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PREC Track 1: Cal State LA - MolSSI PREC Pathway to Diversity Program

PREC 轨道 1：加州州立大学洛杉矶分校 - MolSSI PREC 多元化途径计划

基本信息

批准号：
2216858
负责人：
Olaseni Sode
金额：
$ 88.65万
依托单位：
California State L A University Auxiliary Services Inc.
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2216858&HistoricalAwards=false
关键词：
PREC Track Cal State LA

项目摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The Cal State LA-MolSSI PREC (Partnership for Research and Education in Chemistry) Pathway to Diversity Program is a collaboration between California State University, Los Angeles, a comprehensive public university and Hispanic Serving Institution, and the Molecular Software Sciences Institute (MolSSI) at Virginia Tech to incorporate machine learning (ML) techniques in molecular simulation research and develop innovative pedagogical materials to train early-stage undergraduate students in computational science. Cal State LA undergraduate and master’s students will participate year-round in mentored research and attend an annual workshop at MolSSI. Community college students will take part in mentored summer research experiences at Cal State LA alongside these students. Additionally, early-stage undergraduate students from local community colleges and Cal State LA will participate in an annual computational workshop taught by instructors from Cal State LA and MolSSI that emphasizes scientific programming and a variety of molecular simulation and ML techniques, as well as professional development activities. Overall, this PREC aims to make a significant contribution to the recruitment and training of the next generation of molecular simulation scientists who will require a deep understanding of both physical and chemical principles and computational techniques.Machine learning (ML) methods have transformed the fields of chemistry and molecular sciences in recent years, and will continue to do so in the future. The Cal State LA-MolSSI PREC (Partnership for Research and Education in Chemistry) will be organized around three thematic research thrusts that each use ML and physics-based simulation methods to create new computational models applicable to a range of chemical and biochemical phenomena. Thrust 1 will focus on developing ML approaches for computing the relative entropies and thermodynamic stabilities of molecular crystal polymorphs. Thrust 2 will aim to develop a hybrid physics-based and ML approach for predicting the relative binding free energies of small protein-ligand complexes. Thrust 3 will use ML to parametrize small molecule force fields that include a direct polarization electrostatic model and other advanced nonbonded potentials. The results of this research will help answer pressing questions in chemistry, biophysics, materials science, and pharmacology.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.

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。加州大学洛杉矶分校-MolSSI PREC（化学研究和教育伙伴关系）多样性之路计划是加州州立大学，洛杉矶，一所综合性公立大学和西班牙裔服务机构之间的合作，和弗吉尼亚理工大学的分子软件科学研究所（MolSSI），将机器学习（ML）技术纳入分子模拟研究，并开发创新的教学材料，以培训早期-在计算科学中培养本科生。加州州立大学洛杉矶分校的本科生和硕士生将全年参加指导研究，并参加MolSSI的年度研讨会。社区学院的学生将与这些学生一起参加加州州立大学洛杉矶分校的暑期研究活动。此外，来自当地社区学院和加州州立大学洛杉矶分校的早期本科生将参加由加州州立大学洛杉矶分校和MolSSI的讲师讲授的年度计算研讨会，该研讨会强调科学编程和各种分子模拟和ML技术，以及专业发展活动。总的来说，该PREC旨在为招募和培养下一代分子模拟科学家做出重大贡献，这些科学家需要深入了解物理和化学原理以及计算技术。机器学习（ML）方法近年来已经改变了化学和分子科学领域，并将在未来继续这样做。加州州立大学LA-MolSSI PREC（化学研究和教育合作伙伴关系）将围绕三个主题研究重点组织，每个主题研究重点都使用ML和基于物理的模拟方法来创建适用于一系列化学和生物化学现象的新计算模型。重点1将集中于发展ML方法计算相对熵和分子晶体多晶型物的热力学稳定性。推力2的目标是开发一种基于混合物理和ML的方法，用于预测小蛋白质-配体复合物的相对结合自由能。推力3将使用ML来参数化小分子力场，包括直接极化静电模型和其他先进的非键合势。这项研究的结果将有助于回答化学、生物物理学、材料科学和药理学方面的紧迫问题。该奖项反映了NSF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。