Molecular Crystal Polymorph Prediction: High Accuracy at Lower Computational Cost

加州大学河滨分校的Gregory Beran教授获得了化学学部化学理论、模型和计算方法项目的奖励，以开发新的计算工具，促进三维晶体结构的预测。分子晶体结构的知识在制药和许多其他化学领域是必不可少的。相同分子的不同晶体排列或“多晶”可以表现出截然不同的性质。在过去，不良多态性的出现给患者和制药商造成了重大的药品召回和其他严重的问题。制药行业越来越多地采用晶体结构预测来补充他们的实验药物配方工作，并减少与多态性相关的问题的可能性。人们最近发现，目前广泛使用的理论模型在预测药物分子的晶体结构方面存在重大问题。该项目正在开发新的计算模型，以纠正这些弱点，提高预测晶体结构的可靠性。这个项目开发的软件将作为免费的开源软件发布给社区。在核心研究之外，Beran教授积极参与教学工作，帮助培养下一代科学家，其中很大一部分来自低收入，第一代和/或传统上代表性不足的少数民族人口统计数据。本研究分为三个部分。首先，正在开发新的计算实用的电子结构方法，用于模拟控制分子构象和晶体堆积的非共价相互作用，以识别良好的初始晶体结构。其次，将描述分子内相互作用的新电子结构方法的优势与用于模拟分子间相互作用的密度泛函理论的较低计算成本相结合的方法正在开发中，以改进药物化合物的晶体结构预测。最后，研究人员正在研究新的低成本近似方法来处理振动对晶体稳定性的影响，以便研究温度如何影响晶型稳定性。该项目正在开发新的计算模型，以纠正当前理论模型中的弱点，并提高预测晶体结构的可靠性。该项目开发的软件将作为免费的开源软件发布到社区。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Professor Gregory Beran of the University of California-Riverside is supported by an award from the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop new computational tools that will facilitate the prediction of three-dimensional crystal structures. Knowledge of molecular crystal structures is essential in pharmaceuticals and many other areas of chemistry. Different crystal packing arrangements, or “polymorphs,” of the same molecule can exhibit vastly different properties. The occurrences of undesirable polymorphs have caused major drug recalls and other serious problems for patients and pharmaceutical manufacturers in the past. The pharmaceutical industry increasingly employs crystal structure prediction to complement their experimental drug formulation efforts and to reduce the potential for polymorphism-related problems. It has recently been discovered that the current theoretical models in widespread use exhibit significant problems for predicting the crystal structures of drug molecules. This project is developing new computational models that correct these weaknesses and improve the reliability with which crystal structures can be predicted. Software developed by this project will be released to the community as free, open-sourcesoftware. Beyond the core research, Professor Beran is actively involved in pedagogical efforts to help train next-generation scientists, a large proportion of whom come from low-income, first-generation, and/or traditionally underrepresented minority demographics. This research occurs in three parts. First, new computationally-practical electronic structure methods for modeling the non-covalent interactions that govern molecular conformation and crystal packing are being developed to enable identification of good initial crystal structures. Second, an approach that combines the strengths of the new electronic structure methods for describing intramolecular interactions with the lower computational costs of density functional theory for modeling intermolecular interactions is being developed to enable improved crystal structure predictions in pharmaceutical compounds. Finally, new lower-cost approximations for handling the vibrational contributions to crystalline stability are being investigated to allow investigation of how temperature affects polymorph stability. This project is developing new computational models that correct weaknesses in current theoretical models and improve the reliability with which crystal structures can be predicted. Software developed by this project will be released to the community as free, open-source software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.