Abstract P-2: Modeling Encapsulated Lipid Molecules in Cryo-EM Maps of Membrane Complexes
Bibliographic record
Abstract
Background: Membrane complexes are of great importance for cell functioning.Among the best studied complexes are rotor ATPases which create ATP from ADP, or vice versa (J.E.Walker, Biochem.Soc.Trans.41, pp.1-16, 2013).Generally, rotor ATPases consist of a soluble part and a membraneembedded part.The membrane part includes a c-ringa symmetric oligomer of subunits c, which is rotating in the membrane during the protein operation.The inside pore of the c-rings in some cases is plugged by phospholipids.While the protein components are well ordered in the structures, the surrounding lipid molecules, including those trapped inside the c-ring, usually are not resolved.Most probably this is due to the great flexibility of lipids (P.Buslaev et al., J. Chem.Theory Compyt.12, pp.1019-1028, 2017) and lack of specific lipid-protein interactions, or due to techniques used for sample preparation.Recently, a Cryo-EM structure of spinach chloroplast ATPase with recognizable densities in the membrane region has become available, providing an opportunity to compare the modeled lipid positions with the experimental data (A.Hahn et al., Science eaat4318, 2018).Methods: We introduce nature-inspired approach to model the lipids inside the c-ring.It uses a biasing force to assemble the whole ring, essentially by incorporating experimental restraints into the coarse grained (CG) molecular dynamics (MD) simulation.The numerical comparison of modeled lipid densities with the EM maps was performed using the real space correlation coefficient (RSCC). Results:The structures converged into an assembled ring.The numbers of lipids trapped at the loop side and the NC-side were consistent in different runs: 9 to 11 and 13 to 15, respectively.However, RSCC of modeled lipid densities with the EM map was poor.Thus, we conducted short CG simulations where lipids were removed one-by-one to maximize RSCC (Fig. 1).The best fit (RSCC > 0.8) was observed for a system with 6 lipids at the loop side and 9 lipids at the NC side.The obtained systems were converted to atomistic models and were stable for several hundreds of nanoseconds.The atomistic models also correlated with experimental data well (RSCC > 0.8) and showed the same trend as densities for coarse grained simulations. Conclusion:We expect that the approach will be helpful for modelling of the lipids encapsulated within membrane protein and for studies of assembly of membrane complexes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".