Anti-infective agents are used to kill infectious pathogens or inhibit their replication, expansion, and transmission. Bacteria, fungi, viruses, and protozoa differ markedly in structural composition, replication mode, and host dependence. Therefore, anti-infective research should not remain limited to drug classification, but should further define drug targets, changes in pathogen burden, the degree of host injury, and resistance risk.

Keywords: anti-infective; antibacterial agents; antifungal agents; antiviral agents; antiprotozoal agents; drug targets; resistance mechanisms; host immune response

1 Basic Logic of Anti-Infective Research

1.1 Research Objects and Target Levels

Anti-infective agents cover four major types of pathogens: bacteria, fungi, viruses, and protozoa. Experimental design should first determine the pathogen type, and then set corresponding drug targets and detection endpoints according to its key life processes.

(1) Bacteria

Bacteria have peptidoglycan cell walls, 70S ribosomes, DNA replication systems, and cell membrane structures. Antibacterial agents commonly act on cell wall synthesis, protein synthesis, DNA replication, RNA transcription, or cell membrane integrity. For bacteria capable of forming biofilms, planktonic bacteria, early adhesion, and mature biofilm states should also be distinguished, because their drug sensitivity and tolerance mechanisms differ.

(2) Fungi

Fungi are eukaryotic microorganisms. Their cell membranes contain ergosterol, and their cell walls contain β-glucan, chitin, and mannan. Antifungal agents commonly establish their mechanisms around ergosterol synthesis, cell wall synthesis, nucleic acid synthesis, hyphal formation, and biofilm tolerance. Because fungi and hosts both belong to eukaryotic systems, selectivity and host toxicity are core limiting factors in antifungal research.

(3) Viruses

Viruses do not have complete cellular structures and must rely on host cells to complete entry, uncoating, replication, protein processing, assembly, and release. Antiviral agents usually act on specific stages of the viral life cycle and should not simply be described as “killing viruses.” In experiments, reductions in viral nucleic acids, reductions in infectious virus, and alleviation of cytopathic effects should be distinguished.

(4) Protozoa

Protozoa have complex structures, and some protozoa have special metabolic processes and stage conversion characteristics. Taking Plasmodium as an example, the intraerythrocytic stage depends on hemoglobin digestion, heme detoxification, folate synthesis, mitochondrial function, and redox homeostasis. Antiprotozoal drug research should define the target parasite stage and simultaneously exclude false-positive results caused by host cell injury.

1.2 Core Interpretation of Anti-Infective Efficacy

Anti-infective experiments need to answer the following questions simultaneously:

(1) Whether the pathogen is truly reduced

Bacterial studies should observe CFU, MIC, MBC, and time-kill curves. Viral studies should detect viral load and infectious viral titer. Fungal studies should distinguish inhibition of planktonic cells, inhibition of hyphal formation, and clearance of mature biofilms. Protozoal studies should detect parasite burden, stage distribution, and host cell injury.

(2) Which stage the drug acts on

Antibacterial agents should be localized to cell wall, ribosome, DNA replication, RNA transcription, or membrane structures. Antiviral agents should distinguish the entry, replication, integration, maturation, or release stages. Antimalarial agents should define whether they act on ring forms, trophozoites, schizonts, or other parasite stages.

(3) Whether host injury is improved

Infectious pathology is not caused only directly by pathogens, but is also related to inflammatory responses, cell death, and tissue injury. If inflammatory factors decrease but pathogen burden does not decrease, the result should be described as anti-inflammatory or tissue-protective rather than directly as an anti-infective effect.

(4) Whether resistance risk is controllable

Resistance can arise from target mutations, drug inactivation, enhanced efflux pumps, biofilm tolerance, high-frequency viral mutation, or parasite metabolic adaptation. Candidate drugs should include serial passage, resistant-strain validation, and target sequencing in early-stage research.

Table 1 Key Evaluation Dimensions in Anti-Infective Research

2 Targets of Antibacterial Agents

2.1 Inhibition of Cell Wall Synthesis

(1) Mechanistic core

Penicillins and cephalosporins bind to penicillin-binding proteins (PBPs), inhibit peptidoglycan crosslinking, and thereby block bacterial cell wall synthesis. The cell wall can be understood as a supporting structure that helps bacteria resist osmotic pressure. Once this structure is disrupted, bacteria are more prone to lysis.

