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  1. Free, publicly-accessible full text available May 1, 2023
  2. Genetic information is encoded in the DNA double helix, which, in its physiological milieu, is characterized by the iconical Watson-Crick nucleo-base pairing. Recent NMR relaxation experiments revealed the transient presence of an alternative, Hoogsteen (HG) base pairing pattern in naked DNA duplexes, and estimated its relative stability and lifetime. In contrast with DNA, such structures were not observed in RNA duplexes. Understanding HG base pairing is important because the underlying "breathing" motion between the two conformations can significantly modulate protein binding. However, a detailed mechanistic insight into the transition pathways and kinetics is still missing. We performed enhanced sampling simulation (with combined metadynamics and adaptive force-bias method) and Markov state modeling to obtain accurate free energy, kinetics, and the intermediates in the transition pathway between Watson-Crick and HG base pairs for both naked B-DNA and A-RNA duplexes. The Markov state model constructed from our unbiased MD simulation data revealed previously unknown complex extrahelical intermediates in the seemingly simple process of base flipping in B-DNA. Extending our calculation to A-RNA, for which HG base pairing is not observed experimentally, resulted in relatively unstable, single-hydrogen-bonded, distorted Hoogsteen-like bases. Unlike B-DNA, the transition pathway primarily involved base paired and intrahelical intermediates with transitionmore »timescales much longer than that of B-DNA. The seemingly obvious flip-over reaction coordinate (i.e., the glycosidic torsion angle) is unable to resolve the intermediates. Instead, a multidimensional picture involving backbone dihedral angles and distance between hydrogen bond donor and acceptor atoms is required to gain insight into the molecular mechanism.« less
  3. To directly simulate rare events using atomistic molecular dynamics is a significant challenge in computational biophysics. Well-established enhanced-sampling techniques do exist to obtain the thermodynamic functions for such systems. However, developing methods for obtaining the kinetics of long timescale processes from simulation at atomic detail is comparatively less developed an area. Milestoning and the weighted ensemble (WE) method are two different stratification strategies; both have shown promise for computing long timescales of complex biomolecular processes. Nevertheless, both require a significant investment of computational resources. We have combined WE and milestoning to calculate observables in orders-of-magnitude less central processing unit and wall-clock time. Our weighted ensemble milestoning method (WEM) uses WE simulation to converge the transition probability and first passage times between milestones, followed by the utilization of the theoretical framework of milestoning to extract thermodynamic and kinetic properties of the entire process. We tested our method for a simple one-dimensional double-well potential, for an eleven-dimensional potential energy surface with energy barrier, and on the biomolecular model system alanine dipeptide. We were able to recover the free energy profiles, time correlation functions, and mean first passage times for barrier crossing events at a significantly small computational cost. WEM promises to extendmore »the applicability of molecular dynamics simulation to slow dynamics of large systems that are well beyond the scope of present day brute-force computations.« less
  4. Prior studies have identified the importance of resilience to success both in life and in the workplace. Resilience is also a valued professional skill for academic achievement and student retention in cognitively demanding disciplines such as engineering. However, only limited efforts have been made to characterize how resilience impacts the academic engagement, performance, and retention of engineering students. This study is the first in a program of studies that will map academic resilience, through the measurement of “protective factors” such as optimism and adaptability, with academic performance, as well as identify students at risk of dropping out of their engineering major. In this exploratory study, we examined differences in a group of engineering students on four resilience measures. Participants included 111 engineering students enrolled in six sections of statics taught by one instructor. Participants completed the Psychometric Project Resilience Scale (PPRS) survey online as well as the academic performance requirements for the course. The 50-item instrument surveyed students on five constructs indicative of resilience: adaptability; self-sufficiency; self-control; optimism; and persistence. Learning performance was based on three mid-examinations intended to assess students’ knowledge of the course. The psychometric properties of the instrument used to assess resilience factors were examined and studentmore »groups were compared on resilience and performance measures. Results of the study showed that transfer students seemed to struggle more with resilience and academic performance. Differences between gender and race groups in terms of resilience and academic performance were insignificant. Implications of study findings and direction for future studies of resilience among engineering students are discussed.« less