Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified βCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

中文翻译：

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环糊精：通过在计算机中确定亲和常数，为人工智能驱动的药物设计建立构建模块

环糊精 (CD) 是环状碳水化合物聚合物，在药物输送和工业应用方面具有重大前景。它们的有效性取决于它们以强亲和力和特异性封装目标分子的能力，但由于多种原因，准确量化这些系统中的亲和力具有挑战性。计算方法是对分析的特殊补充，因为它们可用于现有的和假设的分子，除了机械、动力学、动力学和热力学表征之外，还提供高分辨率结构。在这里，我们利用从引导元动力学模拟获得的平均力势 (PMF) 计算来表征四种不同修饰的 βCD 之间的 1:1 包合物，具有不同的类型、数量和取代位置，以及两个甾醇分子（胆固醇和 7 -酮胆固醇）。我们的方法通过每个系统的四次独立重复模拟和不同的后处理技术验证了再现性，为 CD-甾醇包合物的形成和稳定性提供了新的见解。观察到一种系统性的独特方向偏好，其中甾醇尾部从 CD 的较大面突出，并且观察到 CD 取代对结合的显着影响。值得注意的是，在模拟过程中仅对 CD 腔的宽面进行采样产生了与全腔采样相当的结合能，但时间更短且统计不确定性更低，这表明这是一种更有效的方法。我们的研究将计算方法与复杂的分子相互作用联系起来，为不同的应用提供了预测性 CD 设计。此外，所研究方法的高重现性、灵敏度和成本效益为大规模 CD-配体组合的广泛研究铺平了道路，从而实现了人工智能算法训练和自动化分子设计。