A rational approach towards successful crystallization and crystal treatment of human cytomegalovirus protease and its inhibitor complex
Bibliographic record
Abstract
The crystallization and subsequent crystal treatment of both free human cytomegalovirus (hCMV) protease and its inhibitor complexes are reported. For free-enzyme crystals, diffraction was greatly improved by optimizing the crystallization conditions, raising the precipitant concentration in the reservoir and soaking the crystals in artificial mother liquors. Each of the six components in the final crystallization formula (16% PEG 4000, 0.1 M MES pH 6.0, 0.4 M LiCl, 10% glycerol, 5% t-butanol and 5 mM Na(2)S(2)O(3)) plays a distinctive role and is indispensable. A synergistic effect of Na(2)SO(4) and t--butanol on diffraction was observed and studied. A 2.0 A multiwavelength anomalous diffraction (MAD) data set was collected using a synchrotron-radiation source, leading to the elucidation of the three-dimensional structure of the enzyme. For the inhibitor-complex crystals, initial attempts with co-crystallization and soaking experiments at pH 6.0 did not produce conclusive results. Subsequently, experiments were designed to co-crystallize the complex at pH 8.0, the optimal pH for the enzyme and the inhibitor activity. Using 20-50 mM spermine in the crystallization buffer, crystals of two peptidomimetic inhibitor complexes were obtained at pH 7.5 and 8.0. Spermine was required for the inhibitor complexes to be crystallized at pH 8.0, possibly neutralizing net negative charges of hCMV protease owing to its acidic pI of 5.5. A 2.7 A data set was collected from one of the inhibitor complexes and the structure was determined using the molecular-replacement method.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".