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Razmazma, H.

Publications and source records attributed to Razmazma, H..

2 recordsLinked to original sources

Ist2, a protein involved in phosphatidylserine transport, is an ER lipid scramblase

Lipid scramblases allow passive flip-flop of phospholipids between bilayer leaflets, thereby promoting membrane symmetry. At the endoplasmic reticulum (ER), where phospholipid synthesis is restricted to one of the two leaflets, scramblase activity should be essential for equilibrated membrane growth. However, phospholipid scramblases at the ER are poorly understood. The yeast protein Ist2 contains an ER domain and a cytosolic tail that binds the plasma membrane (PM) and participates in the transfer of phosphatidylserine (PS). Here, we show both in vitro and in silico that the ER- domain of Ist2, which bears homology to the TMEM16 proteins, possesses a lipid scramblase activity. Ist2 activity is not regulated by Ca2+, in contrast to TMEM16 proteins, but is affected by the lipid composition of the bilayer used in simulations. In cells, we do not find a strong impact of the scramblase domain of Ist2 in on PS distribution; however, its over-expression or deletion affects processes at the ER such as vesicular transport, lipid droplet biogenesis and general phospholipid transport, with a specific contribution of residues important for lipid scrambling. Our study therefore identifies the first dedicated phospholipid scramblase in yeast and demonstrates that membrane asymmetry can impact diverse membrane-remodeling processes at the ER.

cell biology↗

GoMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The G[o]Martini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced G[o]Martini model, which combines a virtual-site implementation of G[o] models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with G[o] models.

biophysics↗