conformation generation strategy ponds is set, then from strategy pond, randomly select one and generate new conformation, improving convergence of algorithm speed and reliability, selecting link to add distance restraint simultaneously, bootstrap algorithm is sampled in the region that energy is low and rational in infrastructure, improve the ability in sampling of algorithm on the whole, thus improving precision of prediction.

The invention have the benefit that based on fragment package technique, adopt different conformation generation strategies in each stage of algorithm, improve convergence of algorithm speed and conformation ability in sampling；Distance spectrum introduces as auxiliary constraint and selects link, and bootstrap algorithm sampling obtains high-quality conformation.

Accompanying drawing explanation

Fig. 1 is based on conformation when protein 1AIL is sampled by the interim shifty colony conformational space method of sampling and updates schematic diagram.

The conformation scattergram that Fig. 2 obtains when being based on interim shifty colony conformational space method of sampling protein 1AIL sampling；

Detailed description of the invention

Below in conjunction with accompanying drawing, the invention will be further described.

With reference to Fig. 1～2, a kind of based on the interim shifty colony conformational space method of sampling, comprise the following steps:

1) given list entries information；

2) from QUARK server (http://zhanglab.ccmb.med.umich.edu/QUARK/), distance spectrum file profile, rp are obtained according to sequence information_iFor the residue pair recorded in distance spectrum, D_iFor this residue between distance, wherein i ∈ (1, N), N be in distance spectrum residue to quantity；

3) parameter is set: Population Size NP, the iterations G of algorithm, intersection factor CR, stage factor s, put iteration algebraically g=0；

4) initialization of population: produced NP initial configurations C by list entries_i, i={1 ..., NP}, the individual all position fragments of each conformation are assembled；

5) for each conformation individuality C in population_i, i ∈ 1,2,3 ..., and NP}, make C_target=C_i, C_targetRepresent that target conformation is individual, perform following operation and obtain variation conformation C_mutant:

5.1) stochastic generation positive integer rand1, rand2, rand3 ∈ 1,2,3 ... NP}, and rand1 ≠ rand2 ≠ rand3 ≠ i；Regeneration 4 random integers randrange1, randrange2, randrange3, randrange4；Wherein randrange1 ≠ randrange2, randrange3 ≠ randrange4 ∈ 1,2 ..., L}, L is sequence length；

5.2) a=min (randrange1, randrange2), b=max (randrange1, randrange2), k ∈ [a, b] are made；Make c=min (randrange3, randrange4), d=max (randrange3, randrange4), p ∈ [c, d]；Wherein min represents the minima taking two numbers, and max represents the maximum taking two numbers

5.3) if g is < s G, then following operation is performed:

5.3.1) if randn (1,3)=1, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position, then by gained C_rand1Carry out fragment assembling and obtain variation conformation C_mutant, wherein randn (1,3) represents the integer between stochastic generation [1,3]；

5.3.2) if randn (1,3)=2, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand3Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.3.3) if randn (1,3)=3, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.4) if s is G≤g < 2s G, then following operation is performed:

5.4.1) according to energy, the conformation in whole population is carried out ascending order arrangement, then 0.5NP conformation individuality of the past selects a conformation at random and be designated as C_pbest；

5.4.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.4.3) if randn (1,3)=2, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.4.4) if randn (1,3)=3, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.5) if g >=2s is G, then following operation is performed:

5.5.1) whole population stochastic averagina is divided into three groups, it is judged that current goal conformation C_targetThe group at place, then selects the conformation C of minimum energy from corresponding group_lbest；

5.5.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.5.3) if randn (1,3)=2, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.5.4) if randn (1,3)=3, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

6) to variation conformation C_mutantPerform to intersect and operate:

6.1) random number rand4, rand5, wherein rand4 ∈ (0,1), rand5 ∈ (1, L) are generated；

6.2) basis $C_{trail}=\left\{\begin{array}{cc}{C}_{mu\tan t,rand5}\&LeftArrow;C_{t\arg et,rand5},& if(rand4\&le;CR)\\ C_{mu\tan t,rand5},& otherwise\end{array}\right.$ Perform crossover process: if random number rand4≤CR, make a variation conformation C_mutantFragment rand5 replace with target conformation C_targetThe fragment of middle correspondence, is otherwise directly equal to variation conformation C_mutant；

