Calcium-dependent insulin resistance in hepatocytes: mathematical model.

Hepatocyte insulin resistance is one of the early factors of developing type II diabetes. If insulin resistance is treated early, type II diabetes could be prevented. In recent years, scientists have been conducting extensive research on the underlying issues on a cellular and molecular level. It was found that the modulation of IP3-receptors, the mitochondrial ability to form the mitochondria-associated membranes (MAMs) and the endoplasmic reticulum stress during Ca2+ signaling play a key role in hepatocyte being able to maintain euglycemia and provide metabolic flexibility. However, researchers cannot agree on what factor is the key one in resulting in insulin resistance. In this work, we propose a mathematical model of Ca2+ signaling. We included in the model all the major contributors of a proper Ca2+ signaling during both the fasting and the postprandial state. Our modeling results are in good agreement with available experimental data. The analysis of modeling results suggests that MAMs dysfunction alone cannot result in abnormal Ca2+ signaling and the wrong modulation of IP3-receptors is a more definite reason. However, both the MAMs dysfunction and the IP3 signaling dysregulation combined can lead to a robust Ca2+ signal and improper glucose release. In addition, our model results suggest a strong dependence of Ca2+ oscillations pattern on morphological characteristics of the ER and the mitochondria.

COBRAMM 2.0 - A software interface for tailoring molecular electronic structure calculations and running nanoscale (QM/MM) simulations.

We present a new version of the simulation software COBRAMM, a program package interfacing widely known commercial and academic software for molecular modeling. It allows a problem-driven tailoring of computational chemistry simulations with effortless ground and excited-state electronic structure computations. Calculations can be executed within a pure QM or combined quantum mechanical/molecular mechanical (QM/MM) framework, bridging from the atomistic to the nanoscale. The user can perform all necessary steps to simulate ground state and photoreactions in vacuum, complex biopolymer, or solvent environments. Starting from ground-state optimization, reaction path computations, initial conditions sampling, spectroscopy simulation, and photodynamics with deactivation events, COBRAMM is designed to assist in characterization and analysis of complex molecular materials and their properties. Interpretation of recorded spectra range from steady-state to time-resolved measurements. Various tools help the user to set up the system of interest and analyze the results.

New Perspectives on an Old Issue: A Comparative MS-CASPT2 and OM2-MRCI Study of Polyenes and Protonated Schiff Bases.

Polyenic systems are involved in light perception of numerous living organisms. Although a π-conjugated backbone is a common feature of all polyenes, their photophysics may vary. We provide a comparative quantum mechanical study of low-lying S1 and S2 excited states in short (3-5 double bonds) symmetric all-trans linear polyenes and corresponding protonated Schiff bases. In our investigation, we use the well-established ab initio multireference CASPT2 approach and benchmark the efficient semiempirical OM2-MRCI approach against it. For all protonated Schiff bases, MS-CASPT2 results in two distinct S1 minima with inverted and noninverted bond length pattern, respectively. We find that OM2-MRCI is a computationally affordable and reliable alternative to MS-CASPT2 for investigations of polyenic systems, particularly when highly demanding calculations (e.g. excited-state dynamics) need to be performed.

A model of fibroblast motility on substrates with different rigidities.

To function efficiently in the body, the biological cells must have the ability to sense the external environment. Mechanosensitivity toward the extracellular matrix was identified as one of the sensing mechanisms affecting cell behavior. It was shown experimentally that a fibroblast cell prefers locomoting over the stiffer substrate when given a choice between a softer and a stiffer substrate. In this article, we develop a discrete model of fibroblast motility with substrate-rigidity sensing. Our model allows us to understand the interplay between the cell-substrate sensing and the cell biomechanics. The model cell exhibits experimentally observed substrate rigidity sensing, which allows us to gain additional insights into the cell mechanosensitivity.