一种用于预测阻力突变逐步积累中最可能发生的进化轨迹的计算方法
Ruth Charlotte Eccleston1, Emilia Manko1, Susana Campino1
1Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
eLife
|December 22, 2023
概括
像Plasmodium这样的病原体中的耐药性通过突变进化,而表皮病则影响耐药性途径. 结合 afinity 准确地预测了抗性和突变顺序,与突变频率数据保持一致.
科学领域:
- 分子进化是分子进化的过程.
- 药物耐药性 药物耐药性 药物耐药性
- 开发抗疟疾药物的开发工作.
背景情况:
- 病原体的耐药性通常涉及逐步积累的突变与非添加的健身效应 (epistasis).
- 在Plasmodium falciparum (Pf) 和Plasmodium vivax (Pv) 中的二叶酸还原酶 (DHFR) 基因突变是抗甲胺耐药性的关键.
- 在DHFR突变之间的表观相互作用塑造了高耐药性的进化轨迹.
研究的目的:
- 模拟和预测Plasmodium中耐药性的进化途径.
- 研究结合亲和和表皮病在抗性突变的固定顺序中的作用.
- 评估突变频率数据在推断进化轨迹中的有用性.
主要方法:
- 使用Rosetta Flex ddG预测参数化的模型进行分子进化模拟.
- 基于降低目标药物结合亲和力的建模选择.
- 模拟路径与实验IC50值和来自隔离物的突变频率数据的比较.
主要成果:
- 模拟的进化途径与实验确定的甲胺耐药性途径有很强的一致性.
- 结合性亲和力被发现是抗性的强有力的预测因素,而结合性亲和力的表现作用影响了突变固定顺序.
- 从突变频率数据推断出的进化途径与模型预测和实验发现非常相匹配.
结论:
- 药物结合亲和力是抗疟疾耐药性的强有力的预测因素.
- 表观症显著影响抗性突变获得的顺序.
- 人口突变频率数据可以有效地推断病原体的进化途径.
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