Molecular Modeling of the Interaction of Neurotrophins with the P75NTR Common Neurotrophin Receptor
Bibliographic record
Abstract
Neurotrophins are a family of proteins with pleiotropic effects mediated by two distinct receptor types, namely the trk family and the common neurotrophin receptor p75 NTR Binding of four mammalian neurotrophins, nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT-3) and neurotrophin-4/5 (NT-4/5), to p75 NTR is studied by large scale molecular dynamics simulations using CHARMM force field. Geometric match of neurotrophin/receptor binding domains in the complexes is evaluated by the Lawrence & Colman’s shape complementarity statistic S c. The model of neurotrophin/receptor interactions suggests that the receptor binding domains of neurotrophins (loops I and IV) are geometrically and electrostatically complementary to a putative binding site of p75 NTR formed by the second and part of the third cysteine-rich domains. All charged residues within the loops I and IV of the neurotrophins, previously determined as being critical for p75 NTR binding, directly participate in receptor binding in the framework of the model. Principal residues of the binding site of p75 NTR include Asp 47, Lys 56, Asp 75, Asp 76, Asp 88 and Glu 89. The additional involvement of Arg 80 and Glu 73 is specific for NGF and BDNF, respectively, and Glu 73 participates in binding with NT-3 and NT-4/5. The model developed has utility in computer-aided molecular design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".