Naegleria fowleri (N. fowleri) is a free-living thermophilic amoeba of fresh water and soil. The amoeba primarily feeds on bacteria but can be transmitted to humans upon contact with freshwater sources. Furthermore, this brain-eating amoeba enters the human body through the nose and travels to the brain to cause primary amebic meningoencephalitis (PAM). N. fowleri has been reported globally since its discovery in 1961. Recently a new strain of N. fowleri named Karachi-NF001 was found in a patient who had traveled from Riyadh, Saudi Arabia to Karachi in 2019. There were 15 unique genes identified in the genome of the Karachi-NF001 strain compared to all the previously reported strains of N. fowleri worldwide. Six of these genes encode well-known proteins. In this study, we performed in-silico analysis on 5 of these 6 proteins, namely, Rab family small GTPase, NADH dehydrogenase subunit 11, two Glutamine-rich protein 2 proteins (locus tags: 12086 and 12110), and Tigger transposable element-derived protein 1. We conducted homology modeling of these 5 proteins followed by their active site identification. These proteins were subjected to molecular docking against 105 anti-bacterial ligand compounds as potential drugs. Subsequently, the 10 best-docked compounds were determined for each protein and ranked according to the number of interactions and their binding energies. The highest binding energy was recorded for the two Glutamine-rich protein 2 proteins with different locus tags, and results have shown that the protein-inhibitor complex was stable throughout the simulation run. Moreover, future in-vitro studies could validate the findings of our in-silico analysis and identify potential therapeutic drugs against N. fowleri infections.

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The advent of bioinformatics and integrated biology approaches has given rise to new avenues of diagnostic and therapeutic regimes. Living systems have been explored to identify disease-associated biomarkers that facilitate the early diagnosis of perilous medical conditions. Likewise, gene networks are pondered upon to obtain better insights into biochemical systems that can assist in the prediction and testing of the effects of various interactions within the systems. Genomics and proteomics-based approaches are being explored to facilitate the early diagnosis of cancers, shifting the paradigm towards noninvasive diagnostic alternatives. Bioinformatics has also fueled pharmacogenomics and pharmacogenetics-based strategies that have in turn contributed to the development of personalized medications. Similarly, the reverse vaccinology approach has emerged as a prominent option to combat deadly pathogens that were otherwise unrestrainable. This chapter highlights the fruits of integrated bioinformatics in diagnosing and treating detrimental conditions.

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