High-Throughput Simulations of Dimer and Trimer Assembly of Membrane Proteins. The DAFT Approach
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Bibliographic record
Abstract
Interactions between membrane proteins are of great biological significance and are consequently an important target for pharmacological intervention. Unfortunately, it is still difficult to obtain detailed views on such interactions, both experimentally, where the environment hampers atomic resolution investigation, and computationally, where the time and length scales are problematic. Coarse grain simulations have alleviated the later issue, but the slow movement through the bilayer, coupled to the long life times of nonoptimal dimers, still stands in the way of characterizing binding distributions. In this work, we present DAFT, a Docking Assay For Transmembrane components, developed to identify preferred binding orientations. The method builds on a program developed recently for generating custom membranes, called insane (INSert membrANE). The key feature of DAFT is the setup of starting structures, for which optimal periodic boundary conditions are devised. The purpose of DAFT is to perform a large number of simulations with different components, starting from unbiased noninteracting initial states, such that the simulations evolve collectively, in a manner reflecting the underlying energy landscape of interaction. The implementation and characteristic features of DAFT are explained, and the efficacy and relaxation properties of the method are explored for oligomerization of glycophorin A dimers, polyleucine dimers and trimers, MS1 trimers, and rhodopsin dimers. The results suggest that, for simple helices, such as GpA and polyleucine, in POPC/DOPC membranes series of 500 simulations of 500 ns each allow characterization of the helix dimer orientations and allow comparing associating and nonassociating components. However, the results also demonstrate that short simulations may suffer significantly from nonconvergence of the ensemble and that using too few simulations may obscure or distort features of the interaction distribution. For trimers, simulation times exceeding several microseconds appear needed, due to the increased complexity. Similarly, characterization of larger proteins, such as rhodopsin, takes longer time scales due to the slower diffusion and the increased complexity of binding interfaces. DAFT and its auxiliary programs have been made available from http://cgmartini.nl/ , together with a working example.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it