17 minute read
Identification of potential 2-aminothiazole pharmaceuticals
Josh Tung
Barker College
Purpose: This paper aims to identify 2-aminothiazole molecules that may be effective pharmaceuticals for the treatment of the fungal infection Eumycetoma, through extensive data analysis of their activity. Design/methodology/approach: In collaboration with the breaking good project the paper used data sourced by the Open source Mycetoma consortium on screened compounds. The data was sorted to only include the 2 - aminothiazole compounds through the use of a data visualisation and analysis software. Correlation graphs between activity and the properties in the Lipinski's rule of 5 criteria were produced to observe any useful trends. Activity cliff and similar cliff analysis were performed, to determine clusters of useful and undesirable structures. Findings: The particular compounds were all analysed, and the result was that none of them exhibited useful correlations between the activity and Ro5 components. Undesirable structures that showed weak activity were identified. Research limitations/implications: Results were added to the growing body of data of the collaborative Open source Mycetoma consortium project. Sorted dataset consisted of 27 2aminothiazole compounds which limited the correlation graphs and activity analysis. Time constraints did not allow the synthesis and testing of the proposed compounds. Practical implications: 2-aminothiazole molecules are now known not to be a priority for experimental testing for effectiveness for treatment of Eumycetoma, focus should be primarily directed towards the hit compound and its analogues, and other drug families. Social implications: Undesirable structures reported can be used to assist in aiding the identification of 2-aminothiazole pharmaceuticals that could potentially be used for the treatment of Eumycetoma by avoiding compounds with these structures. Originality/value: To the authors and collaborators knowledge, this is the first time the data analysis of these 2-aminothiazole compounds exclusively has been performed. This contributes a new data set within the open source Mycetoma consortium project. Keywords: 2-aminothiazole, Eumycetoma, Lipinski's rules, Activity cliff, Similarity analysis Paper Type: Research paper
Literature Review
Mycetoma
Mycetoma, is a chronic infectious disease caused by the exposure of broken skin to soil and water containing pathogenic bacteria and fungi, resulting in large subcutaneous tissue and grain formation primarily on the foot. The incubation period of the disease is not well defined and variable (Lichon et al 2006). If left untreated or the treatment is unsuccessful, the infection can spread to other parts of the body, eventually debilitating muscle and bone tissue. The majority of cases are primarily located in Asia, Latin America and the equatorial sector of Africa, affecting poorer people living in remote rural regions (CDC, 2021)(see Figure 1). Aerobic branching actinomycete bacteria causes Actinomycetoma and a various genera of fungi causes Eumycetoma, with the most prevalent cases being caused by Madurella myectomatis. Madurella mycetomatis is a fungus that is characterized by its ability to build protective black grains around itself by melanizing and hardening the surrounding tissues. It also possesses an elaborate developed mesosomal system and a smooth endoplasmic reticulum (Findlay et al., 1979).
Treatment is dependent on the causative agent, with treatment for Eumycetoma cases being poor as current methods require a combination of surgery to remove the infected tissue and prolonged antifungal
Figure 1: Global average prevalence of recorded Myectoma cases (Source: van de Sande, 2013, pg 3) medication, with a 30% success rate (Lim et al., 2018), and amputations are common. Itraconazole is the drug treatment of choice usually requiring 12 yea rs of daily medication (Agarwal et al., 2017), however recurrent infections are common (van de Sande et al. 2015). Therefore, more potent alternate drugs are needed.
Aminothiazoles in Literature
The 2-aminothiazole family are heterocyclic aromatic amines that are composed of a thiazole nucleus, a five membered heterocyclic unit with sulfur and nitrogen at 1,3-positions, and an exocyclic amine (Metzger et al.). It has been used as a pharmacophore in pharmaceutical drugs and are considered as privileged structures. In drug discovery they have been used to fine-tune both the pharmacokinetic and pharmacodynamic properties of molecules (Jakopin 2020). 2-aminothiazoles have been primarily known for antifungal and antibacterial activity however in recent years numerous 2-aminothiazole compounds have been shown to exhibit anticancer, antitumor, anticonvulsant, anti-inflammatory and antileishmanial activity (Das et al 2016).
