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Antibiotic resistance has become a major threat to global public health, causing approximately 5 million deaths each year. Among them, Gram-negative bacteria have been listed by the World Health Organization as a pathogen of priority concern due to their strong resistance. However, the research and development of new antibiotics has come to a standstill due to high costs and long cycles. Recently The team from the University of Pennsylvania published the title "Computational exploration of global venoms for antimicrobial" in Nature Communications (with an impact factor of 15.7) Research on "discovery with Venomics artificial intelligence" The team developed an artificial intelligence platform named Venomics AI, which extracted 386 structurally novel antimicrobial peptides from animal venoms worldwide. Among them, 91.4% of the experimentally verified molecules demonstrated strong antibacterial activity and achieved a pathogen clearance rate of 99.9% in mouse infection models. This study systematically analyzed 16,123 venom protein databases through the deep learning model APEX, generating 40.62 million Venom crypto peptides (VEPs). After multi-level screening, 386 candidate molecules with significantly different structures from known antimicrobial peptides were obtained, among which 58 were experimentally verified. The results showed that 53 (91.4%) were effective against drug-resistant bacteria; The mechanism of action is the destruction of bacterial membrane potential. The lead peptide reduced the bacterial load by three orders of magnitude in the mouse skin infection model. This research has opened up a new path for the development of drugs against drug-resistant bacteria.
AI Antimicrobial peptide design
I. Introduction to Basic Environment and Antimicrobial Peptides
Core objective: To clear environmental barriers for students without relevant programming or Linux background and establish a theoretical foundation for antimicrobial peptide design. The basic theory of antimicrobial peptides
The Importance and Application Prospects of antimicrobial peptides: Elaborate on the severe challenges of multi-drug resistant bacteria and the unique advantages of antimicrobial peptides as new antibacterial agents (rapid sterilization, less likely to develop drug resistance)
2. Definition, Classification and Mechanism of action of antimicrobial peptides: It is clear that antimicrobial peptides are short peptides produced by the innate immunity of organisms, with a focus on explaining the mechanism of action mainly involving the destruction of cell membranes, which is an important physical basis for their design.
3. Physicochemical properties of antimicrobial peptides: In-depth analysis of the key parameters determining their activity: Amphiphilicity: The spatial arrangement of hydrophilic and hydrophobic residues affects their interaction with the cell membrane. Net positive charge: Usually positive, it enables it to attract negatively charged bacterial membranes. Helical property: A common secondary structure that affects its ability to insert into membranes.
4.APD3 Database: Introduce its activity-based classification system and how to quickly search for relevant peptide sequences based on target microorganisms.
5.DRAMP Database: It emphasizes its comprehensiveness in including antimicrobial peptides, anti-cancer peptides, and antiviral peptides, as well as its rich annotation information (such as modifications and conformations).
6.CAMP Database: It focuses on introducing its integrated online prediction tools, which can serve as a preliminary verification reference for subsequent model results.
7. Design principles from natural to artificial: Analyze the structural characteristics of natural antimicrobial peptides and summarize the basic rules followed in artificial design, such as the specific amino acid composition ratio and charge range.
On-machine operation
1.Linux Basics Introduction: For students with a background in biology, this course explains essential commands. Such as using cd and ls for navigation and viewing directories; chmod manages file permissions; grep and pip are used for text search and package installation.
2. Installation and Configuration of Conda and Jupyter Notebook: Demonstrate how to create an independent Python environment using Conda to avoid package conflicts. And configure Jupyter Notebook to run in this environment.
3. Basic Usage of Jupyter Notebook: Guide students to create their first Notebook, mix and use Markdown to write experimental notes and code blocks to execute Python commands, and form a good habit of repeatable research.
This chapter is not completed. You can click on it later：
https://mp.weixin.qq.com/s/PiBCqatIK3mhIBDFBsPStw
Source: Advances in Nanomedicine