7) to target conformation C_targetWith test conformation C_trailCarry out selecting operation；

7.1) C is calculated_targetAnd C_trailEnergy: E (C_target) and E (C_trail)；

7.2) if E is (C_target)>E(C_trail), then C_trailReplace C_target, and forward step 8 to), otherwise continue executing with step 7.3)；

7.3) target conformation C is calculated respectively_targetWith test conformation C_trailMiddle residue is to the range difference between the distance corresponding with distance spectrum of the distance between rpiWith

7.4) judgeWithValue whether more than 6, if more than 6, then make it be equal to 6, remove the abnormal numerical value that some distance difference are bigger；

7.5) calculate respectively all residues in target conformation and test conformation between distance and distance spectrum in the meansigma methods of difference of distance, $\&dtri;D_{t\arg et}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{t\arg et},\&dtri;D_{trail}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{trail};$

7.6) if D_trail> D_target, then step 8 is forwarded to)；

7.7) if D_trail< D_target, then produce the random number rand6 between (0,1), if rand6 is less than 0.2, then use C_trailReplace C_target, otherwise enter step 8)；

8) i=i+1；Judge that whether i is be more than or equal to NP, if it is g=g+1, otherwise enter step 9)；

9) operating procedure 5 of iteration)～7), to meeting end condition.

The present embodiment with sequence length be 73 protein 1AIL for embodiment, a kind of based on the interim shifty colony conformational space method of sampling, wherein comprise the steps of

1) sequence information of given protein 1AIL；

2) from QUARK server (http://zhanglab.ccmb.med.umich.edu/QUARK/), distance spectrum file profile, rp are obtained according to sequence information_iFor the residue pair recorded in distance spectrum, D_iFor this residue between distance, wherein i ∈ (1, N), N=75 be in distance spectrum residue to quantity；

3) parameter is set: Population Size NP=30, the iterations G=10000 of algorithm, intersection factor CR=0.5, stage factor s=1/3, put iteration algebraically g=0；

4) initialization of population: produced NP initial configurations C by list entries_i, i={1 ..., NP}, the individual all position fragments of each conformation are assembled；

5) for each conformation individuality C in population_i, i ∈ 1,2,3 ..., and NP}, make C_target=C_i, C_targetRepresent that target conformation is individual, perform following operation and obtain variation conformation C_mutant:

5.1) stochastic generation positive integer rand1, rand2, rand3 ∈ 1,2,3 ... NP}, and rand1 ≠ rand2 ≠ rand3 ≠ i；Regeneration 4 random integers randrange1, randrange2, randrange3, randrange4；Wherein randrange1 ≠ randrange2, randrange3 ≠ randrange4 ∈ 1,2 ..., L}, L is sequence length；

5.2) a=min (randrange1, randrange2), b=max (randrange1, randrange2), k ∈ [a, b] are made；Make c=min (randrange3, randrange4), d=max (randrange3, randrange4), p ∈ [c, d]；Wherein min represents the minima taking two numbers, and max represents the maximum taking two numbers

5.3) if g is < s G, then following operation is performed:

5.3.1) if randn (1,3)=1, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position, then by gained C_rand1Carry out fragment assembling and obtain variation conformation C_mutant, wherein randn (1,3) represents the integer between stochastic generation [1,3]；

5.3.2) if randn (1,3)=2, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand3Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.3.3) if randn (1,3)=3, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.4) if s is G≤g < 2s G, then following operation is performed:

5.4.1) according to energy, the conformation in whole population is carried out ascending order arrangement, then 0.5NP conformation individuality of the past selects a conformation at random and be designated as C_pbest；

5.4.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.4.3) if randn (1,3)=2, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.4.4) if randn (1,3)=3, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.5) if g >=2s is G, then following operation is performed:

5.5.1) whole population stochastic averagina is divided into three groups, it is judged that current goal conformation C_targetThe group at place, then selects the conformation C of minimum energy from corresponding group_lbest；