Evaluating druggability Lipinski’s rule of 5
Lipinski’s rule of 5 (Ro5) is a widely used set of guidelines used in drug discovery, to aid the evaluation of a drug’s pharmacokinetics and determine its likelihood to be orally active. The Ro5 predicts poor absorption is more likely when there are more than 5 hydrogen bond donors, more than 10 hydrogen bond acceptors, the molecular mass is greater than 500 and the Log P value (logarithm of the partition coefficient [ratio of the compounds oil to aqueous phase] which indicates the drugs lipophilicity and permeability to reach target tissue) exceeds the value of 5 (Lipinski et al, 2001).
It is a reasonable method of classification to a degree, but it is possible for drugs to have no Ro5 violations and not be orally bioavailable and vice versa (see figure 4). However, it is useful in filtering molecules that are predicted to have poor performance in oral activity, with those molecules being a waste of essential drug development resources. Therefore, it served as a suitable guideline that was incorporated within the methodology of this investigation, to predict drug permeability and to determine trends between the Ro5 criteria and activity. In order to use these potential trends to identify any potential 2aminothiazole compounds for testing by looking at their Ro5 criteria properties and seeing if they matched any of the trends observed.
Figure 2 : Ro5 violations in drugs of different class, (Source: Benet et al., 2016)
Rotatable bonds
Rotatable bonds are bonds that allow free rotation, they are commonly defined as single bonds that are not part of a ring that are bound to a non-terminal heavy atom excluding amide bonds. In drug discovery an increased rotatable bond count adversely effects the permeation rate of drug compounds (Veber et al 2002). Thus this property was incorporated within the correlation part of the methodology of this report.
Polar surface area
The polar surface area of a compound is used to quantify polarity, the more polar a molecule is then the less permeable it will be. This molecular property is also shown to correlate well with a drugs ability of passive molecular transport through membranes and allows for the prediction of transport properties of drugs (Ertl et al. 2000). Therefore it was included within the correlations to be produced within this investigation.
Open source Mycetoma Consortium (MycetOS):
This project has worked in collaboration with MycetOS an open-source research project that is researching for pharmaceuticals to treat Eumycetoma, through the synthesis and screening of molecules for activity against relevant pathogens. In this collaboration, MyectOS has supplied the necessary molecule data for analysis.
Series 2-aminothiazoles repository
The series 2 hit compound (see Figure. 2) with the IUPAC name N-(4-methylpyridin-2-yl)-4-(pyridin2-yl)thiazol-2-amine and molecular formula (C14H12N4S) is a 2-aminothiazole derivative that is formed between the reaction of a 1-4(methylpyridin-2-yl)thiourea and 2-bromo-1(pyridin-2-yl)ethanone hydrobromide in ethanol heated to reflux (see figure 4 for synthesis route).
Figure 3: Hit compound, N-(4-methylpyridin-2-yl)-4(pyridin-2-yl)thiazol-2-amine
The compound was identified as a molecule with useful activity that has been screened extensively and undergone in vivo & vitro testing. In these tests, the molecules were administered to larva infected with Madurella mycetomatis and was found to be a potent inhibitor (see Table 1). The hit compound also possesses no Ro5 violations making it a possible drug candidate that can be used for future treatment. Therefore, a necessary course of action for this repository is to evaluate molecules with the 2-aminothiazole core, observe potential druggability and compare structures with the hit compound, which will be conducted within this investigation.
Table 1: Activity of the hit compound Source: (Scroggie, 2021)
Origin [c] Statis Box Re-synthesised
100 μM 2.5 ± 1.4 4.3 ± 3.6 25 μM -2.36 ± 31.4 5.0 ± 1.9
Scientific Research Question
To identify which 2-aminothiazole molecules from a given database show potential for the treatment of Eumycetoma.
