CN104036155B

CN104036155B - Antibacterial peptide antibacterial activity Forecasting Methodology and antibacterial peptide

Info

Publication number: CN104036155B
Application number: CN201410241068.9A
Authority: CN
Inventors: 杨莉; 王震玲; 何谷; 魏于全
Original assignee: Sichuan University
Current assignee: Sichuan University
Priority date: 2014-05-30
Filing date: 2014-05-30
Publication date: 2018-01-05
Anticipated expiration: 2034-05-30
Also published as: CN109988224A; CN109988224B; CN109988225A; CN105801670B; CN105801670A; CN104036155A; CN109988225B

Abstract

The invention belongs to polypeptide design field, and in particular to the antibacterial activity Forecasting Methodology and antibacterial peptide of polypeptide.The purpose of the present invention is to overcome current antibacterial peptide antibacterial activity prediction relative complex, does not possess the shortcomings that operability.The present invention solves the technical scheme that its technical problem uses and is to provide antibacterial peptide antibacterial activity Forecasting Methodology.Antibacterial peptide sequence and its antibacterial activity data known to this method acquisition, are calculated each amino acid at each position to the contribution margin of whole section of antibacterial peptide activity, forecast model are established according to the contribution margin；The polypeptid acid sequence for needing to predict finally is substituted into standard prediction, obtains antibacterial activity predicted value.The antibacterial activity of the polypeptide obtained at random can be predicted using the Activity Prediction method.The present invention obtains a kind of polypeptide with broad spectrum antibiotic activity on this basis, has good application prospect.

Description

Antibacterial peptide antibacterial activity Forecasting Methodology and antibacterial peptide

Technical field

The invention belongs to polypeptide design field, and in particular to the antibacterial activity prediction of polypeptide and antibacterial peptide.

Background technology

Currently, the reason for bacterial infection and disease are in rising trend, and the formation of bacterial drug resistance is one important.By resistance to Property of medicine bacterium, such as drug resistant M bacillus, Escherichia coli and is referred to as " superbacteria " Methicillin-resistant Staphylococcus aureus (MRSA) Endanger and be on the rise to caused by humans and animals.The sprawling of antibiotic resistance may make eighties of last century drug treatment Many breakthroughs have not existed.Infectious agent has produced increasingly stronger drug resistance to the medicine used at present, but so far still It is untapped go out enough medicines solve this problem.Therefore, many infectious diseases, which may have, can become uncontrollable for one day, and can be Rapid sprawling all over the world.The appearance of drug tolerant bacteria causes the effect of existing antibacterials are to bacterial infection treatment low or nothing Effect, the harm getting worse of formation.As existing Drug-resistant sex chromosome mosaicism is on the rise, antibiotic pipeline is on the verge of exhaustion, urgently Need to develop new antibiotic preparation.Researchers are just making great efforts to seek new antibacterial strategy, and these strategies include：Rationally Using antibiotic；Transform existing antibiotic or research and develop new antibiotic；The research and application of probiotics；Phage preparation is ground Study carefully and apply；Chinese herbal medicine bacterial resistance inhibitor is studied and application；Antibacterial peptide research and application etc..Wherein efficiently, low toxicity, wide spectrum Antibacterial peptide as the new drug preparation being most hopeful instead of antibiotic by the concern of domestic and international researcher, turn into current Study hotspot.

Antibacterial peptide is typically produced by each organ in organism to resist microorganism infection, and many antibacterial peptides all have and exempted from Epidemic disease adjustment effect.In order to strengthen the antibacterial action of antibacterial peptide and immunoregulation effect, alleviate the resistance that all kinds of strains increasingly strengthen Property, scientists have developed many design synthesis or the method for transforming natural antibacterial peptide.Although different antibacterial peptides has a variety of length The features such as degree, amino acid composition or secondary structure, but there is similitude amphipathic, charge etc., and may have other Some common traits that can not intuitively find, these features may all have significant impact to the antibacterial activity of antibacterial peptide.It is based on This, scientists establish many bioinformatics tools to Forecasting Methodology to find the rule related with antibacterial peptide activity, greatly Most methods is all relevant with the similitude of high activity antibacterial peptide to a certain extent.

When optimizing an antibacterial peptide with preferable antibacterial activity, significantly alterring often in sequence is carried out The great variety of antibacterial activity can be caused, and is difficult to determine effects affecting activity because variable therein is too many.And only change When becoming a small amount of amino acid, because both sequence similarities are too high, most of Activity Prediction method can not all be distinguished well Both activity.The higher peptide sequence of similarity and energy can be distinguished in order to solve problem above and find a Forecasting Methodology Success is that this area is urgently to be resolved hurrily at present to being transformed existing polypeptide or directly being judged the new antibacterial activity for building polypeptide Technical problem.

The content of the invention

The purpose of the present invention is to overcome current antibacterial peptide antibacterial activity prediction relative complex, does not possess the shortcomings that operability, A kind of antibacterial peptide antibacterial activity Forecasting Methodology is provided.

The present invention solves its technical problem, and the technical scheme of use is that antibacterial peptide antibacterial activity Forecasting Methodology, its feature exists In comprising the following steps：

Antibacterial peptide sequence and its antibacterial activity data known to step 1, acquisition, and to the antibacterial activity number of all antibacterial peptides Antibacterial activity standardized value is obtained according to using antibacterial activity standardization conversion, randomly selects the antibacterial peptide sequence of a portion And its antibacterial activity standardized value is as training set, by the antibacterial peptide sequence and its antibacterial activity standardized value of remainder As test set；

Step 2, the antibacterial peptide sequence of training set is converted to by position of the amino acid in antibacterial peptide and amino acid name The amino acid matrix of composition；

Step 3, antibacterial activity standardized value and amino acid matrix according to training set, are calculated each amino acid and exist To the contribution margin of whole section of antibacterial peptide activity during each position, forecast model is established according to the contribution margin；

Step 4, test set substituted into forecast model, prediction activity value is calculated；

Step 5, the linear relationship for calculating all antibacterial activity standardized values for predicting activity values and test set, compare it Regression coefficient, the maximum forecast model of at least two regression coefficients is selected, as standard prediction；

Step 6, the polypeptid acid sequence for predicting needs substitute into standard prediction, obtain antibacterial activity predicted value.

Specifically, in step 1, the method for the antibacterial activity standardization conversion is：By in antibacterial activity data with quality How much it is converted into embody the IC50 values that the mg/L of active power is unit so that the unit mole of single polypeptide activity can be embodied often The activity value of (M/L) is risen, then the activity value is converted to and is the bigger the better and the antibacterial activity standardized value of linear distribution.

Further, the formula of the antibacterial activity standardization conversion is：F (a)=- ln (a/K × 10^-3), wherein, f (a) For antibacterial activity standardized value, a is the IC50 values of the antibacterial peptide, and unit mg/L, K are the molecular weight of the antibacterial peptide, unit For mol/kg.

Specifically, in step 3, the antibacterial activity standardized value according to training set and amino acid matrix, calculate It is to the method for the contribution margin of whole section of antibacterial peptide activity at each position to each amino acid：Using formulaCalculated, wherein, n is the amino acid number of the antibacterial peptide peptide chain, and i span is any 20 Value, each value represent a kind of amino acid in 20 kinds of natural amino acids, j be the i amino acid in the antibacterial peptide from nitrogen end To the position of carbon teminal, span is 1 to the positive integer between n；Bj is the constant coefficient of j positions amino acid in the antibacterial peptide, when When there is amino acid the j positions, Bj 1, when the j positions are without amino acid, Bj 0；Xij is i amino acid j positions in antibacterial peptide When to the contribution margin of whole section of antibacterial peptide activity.

