Osteoporosis is a common bone degenerative disease that seriously affects the lives of people with osteoporosis. Cannabinoid receptor subtype 2(CB2) as a potential target of osteopathy, is expected to improve the quality of life of osteoporosis patients and provide a new avenue for osteoporosis treatment. This study aims to utilize the CB2 structure for high-throughput peptide screening and validation of its osteogenic activity. We have constructed a database of bioactive peptides and a virtual peptide library for tripeptide screening. Use the AutoDock and Glide Methods for Docking to screen peptides with strong CB2 binding. Subsequently, the secondary docking is carried out using AutoDock Vina. We selected the top 10 bioactive peptides for further study.Validating the agonistic activity of the screened peptides agoinst CB2 by measuring cAMP accumulation in HEK293 cells expressing CB2, we found that three peptides (APOCB2R3, APOCB2R4, APOCB2R7) significantly activated CB2. Then, we evaluated the regulatory effect of the screened compounds on bone metabolism in different osteoblasts and found that the peptides had osteogenic activity. In summary, combined with virtual screening and cell-based experiments, we successfully identified potential peptides with CB2 agonist and osteogenic activity, providing a new avenue for the development of osteoporosis drugs.
Target-based drug development plays an important role in disease research. In this study, CB2 was selected as our research target. Based on the virtual screening strategy, we found candidate peptides with good docking with CB2 from the bioactive peptide library we collected and constructed. Next, we further validated the osteotropic activity of these candidate peptides through cell experiments. Overall, this study provides potential peptide candidates for the treatment of osteoporotic diseases.
Osteoporosis is a common bone disorder characterized by decreased bone mineral density and deterioration of bone microstructure, leading to an increased risk of fracture and a reduced quality of life. At present, pharmacological interventions are the mainstay of osteoporosis, such as denosumab, which inhibits bone resorption in osteoclasts, or teriparatide, which promotes bone formation in osteoblasts. Although there are medications that can be used to reduce osteoporosis symptoms, such as bisphosphonates, estrogen receptor modulators, and parathyroid analogues, these drugs can also have serious adverse effects.
Then the development of new therapeutic targets for osteoporosis is necessary. Cannabinoid receptor subtype 2 (CB2) is a seven-transmembrane receptor that is highly expressed in the immune system and bone marrow, and numerous studies have shown that the activation of CB2 receptor can enhance the activity of osteoblasts, thereby promoting bone formation. Therefore, CB2 has become a promising target in bone metabolism. At present, the development of CB2 small molecule agonists has entered the clinical stage, but all of them have failed to reach the market due to their toxic effects. Preclinical studies have shown the role of CB2 activation in promoting osteoblast activity and bone formation, highlighting its potential as a therapeutic target for osteoporosis. However, the identification of CB2-specific agonists with good pharmacological properties remains a challenge due to their toxicity concerns.
Bioactive peptides are natural biologics consisting of amino acids shorter than 50 and are able to bind to important proteins such as G protein-coupled receptors and ion channels. These peptides exert key effects on human physiological activities, such as neurotransmission, antimicrobial properties, ion channel regulation, growth factor activity, and hormone regulation. Compared with macromolecule biopharmaceuticals such as proteins, bioactive peptides have low molecular weights, are easy to synthesize, and require relatively low cost. Compared with traditional small molecule drugs, which are more likely to produce off-target effects due to their smaller molecular weights, which may lead to adverse reactions, peptide drugs have higher selectivity and safety in targeting the therapeutic site.
In recent years, virtual screening has been combined with structural biology techniques to become a new strategy for drug discovery. This method also provides a pathway for the rapid identification and characterization of bioactive peptides targeting specific receptors. In this context, based on the CB2 target structure and virtual screening strategy, this study developed an active peptide targeting CB2, and verified the osteogenic activity of the preliminary CB2 agonist, so as to provide a new peptide candidate for the treatment of osteoporosis.
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Existing peptide databases tend to focus on certain properties of peptides, such as antimicrobial properties, anticancer properties, antihypertensive properties, toxicity, etc. After extensive and in-depth research, all bioactive peptide databases from 2000 to 2020 are collected, consolidated, classified, and weighted. Finally, we collected a total of 26 bioactive peptide databases, grouped by function. Table 1 shows the information for each database. In the end, a total of 118,663
In this study, we combined methods such as computer technology, virtual screening, and cellular and molecular biology to find new CB2 agonists. Combined with the clinical needs of drug target development, the virtual screening strategy is used to screen target drugs, which is highly innovative and practical. In total, we performed three different methods of virtual screening docking of the database based on the CB2 structure to obtain peptide molecules with CB2 agonists. According to the
A total of 26 bioactive peptide databases were collected by searching for keywords such as “peptide database” and “bioactive peptide database”. Peptide sequence-related data was retrieved from the Uniform Resource Location(URL) of these 26 databases. Sequences containing special features are removed and redundant reductions are performed on all amino acid sequences. After these steps, a total of 118,663 unique amino acid sequences were obtained. Bioactive peptide databases are listed in Table 1.
Article revision, typesetting and journal selection for submission were undertaken by Zhiheng Chen and Ying Yu. Data collection (e.g., literature) and organization is the responsibility of Zehua Lu, Ruoxi Wang and Junqi Guo. The overall framework and direction is guided by Xiaogang Wang.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
This study was supported by Foundation A (No. 82350003 ,China). Tanks for National Natural Science Foundation Projects of China. Note:Zhiheng Chen and Ying Yu have equal contributions to this article.