Scientific Hypothesis
Molecules with similar structures and analogues of the hit compound N-(4-methylpyridin-2-yl)-4(pyridin-2-yl)thiazol-2-amine will have potent activity against larva infected with Mycetoma.
Figure 5: 2-aminothiazole core (green representing substituents)
Figure 4 Synthesis route of the hit compound (Source: Scroggie, 2021)
Methodology
The compounds in the MMV boxes screened against Madurella mycetomatis were obtained from the Open Source Mycetoma masters list and were organised, by removing molecules that did not contain the 2-aminothiazole core (see figure. 5) through the use of the DataWarrior application.
The molecular properties of each of the 2aminothiazole molecules were then obtained through accessing the PubChem database, adhering to the Lipinski’s rule of 5 components which included the molecular weight, the log P value, the number of hydrogen bond donors and acceptors with the inclusion of the polar surface area and number of rotational bonds for each molecule. The number of Ro5 violations for each molecule was recorded to predict performance in potential drug trialling.
Step 3: Correlation graphs
Correlation graphs were produced graphing the molecular properties against the mean growth (%) at 100 µm and at 25 µm and an R value for was calculated for each correlation.
Step 4: Similarity and cliff activity analysis
In order to identify desirable and undesirable structures an activity cliff analysis and similarity analysis were performed using the DataWarrior application, with the inclusion of the hit compound as a point of comparison. 2-aminothiazole drugs for synthesis and testing were designed using the data collected on structures that showed promising activity.
Results
Of the total 1360 of screened molecules, 27 were found to include the 2-aminothiazole core structure. They are all pictured in Figure 6.
Data on each molecule was extracted adhering to the molecular properties of Lipinski’s Ro5 and the addition of polar surface area and rotational bonds. Whether or not these rules were violated was recorded in the table.
Figure 6: Sorted dataset of 27 2-aminothiazole compounds from the Open Source Mycetoma masters list (highlighted in blue: the hit compound)
Table 2: Molecular properties, activities and number of Ro5 violations for each of the sorted 2-aminothiazole compounds
Step 3: Correlation graphs
Each correlation graph had weak correlations as shown in table 2. Because low R value alone is insufficient, each individual graph needed to be visually inspected. None of the graphs inspected were shown to display any trends worth reporting.
Table 3: R value of each correlation between the molecular properties of each compound and the mean growth 100 µm and 25 µm.
R value
Molecular properties
Mean growth 100μM (%)
Mean growth 25μM (%)
Molecular weight 0.099511 0.159187 Polar surface area 0.301316 0.483294 Rotational bonds 0.05377 0.142797 LogP -0.08389 -0.04604 HBD -0.06046 -0.26447 HBA 0.129102 0.28981
Step 4: Similarity and cliff activity analysis
Figure 7 depicts a similarity chart produced from a similarity analysis. Each dot represents one of the 27 compounds and the hit compound and the colour gradient represents structural similarity to the hit compound, with the green dot circled in red representing the hit compound.
The lines joining molecules together are representative of compounds which are very similar structurally to each other.
Figure 7: Similarity chart, green dot circled in red: hit compound
Figure 8 and 9 depicts SALI plots produced by a cliff activity analysis. The mean growth at 100 µm and 25 µm makes up the x axis for both plots. Large circle markers indicate activity cliffs. Activity cliffs essentially show molecules that show an abrupt change in activity as a result of a relatively small change in structure.
Grey dots in the shaded area represent compounds that were not tested in 25 µm.
Discussion
The 27 compounds that consisted of the 2aminothiazole core structure that were gathered from the masters list consisting of 1360 screened molecules was less than expected and the narrow sample size impacted the correlations and cliff activity analysis.
Figure 9: Cliff activity analysis mean growth 25 µm (%)
The majority of the 2-aminothiazole compounds in the screened set were found to have no Ro5 violations, therefore indicating most of them are viable candidates for future testing and trialling.