Further, in step 3, if due to when the lazy weight of known f (a) enough solves all Xij, according to amino The property of acid, calculated after the Xij representated by the most similar amino acid of property to be carried out to minimum merging.

Specifically, the property includes charge and hydrophily.

Further, in step 1, the antibacterial peptide sequence for randomly selecting a portion and its antibacterial activity standard Change antibacterial peptide sequence and its antibacterial activity standardized value that numerical value refers to randomly select wherein 80%~90% as training set As training set.

Specifically, also have steps of：

Step 7, the antibacterial peptide sequence predicted needs, according to the electric charge size of each of which amino acid itself, it is anti-to calculate this The isoelectric point value of bacterium peptide, filter out the antibacterial peptide of suitable isoelectric point value.

Further, in step 7, the suitable isoelectric point value is 11~13.

The present invention is based on the above method, there is provided a kind of polypeptide, its amino acid sequence are：

V-Q-W-R-I-R-X1-X2-V-I-R-X3 (SEQ ID No.17), wherein X1=I or V, X2=A or C, X3=A, R or K；Or it is：

V-Q-L-R-I-R-V-X4-V-I-R-X5 (SEQ ID No.18), wherein X4=A or C, X5=R or K.

In the present invention, unless otherwise specified, all amino acid sequences are from left to right from nitrogen end to carbon teminal.

Further, the polypeptide has any bar amino acid sequence shown in SEQ ID No.1~SEQ ID No.16 in table 1 Row：

Table 1

Polypeptide title	Sequence number	Amino acid sequence
			DP2	SEQ ID No.1	VQWRIRVCVIRA
DP3	SEQ ID No.2	VQWRIRIAVIRA
			DP5	SEQ ID No.3	VQLRIRVCVIRR
DP7	SEQ ID No.4	VQWRIRVAVIRK
			DP8	SEQ ID No.5	VQLRIRVCVIRK
DP11	SEQ ID No.6	VQWRIRIAVIRK
			DP18	SEQ ID No.7	VQWRIRVCVIRR
DP19	SEQ ID No.8	VQWRIRICVIRA
			DP25	SEQ ID No.9	VQWRIRVAVIRA
DP27	SEQ ID No.10	VQWRIRIAVIRR
			DP29	SEQ ID No.11	VQWRIRICVIRR

DP35	SEQ ID No.12	VQWRIRVAVIRR
			DP36	SEQ ID No.13	VQWRIRICVIRK
DP39	SEQ ID No.14	VQWRIRVCVIRK
			DP43	SEQ ID No.15	VQLRIRVAVIRR
DP48	SEQ ID No.16	VQLRIRVAVIRK

Invention also provides purposes of the above-mentioned polypeptide in antibacterials are prepared.

Certain, present invention also offers using above-mentioned polypeptide as antibacterials made of main active.

Wherein, refer to can antibacterium and antimycotic for above-mentioned antibacterials.

Wherein, described bacterium is staphylococcus aureus (Staphylococcus aureus), Escherichia coli (Escherichia colibacillus), Acinetobacter bauamnnii (Acinetobacter baumanmii), Pseudomonas aeruginosa (Pseudomonas aeruginosa) or typhoid bacillus (Salmonella typhi).Wherein, described fungi is read for white Pearl bacterium (Canidia Albicans) or Candida parapsilosis (Candida parapsilosis).

The present invention is utilized based on the theory of amino acid active contribution degree to establish a machine learning method to predict polypeptide Activity, especially a large amount of quantity that random mutation obtains polypeptide.In this approach by calculating, obtain each different Amino acid polypeptide different relative positions for the not same-action of the antibacterial activity of polypeptide, and the antibacterial activity of whole polypeptide is just It is the embodiment of the summation of the antibacterial activity of wherein each amino acid.By this Forecasting Methodology, the inventive method can be predicted existing The antibacterial activity of polypeptide for having polypeptide and newly building, and the antibacterial peptide of possible high antibacterial activity is screened on this basis.

The beneficial effects of the present invention are：Although it is all based on the antibacterial peptide activity research and design method of masterplate, phase Descriptor for selecting characteristic to a large amount of related datas by statistical series and with computer, and by descriptor and work Property think that the QSAR Forecasting Methodologies of association and Forecasting Methodology, the prediction algorithm model of the invention such as genetic algorithm have more specific Principle and operability and repeatability.

Can all there are some common come the antibacterial peptide for selecting the method for characteristic descriptor to be based primarily upon high activity with computer Feature, do not know be which feature play a major role and the correlation degree height of each feature and activity in the case of, With computer come calculate its relevance can be by this Resolving probiems, and achieve and test the result being consistent, this is also this One important breakthrough of inventive method.

The antibacterial peptide Activity Prediction model that the inventive method is established by the antibacterial peptide Activity Prediction algorithm designed use, The multiple amino acid entered to template peptide carry out a series of polypeptides that random mutation obtains, then the carry out polypeptide active to obtaining Prediction and screening, screening obtain several antibacterial peptides, are named as DP series antibacterial peptides.This hair antibacterial peptide have obvious antibacterium and Antimycotic effect, experiment shows to a variety of sensitive bacterias and is clinically separated drug-fast bacteria and has good fungistatic effect, to bacterium The animal of infection has preferable therapeutic effect, and is respectively provided with relatively low toxicity to a variety of human normal cells of test.It is and more The prediction result of peptide activity experimental result and antibacterial peptide polypeptide active Forecasting Methodology of the present invention has uniformity.

Brief description of the drawings

Fig. 1, antibacterial peptide Activity Prediction model regression coefficient schematic diagram.

Bacterial infection mouse therapeutic effect inside Fig. 2, novel antimicrobial peptide DP7.Cecropin D P7 and HH2 are in intraperitoneal administration Concentration is respectively 20,40,60mg/kg when, detect bacterial content in 24 hours pneumoretroperitoneums, control positive drug is 20mg/kg's Vancomycin.

The toxicity of Fig. 3, novel antimicrobial peptide DP7 to human normal cell.X-axis is two times of antibacterial peptide since initial concentration Gradient dilution drug concentration change.Y-axis be polypeptide processing after haemolysis situation or polypeptide processing after human body cell survival rate. (A) be the erythrocyte splitting degree that is calculated by determining the burst size of ferroheme, people's epithelial fibroblast cells (B), people into Fibrocyte strain MRC-5 (C), human normal cell's strain HEK293 (D) use CCK-8 cytoactive detection reagents after polypeptide processing Box detects cell survival rate；The standard deviation between 3 different experiments is marked in figure.

Fig. 4, influences of the novel antimicrobial peptide DP7 to ne ar is detected using ESEM and transmission electron microscope.(a) to be golden yellow Color staphylococcus is handled the result (× 50,000) of scanning electron microscopic observation after 1 hour by the DP7 of various concentrations.With DP7 concentration Increase, bacterium surface is by smoothly becoming fold and slight crack occur, as shown by arrows.(b) (c) is that staphylococcus aureus is identical The result (× 10,000) of transmission electron microscope observing after the DP7 processing different times of concentration.

Embodiment

Below in conjunction with the accompanying drawings and embodiment, technical scheme is described in detail.

Below in conjunction with accompanying drawing, by the description of embodiment, the invention will be further described, but this is not to this hair Bright limitation, those skilled in the art according to the present invention basic thought, various modifications or improvement can be made, without departing from The basic thought of the present invention, within the scope of the present invention.

