<p>One of the important model employed in many biological processes is the Schnakenberg model. The suggested model is based on an autocatalytic process that occurs naturally in a number of biological models. In these kinds of reactions, the rate of reaction increases as it moves ahead. This occurs when a product works as a catalyst on its own. In reality, the model provides fractional derivatives, which have greatly advanced the study of mathematical modelling involving memory effect. Thus, the authors of this study developed an approach for solving the fractional order Schnakenberg model. An autochemical reaction with potential oscillatory behaviour is described by the suggested model, which could come into application across a variety of biological and biochemical processes. The authors of this study extended the theory of the integer-order Schnakenberg model to the fractional Schnakenberg model. We presented the approximate solution using the Natural transform decomposition technique (NTDM) for the basic modified nonlinear Schnakenberg model in the sense of the Caputo–Fabrizio and Atangana–Baleanu differential operator. Obtaining numerical findings in the form of a fast-convergent series significantly improves the proposed technique accuracy. The behaviour of the approximate series solution for several fractional orders is shown graphically, which are derived through Maple. The derived results demonstrate how simple and efficient the proposed method is to apply for analysing the behaviour of fractional-order nonlinear differential equations that arise in related fields of engineering and science.</p>