The mechanism of noncompetitive inhibition has been understood using the Michaelis-Menten model of enzyme kinetics for a century now. In noncompetitive inhibition, the inhibitor binds at an allosteric site separate from the active site of substrate binding. Thus in noncompetitive inhibition, the inhibitor can bind its target enzyme regardless of the presence of a bound substrate. Put differently; the inhibitor has the same affinity for both the enzyme and enzyme-substrate complex. Binding of the inhibitor to the enzyme or enzyme-substrate complex inactivates the enzyme, disallowing the production of its end product. Inactivation of the enzyme decreases the maximum rate of the reaction (Vmax), defined as the rate of the reaction at a substrate concentration that fully saturates all active sites of the specific enzyme. The Michaelis constant (Km) is the substrate concentration at which the reaction rate is half of Vmax. Km can also be interpreted as an inverse measurement of the enzyme-substrate affinity. In noncompetitive inhibition, the affinity of the enzyme for its substrate (Km) remains unchanged as the active site is not competed for by the inhibitor. Increasing substrate concentration to overcome the decrease in Vmax caused by noncompetitive inhibition is fruitless, as competition for the active site between inhibitor and substrate is not the limiting issue. The decrease in Vmax and the unchanged Km is the primary way to differentiate noncompetitive inhibition from competitive (no direct change in Vmax, increased Km) and uncompetitive (decreased Vmax and Km). 

Before the convenience of powerful software used today in enzyme kinetics, data from enzymatic activity and inhibition was plotted on graphs to get a better understanding of the results. In education, a Lineweaver-Burk plot is the most frequent graph. Lineweaver-Burk plots are characterized by 1/V (V being velocity) plotted on the y-axis and 1/[S] ([S] being substrate concentration) on the x-axis. After plotting the data points, the x-intercept represents 1/-Km, while the y-intercept represents 1/Vmax. In non-competitive inhibition, when comparing pre- and post- inhibition plots, an increase in the y-intercept is seen (Figure 1). This graph correlates with the decrease in Vmax (increase in 1/Vmax) caused by inhibition. The x-intercept remains unchanged, as the apparent affinity of the enzyme for its substrate (Km, and thus 1/-Km) is not changed. The changes (or lack thereof) in Vmax and Km and their graphical depictions on the Lineweaver-Burk plot are the primary way to differentiate noncompetitive inhibition from competitive and uncompetitive inhibition.[5]

Cyanide Poisoning

Cyanide is a rapidly acting, potentially fatal substance if ingested. Most commonly, cyanide toxicity is the result of smoke inhalation during domestic fires. Toxicity is due to the cessation of oxidative phosphorylation (the production of ATP via the use of oxygen).[6] More specifically, cyanide noncompetitively inhibits cytochrome c oxidase, the last enzyme in the electron transport chain. Current treatments for cyanide toxicity focus on intercepting cyanide before it can reach the enzyme or displacing it from the enzyme, rather than overcoming the inhibition of the enzyme itself ( potentially due to the non-competitive nature of inhibition).[7]

 Heavy Metals

Metals such as mercury, cadmium, and lead can all lead to poisoning in humans.[8][9][10] Mechanisms involving non-competitive inhibition of vital enzymes have correlations with all three. While it is unclear how much these specific inhibitions contribute to the overall toxicity of these metals, such findings warrant further investigation.

While the implications of noncompetitive inhibition in metal poisoning are still under study, their use as therapeutic agents outside of anticancer drugs is just beginning. Research has recently demonstrated that copper and mercury as potent noncompetitive inhibitors of a light-chain protease in botulinum neurotoxin poisoning. They were found to delay botulinum neurotoxin poisoning-mediated lethality in rodents via their noncompetitive inhibition of enzymes within the neurotoxin.[11]

Chronic Disease

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases plaguing the healthcare system with high morbidity and mortality. While vast sums of time and money have gone towards developing safe, effective medical therapies for T2DM, these medications are not without side effects and are tolerated differently on an individual basis. Research continues to investigate “less invasive” means of controlling blood sugar. Inhibition of intestinal enzymes responsible for the breakdown of dietary sugar (such as alpha-glucosidase and alpha-amylase) has been found to be effective in preventing postprandial hyperglycemia in the diabetic population. Rosha grass (Cymbopogon martinii) has shown activity as a noncompetitive inhibitor of alpha-glucosidase, explaining its effectiveness as a traditional Indian treatment for T2DM.[12] Similarly, a plant used as folk treatment throughout Indonesia for T2DM was found to possess a component that acts as a noncompetitive inhibitor of alpha-amylase, effectively lowering blood glucose levels in diabetic rats.[13]

Also, pharmacological companies have emphasized the need to explore new molecular targets for novel drug development in the treatment of diabetes mellitus. Increased glucose production via gluconeogenesis is a well-defined problem in all Type 2 diabetics, yet not a single medication addresses this route of hyperglycemia. Fructose-1,6-bisphosphatase is the rate-controlling enzyme in gluconeogenesis, and recent insight has suggested noncompetitive inhibitors of the enzyme may be a useful therapy in T2DM.[14]

Finally, implications point to noncompetitive inhibition in disulfiram's inhibition of pro-hepatocellular carcinoma enzymes,[15] benzodiazepines' inhibition of specific families of CYP450 enzymes,[16] and as a potential mechanism for the blocking of neuraminidase in the treatment of the avian flu.[17] A short search on PubMed will show thousands of results that include new implications for the use of noncompetitive inhibition in disease understanding, drug therapy, and anti-cancer research.