Coarse-Grained Free-Energy Simulations of Conformational State Transitions in an Adenosine 5′-Triphosphate-binding Cassette Exporter

ATP-binding cassette exporters transport many substrates out of cellular membranes via alternating between inward-facing and outward-facing conformations. Despite extensive research efforts over the past decades, understanding of the molecular mechanism remains elusive. As these large-scale conformational movements are global and collective, we have previously performed extensive coarse-grained molecular dynamics simulations of the potential of mean force along the conformational transition pathway [J. Phys. Chem. B 119, 1295(2015)]. However, the occluded conformational state, in which both the internal and external gate are closed, was not determined in the calculated free energy profile. In this work, we extend the above methods to the calculation of the free energy profile along the reaction coordinate, d1-d2, which are the COM distances between the two sides of the internal(d1)and the external gate(d2). The potential of mean force is thus obtained to identify the transition pathway, along which several outward-facing, inward-facing, and occluded state structures are predicted in good agreement with structural experiments. Our coarse-grained molecular dynamics free-energy simulations demonstrate that the internal gate is closed before the external gate is open during the inward-facing to outward-facing transition and vice versa during the inward-facing to outward-facing transition. Our results capture the unidirectional feature of substrate translocation via the exporter, which is functionally important in biology. This finding is different from the previous result, in which both the internal and external gates are open reported in an X-ray experiment [Proc. Natl. Acad. Sci. USA 104,19005(2007)]. Our study sheds light on the molecular mechanism of the state transitions in an ATP-binding cassette exporter.

Agent-Based Network Modeling Study of Immune Responses in Progression of Ulcerative Colitis

Ulcerative colitis, an inflammatory bowel disease, is a chronic inflammatory disorder that results in ulcers of the colon and rectum without known etiology. Ulcerative colitis causes a huge public health care burden particularly in developed countries. Many studies suggest that ulcerative colitis results from an abnormal immune response against components of cornrnensal rnicrobiota in genetically susceptible individuals. However, understanding of the disease mechanisms at cellular and molecular levels remains largely elusive. In this paper, a network model is developed based on our previous study and computer simulations are perforrned using an agent-based network modeling to elucidate the dynamics of immune response in ulcerative colitis progression. Our modeling study identifies several important positive feedback loops as a driving force for ulcerative colitis initiation and progression. The results demonstrate that although immune response in ulcerative colitis patients is dominated by anti-inflarnrnatory/regulatory cells such as alternatively activated rnacrophages and type II natural killer T cells, proinflarnrnatory cells including classically activated rnacrophages, T helper 1 and T helper 17 cells, and their secreted cytokines tumor necrosis factor-α, interleukin-12, interleukin-23, interleukin-17 and interferon-γ remain at certain levels （lower than those in Crohn＇s disease, another inflammatory bowel disease）. Long-terrn exposure to these proinflarnrnatory components, causes rnucosal tissue damage persistently, leading to ulcerative colitis. Our simulation results are qualitatively in agreement with clinical and laboratory measurements, offering novel insight into the disease mechanisms.

Network Modeling of Inammatory Dynamics Induced by Biomass Smoke Leading to Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease(COPD) is a chronic inflammatory disorder characterized by airflow obstruction and progressive damage of lung tissues. As currently more than 3 billion people use biomass fuel for cooking and heating worldwide, exposure to biomass smoke(BS) is recognized as a significant risk factor for COPD. Recent clinical data have shown that BS-COPD patients have a Th2-type inflammatory profile significantly different from that in COPD induced by cigarette smoke. As COPD is essentially proinflammatory,however, the mechanism underlying this Th2-type anti-inflammatory profile remains elusive.In this work, a network model is applied to study BS-induced inflammatory dynamics. The network model involves several positive feedback loops, activations of which are responsible for different mechanisms by which clinical phenotypes of COPD are produced. Our modeling study in this work has identified a subset of BS-COPD patients with a mixed M1-and Th2-type inflammatory profile. The model’s prediction is in good agreement with clinical experiments and our in silico knockout simulations have demonstrated several important network components that play an important role in the disease. Our modeling study provides novel insight into BS-COPD progression, offering a rationale for targeted therapy and personalized medicine for treatment of the disease in future.

Analytical modeling of the junction evolution in single-molecule break junctions: towards quantitative characterization of the time-dependent process

The conductance through single-molecule junctions characterized by the break junction techniques consists of the through-space tunneling and through-molecule tunneling conductance, and the existence of through-space tunneling between the electrodes makes the quantitative extraction of the intrinsic molecular signals of single-molecule junctions challenging. Here, we established an analytic model to describe the evolution of the conductance of a single molecule in break junction measurements. The experimental data for a series of oligo(aryleneethynylene) derivatives validate the proposed model, which provides a modeling insight into the conductance evolution for the opening process in a "real" break junction experiment. Further modulations revealed that the junction formation probability and rupture distance of the molecular junction, which reflect the junction stability, will significantly influence the amplitude and position of the obtained conductance peak. We further extend our model to a diffusion and a chemical reaction process, for which the simulation results show that the break junction technique offers a quantitative understanding of these time-dependent systems, suggesting the potential of break junction techniques in the quantitative characterization of physical and chemical processes at the single-molecule scale.