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Drug Discovery with Immunopharmacology





Title: Assaying Nitrate using the spectrophotometric method

Aims: This study is done to determine the effectiveness of different drugs provided as samples for different inflammatory pathologies. The result of the study can provide direction on which drug can be used in the future in treating inflammatory pathologies

Methods: The appropriateness of the Greiss assay in this experiment is one of the factors for the success of this experiment. The Greiss test can be described as an analytical chemistry test developed by Peter Greiss that detects availability of nitrite ions in a given solution. The basis for its use is the fact that it is highly sensitive to nitrite. There are other alternatives for assaying nitrite such as fluorimetric DAN which sometimes is not so sensitive to nitrite like the colorimetric Greiss assay is (García-Robledo & Papaspyrou, 2014).

Based on the concentration of nitrite in the provided samples, the intensity of the coloration will be different. A scale of 1 to 7 can be used to evaluate the intensity of the coloration where anything that falls between 1 and 3 is said to be having low color intensity while anything that fall between 4 and 7 has a high intensity color. In setting up a zymosan peritonitis model of inflammation, one needs Saccharomyces cerevisiae. The Zymosan is derived from it. The Zymosan is injected into the intraperitoneal which subsequently allows for the obtaining the neutrophils for down-stream analysis.

Results 1 Qualitative:

A total of 5 samples were provided and were to be used in determining the concentration of nitrite into the different solutions. The samples included therapeutics drug samples that can be used as solution for inflammatory pathologies. Lack of nitrite ion inside these solutions is supposed to be indicated by a clear concentration. Based on a detection limit that ranges between 0.02 and 2.5μM, the samples showed different color intensity. The red pink color that represents the presence of nitrite was displayed in a number of the samples provided. Sample 1 recorded a 2.41 while sample 2 had 1.169. Below is a full table that shows the results of the 5 samples used for this study.

Sample Result (μM)
Sample 1 2.41
Sample 2 1.169
Sample 3 0.67
Sample 4 0.372
Sample 5 0.251

Figure 1: Table showing the results from screening nitrite from 5 samples provided. It is based on color intensity range.

Of all the samples that were provided, none of them had a clear solution after the nitrite concentration test. This therefore means that all the samples had concentration of nitrite inside them. The concentration however varied. The red pink color can therefore be said to have more intensified in sample 1 as compared to any other sample. Sample 1 therefore had the highest of the nitrite concentration. The second of the samples that registered a more intense red pink color is sample 1. It also means that nitrite was relatively high in this sample. Samples 2 and 3 had a close color intensity and therefore nitrite concentration. The sample that recorded the lowest color intensity was sample 5 which had a 0.251. It therefore means that this sample was the lowest in nitrite concentration. The test was done at 550nm.

Result 2: Quantitative

The stock solution nitrite can be determined by addition of the reagent into the provided solution. Given 400 µM, we can determine the stock solution for the nitrite. The solution will be 200ppm of nitrite. The standard curve can be made from the results obtained. A Y-axis will represent the absorbance while the X-axis will represent the concentration level. It is calculated based on a general equation y=mx + b that also aids in drawing the line of best fit (Waltz et.al. 2015). Computations such as standard deviations and others play a part in the creation of the standard deviation curve. Below is the standard curve derived for this expreriment.


Figure 2: The standard curve where y = 0.007x + 0.0212 and R² = 0.9987

The calculation of the standard curve on the other simply relies on the concentration from all the concentration and the dilution factor for each. What we do is simply to multiply the concentration values with the dilution factor. What follows is the calculation of the standard deviation from the set determined values. The effectiveness of the drugs also varies significantly (Delmastro-Greenwood, 2015). Based on the provided and worked out result from the experiment, it is possible to rank the drugs in order of their effectiveness to inhibit the release of nitrite. The table below shows the result of the drugs that are most effective and those that are least effective.

Rank Drug Able to inhibit nitrite release (Yes/No)
1 Placebo Yes
2 Sample 5 Yes
3 Sample 1 Yes
4 Sample 3 Yes
5 Sample 2 No
6 Sample 4 NO
7 Prednisone No

A significant part of the lab report was about quantitative result for the Greiss assay. The result was able to show the concentration levels based on dilution. According to the raw data, sample 1 recorded the highest value with a 2.47 and 2.39. The standard samples could be used to rank the sample drugs provided. The concentration was therefore high in the first sample as compared to the other sample. Apart from the five samples provided, it was also important to have two other samples that could be used as controlled variable. They were therefore part of the samples where the Greiss assay was employed. Part C on the other hand had the samples as the pre-treatment strategies. It showed the neutrophil outcome range and the chemokine range. As discussed earlier, the placebo sample had the highest range followed by sample 5 and sample 1. It therefore elicits the thoughts of controlled test actually being effective than the actual samples provided in the inhibition of nitrite release.