5.5.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.5.3) if randn (1,3)=2, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Upper position c replaces C to dihedral angle phi, psi, omega corresponding for aminoacid institute p of the fragment of position d_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.5.4) if randn (1,3)=3, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

6) to variation conformation C_mutantPerform to intersect and operate:

6.1) random number rand4, rand5, wherein rand4 ∈ (0,1), rand5 ∈ (1, L) are generated；

6.2) basis $C_{trail}=\left\{\begin{array}{cc}{C}_{mu\tan t,rand5}\&LeftArrow;C_{t\arg et,rand5},& if(rand4\&le;CR)\\ C_{mu\tan t,rand5},& otherwise\end{array}\right.$ Perform crossover process: if random number rand4≤CR, make a variation conformation C_mutantFragment rand5 replace with target conformation C_targetThe fragment of middle correspondence, is otherwise directly equal to variation conformation C_mutant；

7) to target conformation C_targetWith test conformation C_trailCarry out selecting operation；

7.1) C is calculated_targetAnd C_trailEnergy: E (C_target) and E (C_trail)；

7.2) if E is (C_target)>E(C_trail), then C_trailReplace C_target, and forward step 8 to), otherwise continue executing with step 7.3)；

7.3) target conformation C is calculated respectively_targetWith test conformation C_trailMiddle residue is to the range difference between the distance corresponding with distance spectrum of the distance between rpiWith

7.4) judgeWithValue whether more than 6, if more than 6, then make it be equal to 6, remove the abnormal numerical value that some distance difference are bigger；

7.5) calculate respectively all residues in target conformation and test conformation between distance and distance spectrum in the meansigma methods of difference of distance, $\&dtri;D_{t\arg et}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{t\arg et},\&dtri;D_{trail}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{trail};$

7.6) if D_trail> D_target, then step 8 is forwarded to)；

7.7) if D_trail< D_target, then produce the random number rand6 between (0,1), if rand6 is less than 0.2, then use C_trailReplace C_target, otherwise enter step 8)；

8) i=i+1；Judge that whether i is be more than or equal to NP, if it is g=g+1, otherwise enter step 9)；

9) operating procedure 5 of iteration)～7), to iterations G=10000 time.

With sequence length be 73 protein 1AIL for embodiment, above method is used to obtain the nearly native state conformation of this protein, the average root-mean-square deviation run between 30 obtained structures and native state structure is 3.75, lowest mean square root deviation is 2.83, conformation renewal figure in conformation assemblage as it is shown in figure 1, the conformation scattergram that obtains of sampling as shown in Figure 2.

The excellent results that the embodiment that the present invention provides that described above is shows, the obvious present invention is not only suitable for above-described embodiment, it can be done many variations and be carried out under not necessarily departing from essence spirit of the present invention and the premise without departing from content involved by flesh and blood of the present invention.

Claims (1)

1. one kind based on the interim shifty colony conformational space method of sampling, it is characterised in that: the described conformational space method of sampling comprises the following steps:

1) given list entries information；

2) from QUARK server, distance spectrum file profile, rp are obtained according to sequence information_iFor the residue pair recorded in distance spectrum, D_iFor this residue between distance, wherein i ∈ (1, N), N be in distance spectrum residue to quantity；

3) parameter is set: Population Size NP, the iterations G of algorithm, intersection factor CR, stage factor s, put iteration algebraically g=0；

4) initialization of population: produced NP initial configurations C by list entries_i, i={1 ..., NP}, the individual all position fragments of each conformation are assembled；

5) for each conformation individuality C in population_i, i ∈ 1,2,3 ..., and NP}, make C_target=C_i, C_targetRepresent that target conformation is individual, perform following operation and obtain variation conformation C_mutant:

5.1) stochastic generation positive integer rand1, rand2, rand3 ∈ 1,2,3 ... NP}, and rand1 ≠ rand2 ≠ rand3 ≠ i；Regeneration 4 random integers randrange1, randrange2, randrange3, randrange4；Wherein randrange1 ≠ randrange2, randrange3 ≠ randrange4 ∈ 1,2 ..., L}, L is sequence length；