Embodiment one, antibacterial peptide antibacterial activity Forecasting Methodology of the present invention and its principle

In the antibacterial peptide antibacterial activity Forecasting Methodology of this example, it specifically includes following steps：

Antibacterial peptide sequence and its antibacterial activity data known to step 1, acquisition, and to the antibacterial activity number of all antibacterial peptides Antibacterial activity standardized value is obtained according to using antibacterial activity standardization conversion, randomly selects the antibacterial peptide sequence of a portion And its antibacterial activity standardized value is as training set, by the antibacterial peptide sequence and its antibacterial activity standardized value of remainder As test set.

In this step, the method for antibacterial activity standardization conversion can be：How much will be come with quality in antibacterial activity data The IC50 values that the strong and weak mg/L of activity is unit are embodied to be converted into so that every liter of the unit mole (M/L) of single polypeptide activity can be embodied Activity value, then the activity value is converted to and is the bigger the better and the antibacterial activity standardized value of linear distribution.Antibacterial activity mark Standardization conversion formula can be：F (a)=- ln (a/K × 10^-3), wherein, f (a) is antibacterial activity standardized value, and a is should The IC50 values of antibacterial peptide, unit mg/L, K are the molecular weight of the antibacterial peptide, unit mol/kg.

Randomly select a portion antibacterial peptide sequence and its antibacterial activity standardized value as training set refer to The antibacterial peptide sequence and its antibacterial activity standardized value of machine selection wherein 80%~90% are as training set.

Acquired antibacterial peptide sequence and its antibacterial activity standardized value is as follows：

Step 2, the antibacterial peptide sequence of training set is converted to by position of the amino acid in antibacterial peptide and amino acid name The amino acid matrix of composition.

In this step, acquired amino acid matrix is exemplified below：

K 0 K 0 0 S 0 K Q L W K 0 R

M 0 I N 0 R 0 V 0 R L R 0 W

……

Wherein, each non-zero letter represents the amino acid that certain letter of the position refers to.

The antibacterial activity standardized value and amino acid matrix that step 3, basis obtain, are calculated each amino acid every To the contribution margin of whole section of antibacterial peptide activity during individual position, forecast model is established according to the contribution margin.

In this step, according to obtained antibacterial activity standardized value and amino acid matrix, each amino acid is calculated Can be to the method for the contribution margin of whole section of antibacterial peptide activity at each position：Using formulaCounted Calculate, wherein, n is the amino acid number of the antibacterial peptide peptide chain, and i span is any 20 values, and each value represents 20 kinds A kind of amino acid in natural amino acid, j are position from nitrogen end to carbon teminal of the i amino acid in the antibacterial peptide, value model Enclose for 1 to the positive integer between n；Bj is the constant coefficient of j positions amino acid in the antibacterial peptide, when there is amino acid the j positions, Bj For 1, when the j positions are without amino acid, Bj 0；Xij be i amino acid in antibacterial peptide during j positions to whole section of antibacterial peptide activity Contribution margin, wherein, the amino acid matrix being made up of position of the amino acid in antibacterial peptide and amino acid name in step 2 is Refer to the amino acid matrix being made up of Xij.If enough solve all Xij due to the lazy weight of known f (a), according to amino acid Property, will Xij representated by the most similar amino acid of property carry out minimum merging after calculate, the property include it is charge and Hydrophily etc..

Draw value of each non-zero letter in being illustrated such as step 2 in each position.

Step 4, test set substituted into forecast model, prediction activity value is calculated.

In this step, the prediction activity value being calculated is as follows：

1 activity value of peptide=R+W+M+G+V+I+I+K+Y

2 activity values of peptide=A+V+K+G+C+P+G+K+C

3 activity values of peptide=F+D+M+G+L+I+O+K+N

……

Step 5, the linear relationship for calculating all antibacterial activity standardized values for predicting activity values and test set, referring to figure 1, compare its regression coefficient, the maximum forecast model of at least two regression coefficients is selected, as standard prediction.

Step 6, the antibacterial peptide sequence for predicting needs substitute into standard prediction, obtain predicted value.

It can also have steps of：

In this step, suitable isoelectric point value is 11~13.

The principle of above-mentioned used method or algorithm is described in detail below：

1. antibacterial peptide forecast model

With certain active antibacterial peptide, the change of each position amino acid can influence its active height, predict mould The activity of whole antibacterial peptide is considered as the summation that each position amino acid is contributed the activity of whole antibacterial peptide thereon by the algorithm of type, By the point mutation data of each amino acid on complete antibacterial peptide, each amino acid on each antibacterial peptide position can be obtained To the active contribution margin of whole antibacterial peptide, the matrix that forecast model is formed by amino acid active contribution margin, new structure can be calculated Antibacterial peptide sequence on all amino acid contribution margin sum come obtain its prediction activity value.

2. the antibacterial peptide Activity Prediction method shorter than template

The structure antibacterial peptide sequence similar to natural antibacterial peptide nature, even if sequence amino acid composition is different, sequence length Difference, but can also reach even better than original antibacterial activity.In prediction algorithm, before small peptide is considered as into long peptide deletion sequence Caused sequence behind face or amino acid below, but shorter sequence and template sequence ratio, in this case it is not apparent that small peptide missing Be residue above or residue below or it is front and rear have disabled missing, our work to small peptide after all topagnosis deformity Property be all predicted, and prediction will be obtained and obtain active highest missing pattern as its actual amino acid deletions pattern, Prediction activity of its activity i.e. as this small peptide.

3. the standardization conversion of antibacterial activity

Because the antibacterial activity value (IC50 values) that experiment direct measurement obtains does not have preferable linear relationship, and add sum Form of calculation is not particularly suited for being worth the higher relation of smaller activity.And in order to avoid point different possessed by different antibacterial peptides How much the influence of son amount was, it is necessary to come the IC50 values in units of embodying the mg/L of active power will be converted into and can embodied by quality originally Every liter of the unit mole (M/L) of single polypeptide activity.Therefore prediction algorithm is converted the activity of polypeptide by below equation Optimize to be more suitable for being simulated with equation：F (a)=- ln (a/M × 10^-3).M is the molecular weight of polypeptide in formula, and a is antibacterial peptide IC50 values, a/M × 10^-3Active unit's conversion is turned into mole every liter, ln will be the smaller the better by the expression of original exponential distribution Activity value be converted into and be the bigger the better and the numerical value of linear distribution.

4. activity contribution value calculating method

Due to and uncertain antibacterial peptide sequence in each amino acid between effect be similar to adding in mathematics, multiply, Or other patterns, are simplified operation, this patent simulates contribution of each amino acid to antibacterial peptide activity with additive.To obtain The active contribution margin of all position all kinds amino acid of sequence, be with every kind of amino acid active of each position of antibacterial peptide sequence Contribution is used as unknown number, and the activity of antibacterial peptide is as datum, it is therefore desirable to the side of a unknown number for being capable of dematrix distribution Journey, following N members linear function is employed as active calculation formula in this patent：

F (a) is the activity of current antibacterial peptide in equation, and n is the length of the amino acid number, i.e. peptide chain of the antibacterial peptide peptide chain Degree, i span is any 20 values, and each value represents a kind of amino acid in 20 kinds of natural amino acids, and j is the i ammonia Position from nitrogen end to carbon teminal of the base acid in the antibacterial peptide, span are 1 to the positive integer between n；Bj is the antibacterial peptide The constant coefficient of middle j positions amino acid, Xij be i amino acid in antibacterial peptide during j positions to the contribution margin of whole section of antibacterial peptide activity.i The square that an amino acid classes and amino acid position in antibacterial peptide be mutually the amino acid active contribution margin of row is formd with j Battle array, it is known that Xij value is according to the different and amino acid different and different of sequence.

