l o a d i n g
Project Contribution

Synthetic Products

The common diabetes drugs on the market are as follows: insulin, metformin, SGLT-2 inhibitor, α - glycosidase inhibitor, sulfonylurea insulin secretagogues, glinide insulin secretagogues, thiazolidinedione insulin sensitizers and DPP-4 inhibitors, smeglutide, etc[1]. In the field of diabetes treatment, the current trend is to develop drugs for a variety of pathological mechanisms, including stimulating insulin secretion, increasing peripheral glucose uptake and reducing glucose reabsorption. For example, GLP-1 receptor agonists and DPP-4 inhibitors are increasingly popular because of their remarkable effects in the treatment of diabetes, but their concerns about cardiovascular safety are also controversial[2]. With the rapid development of diabetes treatment, nearly 60 drugs have been approved by FDA, and nearly 100 additional hypoglycemic drugs are being evaluated in clinical trials. In addition to standard insulin therapy, there are also new drug combinations, such as those containing metformin, SGLT2 inhibitors, and DPP4 inhibitors, which have been widely used in the past decade[2]. When considering future treatment strategies and possible drug targets, factors such as patient compliance, ease of administration, weight gain and hypoglycemia risk need to be considered, not just the tolerance and efficacy of anti diabetes drugs. Compared to the above-mentioned drugs, P37 has significant glucose-lowering activity without side effects, and it has been shown to contribute to the regeneration of damaged pancreatic islets[3]. We chose Vglycin (a member of P37 family) for biosynthesis due to its promising potential as a treatment for diabetes.

Please refer to Table 1 for detailed information.

Number Drug type Comparative advantage
1 Biguanide drugs May cause patients to experience more adverse symptoms and reactions:
⚫ Lactic acidosis may occur;
⚫ Partial gastrointestinal reactions;
⚫ Make the patient's ketoacidosis more severe.
2 Sulfonylurea drugs May cause patients to experience more adverse symptoms and reactions:
⚫ Hypoglycemia;
⚫ Causing weight gain in patients.
3 Thiazolidinedione May cause patients to experience more adverse symptoms and reactions:
⚫ Lactic acidosis may occur;
⚫ Type 1 diabetes, cardiac insufficiency, abnormal liver function, etc. are forbidden.
4 Glipenem class drugs May cause patients to experience more adverse symptoms and reactions:
⚫ Hypoglycemia;
⚫ Gain weight;
⚫ Gastrointestinal symptoms;
⚫ Allergic reactions.
5 α-glucosidase inhibitor May cause patients to experience more adverse symptoms and reactions:
⚫ Gastrointestinal bloating;
⚫ Hyperactivity of bowel sounds.

Table 1 Defects of popular diabetes drugs on the market

At present, the preparation of hypoglycemic peptide P37 is extracted from soybean with physical and chemical methods. There are some shortcomings such as low extraction efficiency, high cost and big crops consumption, which seriously limit the production capacity of the drug. In view of the alarming growth of global diabetes cases, it is urgent to develop effective, safe, low-cost and high-yield innovative hypoglycemic drugs. Synthetic biology offers a pathway to create such agents through more efficient, scalable, and reproducible methods. According to our predictions and calculations, expressing and purifying the hypoglycemic peptide P37 using synthetic biology methods has a lower production cost, which is only half of that directly extracted from soybeans. For details, please refer to the business plan section in the entrepreneurial spirit. In addition, based on the production of the hypoglycemic peptide P37 expressed and extracted in the laboratory, we expect that after expanding production in the factory, its yield can reach more than twice that of directly extracted from soybeans. In the future, our team may also target other common diseases prevalent in specific populations, focusing on the development of biosynthetic therapeutics with enhanced safety profiles and minimal toxicity.

Part Contribution

We successfully engineered an optimized expression system for Vglycin using Pichia pastoris GS115 as the host. This system allows for high-efficiency production of Vglycin, overcoming the limitations associated with traditional extraction methods.We have also registered all the genetic sequences involved in Vglycin biosynthesis in Parts, providing a valuable resource for future research teams. This will not only facilitate the repeat of our work but also support other teams seeking to build upon it, either through genetic modification or by integrating our components into new systems. The following sections outline the respective downstream applications and potential derivatives.