(2) Experimental indicators

Common indicators include MIC, MBC, time-kill curves, β-lactamase activity, PBP expression or mutation, bacterial morphology observation, and regrowth assays.

(3) Result interpretation

An increase in MIC only indicates decreased drug sensitivity and does not directly explain the resistance mechanism. Increased β-lactamase activity suggests drug hydrolysis, while PBP alterations suggest reduced target affinity. If MIC is not high but killing is slow, tolerance, persister cells, or the biofilm microenvironment should be considered.

2.2 Inhibition of Protein Synthesis

(1) Mechanistic core

Aminoglycosides, tetracyclines, and macrolides mainly act on bacterial ribosomes. Ribosomes are the core structures for bacterial protein synthesis. When drugs interfere with translation, bacteria cannot continuously produce proteins required for vital activities. Aminoglycosides are often associated with mistranslation and rapid bactericidal activity, while tetracyclines and macrolides more often show bacteriostatic effects.

(2) Experimental indicators

Common indicators include protein synthesis level, bacterial growth curve, CFU, ribosomal target mutations, target methylation, efflux pump expression, and membrane potential changes.

(3) Result interpretation

Inhibition of protein synthesis is not equivalent to bacterial killing. If OD no longer increases but CFU does not decrease significantly, the effect should be described as bacteriostatic. Only a clear decrease in viable count supports a bactericidal effect. For aminoglycosides, low-oxygen, acidic, or biofilm environments may reduce drug uptake and killing efficiency.

2.3 Inhibition of DNA Replication and RNA Transcription

(1) Mechanistic core

Fluoroquinolones inhibit DNA gyrase and topoisomerase IV, blocking bacterial DNA replication. Rifamycins inhibit bacterial RNA polymerase and affect RNA transcription. These drugs act on genetic information replication and expression processes and can produce obvious growth inhibition or bactericidal effects.

(2) Experimental indicators

DNA damage response, SOS response, gyrA/gyrB/parC/parE mutations, rpoB mutations, time-kill curves, and MIC changes after serial passage can be detected.

(3) Result interpretation

Strong short-term killing does not mean low resistance risk. If sub-inhibitory concentrations induce an SOS response or MIC increases after serial passage, this suggests that drug pressure may promote accumulation of resistance mutations and should be evaluated together with dose window and combination strategies.

2.4 Membrane Disruption and Alternative Antibacterial Strategies

(1) Mechanistic core

Antimicrobial peptides, polymyxins, and some membrane-targeting agents can disrupt bacterial membrane structure or membrane potential, leading to leakage of cellular contents. Photodynamic therapy (PDT) uses a photosensitizer, light of a specific wavelength, and oxygen molecules to generate ROS, further damaging bacterial membranes, proteins, and nucleic acids.

(2) Experimental indicators

Common indicators include membrane permeability, membrane potential, ROS, CFU, biofilm clearance rate, host cytotoxicity, and hemolysis risk.

(3) Result interpretation

Membrane-disrupting strategies must be evaluated for selectivity. If the bactericidal concentration is close to the host cytotoxic concentration, the development value is limited even if in vitro antibacterial activity is obvious. PDT experiments should include photosensitizer-only, light-only, and photosensitizer plus light groups; otherwise, it cannot be demonstrated that the bactericidal effect originates from the photodynamic reaction.

3 Targets of Antifungal Agents

3.1 Cell Membrane Ergosterol

(1) Mechanistic core

Fungal cell membranes contain ergosterol, whereas mammalian cell membranes mainly contain cholesterol. Azole drugs inhibit ergosterol synthesis, while polyene drugs bind to ergosterol and disrupt membrane integrity. This difference is an important basis for antifungal selectivity.

(2) Experimental indicators

Ergosterol content, membrane permeability, CYP51/ERG pathway changes, efflux pump expression, fungal growth curves, host cytotoxicity, and selectivity index can be detected.

(3) Result interpretation

Antifungal activity must be evaluated together with host safety. If the fungal inhibitory concentration is close to the host cytotoxic concentration, selectivity is insufficient and the drug is not suitable as a priority candidate. If the CYP51/ERG pathway is altered or efflux pumps are enhanced, resistance to membrane-targeting antifungal agents may be present.