When predicting antibacterial peptide activity, Bj is that 1, Xij takes amino acid contribution margin if the non-NULL of current location, if current location Bj is zero if for empty (when predicting the antibacterial peptide shorter than template length), and current location is without amino acid contribution margin.Because sequence is got over Short peptide activity numerical value add and lack it is more, therefore length it is different polypeptide prediction Activity Results can not directly be compared, in advance The Activity Results of survey are only applicable to the comparison of the polypeptide of same length, and the length of the target polypeptides of this Forecasting Methodology prediction also can only Less than or equal to establish model use most long polypeptide length.

5. the calculating of other antibacterial peptide natures

(1) estimation of antibacterial peptide isoelectric point

According to the electric charge size of each amino acid itself, the isoelectric point value of overall antibacterial peptide is calculated.Due to cationic peptide pair The affinity of bacteria cell wall is stronger, and excessively strong electric charge can be very strong to the toxicity of animal somatic cell, therefore algorithm is resisting After the isoelectric point of bacterium peptide is calculated, screening isoelectric point value carries out result output in 11~13 antibacterial peptide.

(2) antibacterial peptide molecular weight calculation

According to the molecular size range of each amino acid, the molecular weight of whole antibacterial peptide is calculated.

6. the degeneracy of the similar amino acid of property

When calculating amino acid active contribution value matrix, the antibacterial peptide of a n amino acid length needs to solve n × 20 altogether (20 kinds of amino acid) individual unknown number, due to one unknown number of a solution of equation, it is therefore desirable at least n × 20 equation, that is, need At least known antibacterial peptide sequence in n × 20 and its activity.It is more limited when running into more peptide datas for establishing model, not in sequence Each position on when there is every kind of amino acid, can have a limitation with above-mentioned Forecasting Methodology, thus to solve this problem and Propose the degeneracy of the similar amino acid of property.Amino acid is according to having electrically charged property, hydrophilic difference, according to these properties Close situation merges amino acid similar in Nature comparison in all amino acid.By the more of the existing amino acid data possessed Few, the size of the degree of selection combining, i.e., how many similar amino acid merge is calculated as a parameter, the kind of merging Class voluntarily judges that the quantity of merging is according to whether there is solution to be selected according to the property of amino acid.The degeneracy of amino acid can solve Certainly due to there is no the problem of all unknown numbers of enough solution of equations caused by data volume deficiency.But the degree merged, which crosses conference, to be made accurately Degree reduces.

Embodiment two, the foundation of forecast model and the design of novel antimicrobial peptide and Activity Prediction

1st, antibacterial peptide sequence and its antibacterial activity data known to obtaining, for the foundation of forecast model.It is all Know in sequence data, the sequence data for randomly selecting 80%-90% establishes forecast model, remaining 10%- as training set The prediction accuracy for the model that 20% sequence data is established as test set checking.In this modeling, use known to 180 Antibacterial peptide, its amino acid sequence and activity data derive from patent document WO2008/022444, is the anti-of 12 amino acid Bacterium peptide.Training uses antibacterial peptide sequence 174 at random every time, and remaining 14 antibacterial peptide sequences are trained in each test.

2nd, antibacterial activity data are standardized with antibacterial activity standardized method, and are by the Sequence Transformed of antibacterial peptide The amino acid matrix being made up of Xij.

3rd, the antibacterial activity standardized value of all antibacterial peptides substitutes into the left side of active calculation formula, and by corresponding antibacterial The amino acid matrix of peptide substitutes into the right of active calculation formula.

4th, all matrix equations are solved, calculate all Xij value, and antibacterial peptide Activity Prediction model is established with Xij.

5th, with the activity of antibacterial peptide Activity Prediction model prediction test set, and the prediction activity value and test set being calculated The linear relationship of the normalized activity value of itself, regression coefficient is bigger, and linear relationship is better, represents the higher (ginseng of predictablity rate See Fig. 1).The data for selecting training set and test set at random repeatedly are carried out, to obtain the higher forecast model of accuracy rate.

6th, template polypeptide sequence to be optimized is chosen, carries out the replacement of all permutation and combination of several amino acid, and accordingly produce Raw all new antibacterial peptide sequences.

7th, activity is carried out to these novel antimicrobial peptide sequences with two antibacterial peptide Activity Prediction models of prediction accuracy highest Prediction, and take two forecast models while there is the antibacterial peptide of high prediction activity as high activity antibacterial peptide, forecast model is simultaneously Calculate the properties such as its isoelectric point, molecular weight.

Embodiment three is predicted and screened antibacterial peptide using the inventive method

The present invention is set out with known polypeptide VQLRIRVAVIRA (HH2), using computer in each amino acid residue position Point has carried out random change, and the mutation such as deletion or addition, each mutation is all natural amino acid, has obtained having 1324256 The peptide sequence storehouse to be selected of individual peptide sequence.

Two obtained standards are established using the above-mentioned importing embodiment two in peptide sequence storehouse to be selected including template peptide Exactness highest forecast model carries out computing respectively, obtains the activity of wherein each bar polypeptide, that is, carries out the antibacterial of novel polypeptide sequence Activity Prediction.And take two forecast models while there is the antibacterial peptide of high prediction activity as high activity antibacterial peptide, forecast model The properties such as its isoelectric point, molecular weight are calculated simultaneously, and screening isoelectric point value carries out result output in 11~13 antibacterial peptide.Obtain 50 models 1 and model 2 predict that activity all apparently higher than the polypeptide of template peptide, is named as DP1~DP50, and close by chemistry Corresponding polypeptide is obtained into method.

It is predicted using the inventive method and the results are shown in Table 2 with what is screened：

