Conclusion

This investigation, which focuses primarily on exploring the potential of chemical compounds as inhibitors of exotoxin A from the bacterium Pseudomonas aeruginosa, uses bioinformatics paradigms as its basis.

Bioinformatics was the vehicle for carrying out this research into the design of inhibitors of exotoxin A from Pseudomonas aeruginosa. This project is based on the pillars of informatics – the automation of work routines, the ability to process large volumes of data and the ability to analyze complex information. Automation, through computer programs with customized operating scripts, guided the execution of simulations and analyses that would be impractical to perform manually, which saved time and available resources. This prioritization of in silico allows for a fast, accessible and sustainable analysis of compounds (FERREIRA, 2011).

Computational methodologies – ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) analyses and molecular docking – generate a spectrum of pharmacological qualifications that place the compounds in categories of clinical applicability and interest for future testing. In this way, a screening of drug candidates is facilitated, considering the underlying molecular interactions between the inhibitors and exotoxin A (FERREIRA, 2011).

The preliminary results obtained to date indicate that three samples derived from PJ34, by exhibiting more extensive R groups, showed a therapeutic potential up to approximately 10% greater compared to the standard compound. This finding is of utmost importance, because it suggests that structural modifications in the compounds can result in marked improvements in therapeutic efficacy.

It is important to highlight that these identified inhibitors, despite their design having been made in favor of the specific inhibition of exotoxin A, may have applications in other pathological contexts related to Pseudomonas aeruginosa, such as exoenzymes S and T and exotoxin U (excreted by P. aeruginosa).

The multidimensional view of the applicability of these new inhibitors may enable the development of more effective combinatorial therapies in the clinical management of serious infections caused by Pseudomonas aeruginosa.

Therefore, the initial hypothesis was confirmed. This is justified, since derivatives of PJ34, such as Samples 4, 12 and 11, with the extended R group, presented a holistic performance superior to that of the original molecule. Thus, this modification resulted in an improvement, which can be explored for the development of drugs.

FERREIRA, R S, GLAUCIUS, O e ANDRICOPULO, A D. Integração das técnicas de triagem virtual e triagem biológica automatizada em alta escala: oportunidades e desafios em P&D de fármacos. Química Nova [online]. 2011, v. 34, n. 10 [Acessado 16 Outubro 2024], pp. 1770- 1778. Disponível em: <https://doi.org/10.1590/S0100-40422011001000010>. Epub 06 Dez 2011. ISSN 1678-7064. https://doi.org/10.1590/S0100-40422011001000010.