A figure legend can be used to clearly describe the information that is actually displayed in part c. below is a figure legend for the part

Figure: The in vivo data set after the 4h zymosan peritonitis model. Column 1, the pretreatment samples and controlled test variables. Column 2, the Neutrophil x106/ml outcome range. Column 3, the CXCL1 chemokine KC pg/ml outcome range


The production of nitrite is normally witnessed during the inflammation process. When one is injured and an inflammation process begins, the Nitrite synthase is normally activated in Neutrophilis. This is normally in response to the inflammation stimuli. It is a sort of immune response to the inflammatory process. There are also other diseases that see the production of nitrite apart from the inflammatory process. One of these diseases is the bowel diseases. Studies have shown that the production of nitrite can be high in bowel diseases. The bowel diseases can include colon cancer, esophageal cancer and gastric cancer among others (Mellyana et.al. 2015). The production is also witnessed in tumors. Nitric oxide (No) is involved in several physiological processes inside the body. It is basically a free radical whose production takes place inside a wide range of tissues and cell inside the body. Nitric Oxide is involved in physiological processes such as cell death, immune regulation, neurotransmission and vascular relaxation (Jädert et.al. 2014). Its production is mainly by Nitric oxide synthase that contains different neural types.

The inclusion of placebo and prednisone in the Greiss assay of nitrite was very important for the success of the experiment. First, the prednisone is used to study the chances of a reduced morbidity among patients with several inflammatory pathologies (Greenberg et.al. 2015). On the other hand the placebo is used a controlled trial for the prednisone. For example, the results can be used to compare the morbidity reduction among patients in the case of prednisone and the placebo. The two played a significant role in result comparison and can be used to single out the best option in a bid to find solution for the inflammatory pathologies. A preoperative MOFA program would not only be appropriate for the drugs that lower NO but also limit the side effects that come along with some of these drugs (Looft & Dmitriev, 2017). Few researches that have been done on MOFA in relations to drugs that lower NO have inhibited clear evidence that could be used in future pharmacology research.

In a sensitive study such as that showed in this paper need a lot of accuracy to arrive at a conclusion. There are several things that can be done to improve the experimental design. One of these things is the limiting the errors that are often experienced when using the pipette. Checking the pipette daily, using the appropriate pipette such as an air displacement pipette and reverse pipetting can help avoid the errors when pipetting. Another way to improve the experimental design is to increase the randomization. It can help any kind of sample biasness that may be experienced. Addition of placebo groups or control and even blinding the experiment are good ways of improving the experimental design of the study. We cannot also underestimate controlling of more variables in an experiment and what it can do in a bid to increase the validity of an experiment. A controlled test for example would give information on alternatives for the study.

In conclusion, the spectrophotometric method has been shown to be a good method or assaying Nitrate. This experiment is a leeway to future research that can be used to develop a wide range of drugs that can be used for inflammatory pathologies.

Reference List

Delmastro-Greenwood, M., Hughan, K.S., Vitturi, D.A., Salvatore, S.R., Grimes, G., Potti, G., Shiva, S., Schopfer, F.J., Gladwin, M.T., Freeman, B.A. and Wendell, S.G., 2015. Nitrite and nitrate-dependent generation of anti-inflammatory fatty acid nitroalkenes. Free Radical Biology and Medicine89, pp.333-341.

García-Robledo, E., Corzo, A. and Papaspyrou, S., 2014. A fast and direct spectrophotometric method for the sequential determination of nitrate and nitrite at low concentrations in small volumes. Marine Chemistry162, pp.30-36.

Greenberg, S.S., Xie, J., Spitzer, J.J., Wang, J.F., Lancaster, J., Grisham, M.B., Powers, D.R. and Giles, T.D., 2015. Nitro containing L-arginine analogs interfere with assays for nitrate and nitrite. Life sciences57(21), pp.1949-1961.

Jädert, C., Phillipson, M., Holm, L., Lundberg, J.O. and Borniquel, S., 2014. Preventive and therapeutic effects of nitrite supplementation in experimental inflammatory bowel disease. Redox biology2, pp.73-81.

Looft, V.M. and Dmitriev, A.V., 2017. The Metabolic Optimized Fast Track Concept: preoperative preparation for abdominal surgery. Khirurgiia, (10), 

Mellyana, O., Dharmana, E., Susanto, H. and Sekarwana, N., 2015. Effects of combined supplementation of vitamins C and E on the oxidative modification of low-density lipoprotein, soluble form of CD36, soluble vascular cell adhesion molecule-1, and nitrite/nitrate oxide levels in idiopathic nephrotic syndrome. Biomarkers and Genomic Medicine7(3), pp.125-130.

Waltz, P., Escobar, D., Botero, A.M. and Zuckerbraun, B.S., 2015. Nitrate/nitrite as critical mediators to limit oxidative injury and inflammation. Antioxidants & redox signaling23(4), pp.328-339.

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