Table 2, prediction and the selection result

Polypeptide title

Polypeptide is numbered

Amino acid sequence

Sequence number

The prediction result of model 1

The prediction result of model 2

Predict isoelectric point

Template peptide

HH2

VQLRIRVAVIRA

SEQ ID No.53

7.6366

7.4887

12.7832

DP1

vari2-18919

VQLRIRIAVCRA

SEQ ID No.19

8.4296

8.5012

12.18164

DP2

vari2-10368

VQWRIRVCVIRA

SEQ ID No.1

8.9990

9.1620

12.18164

DP3

vari2-10356

VQWRIRIAVIRA

SEQ ID No.2

8.9635

8.7939

12.7832

DP4

vari2-4161

VCWRIRVAVIRA

SEQ ID No.20

8.4744

8.4668

12.18164

DP5

vari2-20090

VQLRIRVCVIRR

SEQ ID No.3

9.3337

8.8111

12.48242

DP6

vari2-1701

KQWRIRVAVIRA

SEQ ID No.21

8.4291

8.5605

12.7832

DP7

vari2-10451

VQWRIRVAVIRK

SEQ ID No.4

8.7877

9.1216

12.7832

DP8

vari2-20084

VQLRIRVCVIRK

SEQ ID No.5

8.8172

8.9816

12.19531

DP9

vari3-174243

KQWRIRVCVIRA

SEQ ID No.22

8.6532

9.0990

12.19531

DP10

vari3-898602

VQLRCRVCVIRK

SEQ ID No.23

9.1880

9.0391

11.29297

DP11

vari3-662285

VQWRIRIAVIRK

SEQ ID No.6

9.1462

9.0221

12.7832

DP12

vari2-10407

VQWRIRVAVCRA

SEQ ID No.24

8.9356

9.0093

12.18164

DP13	vari2-10312	VQWRCRVAVIRA	SEQ ID No.25	8.8510	8.9757	12.18164
							DP14	vari2-10328	VQWRWRVAVIRA	SEQ ID No.26	8.3969	7.8671	12.7832
DP15	vari2-10350	VQWRIRCAVIRA	SEQ ID No.27	8.7761	8.4008	12.18164
							DP16	vari2-10388	VQWRIRVACIRA	SEQ ID No.28	8.7316	8.8723	12.18164
DP17	vari2-10457	AQWRIRVAVIRA	SEQ ID No.29	8.3042	8.6511	12.95752
							DP18	vari2-10371	VQWRIRVCVIRR	SEQ ID No.7	9.5438	9.3741	12.48242
DP19	vari2-15821	VQWRIRICVIRA	SEQ ID No.8	9.4866	9.3334	12.18164
							DP20	vari2-10375	VQWRIRVKVIRA	SEQ ID No.30	8.6234	8.7730	12.7832
DP21	vari2-10381	VQWRIRVRVIRA	SEQ ID No.31	8.6142	8.9637	12.95752
							DP22	vari2-5491	VKWRIRVAVIRA	SEQ ID No.32	8.5941	8.5865	12.7832
DP23	vari2-3573	WQWRIRVAVIRA	SEQ ID No.33	8.5802	8.7115	12.7832
							DP24	vari2-10413	VQWRIRVAVKRA	SEQ ID No.34	9.0752	8.7100	12.7832
DP25	vari2-10449	VQWRIRVAVIRA	SEQ ID No.9	8.4693	8.7291	12.7832
							DP26	vari2-15860	VQLRWRVAVCRA	SEQ ID No.35	8.5630	8.4744	12.18164
DP27	vari2-10318	VQWRIRIAVIRR	SEQ ID No.10	9.1757	9.0386	12.95752
							DP28	vari2-10360	VQWRIRNAVIRA	SEQ ID No.36	8.5577	8.6824	12.7832
DP29	vari2-10374	VQWRIRICVIRR	SEQ ID No.11	9.8684	9.7085	12.48242
							DP30	vari2-10386	VQWRIRVYVIRA	SEQ ID No.37	7.8468	7.6383	12.19531
DP31	vari2-10424	VQWRIRVAVYRA	SEQ ID No.38	8.1271	7.9320	12.19531
							DP32	vari2-10454	VQWRIRVAVIRN	SEQ ID No.39	8.5212	8.6550	12.7832
DP33	vari2-10373	VQWRIRVHVIRA	SEQ ID No.40	8.5193	8.3688	12.7832
							DP34	vari2-10384	VQWRIRVTVIRA	SEQ ID No.41	8.5107	8.6603	12.7832
DP35	vari2-10459	VQWRIRVAVIRR	SEQ ID No.12	8.8511	8.9042	12.95752
							DP36	vari2-7022	VQWRIRICVIRK	SEQ ID No.13	9.8389	9.6920	12.19531
DP37	vari2-18880	VQLRIRICVIRA	SEQ ID No.42	9.4930	8.8539	12.18164
							DP38	vari2-10419	VQWRIRVAVRRA	SEQ ID No.43	8.7890	9.1939	12.95752
DP39	vari2-10421	VQWRIRVCVIRK	SEQ ID No.14	9.5143	9.3576	12.19531
							DP40	vari2-10401	VQWRIRVARIRA	SEQ ID No.44	8.4786	8.6348	12.95752
DP41	vari2-22616	VQLRIRVAVCRR	SEQ ID No.45	8.7703	8.9584	12.48242

DP42	vari2-10385	VQWRIRVWVIRA	SEQ ID No.46	8.7689	8.8185	12.7832
							DP43	vari2-10300	VQLRIRVAVIRR	SEQ ID No.15	7.9612	7.8231	12.95752
DP44	vari2-7212	VYWRIRVAVIRA	SEQ ID No.47	8.4648	8.2571	12.19531
							DP45	vari2-10414	VKLRIRVCVIRA	SEQ ID No.48	8.8236	9.4465	12.19531
DP46	vari2-4921	VGWRIRVAVIRA	SEQ ID No.49	8.7578	8.8502	12.7832
							DP47	vari2-22610	VQLRIRVAVCRK	SEQ ID No.50	8.4538	8.3289	12.19531
DP48	vari2-10358	VQLRIRVAVIRK	SEQ ID No.16	8.3135	8.1817	12.7832
							DP49	vari2-10376	VQWRIRVAYIRA	SEQ ID No.51	8.8178	8.7562	12.19531
DP50	vari2-5111	VHWRIRVAVIRA	SEQ ID No.52	7.8322	7.9245	12.7832

The antibacterial activity detection of example IV, the polypeptide filtered out

1. bacterium antibacterial experiment in vitro

(1) culture medium is prepared

MHB broth bouillons and MHA meat soup solid mediums, are illustratively formulated respectively, addition deionized water dissolving, and 120 DEG C autoclaving after 20 minutes 4 degrees Celsius of preservations it is stand-by.

(2) strain prepares

5ml MHB broth bouillons are added in real pipe, 20 μ l strain conservations liquid of addition (including gram-positive bacteria gold Staphylococcus aureus 25923 (being purchased from American Type Culture Collecti ATCC) and Gram-negative bacteria：It is Escherichia coli 25922, green Purulence bacillus PAO-1 (being purchased from ATCC) and typhoid bacillus RE88 (Canadian The Scripps Research Inst. give), 220RPM, 37 DEG C After shaking table culture 16 hours, MHA flat boards are applied to, 37 DEG C of bacteriological incubator cultures are sealed after 18 hours with sealed membrane, and 4 DEG C of preservations are treated With the holding time is 1 week.

(3) antibacterials storage liquid prepares

All medicines are configured to 10mg/ml storage liquid.Antibacterial peptide medicament is first dissolved with the DMSO of final volume 20%, so The sterilized water for adding residual volume afterwards is dissolved to aimed concn.Chemicals is dissolved by medicine requirement, and is diluted to target Concentration.

(4) preparation and dilution of bacterium solution are hanged

By the strain of experiment, one form of picking is good from solid medium, diameter 1mm or so bacterium colony picking 3 It is cloned in 1ml fluid nutrient medium.Existed with spectrophotometer (3 milliliters of outstanding bacterium solutions) or ELIASA (200 μ l hang bacterium solution/hole) Absorbance is measured under 600nm, the absorbance of bacterium solution, root is calculated in the absorbance for subtracting the culture medium control of isodose Converted according to the result of early stage by 1OD values and CFU ratio, and bacterium solution is diluted to 1 × 10⁷CFU/ml。

(5) dilution of antibacterials

10 0.5ml centrifuge tubes are taken, the 1st pipe adds the μ l of culture medium 335.64, and the 2nd to 10 pipe is separately added into 170 μ l cultures Base, the μ l to the 1st of storage liquid 4.36 pipes for thing of getting it filled, draws 170 μ l to the 2nd pipe after well mixed and mixes, and operates the 10th pipe successively. The drug concentration of acquisition from the first hole to the tenth hole be 128,64,32,16,8,4,2,1,0.5,0.25 μ g/ml.Compare positive drug Thing gentamicin, Linezolid, lavo-ofloxacin proceed by two times of gradient dilutions from 8 μ g/ milliliters.