3.2 Cell Wall β-Glucan

(1) Mechanistic core

The fungal cell wall contains β-glucan, chitin, and mannan, which are important structures distinguishing fungi from host cells. Echinocandins inhibit β-1,3-glucan synthesis, weaken cell wall integrity, and make fungi more sensitive to osmotic and environmental stress.

(2) Experimental indicators

β-glucan content, chitin compensation, cell wall integrity, FKS mutations, hyphal formation, biofilm formation, and osmotic sensitivity can be detected.

(3) Result interpretation

Cell wall-targeting drugs do not necessarily show strong fungicidal effects; they may mainly weaken hyphal formation, invasive capacity, or in vivo adaptation. Therefore, MIC results should be evaluated together with morphology, biofilm models, and infection models.

3.3 Biofilms and Drug-Resistant Fungi

(1) Mechanistic core

Fungal biofilms can increase drug tolerance through extracellular matrix barriers, altered metabolic states, enhanced efflux pumps, and stress adaptation. Sensitivity of planktonic cells does not mean that mature biofilms can be cleared.

(2) Experimental indicators

Planktonic MIC, biofilm biomass, mature biofilm clearance rate, XTT/ATP metabolic activity, extracellular matrix, hyphal proportion, and efflux pump expression can be detected.

(3) Result interpretation

If a drug reduces crystal violet staining signals but does not reduce CFU within the biofilm, it may only reduce matrix or adhesion and does not necessarily represent true clearance of infectious fungal cells. Mature biofilm evaluation should preferably combine viable counts or metabolic activity detection.

4 Targets of Antiviral Agents

Figure 1. Schematic Diagram of the HIV Replication Cycle

4.1 Viral Entry Stage

(1) Mechanistic core

Viral entry into host cells usually includes adsorption, receptor binding, membrane fusion, or endocytosis. Entry inhibitors and neutralizing antibodies mainly act before infection is established and can reduce the opportunity for viruses to enter cells.

(2) Experimental indicators

Adsorption assays, fusion assays, time-of-addition experiments, detection of infection-positive cell proportion, and early viral RNA detection can be performed.

(3) Result interpretation

If the drug is effective when added before infection or during early infection but ineffective when added after infection, this usually suggests that it acts on viral entry or early uncoating. If it remains effective after infection, actions on replication, protein processing, or release should be further investigated.

4.2 Viral Replication Stage

(1) Mechanistic core

Viral replication depends on viral polymerases, reverse transcriptases, or the host cellular replication environment. Nucleoside/nucleotide analogs can block viral genome amplification through chain termination or polymerase inhibition. Retroviruses such as HIV also involve conversion of RNA to DNA and genome integration.

(2) Experimental indicators

Viral load, qPCR, replicon systems, polymerase activity, reverse transcription products, integrated copy number, chain termination effects, and resistance mutations can be detected.

(3) Result interpretation

Alleviation of cytopathic effects does not equal inhibition of viral replication. If cell viability improves but viral nucleic acids or infectious titers do not decrease, the drug may mainly have cytoprotective or anti-inflammatory effects. Antiviral studies should report both viral nucleic acid levels and infectious viral titers whenever possible.

4.3 Viral Maturation and Release Stage

(1) Mechanistic core

Some viruses require protease processing to form mature viral particles or depend on release-related enzymes to spread to new cells. HIV protease inhibitors and influenza virus neuraminidase inhibitors belong to this mechanism category.

(2) Experimental indicators

Viral protein processing, mature viral particles, viral titer in supernatants, infectious titer, and second-round infection capacity can be detected.

(3) Result interpretation

The presence of intracellular viral proteins does not mean that the drug is ineffective. If infectious virus in the supernatant decreases while intracellular viral proteins show limited changes, the drug may act on viral maturation, assembly, or release.

4.4 Antiviral Resistance

(1) Serial passage

Viruses are observed under continuous drug pressure to determine whether sensitivity decreases across passages. If EC50 stably increases with passage, resistance selection may have occurred. If it is only a single fluctuation in efficacy, viral inoculum, cell status, drug stability, and batch differences should first be excluded.

