Molecular Dynamic Simulation on Flexible Binding of Broad-specific Neutralizing Antibody CDR3 with Avian Influenza Virus Receptor Binding Site (RBS) and Structure-based Rational Design of RBS-binding

流感病毒以其持续变异能力和在全球范围内的广泛传播，引发人类呼吸道传染病，严重威胁着人类的健康，是全球公共卫生的重大问题。每年都有大量的人感染流感病毒，或因季节性流感和流感大爆发而死亡。其中，禽流感病毒的威胁，尤其是H5N1型和H7N9型等高致病性禽流感病毒已逐渐成为对人类最具威胁的传染病之一。由于流感病毒的高度变异性，现有的疫苗研发策略需要每年更新流行株，而传统抗病毒药物的治疗效果也会受到影响，因此开发新型抗流感药物是流感防治的迫切需要。 流感病毒包膜外的血凝素蛋白是中和抗体识别的主要靶标，介导流感病毒与宿主细胞结合。血凝素蛋白头部区的受体结合域具有一个凹槽形结构，其保守性位点能与唾液酸受体...Influenza virus evolve and circulate continuesly and widely in the global, causing human respiratory disease which is a serious threat to human health, and it has become a major global public health problem. Every year a large number of people infected with influenza virus, or die from seasonal flu and influenza pandemic. Among them, the threat of avian influenza virus, especially the H5N1 and H7N...学位：医学硕士院系专业：公共卫生学院_转化医学学号：3262014115057

Progress and Application on in silico Prediction of Aggregation of Therapeutic Antibodies

由于具有靶向性高、不良反应少等优势,治疗性抗体已成为生物技术产业的重要研究领域。诸多重大疾病如肿瘤、自身免疫性疾病、心血管疾病、糖尿病、老年性痴; 呆等都有望用抗体药物进行治疗,以抗体为基础的分子设计和靶向治疗也是近年生物医药产业的最大增长点。但目前在抗体药物的研发和生产过程中仍然存在一些问; 题亟待解决。其中,抗体分子聚集是影响药物成药性的关键因素之一,筛选和设计稳定高效的抗体药物是药物研发早期阶段的重要目标。相较于传统筛选方法,应用; 计算机模拟技术预测蛋白质的聚集倾向为抗体药物的稳定性和高度可溶性提供了重要参考信息,将有效地提高药物的研发效率。本文重点介绍了已成功应用于治疗性; 抗体领域的聚集预测方法,并对这些方法的原理与应用前景进行总结,为基于计算机模拟的抗体研究提供参考。Due to precise specificities and low side-effects, therapeutic; antibodies are becoming more and more important in the biotechnology; industry. With promising application prospects in clinical practice,; therapeutic antibodies are expected to treat diseases like cancers,; autoimmune diseases, cardiovascular diseases, diabetes, Alzheimer's; diseases and so on. Antibody-based molecular design and targeted therapy; is the fastest growing field of biomedical industry in recent years.; However, there are still challenges for the development and production; process of therapeutic antibodies. Among these challenges, antibody; aggregation is one of the key determinants for antibody. Screening and; rational design of potent antibody candidates without obvious; aggregation propensity are critical in the earlier stage of antibody; development. Comparing to conventional methods, in silico prediction of; protein aggregation can provide key information on the stability and; solubility of the antibody drugs and hence greatly improve the; efficiency of drug development. Here, we summarize the approaches into; sequence-based method and structure-based method. The former makes; predictions from amino acid sequence only, while the latter approaches; predict aggregation by calculating interactions on structures model.; Furthermore, we illustrate their principles and prospects in therapeutic; antibodies development which might provide paradigmatic reference for; computation-based antibody design in the future. Depending on the; different advantages of these approaches, a right choice could be; potentially useful in the rational design of therapeutic candidates with; not only high potency and specificity but also improved stability and; solubility.国家自然科学基金; 福建省自然基