(6) preparation of control group：

Tenth hole and 11-holes add 50 μ l culture mediums and (add the μ of culture medium 335.64 if test medicine is antibacterial peptide L, 4.36 μ l 20%DMSO aseptic aqueous solutions, it is separately added into control wells, 50 μ l/ holes)

(7) inoculation of bacterium solution：

By dilution order from diluted antibacterials solution draw 50 μ l add 96 orifice plates second row, the 3rd row, the 4th Arrange (three wells), then add 50 μ l1 × 10 into the hole of the 11st row in first row⁷CFU/ml outstanding bacterium solution, 11-holes Add 50 μ l culture medium.Final result is：First row is classified as experiments of the μ g/ml of antibacterials 64 to 0.125 μ g/ml to the tenth Group, the 11st is classified as medium controls, each three multiple holes.12nd row add 100 μ l culture mediums as blank group, finally will 96 orifice plates after above-mentioned inoculation were as 37 degrees Celsius of bacteriological incubator cultures 20 hours.

(8) result is read：

Then 96 orifice plates measure absorbance, the value that three wells measures is averaged as ELIASA under 600nm wavelength Value, and calculate bacteriostasis rate：

Antibacterials concentration using bacteriostasis rate more than or equal to 80% is used as its MIC value to this bacterium.

2. fungi antibacterial experiment in vitro

(1) preparation of culture medium：

A) sabouraud culture medium solid medium：

Composition：Dusty yeast 10g/L, glucose 40g/L, agar 15g/L, target volume is dissolved to deionized water, 120 DEG C Autoclaving falls in glass plate after 20 minutes, makes culture medium thickness 5mm.

B) Sharpe fluid nutrient medium：

Dusty yeast 10g/L, glucose 40g/L, target volume is dissolved to deionized water, 120 DEG C of autoclavings 20 minutes 4 DEG C of preservations afterwards.

C) RPMI1640 culture mediums：

10.4g/L RPMI1640 powder, 34.53g/L MOPS (final concentration 0.165mol/L), adjusted with 1mol/L NaOH Whole pH to 7.0.After filtration sterilization plus sterilized water is to target volume, and 4 DEG C preserve.

(2) medicament storage liquid：

Polypeptide drugs powder makes its concentration be 10mg/ml with 20%DMSO sterilized water dissolving.

Fluconazole drug powder makes its concentration be 10mg/ml with sterilized water dissolving.

(3) strain prepares：

20 μ l are taken to be based on 37 as 5ml RPMI1640 cultures from Candida albicans strain (being purchased from U.S. ATCC) conservation liquid DEG C bacterium incubator culture 48 hours, the same day obtain bacterium solution on the day of use.

(4) inoculation liquid prepares：

Strain is taken to 20 μ l from bacteria suspension, method of scoring is seeded on Sharpe solid medium, after cultivating 48 hours, picking 1mm or so bacterium colony 3, it is suspended in 1ml8.5g/L aseptic sodium chloride solution (0.85%), adjustment turbidity to 0.5 Maxwell Standard (1x10⁶~5x10⁶cfu/ml).Then RPMI1640 culture mediums 1 are used:20 dilutions, are further continued for 1:100 dilute, now bacterium Liquid concentration is 5x10²~2.5x10³Cfu/ml, as bacterium solution to be seeded.

(5) dilution of medicine：

Dilution medicine by drug dilution into concentration for 256mg/ml.Method is：The μ l of medicament storage liquid 15.128 are taken to add 614.872 μ l RPMI1640 culture mediums, 3 multiple holes are then done with every μ l of hole 200 and added in 96 orifice plate secondary series, then from this It is to be not added with that concentration, which proceeds by gradient dilution to the tenth hole, the final concentration of 128 μ g/ml to 0.5 μ g/ml of medicine, 11-holes, The negative control of medicine, the 12nd hole are the culture medium control for being not added with bacterium, and other edge holes add 300 μ l sterilized water.

(6) it is inoculated with：

Taking the inoculation μ l of bacterium solution 100, final bacterial concentration is 2.5 × 10 to having added in the hole of 100 μ l drug solutions²~ 1.25×10³cfu/ml。

(7) culture is observed with result：

After orifice plate is placed in into the incubation in 48 hours of 37 DEG C of incubators, bacterial concentration, bacteriostasis rate more than 80% are measured with ELIASA MIC of the least concentration as polypeptide, the MIC of the concentration of bacteriostasis rate 50% as Fluconazole.If fungi forms bacterium colony, with the naked eye The least concentration that observation does not grow bacterium is the MIC of medicine.

3. bacterium and fungi antibacterial experiment in vitro result

DP1-50 series polypeptide is shown in Table 3 to the minimal inhibitory concentration MIC value of above bacterium and fungi.Experiment repeats at least 3 Time, the MIC value shown in table is the median in all results.The polypeptide therein for being named as Indolicidin be and DP systems Row antibacterial peptide is the same as batch synthesis.

The MIC value testing result of the antibacterial peptide of table 3

Test result indicates that：By design the obtained polypeptide of screening than template peptide for staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, the common gramnegative bacterium and gram-positive bacterium that typhoid bacillus is representative, and with The fungi that Candida albicans represents generally has more preferable fungistatic effect.And above strain is antibacterium and antimycotic research Type culture, can deduce that aforementioned polypeptides also have to remaining bacterium and fungi and have certain effect, be a kind of the anti-of wide spectrum Bacterium polypeptide.

According to result above, it has been found that the significantly higher polypeptide of antibacterial activity is shown in table 4.

The preferable antibacterial peptide of the activity of table 4

Polypeptide title	Amino acid sequence	Sequence number
			DP2	VQWRIRVCVIRA	SEQ ID No.1
DP3	VQWRIRIAVIRA	SEQ ID No.2
			DP5	VQLRIRVCVIRR	SEQ ID No.3
DP7	VQWRIRVAVIRK	SEQ ID No.4
			DP8	VQLRIRVCVIRK	SEQ ID No.5
DP11	VQWRIRIAVIRK	SEQ ID No.6
			DP18	VQWRIRVCVIRR	SEQ ID No.7
DP19	VQWRIRICVIRA	SEQ ID No.8
			DP25	VQWRIRVAVIRA	SEQ ID No.9
DP27	VQWRIRIAVIRR	SEQ ID No.10
			DP29	VQWRIRICVIRR	SEQ ID No.11
DP35	VQWRIRVAVIRR	SEQ ID No.12
			DP36	VQWRIRICVIRK	SEQ ID No.13
DP39	VQWRIRVCVIRK	SEQ ID No.14
			DP43	VQLRIRVAVIRR	SEQ ID No.15
DP48	VQLRIRVAVIRK	SEQ ID No.16

The significantly higher polypeptide of these antibacterial activities has similar structure, and amino acid sequence can represent in following formula：

V-Q-W-R-I-R-X1-X2-V-I-R-X3 (SEQ ID No.17), wherein X1=I or V, X2=A or C, X3=A, R or K；And V-Q-L-R-I-R-V-X4-V-I-R-X5 (SEQ ID No.18), wherein X4=A or C, X5=R or K.

Wherein 4 antibacterial activities high polypeptide DP3,5,7,8 are subjected to further clinical separation strain (for different anti-again The persister of raw element) antibacterial effect checking.The source of clinical separation strain is that Southwest Hospital, Chongqing City burn research institute is clinical It is isolated.Every kind of bacterial strain takes 10 plants of clinical separation strain, and experiment repeats at least 3 times, and the MIC value shown in table 5 is all results In median, be the MIC scopes to all test strains in bracket.

5 preferable polypeptide of table is to being clinically separated the fungistatic effect of drug-fast bacteria

DP3, DP5, DP7, DP8 result show that its synthesis fungistatic effect to various clinically separated drug-fast bacteria is better than The effect of HH2 polypeptides, especially DP7 is more notable, and compared with HH2, its MIC value to various bacterial strains reduces 4 to 8 times.