(2) Target sequencing

Key drug targets such as polymerase, reverse transcriptase, integrase, protease, and neuraminidase should be examined. If reduced efficacy is accompanied by target mutations, the resistance mechanism is more strongly supported. If no target mutation is found, changes in host-dependent factors, viral adaptation, or non-target tolerance mechanisms should be further considered.

(3) Replicative fitness

Resistance mutations may reduce, maintain, or enhance viral replication capacity. If mutant viruses retain strong replication capacity, the resistant strain has expansion and transmission risk. If replication capacity is clearly reduced, the fitness cost of the resistance mutation should be evaluated.

(4) Result interpretation

Antiviral resistance cannot be judged solely by a single decrease in efficacy. Resistance mechanisms are supported only when stable EC50 shifts appear under drug pressure and are accompanied by target mutations or changes in replicative fitness.

Table 2 Action Stages of Antiviral Agents and Validation Methods

5 Antiprotozoal Agents and Antimalarial Research

5.1 Heme Metabolism

(1) Mechanistic core

During the intraerythrocytic stage, Plasmodium digests hemoglobin and produces free heme, which is toxic to the parasite. Some antimalarial agents interfere with the conversion of heme into hemozoin, causing toxic heme accumulation and parasite injury.

(2) Experimental indicators

Parasite burden, intraerythrocytic morphology, heme, hemozoin, ROS, IC50, erythrocyte lysis, and host cytotoxicity can be detected.

(3) Result interpretation

If parasite reduction is accompanied by obvious erythrocyte rupture, false-positive antimalarial results caused by nonspecific erythrocyte injury should be excluded. Antimalarial evaluation should focus simultaneously on parasite killing and host erythrocyte safety.

5.2 Folate Metabolism and Mitochondrial Function

(1) Mechanistic core

Folate metabolism participates in nucleic acid synthesis, while mitochondrial function participates in energy metabolism and redox homeostasis. Different parasite stages depend differently on metabolic targets, so drug sensitivity may be stage-selective.

(2) Experimental indicators

For folate metabolism, DHFR/DHPS, nucleic acid synthesis, and combination effects can be detected. For mitochondrial function, membrane potential, ATP levels, ROS, and parasite stage distribution can be detected.

(3) Result interpretation

When a drug is effective only at a specific parasite stage, the target stage should be clearly stated, and the drug should not be directly described as having broad-spectrum antiprotozoal activity. If a candidate is effective against sensitive strains but clearly loses activity against resistant strains, the value of structural optimization or combination therapy should be further evaluated.

5.3 Antimalarial Drug Discovery Strategies

(1) Natural product screening

Natural product screening is suitable for discovering new structural scaffolds, but parasite inhibitory activity, selectivity index, and mechanism of action must be further confirmed. In vitro inhibitory signals alone are insufficient to support candidate drug positioning.

(2) Structural modification of existing drugs

This approach is often used to improve activity, reduce toxicity, or overcome existing resistance. After structural modification, the parent compound and derivatives should be compared simultaneously for IC50, host toxicity, resistant-strain sensitivity, and metabolic stability.

(3) Hybrid compound development

This strategy attempts to achieve multi-target activity by combining different pharmacophoric fragments. It is necessary to prove that the hybrid structure truly provides synergy or improves the resistance barrier, rather than simply combining two pharmacophoric fragments.

(4) Repurposing of approved drugs

This can shorten the development cycle, but nonspecific cytotoxicity must be excluded. If the antiparasitic concentration is close to the host cytotoxic concentration, its development value should be judged cautiously.

(5) Virtual screening and molecular docking

These methods can predict the binding ability of candidate molecules to targets, but cannot replace phenotypic efficacy and target validation. Molecular docking results should enter the workflow of parasite growth inhibition, target validation, resistant-strain sensitivity testing, and selectivity index evaluation.

6 Host Anti-Infective Signaling Pathways

6.1 TLR/NF-κB Pathway

(1) Mechanistic core

The TLR/NF-κB pathway can recognize bacterial, fungal, and some viral components and induce expression of inflammatory factors such as TNF-α, IL-1β, and IL-6. This pathway acts like an early alarm system during infection and helps initiate immune responses, but excessive activation can also cause tissue injury.

