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Record W2070591490 · doi:10.3390/ijms150610459

Computational Study on Substrate Specificity of a Novel Cysteine Protease 1 Precursor from Zea mays

2014· article· en· W2070591490 on OpenAlexaff
Huimin Liu, Liangcheng Chen, Quan Li, Mingzhu Zheng, Jingsheng Liu

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsMinistry of Education and Child Care
FundersKey Technologies Research and Development ProgramNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsZea maysSubstrate specificitySubstrate (aquarium)ProteaseCysteineChemistryBiochemistryBiologyEnzymeAgronomy

Abstract

fetched live from OpenAlex

Cysteine protease 1 precursor from Zea mays (zmCP1) is classified as a member of the C1A family of peptidases (papain-like cysteine protease) in MEROPS (the Peptidase Database). The 3D structure and substrate specificity of the zmCP1 is still unknown. This study is the first one to build the 3D structure of zmCP1 by computer-assisted homology modeling. In order to determine the substrate specificity of zmCP1, docking study is used for rapid and convenient analysis of large populations of ligand-enzyme complexes. Docking results show that zmCP1 has preference for P1 position and P2 position for Arg and a large hydrophobic residue (such as Phe). Gly147, Gly191, Cys189, and Asp190 are predicted to function as active residues at the S1 subsite, and the S2 subsite contains Leu283, Leu193, Ala259, Met194, and Ala286. SIFt results indicate that Gly144, Arg268, Trp308, and Ser311 play important roles in substrate binding. Then Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) method was used to explain the substrate specificity for P1 position of zmCp1. This study provides insights into the molecular basis of zmCP1 activity and substrate specificity.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.287
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2014
Admission routes1
Has abstractyes

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