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Toward Improved Force-Field Accuracy through Sensitivity Analysis of Host-Guest Binding Thermodynamics

机译:通过主客体结合热力学的敏感性分析来提高力场精度

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摘要

Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by non-optimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery.
机译:改进原子计算机模型预测非共价结合热力学的能力对于成功的基于结构的药物设计至关重要,并且此类计算的准确性仍然受到非最佳力场参数的限制。理想情况下,将蛋白质-配体亲和力数据整合到力场参数化中,但这将效率低下且成本高昂。现在,我们证明了灵敏度分析可用于有效地调节水性宿主-客体系统的Lennard-Jones参数,以提高结合焓的精确计算。这些结果突显了有望全面使用量热宿主-客体结合数据以及现有的验证数据集,以改善用于模拟非共价结合的力场参数,最终目的是使蛋白质-配体建模更加准确,从而加快药物发现。

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