3. remove the Experiment on therapy of neutrophil leucocyte mouse muscle bacterial infection model

(1) the previous day is infected with MHB culture medium shaking table culture staphylococcus aureuses (ATCC：29213), 220rpm, 37 DEG C, 18 hours.

(2) the OD values of infection same day survey bacterium solution estimate that bacterial concentration, 3000rpm5 minutes remove culture medium PBS weights after centrifuging Outstanding bacterium solution, is resuspended to bacterial concentration 1 × 10 after centrifuging again with PBS⁸CFU/ml。

(3) injection 0.1ml 29213 bacterium solutions, bacterial load 10 are surveyed in the left leg leg muscle of mouse back leg⁷CFU/ Point.

(4) mouse is put to death after infecting 24 hours, quantity takes centrifuge tube on demand, and 6 are added into each pipe and is ground with small Magnetic bead and 600 μ lPBS solution, weigh.The leg muscle of infection is taken, is placed in after tentatively shredding in the centrifuge tube weighed in advance, often Bar leg one is managed, and the weight then weighed and calculate muscle is recorded.

(5) centrifuge tube equipped with musculature is placed in into fastprep tissue grinders to be ground, parameter is arranged to most Greatly, 60sec is ground, twice.

(6) 20 μ l are taken to carry out waiting 10 times of dilutions from homogenate, with 10³, 10⁴, 10⁵Times dilution applies MHA solid mediums, In 37 DEG C of overnight incubations of bacteriological incubator.

(7) bacterium colony counting is carried out on solid medium, obtained count results are multiplied by after extension rate divided by organized weight Amount calculates the amount of bacteria that per gram of tissue contains.

4. Murine Model of Intraperitoneal Infection simultaneously takes ascites to test

(1) the previous day is tested with MHB activated strains staphylococcus aureuses (ATCC：33591).

(2) experimental day takes the bacterial strain after activation, 3600rpm centrifugation 5min, goes culture medium to be resuspended with physiological saline.

(3) continue centrifugation and remove supernatant, 200 μ l bacterium solutions, the bacterium after 200 μ l doubling dilution are taken after being resuspended with 10ml physiological saline Liquid, survey OD₆₃₀Absorbance, and stoste how many bacterium calculated.

(4) addition designated volume physiological saline is resuspended to prescribed concentration after supernatant is removed in centrifugation again.

(5) laboratory mice every group 6 is grouped at random, with 33591 infecting mouse abdominal cavities, every mouse peritoneal injection Bacterium solution 0.5ml.

(6) polypeptide drugs of the 1 hour pneumoretroperitoneum of infection to each prescribed concentration, 0.5ml/, every mouse of negative control group Intraperitoneal injection 0.5ml physiological saline.

(7) 24 hours backward mouse peritoneal injection 5ml physiological saline, soft belly, and put to death, disappeared with 75% alcohol Poison, abdominal cavity epithelium is cut off after 5min, an osculum is opened in abdominal cavity, as far as possible more ascites is therefrom drawn with 1ml syringes, is then shifted Mixed into sterile EP pipes.

(8) 20ml is taken, 10 times of gradient dilution is carried out with physiological saline, such as 10 times of dilution, 100 times, 1000 times, 10000 Times etc., and the μ l of bacterium solution 20 of three suitable concentration are taken, apply MHA flat boards, bacterium incubator overnight incubation.

(9) the flat board mouse clump count of 20~200 bacterium colonies of picking one and every milliliter in original 5ml ascites of bacterium is calculated Amount.

Fig. 2 is shown in the antibacterial peptide Experiment on therapy result of the mouse of staphylococcus aureus abdominal cavity infection.It is shown as in figure anti- Bacterium PEPD P7 and HH2 intraperitoneal administration concentration be respectively 20,40,60mg/kg when, bacterial content in 24 hours pneumoretroperitoneums, control sun Property medicine be 20mg/kg vancomycin (vanc).

Test result indicates that：When HH2 and DP7 are treated, in mouse peritoneal bacterium residual quantity and dosage exist dosage according to Sustainability, administration concentration is bigger, and therapeutic effect is better.During with concentration intraperitoneal administration, DP7 will have than template peptide HH2 preferably to be controlled Therapeutic effect, and 60mg/kg administrations DP7 has the effect that 20mg/kg is administered with positive controls vancomycin close.

The cell toxicity test of embodiment five, polypeptide of the present invention

1st, to the toxicity detection of red blood cell

(1) take anticoagulation to add the physiological saline of equivalent, mix, 2000rpm centrifugation 5min, remove supernatant.

(2) with PBS (the 150mM NaCl solutions of the sodium phosphate containing 9mM, PH7.0) by red blood cell washing 3 times, first 2 times 2000rpm centrifuges 5min, last 2000rpm centrifugation 10min, removes supernatant.

(3) diluted with PBS, obtain 20% (v/v) red blood cell/PBS solution, cell solution can use or Celsius in 4 immediately Degree preserves.

(4) 100 μ l polypeptide drugs are taken in 96 orifice plates, with the doubling dilution such as PBS (640mg/L, 320mg/L, 160mg/L, 80mg/L、40mg/L、20mg/L、10mg/L)。

(5) 20% RBC solution is taken with 1：20 are dissolved in PBS.Add 96 orifice plates, 100 μ l2% of positive control polysorbas20 Reach haemolysis, negative control adds 100 μ l PBS.37 DEG C are shaken incubation 1h.

(6) 3000rpm centrifuges 5min, takes the μ l of supernatant 160 to be added in 96 orifice plates, and hemoglobin is read at OD450nm Concentration.

(7) haemolysis ratio calculates：[(polypeptide treatment group A405-PBS treatment group A450)/(polysorbas20 treatment group A450-PBS Treatment group A450)] × 100%, haemolysis ratio is HC50 values in 50% peptide concentration.Antibacterial peptide is shown in erythrocyte splitting situation Fig. 3 a.Shown in figure as the rising of drug-treated concentration, the cleavage rate of red blood cell are in rising trend.During with concentration increase, DP7 Curve ascendant trend it is more slow, HH2 rising then faster, illustrates that cecropin D P7 is less than HH2 to the toxicity of red blood cell.

2nd, human normal Cytotoxicity is detected

(1) after cell dissociation in 293TD or human fibroblasts culture dish DMEM culture mediums will be used to be resuspended, counted, and it is dilute Release to 50000 cell/ml.

(2) 100 μ l cell suspensions are added in 96 orifice plates, 5000 cells/wells, it is small that cell culture incubator continues culture 20 When.

(3) take DP7 and HH2 polypeptide to store liquid (10mg/ml) 90 μ l to add in 610 μ lDEMM culture mediums, be made into 1₂₈₀The mg/L μ l of polypeptide DMEM solution 700, take 100 μ l, respectively the gently pressure-vaccum on two kinds of cell culture mediums of 96 orifice plates Do 1:1 two times of gradient dilutions (7 gradients, least concentration 10mg/L), every kind of cell does 3 multiple holes, and every kind of cell sets 3 again The blank controls that hole is acellular containing cell but are not added with compareing for polypeptide processing with 3 holes.Cell culture incubator is subsequently placed in continue to cultivate 24 hours.

(4) 10 μ l CCK-8 solution are added in all holes of 96 orifice plates, are placed in incubator processing 2h.

