Mode-coupling theory (MCT) constitutes one of the few first-principles-based approaches to describe the physics of the glass transition, but the theory’s inherent approximations compromise its accuracy in the activated glassy regime. Here, we show that microscopic generalized mode-coupling theory (GMCT), a recently proposed hierarchical framework to systematically improve upon MCT, provides a promising pathway toward a more accurate first-principles description of glassy dynamics. We present a comprehensive numerical analysis for Percus–Yevick hard spheres by performing explicitly wavenumber- and time-dependent GMCT calculations up to sixth order. Specifically, we calculate the location of the critical point, the associated non-ergodicity parameters, and the time-dependent dynamics of the density correlators at both absolute and reduced packing fractions, and we test several universal scaling relations in the α- and β-relaxation regimes. It is found that higher-order GMCT can successfully remedy some of MCT’s pathologies, including an underestimation of the critical glass transition density and an overestimation of the hard-sphere fragility. Furthermore, we numerically demonstrate that the celebrated scaling laws of MCT are preserved in GMCT and that the predicted critical exponents manifestly improve as more levels are incorporated in the GMCT hierarchy. Although formally the GMCT equations should be solved up to infinite order to reach full convergence, our finite-order GMCT calculations unambiguously reveal a uniform convergence pattern for the dynamics. We thus argue that GMCT can provide a feasible and controlled means to bypass MCT’s main uncontrolled approximation, offering hope for the future development of a quantitative first-principles theory of the glass transition.
Generalized mode-coupling theory (GMCT) constitutes a systematically correctable, first-principles theory to study the dynamics of supercooled liquids and the glass transition. It is a hierarchical framework that, through the incorporation of increasingly many particle density correlations, can remedy some of the inherent limitations of the ideal mode-coupling theory (MCT). However, despite MCT’s limitations, the ideal theory also enjoys several remarkable successes, notably including the analytical scaling laws for the α- and β-relaxation dynamics. Here, we mathematically derive similar scaling laws for arbitrary-order multi-point density correlation functions obtained from GMCT under arbitrary mean-field closure levels. More specifically, we analytically derive the asymptotic and preasymptotic solutions for the long-time limits of multi-point density correlators, the critical dynamics with two power-law decays, the factorization scaling laws in the β-relaxation regime, and the time-density superposition principle in the α-relaxation regime. The two characteristic power-law-divergent relaxation times for the two-step decay and the non-trivial relation between their exponents are also obtained. The validity ranges of the leading-order scaling laws are also provided by considering the leading preasymptotic corrections. Furthermore, we test these solutions for the Percus–Yevick hard-sphere system. We demonstrate that GMCT preserves all the celebrated scaling laws of MCT while quantitatively improving the exponents, rendering the theory a promising candidate for an ultimately quantitative first-principles theory of glassy dynamics.
The emergence of glassy dynamics and the glass transition in dense disordered systems is still not fully understood theoretically. Mode-coupling theory (MCT) has shown to be effective in describing some of the non-trivial features of glass formation, but it cannot explain the full glassy phenomenology due to the strong approximations on which it is based. Generalized mode-coupling theory (GMCT) is a hierarchical extension of the theory, which is able to outclass MCT by carefully describing the dynamics of higher-order correlations in its generalized framework. Unfortunately, the theory has so far only been developed for single-component systems and as a result works poorly for highly polydisperse materials. In this paper, we solve this problem by developing GMCT for multi-component systems. We use it to predict the glassy dynamics of the binary Kob–Andersen Lennard-Jones mixture, as well as its purely repulsive Weeks–Chandler–Andersen analogue. Our results show that each additional level of the GMCT hierarchy gradually improves the predictive power of GMCT beyond its previous limit. This implies that our theory is able to harvest more information from the static correlations, thus being able to better understand the role of attraction in supercooled liquids from a first-principles perspective. Graphic abstract
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Membrane transporters, including two members: ATP-binding cassette (ABC) transporters and solute carrier (SLC) transporters are proteins that play important roles to facilitate molecules into and out of cells. Consequently, these transporters can be major determinants of the therapeutic efficacy, toxicity and pharmacokinetics of a variety of drugs. Considering the time and expense of bio-experiments taking, research should be driven by evaluation of efficacy and safety. Computational methods arise to be a complementary choice. In this article, we provide an overview of the contribution that computational methods made in transporters field in the past decades. At the beginning, we present a brief introduction about the structure and function of major members of two families in transporters. In the second part, we focus on widely used computational methods in different aspects of transporters research. In the absence of a high-resolution structure of most of transporters, homology modeling is a useful tool to interpret experimental data and potentially guide experimental studies. We summarize reported homology modeling in this review. Researches in computational methods cover major members of transporters and a variety of topics including the classification of substrates and/or inhibitors, prediction of protein-ligand interactions, constitution of binding pocket, phenotype of non-synonymous single-nucleotide polymorphisms, and the conformation analysis that try to explain the mechanism of action. As an example, one of the most important transporters P-gp is elaborated to explain the differences and advantages of various computational models. In the third part, the challenges of developing computational methods to get reliable prediction, as well as the potential future directions in transporter related modeling are discussed.
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