Fusion protein

Nattokinase (NK) is an enzyme (protein) found in natto, a traditional Japanese dish made from fermented soybeans[4]. Also sold as a dietary supplement to promote heart health, nattokinase side effects are generally mild. Nattokinase may help to prevent heart attacks and improve heart health. Research shows it offers cardiovascular benefits, including: lowering blood pressure, lowering cholesterol, preventing blood clots, slowing atherosclerosis[5]. The introduction of NK and the expression of three tandem Vglycin fusions can to some extent prolong the size of fusion expression fragments, such as the detection of late stage proteins. Fusion protein is a novel protein formed by connecting two or more different proteins or protein fragments together through genetic engineering technology[6]. This technology can provide new strategies for treatment, improve the pharmacokinetic properties of drugs, enhance efficacy, reduce side effects, and play an important role in disease diagnosis and treatment. Fusion protein technology can be used to develop novel biopharmaceuticals, such as fusing cytokines, growth factors, or antibody fragments with Fc fragments to improve drug stability and half-life. Through fusion protein technology, efficient therapeutic drugs targeting specific disease targets can be developed, such as tumor targeted therapy drugs. Fusion proteins can more accurately target lesion sites, reduce damage to normal cells, help achieve precision medicine tailored to individual differences, improve treatment efficacy, and meet the treatment needs of different patients. Compared to traditional protein drugs, the long-term efficacy of fusion proteins may reduce the frequency of administration, thereby lowering overall medical costs. In vaccine development, fusion protein technology can be used to prepare multivalent vaccines, improving the immune efficacy and coverage of vaccines.

Acid sensitive sites

We connected three coding Vglycin genes during the plasmid design process. In the later stage of product enrichment, the peptides will be separated in an acidic solution at pH of 2-5, causing the acid sensitive sites automatically break to get the singlet of Vglycin. In the field of biomedical research, the discovery and study of acid sensitive sites help us understand various physiological and pathological processes, provide potential targets for targeted drug design, and contribute to the development of new therapies for the above-mentioned diseases. The research on acid sensitive sites has promoted the development of intelligent materials such as pH sensitive hydrogels[7]. These materials can respond to and change their properties in different pH environments, providing a new strategy for targeted delivery and controlled release of drugs. These research findings contribute to improving public awareness of related diseases, promoting health education and disease prevention. At the same time, biotechnology and drug development related to acid sensitive sites can also promote the development of the biopharmaceutical industry, create economic value, and improve social welfare.

Model Contribution

Our team used dry lab experiments to complement the features of the Vg element and its family proposed by our team, which can facilitate future iGEM teams in utilizing our components. Additionally, teams can use the methods proposed by our dry lab group to gain a preliminary understanding of an element, especially protein elements, thereby more efficiently referencing components from other iGEM teams.

Our dry lab group employed a series of bioinformatics methods to understand the properties and functions of the Vg element and its family, including the alignment of Vg homologous fragments, the construction of phylogenetic trees, the determination of secondary structures, the search for functional domains, the identification of phosphorylation sites, disulfide bonds, and conserved regions. The databases used by our team are open-source, and most of the software is free. We will introduce various algorithms, software, and some tools in detail below to assist future iGEM teams in completing the Model section.

For the determination of the ancestral sequence of Vg, we used the MEGAX software and cnsknowall for beautification. For sequence alignment and homologous sequence comparison, we used MEGAX with the Align by ClustalW feature to align the sequences. To construct the phylogenetic tree of Vg, we used the latest version of MEGAX software, employing the Maximum Likelihood algorithm in the Jones-Taylor-Thornton (JTT) model. However, the resulting tree is default to a horizontal layout, which can become very crowded with a large number of samples like our team. We used the free online tool cnsknowall (https://cnsknowall.com/) to draw the tree in a circular format, making it more visually appealing.

For the structural determination of Vg, we utilized AlphaFold3 to predict the three-dimensional structure due to its excellence in deep learning architecture and neural network applications, and we used pymol software for visualization. We also used pymol to complete the diagrams of single-point mutations and molecular docking complexes. We used the latest Jpred4 algorithm from the JNet series to predict the secondary structure of VgDue to its extensive and systematic learning through the use of Artificial Neural Network (ANN) algorithms to capture the relationship between protein three-dimensional structure and function, which is often overlooked in traditional sequence-based prediction tools[2]. In the NCBI database, we used the CD-Search tool in the Conserved Domain Database (CDD) to find functional domains. We hope that the databases and methods we share can provide some reference for subsequent teams.

Our dry lab group also compared proteins with amino acid sequences similar to the Vg element and screened them through the calculation of molecular docking free binding energy. Our team hopes that other teams can flexibly use our components, mutate them according to their team's needs, and conduct screening accordingly.

In terms of molecular docking, we divided the process into a preliminary screening and a refined screening, consisting of six algorithms in total. For the preliminary screening, we chose the chemScore algorithm because of its fast calculation speed, allowing for a broad and rapid initial screening. Subsequently, our team evaluated the stability of the protein-ligand complexes from the perspective of stability, and we selected the Hex scoring function of Discovery Studio software. This involved collecting and calculating the energy terms of various virtual docked protein-ligand complexes, which were then weighted and combined through the scoring function. We considered the Hex scoring function for its consideration of multiple interactions, especially in terms of hydrophobic effects, entropy effects, and electrostatic interactions, as well as its advantage of requiring less computational power, making it our second reference result for the preliminary screening. Finally, from the perspective of the speed at which the protein-ligand complex reaches binding energy equilibrium, we chose the Glide module within Glide Score, using the OPLS all-atom molecular force field. We utilized the all-atom model mechanics analysis of the OPLS force field, which simplifies some parameter ranges to maintain computational efficiency, thus serving as our third result.

