Department of Chemistry, New York University, New York, New York 10003, USA; email:
Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA.
Annu Rev Biophys. 2021 May 6;50:267-301. doi: 10.1146/annurev-biophys-091720-102019. Epub 2021 Feb 19.
We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy andscope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners.
我们重新评估了生物分子建模和模拟领域的进展，这是对我们在 2011 年发表的观点的跟进。通过回顾该领域生产力的衡量标准，并提供成功案例，我们强调了该领域的多产阶段，其短期预期被高估，长期影响被低估。这些成功包括对结构和机制的预测；对生物分子活性的新见解的产生；以及建模和实验之间的蓬勃合作，包括由建模驱动的实验。我们还讨论了领域练习和网络游戏对该领域进展的影响。总的来说，我们注意到生物分子建模社区在利用计算机能力方面取得了巨大的成功；力场的改进；以及新算法的开发和应用，特别是机器学习和人工智能。这些综合进展正在提高建模和模拟的准确性和范围，建立了一个典范的学科，其中实验和理论或模拟是完全的合作伙伴。
