Molecular recognition is of paramount interest in many applications. Here we investigate a series of host-guest systems previously used in the SAMPL4 blind challenge by using molecular simualtions and the AMOEBA polarizable force field. The free energy results computed by Bennett’s acceptance ratio (BAR) method using the AMOEBA polarizable force field ranked favorably among the entries submitted to the SAMPL4 host-guest competition [Muddana et al., J. Comput.-Aided Mol. Des., 2014, 28, 305-317.]. In this work we conduct an in-depth analysis of the AMOEBA force-field host-guest binding thermodynamics by using both BAR and the orthogonal space random walk (OSRW) methods. The binding entropy-enthalpy contributions are analyzed for each host-guest system. For systems of inordinate binding entropy-enthalpy values, we further examine the hydrogen bonding patterns and configurational entropy contribution. The binding mechanism of this series of host-guest systems varies from ligand to ligand, driven by enthalpy and/or entropy changes. Convergence of BAR and OSRW binding free energy methods are discussed. Ultimately, this work illustrates the value of molecular modelling and advanced force fields for the exploration and interpretation of binding thermodynamics.

NA Laryngoscope, 127:1525-1530, 2017.

NA Laryngoscope, 127:E253-E257, 2017.

This study examines the influence of various individual demographic and risk factors on the use of unscheduled healthcare (emergency and inpatient visits) among pediatric outpatients with asthma over three retrospective timeframes (12, 18, and 24 months) at an academic health center. Out of a total of 410 children who visited an academic medical center for asthma outpatient care between 2019 and 2020, 105 (26%) were users of unscheduled healthcare for childhood asthma over the prior 12 months, 131 (32%) over the prior 18 months, and 147 (36%) over the prior 24 months. multiple logistic regression (MLR) analysis of the effect of individual risk factors revealed that asthma severity, age of child, and clinic no-shows were statistically significant predictors of unscheduled healthcare use for childhood asthma. Children with higher levels of asthma severity were significantly more likely to use unscheduled healthcare (compared to children with lower levels of asthma severity) across all three timeframes. Likewise, children with three to four clinic no-shows were significantly more likely to use unscheduled healthcare compared to children with zero clinic no-shows in the short term (12 and 18 months). In contrast, older children were significantly less likely to use unscheduled healthcare use compared to younger children in the longer term (24 months). By virtue of its scope and design, this study provides a foundation for addressing a need identified in the literature for short- and long-term strategies for improving supported self-management and reducing unscheduled healthcare use for childhood asthma at the patient, provider, and organizational levels, e.g., (1) implementing telehealth services for asthma outpatient care to reduce clinic no-shows across all levels of asthma severity in the short term; (2) developing a provider–patient partnership to enable patient-centered asthma control among younger children with higher asthma severity in the long term; and (3) identifying hospital–community linkages to address social risk factors influencing clinic no-shows and unscheduled healthcare use among younger children with higher asthma severity in the long term.