For the refined screening, we first used blind protein-ligand docking to simulate molecular behavior in real biological environments. By learning from the molecular docking results, we analyzed the binding pocket of the receptor VDAC- to obtain an important parameter for the next step of specific docking. In the blind protein-ligand docking, we selected the Vina force field combined with the Autodocking algorithm. We used the Vina force field to create a mathematical expression of the system's energy dependence on the particle coordinates, calculating the total energy of the molecular system to assess the stability of different conformations, thereby obtaining the most stable three-dimensional structure and system energy. Finally, we utilized Autodocking's global optimization algorithm, which can search more extensively to find the optimal binding mode[3].

We then used the same MMGBSA calculation scheme, TIP4P water and solvent models for the GBSA solvent model, with different molecular force fields, namely the AMBER force field and the OPLS-AA force field. Depending on the force field chosen, the remaining two groups of algorithms were Prime MMGBSA and AMBER. The AMBER force field is a classic molecular force field with high accuracy, integrated from a large amount of experimental data and quantum calculation results[4]. The OPLS-AA force field borrows some torsional parameters from the AMBER force field and refits the quantum chemical energy of dipeptides to obtain parameters suitable for its all-atom model, which is more appropriate for our research on peptide-protein binding models. We hope that the molecular docking methods we used can serve as a reference for subsequent teams.

For more information, please refer to Modeling.

Social Contribution

We organized a diverse range of outreach activities. Firstly, we utilized university resources to host booths on campus, where we introduced our project to fellow students. Through these highly interactive booth activities, we not only successfully sparked students' interest, but also enhanced their understanding of synthetic biology and its applications in healthcare, agriculture, and environmental protection. According to feedback, the participants have gained a deeper understanding of synthetic biology and developed a strong interest in how to apply this knowledge to the real-world problems. Our efforts have laid foundation for the future scientific education and research, and promoted the development and application of synthetic biology technology.

We also held a community event to provide free blood glucose testing for the elderly. In this activity, we not only provided testing services, but also provided simple and easy to understand information about diabetes, and explained in detail the production and significance of hypoglycemic peptide P37 in the treatment of diabetes. Through free blood glucose detection, we help the elderly to know their blood glucose status timely, and enhance their awareness and prevention awareness of diabetes, a chronic disease. With the aging of the population, the incidence rate of chronic diseases such as diabetes is rising in the elderly. Through free blood glucose testing, we help the elderly to understand their blood glucose status in a timely manner, and enhance their awareness and prevention awareness of diabetes, a chronic disease. We can provide more considerate services for the elderly, help them cope with the application of health challenges in the medical and health field, and improve their awareness and acceptance of modern biotechnology. The diabetes information education we provide will help the elderly to better manage their own conditions and improve their self-management ability, which is crucial to control blood sugar and delay the occurrence and development of complications. At the same time, explaining the production and significance of the hypoglycemic peptide P37 can help the public understand synthetic biology. By promoting the application of synthetic biology in the treatment of diabetes, we have encouraged more innovation and research, which may lead to more effective and economical treatment methods and promote the development of medical and health fields.

In addition to these educational efforts, we collaborated with industry partners, engaging in in-depth discussions to better understand the biomanufacturing sector. This collaboration allowed us to explore the technical and logistical challenges of scaling up the fermentation of exogenous proteins from lab-scale experiments to industrial production. By translating scientific research achievements into practical production processes, it helps to transform and upgrade traditional manufacturing industries, improve production efficiency and product quality, while reducing environmental impact. With the development of the biomanufacturing industry, more high skilled jobs will be created, promoting employment in related fields and driving the development of upstream and downstream industrial chains. In the field of medicine, the application of biomanufacturing technology helps to develop personalized drugs and treatment methods, improve the efficiency and success rate of disease treatment, and thus enhance public health.

References

[1]. American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care 2021, 44 (Suppl. 1), S15–S33.

[2] Sterrett, J.J.; Bragg, S.; Weart, C.W. Type 2 Diabetes Medication Review. Am. J. Med. Sci. 2016, 351, 342–355.

[3] Kanghong Hu, Huizhong Huang, Hanluo Li, Yanhong Wei and Chenguang Yao. Legume-Derived Bioactive Peptides in Type 2 Diabetes: Opportunities and Challenges.

[4] Yuan L, Liangqi C, Xiyu T, Jinyao L. Biotechnology, Bioengineering and Applications of Bacillus Nattokinase. Biomolecules. 2022 Jul 13;12(7):980.

[5] Weng Y, Yao J, Sparks S, Wang KY. Nattokinase: An Oral Antithrombotic Agent for the Prevention of Cardiovascular Disease. Int J Mol Sci. 2017 Feb 28;18(3):523.

[6] Esposito D, Chatterjee DK. Enhancement of soluble protein expression through the use of fusion tags. Curr Opin Biotechnol. 2006 Aug;17(4):353-8.

[7] Thambi T, Jung JM, Lee DS. Recent strategies to develop pH-sensitive injectable hydrogels. Biomater Sci. 2023 Mar 14;11(6):1948-1961.