Polypeptide with antibacterial activity and application thereof
An antibacterial and antifungal technology, applied in the field of peptides, can solve the problems of complex antibacterial activity prediction of antibacterial peptides and lack of operability, and achieve the effect of clear principle, operability and repeatability
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Embodiment 1
[0045] Embodiment 1. Antibacterial peptide antibacterial activity prediction method and principle of the present invention
[0046] In the antibacterial peptide antibacterial activity prediction method of this example, it specifically includes the following steps:
[0047] Step 1. Obtain known antimicrobial peptide sequences and their antibacterial activity data, and use the antibacterial activity standardization conversion to obtain the antibacterial activity standardized value for all antibacterial peptide antibacterial activity data, and randomly select a part of the antibacterial peptide sequence and its antibacterial activity standardized value As a training set, the rest of the antimicrobial peptide sequences and their antibacterial activity normalized values were used as a test set.
[0048] In this step, the method for the standardized conversion of antibacterial activity can be: convert the IC50 value in the unit of mg / L that reflects the activity strength in the an...
Embodiment 2
[0093] Example 2. Establishment of prediction model and design and activity prediction of new antimicrobial peptides
[0094] 1. Obtain known antimicrobial peptide sequences and their antibacterial activity data for the establishment of prediction models. Among all the known sequence data, 80%-90% sequence data are randomly selected as the training set to build the prediction model, and the remaining 10%-20% sequence data are used as the test set to verify the prediction accuracy of the established model. In this modeling, 180 known antimicrobial peptides were used. The amino acid sequence and activity data were all derived from the patent document WO2008 / 022444, which is an antimicrobial peptide with 12 amino acids. 174 antimicrobial peptide sequences were randomly used for each training, and the remaining 14 antimicrobial peptide sequences were used for each test.
[0095] 2. Use antibacterial activity standardization method to standardize antibacterial activity data, and t...
Embodiment 3
[0101] Example three using the method of the present invention to predict and screen antimicrobial peptides
[0102] The present invention starts from the known polypeptide VQLRIRVAVIRA (HH2), uses a computer to randomly change, delete or add mutations at each amino acid residue site, each mutation is a natural amino acid, and obtains a polypeptide sequence of 1,324,256 polypeptides. Choose a peptide sequence library.
[0103] Using the above-mentioned candidate polypeptide sequence library including the template polypeptide to import the two most accurate prediction models established in Example 2 to perform calculations respectively to obtain the activity of each polypeptide, that is, to predict the antibacterial activity of the new polypeptide sequence. The antimicrobial peptides with high predictive activity by the two prediction models were selected as highly active antimicrobial peptides. The prediction models simultaneously calculated their properties such as isoelectri...
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