CDS&E: D3SC: Developing A Molecular Mechanics Modeling Platform (MMMP) for Studying Molecular Interactions

匹兹堡大学的Junmei Wang获得了化学系化学理论，模型和计算方法项目的奖励，以开发一套计算工具并建立一个公开的平台，以方便用户研究生物分子系统。该奖项由高级网络基础设施办公室共同资助。 高质量的分子力学力场（MMFF）参数是成功地对各种分子系统进行建模和模拟的关键。然而，对分子建模不熟悉的用户可能会发现，在没有帮助的情况下获得高质量的MMFF参数和模型是一项艰巨的任务。 王博士和他的团队正在进行 研究开发新的软件工具，获得MMFF参数，建立高质量的模型，然后将它们集成到一个免费访问的分子力学建模平台（MMMP）。MMMP将帮助来自广泛学科的用户研究生物分子-配体相互作用的分子机制，并轻松准确有效地计算结合亲和力。来自药物发现社区的研究人员可以使用MMMP来提高发现候选药物的成功率，以对抗包括2019冠状病毒病（COVID-19）在内的各种疾病。 研究新型分子系统的一个主要瓶颈是一致的分子力学参数集的可用性，准确性和验证。王俊梅博士正在开发一个分子力学建模平台（MMMP），该平台集成了力场参数和残基拓扑结构，新颖的在线工具和应用程序编程接口（API），以打破瓶颈。他正在进行研究，以（1）改进原子类型和键类型感知算法，以处理任意小分子;（2）在蛋白质数据库中开发非标准氨基酸/核酸残基和共结晶配体的分子力学模型数据库，和其他化合物（3）开发和推进一个软件工具，弥合有效对接方法与需要更多计算机资源但更精确的基于自由能的方法之间的差距的亲和力;（4）建立一个物理的、有效的和高度可转移的电荷模型，该模型可以显著提高自由能计算的准确性;和（5）创建一个用户友好的图形用户界面（GUI），ClickFF，它允许用户生成能量曲线，比较力场，并通过几次点击优化选定的键合力场参数的力场参数。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Junmei Wang of The University of Pittsburgh is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop a set of computational tools and build a publicly available platform to facilitate users to study biomolecular systems. The award is cofunded by the Office of Advanced Cyberinfrastructure. High quality molecular mechanics force field (MMFF) parameters are critical to the successful modeling and simulations of various molecular systems. However, users naïve to molecular modeling may find it a daunting task to obtain high-quality MMFF parameters and models without assistance. Dr. Wang and his team are conducting research to develop novel software tools, derive MMFF parameters, build high-quality models, and then integrate them into a freely accessible Molecular Mechanics Modeling Platform (MMMP). MMMP will help users from a broad range of disciplines to study molecular mechanisms of biomolecule-ligand interactions and to calculate the binding affinity accurately and efficiently with ease. Researchers from the drug discovery community can employ MMMP to increase the success rate on the discovery of drug candidates for combating a variety of diseases including the Coronavirus Disease 2019 (COVID-19). A major bottleneck for studying novel molecular systems is the availability, accuracy and validation of consistent molecular mechanics parameter sets. Dr. Junmei Wang is developing a Molecular Mechanics Modeling Platform (MMMP) which integrates force field parameters and residue topologies, novel online tools, and Application Programming Interfaces (APIs) to break the bottleneck. He is conducting research to (1) improve the atom type and bond type perception algorithm to handle arbitrary small molecules; (2) develop molecular mechanics model databases for non-standard amino acid/nucleic acid residues and co-crystallized ligands in the Protein Data Bank, and other compounds (3) develop and advance a software tool coined re-Affinity to bridge the the gap between the efficient docking methods and more computer resource-demanding yet more accurate free energy-based methods; (4) develop a physical, efficient and highly transferrable charge model which can significantly improve the accuracy of free energy calculations; and (5) create a user-friendly Graphic User Interface (GUI), ClickFF, which allows users to generate energy profiles, compare force fields, and optimize force field parameters for selected bonded force field parameters with a few clicks.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.