5.2) a=min (randrange1, randrange2), b=max (randrange1, randrange2), k ∈ [a, b] are made；Make c=min (randrange3, randrange4), d=max (randrange3, randrange4), p ∈ [c, d]；Wherein min represents the minima taking two numbers, and max represents the maximum taking two numbers

5.3) if g is < s G, then following operation is performed:

5.3.1) if randn (1,3)=1, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position, then by gained C_rand1Carry out fragment assembling and obtain variation conformation C_mutant, wherein randn (1,3) represents the integer between stochastic generation [1,3]；

5.3.2) if randn (1,3)=2, then C is used_rand2Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand3Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.3.3) if randn (1,3)=3, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.4) if s is G≤g < 2s G, then following operation is performed:

5.4.1) according to energy, the conformation in whole population is carried out ascending order arrangement, then 0.5NP conformation individuality of the past selects a conformation at random and be designated as C_pbest；

5.4.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.4.3) if randn (1,3)=2, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.4.4) if randn (1,3)=3, then C is used_pbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

5.5) if g >=2s is G, then following operation is performed:

5.5.1) whole population stochastic averagina is divided into three groups, it is judged that current goal conformation C_targetThe group at place, then selects the conformation C of minimum energy from corresponding group_lbest；

5.5.2) if randn (1,3)=1, then C is used_rand1Dihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_pbestDihedral angle phi, psi, omega corresponding to same position, then by gained C_pbestCarry out fragment assembling and obtain variation conformation C_mutant；

5.5.3) if randn (1,3)=2, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_rand1Dihedral angle phi, psi, omega corresponding to same position；Re-use C_rand2Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_rand1Dihedral angle phi, psi, omega corresponding to upper same position, then by gained C_rand1Carry out fragment assembling to obtain testing individual C_mutant；

5.5.4) if randn (1,3)=3, then C is used_lbestDihedral angle phi, psi, omega corresponding to upper position a to the aminoacid k of the fragment of position b replaces C_targetDihedral angle phi, psi, omega corresponding to same position；Re-use C_rand1Dihedral angle phi, psi, omega corresponding to upper position c to the aminoacid p of the fragment of position d replaces C_targetDihedral angle phi, psi, omega corresponding to upper same position, then by gained C_targetCarry out fragment assembling to obtain testing individual C_mutant；

6) to variation conformation C_mutantPerform to intersect and operate:

6.1) random number rand4, rand5, wherein rand4 ∈ (0,1), rand5 ∈ (1, L) are generated；

6.2) basis $C_{trail}=\left\{\begin{array}{cc}{C}_{mu\tan t,rand5}\&LeftArrow;C_{t\arg et,rand5},& if(rand4\&le;CR)\\ C_{mu\tan t,rand5},& otherwise\end{array}\right.$ Perform crossover process: if random number rand4≤CR, make a variation conformation C_mutantFragment rand5 replace with target conformation C_targetThe fragment of middle correspondence, is otherwise directly equal to variation conformation C_mutant；

7) to target conformation C_targetWith test conformation C_trailCarry out selecting operation；

7.1) C is calculated_targetAnd C_trailEnergy: E (C_target) and E (C_trail)；

7.2) if E is (C_target)>E(C_trail), then C_trailReplace C_target, and forward step 8 to), otherwise continue executing with step 7.3)；

7.3) target conformation C is calculated respectively_targetWith test conformation C_trailMiddle residue is to rp_iBetween the distance distance corresponding with distance spectrum between range differenceWith

7.4) judgeWithValue whether more than 6, if more than 6, then make it be equal to 6, remove the abnormal numerical value that some distance difference are bigger；

7.5) calculate respectively all residues in target conformation and test conformation between distance and distance spectrum in the meansigma methods of difference of distance, $\&dtri;D_{t\arg et}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{t\arg et},\&dtri;D_{trail}=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\&dtri;D_i^{trial};$

7.6) if D_trail> D_target, then step 8 is forwarded to)；

7.7) if D_trail< D_target, then produce the random number rand6 between (0,1), if rand6 is less than 0.2, then use C_trailReplace C_target, otherwise enter step 8)；

8) i=i+1；Judge that whether i is be more than or equal to NP, if it is g=g+1, otherwise enter step 9)；

9) operating procedure 5 of iteration)～7), to meeting end condition.