Faculty Publications
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Item Multi-ENPS simulator support tool with automatic file inter-conversion and multi-membrane execution(Elsevier Ireland Ltd, 2020) Raghavan, S.; Gangadhar, Y.; Pattar, V.; Chandrasekaran, K.P System or Membrane Computing is an unconventional and natural computing model inspired by the functioning of a living cell. This model has an inherently parallel structure. There are several variants of P System developed, each of which has a different application. One of the variants, Enzymatic Numerical P System (ENPS), has primarily been developed to be used with numerical values (as in economics) and thus has vast applications. For realizing ENPS there are several tools available, primarily based on Java and Python, each of which has a different input format. Currently, there is no tool which allows the user to execute ENPS using both the simulators on the same platform, the issue being inter-conversion between input formats, namely, XML and PeP (specific format designed for Python based ENPS). Another major issue with existing simulators is their inability to allow multiple membrane systems to be executed and there is no facility for interconnection between two membrane systems. A tool developed here solves both problems namely, file inter-conversion and multiple membrane support by transferring dependent variable values automatically according to users’ choice. The tool is developed using Python 3.0 and has only a few dependencies. The tool is tested under different scenarios and the results confirm the correctness of the tool. © 2019 Elsevier B.V.Item GPUPeP: Parallel Enzymatic Numerical P System simulator with a Python-based interface(Elsevier Ireland Ltd, 2020) Raghavan, S.; Rai, S.S.; Rohit, M.P.; Chandrasekaran, K.Membrane computing is a computational paradigm inspired by the structure and behavior of a living cell. P Systems are the computing devices that are used to realize membrane computing models. Numerous theoretical studies on many variants of P Systems have shown them to be computationally universal. There is a wide range of applications of P Systems from modeling of biological processes to image processing. Among many variants of P Systems, one of the most important is Enzymatic Numerical P System (ENPS). ENPS is a class of P System in which membranes operate on numerical values. To realize the power of ENPS there are a few simulators developed. Each and every simulator has some advantages as well as some disadvantages. Here, a GPU based simulator using Python as a user interaction language is developed. This tool is a completely parallel variant, compatible with a Python based sequential simulator (PeP) which was the first Python based work for ENPS. The developed simulator uses CUDA to interact with GPU and gives the desired speed up, while processing the membranes. There are two important case studies which show the performance of the developed tool to be far better than the other serial simulators. © 2020 Elsevier B.V.Item Effect of peptide hydrophilicity on membrane curvature and permeation(American Institute of Physics, 2024) Mathath, A.V.; Chakraborty, D.Using a well-developed reaction coordinate in umbrella sampling, we studied the single peptide permeation through a model cancerous cell membrane, varying the hydrophilicity and the charge of the peptides. Two peptides, melittin and pHD108, were studied. The permeation mechanism differs from a barrel-stave-like mechanism to toroidal pore and vesicle formation based on the number and the placement of the hydrophilic amino acids in the peptide. Membrane curvature changes dynamically as the permeation process occurs. In the case of vesicles, the peptide traverses along a smooth, homogenous pathway, whereas a rugged, steep pathway was found when lipid molecules did not line up along the wall of the membrane (barrel-stave-like mechanism). A mechanism similar to a toroidal pore consists of multiple minima. Higher free energy was found for the permeating terminal containing charged amino acid residues. Vesicle formation was found for pHD108 peptide N-terminal with a maximum membrane thinning effect of 54.4% with free energy cost of 8.20 ± 0.10 kcal mol?1 and pore radius of 2.33 ± 0.07 nm. Insights gained from this study can help to build synthetic peptides for drug delivery. © 2024 Author(s).Item Evaluating the impact of the membrane thickness on the function of the intramembrane protease GlpG(Elsevier B.V., 2024) Engberg, O.; Mathath, A.V.; Döbel, V.; Frie, C.; Lemberg, M.K.; Chakraborty, D.; Huster, D.Cellular membranes exhibit a huge diversity of lipids and membrane proteins that differ in their properties and chemical structure. Cells organize these molecules into distinct membrane compartments characterized by specific lipid profiles and hydrophobic thicknesses of the respective domains. If a hydrophobic mismatch occurs between a membrane protein and the surrounding lipids, there can be functional consequences such as reduced protein activity. This phenomenon has been extensively studied for single-pass transmembrane proteins, rhodopsin, and small polypeptides such as gramicidin. Here, we investigate the E. coli rhomboid intramembrane protease GlpG as a model to systematically explore the impact of membrane thickness on GlpG activity. We used fully saturated 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC) and 1,2-dimyristoyl-sn-glycero-3-phosphocholine(DMPC) model lipids and altered membrane thickness by varying the cholesterol content. Physical membrane parameters were determined by 2H and 31P NMR spectroscopy and correlated with GlpG activity measurements in the respective host membranes. Differences in bulk and annular lipids as well as alterations in protein structure in the respective host membranes were determined using molecular dynamics simulations. Our findings indicate that GlpG can influence the membrane thickness in DLPC/cholesterol membranes but not in DMPC/cholesterol membranes. Moreover, we observe that GlpG protease activity is reduced in DLPC membranes at low cholesterol content, which was not observed for DMPC. While a change in GlpG activity can already be due to smallest differences in the lipid environment, potentially enabling allosteric regulation of intramembrane proteolysis, there is no overall correlation to cholesterol-mediated lipid bilayer organization and phase behavior. Additional factors such as the influence of cholesterol on membrane bending rigidity and curvature energy need to be considered. In conclusion, the functionality of ?-helical membrane proteins such as GlpG relies not only on hydrophobic matching but also on other membrane properties, specific lipid interaction, and the composition of the annular layer. © 2024 The Author(s)