(5) because high concentration polypeptide can make part cell death produce precipitation, draw 70 μ l's after 3000rpm centrifugations 5min Supernatant measures OD450 value with ELIASA, then calculates cell viability into 96 orifice plates of cleaning：

Antibacterial peptide is shown in Fig. 3 to the toxicity profile of several normal human cells.It is several with HH2 or DP7 administration concentration increase The survival rate of normal cell gradually reduces.In normal MIC concentration ranges (8-32mg/L), poison of the antibacterial peptide to normal cell Property is little.When peptide concentration it is higher (>When 80mg/L), compared with HH2, DP7 is to fibroblast, erythrocyte, embryo kidney Cell is respectively provided with lower toxicity for the human normal cell of representative.

The antibacterial mechanisms desk study of embodiment six, polypeptide of the present invention

1st, same concentrations antibacterial peptide is with scanning electron microscopic observation after different time processing bacterium

(1) the staphylococcus aureus thalline isolated and purified is chosen in suitable fluid nutrient medium medicine bottle, concussion and cultivate 12h；

(2) centrifugation of 800 μ l bacterium solutions is drawn after cultivating, 3000rpm centrifugation 3min, removes supernatant, the 1 × PBS for adding 500 μ l is washed 2~3 times；

(3) 4% glutaraldehyde 1ml is added in precipitation, is fully mixed, 4 DEG C of standing 4h；

(4) 3000rpm centrifuges 3min, removes supernatant；1 × the PBS for adding 500 μ l is washed 2~3 times；

(5) the μ l of 2% glutaraldehyde 500 are slowly added in precipitation, are fully mixed, 4 degree of placement 1h；

(6) 3000rpm centrifuges 3min, removes supernatant；1 × the PBS for adding 500 μ l is washed 2~3 times；

(7) Gradient elution using ethanol, 20%, 50%, 80%, 100%；Dehydration 10min, 3000rpm centrifugations 3min every time；

(8) replace 100% ethanol 2~3 times with 100% tert-butyl alcohol, after the centrifugation of ethanol bacterium solution, remove supernatant, add 200 μ 4 degree of placement 30min of the l100% tert-butyl alcohols, are re-dissolved in appropriate 100% tert-butyl alcohol sample presentation.Bacteria suspension is dripped on masking foil to divide Dissipate, electron microscopic sample processing and observation are scanned after drying.As a result Fig. 4 a are seen, the visible increase with DP7 concentration in figure is golden yellow There is obvious fold in the staphylococcic cell membrane of color, and polypeptide processing is lower in higher concentrations many slight cracks occurs.

2nd, various concentrations antibacterial peptide is with transmission electron microscope observing after same time processing bacterium

(2) bacterium solution is taken after cultivating, prepares the 1 × 10 of 100 l⁸Cfu/ml or so bacterium solution 3500rpm is centrifuged 5 minutes, is gone Supernatant, the PBS for adding 100 l are washed three times.

(3) 4% glutaraldehyde 1ml is added in precipitation, is fully mixed, 4 degree stand 4h (time should try one's best extension, or overnight) Sample presentation to Institute of Analysis carries out electron microscopic sample processing and observation afterwards.Electron microscopic observation result is shown in Fig. 4 b.In figure it is visible with DP7 at The extension of time is managed, obvious rupture occurs in the cell membrane of staphylococcus aureus, and the floccule in background increases；Not 10 minutes groups of combined treatment are handled, barrier film when bacterium is divided is clear and stablizes, but barrier film is disturbed when handling more than 30 minutes Unrest simultaneously thickens, as shown in arrow in Fig. 4 c.

This test result indicates that：DP7 can be acted on by destroying the cell wall structure of microorganism to play restraining and sterilizing bacteria.This Simultaneously also primary explanation DP7 broad-spectrum antiseptics the reason for, most of mushrooms are respectively provided with the cell wall structure based on polysaccharide, for The bacteriostasis of cell membrane is equal to multiple-microorganism certain effect.And due to the structure between polypeptide of the present invention have compared with High similitude, thus also can primary explanation DP series polypeptide of the present invention there is the reason for broad spectrum antibiotic activity.

Claims

1. antibacterial peptide antibacterial activity Forecasting Methodology, it is characterised in that comprise the following steps：

Antibacterial peptide sequence and its antibacterial activity data known to step 1, acquisition, and the antibacterial activity data of all antibacterial peptides are adopted With antibacterial activity standardization conversion obtain antibacterial activity standardized value, randomly select a portion antibacterial peptide sequence and its Antibacterial activity standardized value as training set, using the antibacterial peptide sequence of remainder and its antibacterial activity standardized value as Test set；

Step 2, the antibacterial peptide sequence of training set is converted to be made up of position of the amino acid in antibacterial peptide and amino acid name Amino acid matrix；

Step 3, antibacterial activity standardized value and amino acid matrix according to training set, are calculated each amino acid each To the contribution margin of whole section of antibacterial peptide activity during position, forecast model is established according to the contribution margin；

Step 5, the linear relationship for calculating all antibacterial activity standardized values for predicting activity values and test set, compare its recurrence Coefficient, the maximum forecast model of at least two regression coefficients is selected, as standard prediction；

2. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 1, it is characterised in that in step 1, the antibacterial activity Standardizing the method to convert is：By in antibacterial activity data by quality how much come the IC50 in units of embodying the mg/L of active power Value is converted into that the unit of single polypeptide activity can be embodied as mole every liter of activity value, then by the activity value be converted to it is more big more Good and linear distribution antibacterial activity standardized value.

3. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 2, it is characterised in that the antibacterial activity standardization is changed The formula of calculation is：F (a)=- ln (a/K × 10^-3), wherein, f (a) is antibacterial activity standardized value, and a is the antibacterial peptide IC50 values, unit mg/L, K are the molecular weight of the antibacterial peptide, unit mol/kg.

4. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 3, it is characterised in that described according to training in step 3 The antibacterial activity standardized value of collection and amino acid matrix, are calculated each amino acid at each position to whole section of antibacterial peptide The method of contribution margin of activity is：Using formulaCalculated, wherein, n is the ammonia of the antibacterial peptide peptide chain Base acid number, i span is any 20 values, and each value represents a kind of amino acid in 20 kinds of natural amino acids, and j is Position from nitrogen end to carbon teminal of the i amino acid in the antibacterial peptide, span are 1 to the positive integer between n；Bj is anti-for this The constant coefficient of j positions amino acid in bacterium peptide, when there is amino acid the j positions, Bj 1, when the j positions are without amino acid, Bj is 0；Xij be i amino acid in antibacterial peptide during j positions to the contribution margin of whole section of antibacterial peptide activity.

5. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 4, it is characterised in that in step 3, if due to known f (a) when lazy weight enough solves all Xij, according to the property of amino acid, by representated by the most similar amino acid of property Xij is calculated after carrying out minimum merging.

6. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 5, it is characterised in that the property includes electrically charged property And hydrophily.

7. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 1, it is characterised in that described to randomly select in step 1 The antibacterial peptide sequence and its antibacterial activity standardized value of a portion refer to randomly select wherein 80% as training set~ 90% antibacterial peptide sequence and its antibacterial activity standardized value is as training set.

8. the antibacterial peptide antibacterial activity Forecasting Methodology as described in claim 1 or 2 or 3 or 4 or 5 or 6 or 7, it is characterised in that also Have steps of：

Step 7, the peptide sequence predicted needs, according to the electric charge size of each of which amino acid itself, calculate the antibacterial peptide Isoelectric point value, filter out the antibacterial peptide of suitable isoelectric point value.

9. antibacterial peptide antibacterial activity Forecasting Methodology as claimed in claim 8, it is characterised in that described properly to wait electricity in step 7 Point value is 11~13.