An Insight into Non‐Covalent Interactions on the Bicyclo[1.1.1]pentane Scaffold
Bibliographic record
Abstract
Abstract Bicyclo[1.1.1]pentane (BCP) is studied extensively as a bioisosteric component of drugs. Not found in nature, this molecular unit approximates the distance of a para ‐disubstituted benzene which is replaced in medicines as a method of improving treatments. Predicting interactions of these drugs with specific active sites requires knowledge of the non‐covalent interactions engaged by this subunit. Structure determinations and computational analysis (Hirshfeld analysis, 2D fingerprint plots, DFT) of seven BCP derivatives chosen to probe specific and directional interactions. X‐ray analysis revealed the presence of various non‐covalent interactions including I ⋅⋅⋅ I, I ⋅⋅⋅ N, N−H ⋅⋅⋅ O, C−H ⋅⋅⋅ O, and H−C ⋅⋅⋅ H−C contacts. The preference of halogen bonding (I ⋅⋅⋅ I or I ⋅⋅⋅ N) in BCP 1 – 4 strictly depends upon the electronic nature and angle between bridgehead substituents. The transannular distance in co‐crystals 2 and 4 was longer as compared to monomers 1 and 3 . Stronger N−H ⋅⋅⋅ O and weaker C−H ⋅⋅⋅ O contacts were observed for BCP 5 while the O ⋅⋅⋅ H interaction was a prominent contact for BCP 6 . The presence of 3D BCP units prevented the π ⋅⋅⋅ π stacking between phenyl rings in 3 , 4 , and 7 . The BCP skeleton was often rotationally averaged, indicating fewer interactions compared to bridgehead functional groups. Using DFT analysis, geometries were optimized and molecular electrostatic potentials were calculated on the BCP surfaces. These interaction profiles may be useful for designing BCP analogs of drugs.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".