Enzkin

버전 2.0.0.0 (17.6 KB) 작성자: Giuseppe Cardillo
a tool to estimate the Michaelis-Menten kinetic parameters
다운로드 수: 2.6K
업데이트 날짜: 2018/4/6

ENZyme KINetics is the study of the chemical reactions that are catalysed by enzymes.
In enzyme kinetics the reaction rate is measured and the effects of varying the conditions of the reaction investigated. Studying an enzyme kinetics in this way can reveal the catalytic mechanism of this enzyme, its role in metabolism, how its activity is controlled, and how a drug or a poison might inhibit the enzyme. Michaelis–Menten kinetics approximately describes the kinetics of many enzymes. It is named after Leonor Michaelis and Maud Menten. This kinetic model is relevant to situations where very simple kinetics can be assumed, (i.e. there is no intermediate or product inhibition, and there is no allostericity or cooperativity). The Michaelis–Menten equation relates the initial reaction rate v0 to the substrate concentration S. The corresponding graph is a rectangular hyperbolic function; the maximum rate is described as Vmax (asymptote); the concentration of substrate where the v0 is the half of Vmax is the Michaelis-Menten costant (Km). To determine the maximum rate of an enzyme mediated reaction, a series of experiments is carried out with varying substrate concentration and the initial rate of product formation is measured. 'Initial' here is taken to mean that the reaction rate is measured after a relatively short time period, during which complex builds up but the substrate concentration remains approximately constant and the quasi-steady-state assumption will hold. Accurate values for Km and Vmax can only be determined by non-linear regression of Michaelis-Menten data. The Michaelis-Menten equation can be linearized using several techniques. ENZKIN uses 6 regression models (2 non-linear and 4 linear) to obtain the kinetic parameters.
Syntax: enzkinout=enzkin(S,v)
Inputs:
S - data array of substrate concentrations
v - data array of measured initial velocity
Outputs:
- Vmax and Km estimation by:
° Michaelis-Menten non linear regression
° loglog non linear regression
° Lineweaver-Burk linear regression
° Hanes-Woolf linear regression
° Eadie-Hofstee linear regression
° Scatchard linear regression
- for the linear regressions, all regression data are summarized
- Plots
The function requires another function of mine MYREGR. If it is not present on the computer, enzkin will try to download it from FEX
Created by Giuseppe Cardillo
giuseppe.cardillo-edta@poste.it

To cite this file, this would be an appropriate format: Cardillo G. (2010). Enzkin: a tool to estimate Michaelis-Menten kinetic parameters http://www.mathworks.com/matlabcentral/fileexchange/26653

인용 양식

Giuseppe Cardillo (2024). Enzkin (https://github.com/dnafinder/enzkin), GitHub. 검색됨 .

MATLAB 릴리스 호환 정보
개발 환경: R2014b
모든 릴리스와 호환
플랫폼 호환성
Windows macOS Linux
카테고리
Help CenterMATLAB Answers에서 QSP, PKPD, and Systems Biology에 대해 자세히 알아보기

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

GitHub 디폴트 브랜치를 사용하는 버전은 다운로드할 수 없음

버전 게시됨 릴리스 정보
2.0.0.0

code makeup (removing of global variables, input parser and table implementation); github link
change in figure
change in figure

1.1.0.0

Change in help section for correct citation

1.0.0.0

이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.
이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.