However the two compounds Cefditoren and Lusutrombopag were identified to possess 2 Ro5 violations. According to the Ro5 guidelines used in this methodology these two compounds are predicted to have poor performance in absorbance and permeability in the event of trialling, suggesting these compounds should not be tested further as they are non-viable candidates. Furthermore, the compounds Cefditoren and Lusutrombopag were observed to have very poor activity in both 100 µm and 25 µm.
Step 3: Correlation graphs
In regards to the correlation graphs produced, none were found to exhibit strong correlations or clear trends between the Lipinski’s Ro5 criteria, polar surface area and number of rotational bonds against the mean growth at 100 µm (%) and at 25 µm (%). With the strongest correlation observed being between the polar surface area and mean growth 25 µm (%) with an R value of 0.483924.
Step 4: Similarity and cliff activity analysis
As stated in the hypothesis molecules that were more similar in structure to the hit compound were found to exhibit greater inhibition than molecules that were less similar in structure. However few structures were found to have a high similarity with the hit compound, with the closest having a similarity of 0.52518.
In regard to the cliff activity analysis performed, two activity clusters were observed. One cluster primarily involved nitazoxanide and analogues of the compound, all of which were observed to demonstrate weak activity. The structures as shown in figure 10 were found to be linked towards poor activity.
Figure 10: Nitazoxanide (red highlight – structures shown to link to poor activity)
Other compounds within the dataset containing these structures were also shown to exhibit poor activity. Therefore, a reasonable mode of action is to avoid including compounds with these structures from further testing.
In the other cluster that was observed between the two compounds MMV676383 and MMV611037, a small change in structure which involved the absence of a carbon branch and removal of an nitrogen atom in the thiazole nucleus was shown to result in a great difference in activities. Due to this only involving two compounds, further testing and research is required to determine if this is an anomaly or there is an underlying trend between the absence of these structures and stronger activity.
Since no useful structures were identified, the next step for this repository would be for compounds with the 2-aminothiazole core to no longer be a priority for experimental analysis and instead focus should be primarily directed towards the hit compound. This involves the synthesising of new analogues of the hit compound and screening them, in order to identify any new molecules with possibly stronger activity than the hit compound.
Limitations
Limitations on the sorted sample set of data of 27 negatively impacted the correlations and cliff activity analysis. Therefore a greater sample size of 2-aminothiazole compounds should be used, if this procedure of data analysis is to be repeated and used in any future research. Furthermore, time constraints did not allow the synthesis and testing of the proposed compounds to be undertaken within this report.
Future Research
Due to the time constraints which did not allow for the synthesis and subsequent testing of the proposed compounds, if synthesis is to be approved for these compounds, these molecules can be screened against Madurella mycetomatis. Data can then be added to the broader data set and be used in more cliff activity analysis and go forward into in vivo and in vitro testing if successful.
Another key area of interest for future research is investigating the activity cliff observed between MMV676383 and MMV611037. This could be achieved by synthesising molecules with and without the nitrogen atom in the thiazole nucleus and the carbon branch and performing more activity cliff analysis.
With regards to this report, the same methodology can also be used in future investigations that involve the analysis of compounds from the other repositories in the open source mycetoma consortium.
Conclusion
In working in collaboration with the breaking good project and the open source mycetoma consortium, the research conducted in this investigation gathered data on correlations, similarity and cliff activity analysis which contributed to the growing data set. No useful correlations were produced, however two undesirable structures were identified which will be reported back to the consortium, so as to refrain from these structures being incorporated in future testing. In terms of future action for this repository, the design, synthesis and screening of new analogues of the hit compound should be continued as no other useful structures were identified within this investigation. Doing so will allow for more structural activity analysis to be conducted and the possible discovery of a compound that demonstrates stronger activity against Eumycetoma than the current hit compound.
Acknowledgements
I would like to thank Dr Matthew Hill for regular guidance regarding the scientific process and assisting in connections with external researchers. I especially would like to thank Kymberley Scroggie and the Breaking Good project for providing data, analysis methods, and direction through this project.
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