Abstract:
Living cells embody complex interaction networks with a millieu of reactions among the large numbers and types of molecules. Several distinguishing characteristics of living systeM.S. are that they are far from equilibrium, are inherently multi-component, with several important species, many of which are in low copy numbers. Chemical reactions are the backbone to the functioning of living cells. From basic reactions such as the synthesis of ATP from glucose to the synthesis of proteins or replication of DNA, most the important phenomena are chemically driven. Diffusion of the molecules, physical or chemical interactions among them and the timescales of the processes regulate the functioning of the system. Understanding, the mechanism behind these functions, is necessary both for learning about the basic biology and for research in areas like drug discovery, biotechnology. We illustrate examples of the necessity for understanding reactions in a few biological phenomena below -
Unicellular organisM.S. such as E. coli show an interesting phenomenon called chemotaxis. On average, they drift towards nutrients (chemoattractants) or away from toxins (chemorepellents). But this drift evolves out of a biased random walk, in which, if conditions appear favorable, based on the density of the nutrient molecules that are sensed by the bacterium and the random change in direction (tumble) will be delayed. This biased random walk eventually leads bacteria to chemoattractant. While this phenomenon may be described as a bacterial ‘strategy, the decision making is driven by sensing molecules in low copy numbers. The mechanisM.S. of nutrient sensing by (un)binding, the timescales over which chemical modifications such as methylation that follow it last to constitute a memory, and the mechanisM.S. by which the signals drive the motor proteins are all inherently molecular in nature. Developing a molecular understanding of any of these steps, and understanding how fast biological systeM.S. respond and adapt to environmental changes[1][2][3] requires modelling the phenomenon and following the kinetics of the different processes.
