Bacterial and protozoan diseases continue to exact a heavy global toll. Neglected tropical diseases affect large populations [1], malaria still causes hundreds of thousands of deaths annually [2], and bacterial antimicrobial resistance is steadily rising [3]. Treatments for several protozoan infections, such as Chagas’ disease and leishmaniasis, remain toxic, while emerging resistance—like partial resistance to artemisinin in malaria—threatens efficacy [4,5]. Historically, drug discovery in these areas has relied heavily on phenotypic screening. While effective for identifying active compounds, this approach often leaves mechanisms unresolved and potential liabilities undiscovered until late. On-target effects are typically inferred indirectly through genetic manipulation, phenotypic assays, and rescue experiments—methods that are informative but limited in precision and scalability [6,7].

To overcome these challenges, target engagement (TE) assays have emerged as a powerful complement [8,9]. These approaches directly measure compound–target interactions, offering mechanistic clarity and enabling more rational drug development. In vitro, biophysical and enzymatic assays provide critical insights into affinity, thermodynamics, and kinetics that guide structure–activity relationships (SARs) and medicinal chemistry. In cellular contexts—using intact cells or lysates—proteomics-based strategies help confirm mechanisms and deconvolute targets. Finally, live-cell, single-target TE readouts enable triage of hits with verified engagement and sufficient intracellular exposure under physiologically relevant conditions.

While TE profiling is now routine for human targets—helping identify liabilities, de-risk programs, and accelerate discovery [9]—its application to bacteria and protozoa remains limited. Many pathogen proteins are difficult to express in active, soluble form, and their complex life cycles, specialized intracellular niches, and restricted xenobiotic access complicate cellular readouts. Additionally, the lack of high-quality chemical tools and protein reagents for many pathogen targets continues to hinder assay development. We anticipate this will change as computational approaches, including machine learning, increasingly exploit the wealth of genomic data and emerging high-quality ligand–protein interaction datasets [10] to identify chemical tools and enable TE assay development for pathogens.

The following sections review TE methods for bacterial and protozoan pathogens, with a specific focus on protein targets. We outline the strengths and limitations of each approach to guide method selection. To support this, Figure 1 summarizes the landscape of cellular context target engagement assays for bacterial and protozoan pathogens, organized by label dependence, scope, and experimental context.