Vaccines are biological preparations that help to provide immunity against infectious diseases. They work by introducing a weakened or dead form of a disease-causing organism, or a piece of its genetic material, into the body. This triggers an immune response, which helps the body recognize and remember the pathogen if it infects the body again in the future. As a result, the body can quickly produce an immune response, which helps to prevent the disease from developing or reduces its severity.
Vaccines are enhanced by adjuvants designed using computers.
A Chinese research team has made a breakthrough in vaccine development by using computer-aided molecular design and machine learningMachine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.” data-gt-translate-attributes=”[{“attribute”:”data-cmtooltip”, “format”:”html”}]”>machine learning to create two innovative adjuvants, which are substances added to vaccines to enhance the immune response. These adjuvants, as reported in the journal Angewandte Chemie, have broad-spectrum capabilities and have been shown to significantly amplify the immune response to vaccines, leading to improved immunization against certain forms of cancer in animal models.
Adjuvants play a crucial role in enhancing and prolonging the impact of vaccine immunizations. For many years, aluminum salts have proven to be effective adjuvants. Another option is oil-in-water emulsions that stimulate pattern recognition receptors on immune cells. However, earlier versions of this type of adjuvant suffered from low efficacy or unpleasant side effects. The latest versions are both effective and well-tolerated but need to be tailored for every individual vaccine.
By using computer-aided molecular design and machine learning, Bing Yan, Sijin Liu, and their team at the Research Center for Eco-Environmental Sciences and the Capital Medical University in Beijing, as well as the University of Chinese Academy of Sciences in Beijing and Hangzhou, the Shandong First Medical University & Shandong Academy of Medical SciencesThe Academy of Medical Sciences is an organization that was established in the UK in 1998. It is one of the four UK National Academies, the others being the British Academy, the Royal Academy of Engineering, and the Royal Society.” data-gt-translate-attributes=”[{“attribute”:”data-cmtooltip”, “format”:”html”}]”>Academy of Medical Sciences, and the Guangzhou University, have now developed two novel adjuvants with broad-spectrum effectiveness that can significantly boost the immune response to vaccines.
The new adjuvants are designed to bind to toll-like receptors (TLR), a class of proteins used by dendritic cells to detect the characteristic molecular patterns of pathogens. If an “enemy” is recognized, the dendritic cell moves into a lymph node and “presents” its find to the T-cells. These activated T-cells then multiply and enlist further immune cells in the fight.
The team identified structural characteristics of the binding sites on human TLR and developed a collection, a substance library, with 46 different ligands that are compatible with the binding site. The special twist, in this case, is that these ligands are anchored to the surfaces of biocompatible gold nanoparticles. This causes them to be bound more easily by the TLR. Two of the ligands were found to be especially effective. Comprehensive in vitro, ex vivo, and in vivo studies demonstrated that they bind to several different TLRs and increase the activation of dendritic cells, presentation of antigens to T-cells, and their activation.
Mice treated with tumor-specific antigens plus one of these new adjuvants demonstrated strong immune responses that suppressed tumor growth and lung metastases after implantation of specific cancer cells.
Adjuvants further optimized through this method could reduce the problem of decreasing immunity for current vaccines and perhaps make booster vaccines unnecessary. Their use in immunotherapy to treat cancer is also highly promising.
Reference: “Computer-Aided Discovery of Potent Broad-Spectrum Vaccine Adjuvants” by Juan Ma, Shenqing Wang, Chuanfang Zhao, Xiliang Yan, Quanzhong Ren, Zheng Dong, Jiahuang Qiu, Yin Liu, Qing’e Shan, Ming Xu, Bing Yan and Sijin Liu, 23 February 2023, Angewandte Chemie International Edition.
DOI: 10.1002/anie.202301059
The study was funded by the National Natural Science Foundation of China, the Youth Innovation Promotion Association of Chinese Academy of Sciences, the National Key Research and Development Program of China, the Chinese Academy of Sciences, and The Pearl River Talent Recruitment Program.
Source: SciTechDaily
