PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 6645563

Dynamic behavior of cyclic enzyme systems.

M Okamoto·K Hayashi
View original source ↗Export metadata ↓

Abstract

The dynamic behavior of cyclic enzyme systems where two enzymes share a substrate or cofactor in a cyclic manner is investigated by computer simulation. The dynamic characteristics of cyclic enzyme systems display catastrophic behavior in response to specific changes in external input without assuming allosteric regulation.

Explore related subjects

EnzymesModels, ChemicalJournal ArticleResearch Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M Okamoto, K Hayashi. 1983-10-21. Dynamic behavior of cyclic enzyme systems.. https://doi.org/10.1016/0022-5193(83)90247-3

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

How not to be seen: predicting unseen enzyme functions using contrastive learning.

MOTIVATION: Predicting enzyme function from its sequence is still an unsolved problem in the life sciences. Moreover, with the explosion of annotated genome data, we are inundated with potential enzymatic sequences that have not yet been biochemically characterized. While it is not possible to assign a not-yet-existing label to such a sequence, there is high value in placing the sequence as accurately as possible in known function space. Doing so can help provide more accurate falsifiable hypotheses for experimentalists wishing to characterize enzymes from specific functional families. RESULTS: Here we present a contrastive learning algorithm for predicting enzyme function from sequence. Our method, EnzPlacer, predicts the third, second, and first EC numbers for a protein whose fourth EC number is not in the training corpus. This novel prediction mechanism accurately places a protein sequence within a narrowed-down functional context, even if the precise function remains unknown. AVAILABILITY AND IMPLEMENTATION: EnzPlacer and data is available at https://github.com/drxiangma/EnzPlacer under a GPL3 license.

Enzymes↗
PubMed2007

Searchlight on domains.

In this issue of Structure, examine in detail the functions of selected domains within proteins both when they are alone and when in combination with others. Domain function is relevant to molecular evolution and to annotation of proteins known only by sequence.

Enzymes↗
PubMed2006

Alpha-secondary isotope effects as probes of "tunneling-ready" configurations in enzymatic H-tunneling: insight from environmentally coupled tunneling models.

Using alpha-secondary kinetic isotope effects (2 degrees KIEs) in conjunction with primary (1 degrees ) KIEs, we have investigated the mechanism of environmentally coupled hydrogen tunneling in the reductive half-reactions of two homologous flavoenzymes, morphinone reductase (MR) and pentaerythritol tetranitrate reductase (PETNR). We find exalted 2 degrees KIEs (1.17-1.18) for both enzymes, consistent with hydrogen tunneling. These 2 degrees KIEs, unlike 1 degrees KIEs, are independent of promoting motions-a nonequilibrium pre-organization of cofactor and active site residues that is required to bring the reactants into a "tunneling-ready" configuration. That these 2 degrees KIEs are identical suggests the geometries of the "tunneling-ready" configurations in both enzymes are indistinguishable, despite the fact that MR, but not PETNR, has a clearly temperature-dependent 1 degrees KIE. The work emphasizes the benefit of combining studies of 1 degrees and 2 degrees KIEs to report on pre-organization and local geometries within the context of contemporary environmentally coupled frameworks for H-tunneling.

Enzymes↗