生物信息学 ——药物生物信息学 李霞主编

wumingshi

药物生物信息学

PHARMACEUTICAL BIOINFORMATICS

人体疾病的发生主要是各种原因造成的代谢途径失衡或调节代谢速度的信号通路失衡，药物的主要作用模式是直接或间接调整这些疾病相关物质的稳态水平。目前已有很多免费数据库提供已知的药物靶点及其配体类药物的数据及药物毒副作用的数据。发掘和确认靶点是发现新药的第一步。分析疾病相关的基因组和基因型数据、表达序列特征、反向对接等策略可用于发掘新靶点，并采用多种技术多方面验证确认靶点有效性。提取小分子药物结构特征用于建立其药理活性与结构特征的联系是药物发现的重要方向；基于分子对接判断亲和力、基于ADME-tox预测成药性是快速低成本发现有效新药的重要策略。对蛋白质类大分子药物，预测其免疫原性和对应抗原表位是提高其成药性的重要步骤；基于单抗中结构域保持、结构组装和化学修饰进行结构优化是提高治疗性单抗药理活性的重要手段。基于基因型的关联分析，是预测药效和安全性的有效手段。在药物发现的过程中需要综合利用生物信息学技术。

Summary

Disorders of metabolic and signaling pathways cause common diseases; drugs act to initiate desired or repair disordered pathways. Many databases are available on targets and ligands, adverse activities of common drugs. Discovering and validating targets are generally required for discovering drugs. Analyses of genomic data and genotypes, expression sequence profiles, reversal docking are useful to mine targets for comprehensive validation. Of small ligand drugs, extraction and correlation of their structural properties with pharmacological actions play important roles in their discovery; virtual screening based on affinities predicted via docking and ADME-tox effects help enhance pharmaceutical significance of candidate ligands. Of protein drugs, predictions of their immunogenicity and epitopes help enhance their pharmaceutical values. Optimization of McAb structures based on reservation and assembly of domains besides chemical modification enhance their pharmacological actions. Correlation analyses based on genotypes help predict potency and safety. Drug discovery requires integrated platform of bioinformatics.

（廖
飞
茆灿泉
魏冬青
王靖方）

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