(2) Experimental indicators

TNF-α, IL-1β, IL-6, NF-κB activation, pathogen burden, cell injury, and histopathology can be detected.

(3) Result interpretation

When inflammatory factors decrease but pathogen burden does not decrease, the result should be described as anti-inflammatory or tissue-protective, not directly as anti-infective. Only when inflammation decreases together with pathogen burden can improvement in anti-infective outcome be supported.

6.2 RIG-I/MDA5 and cGAS-STING Pathways

(1) Mechanistic core

RIG-I/MDA5 mainly recognizes cytoplasmic viral RNA, while cGAS-STING mainly recognizes cytoplasmic DNA. Both can induce type I interferon responses. These pathways are important mechanisms by which cells recognize viral infection and are also key targets of viral immune evasion.

(2) Experimental indicators

RIG-I, MDA5, cGAS, STING, p-TBK1, IRF3, IFN-β, ISG15, MX1, OAS1, and viral load can be detected.

(3) Result interpretation

Enhanced interferon signaling must correspond to reduced viral load to support effective antiviral activity. Simply increasing IFN or ISG expression does not prove that viral replication has been inhibited.

6.3 JAK/STAT Pathway

(1) Mechanistic core

After interferons bind to their receptors, the JAK/STAT pathway is activated and induces ISG antiviral gene expression. Many viruses evade immune clearance by inhibiting STAT phosphorylation or blocking ISG effects.

(2) Experimental indicators

p-STAT1, p-STAT2, ISG expression, viral replication level, and cell injury can be detected.

(3) Result interpretation

Only when a drug restores p-STAT and ISG expression and simultaneously reduces viral load can it be supported as enhancing host antiviral activity. If only p-STAT elevation is observed while viral load remains unchanged, overinterpretation as effective antiviral activity should be avoided.

6.4 NLRP3 Inflammasome Pathway

(1) Mechanistic core

The NLRP3 inflammasome can promote Caspase-1 activation, maturation and release of IL-1β and IL-18, and pyroptosis. This pathway can participate in pathogen control, but it may also amplify infectious inflammatory injury.

(2) Experimental indicators

NLRP3, cleaved Caspase-1, mature IL-1β, IL-18, GSDMD cleavage, pathogen burden, and cell death can be detected.

(3) Result interpretation

If tissue injury decreases after NLRP3 inhibition but pathogen burden increases, this indicates that the pathway participates in both inflammatory injury and pathogen clearance. It should not simply be assumed that NLRP3 inhibition is always beneficial for anti-infective outcomes.

Table 3 Host Anti-Infective Pathways and Result Interpretation

7 Resistance Mechanisms and Research Strategies

7.1 Antibacterial Resistance

(1) β-Lactams

β-Lactamase, PBP alterations, and outer membrane porin changes should be emphasized. If β-lactamase activity increases, drug hydrolysis may explain loss of efficacy. If PBPs are altered, reduced target binding ability is suggested.

(2) Quinolones

gyrA, gyrB, parC, and parE mutations should be emphasized. If MIC increases after serial passage and is accompanied by target mutations, clear resistance selection pressure is indicated.

(3) Macrolides

Ribosomal target methylation, efflux pumps, and 50S subunit-related changes should be emphasized. If drug accumulation decreases, enhanced efflux pumps should be investigated first.

(4) Biofilm-related resistance

The number of viable cells within mature biofilms should be emphasized, rather than evaluating only planktonic MIC. Low-metabolic cells and persister cells in mature biofilms can significantly reduce drug sensitivity.

7.2 Antifungal Resistance

(1) Membrane-targeting drugs

CYP51, the ERG pathway, and efflux pumps should be emphasized. Alterations in the ergosterol pathway or enhanced drug efflux can reduce sensitivity to azole drugs.

(2) Cell wall-targeting drugs

FKS mutations and changes in β-glucan synthesis should be emphasized. Some fungi can compensate for cell wall stress by increasing chitin synthesis.

(3) Biofilm tolerance

Mature biofilm clearance rate and metabolic activity should be emphasized. If planktonic cells are sensitive but biofilms are tolerant, combination therapy or biofilm-inhibitory strategies should be considered.

7.3 Antiviral Resistance

(1) Serial passage

Viruses are observed under continuous drug pressure to determine whether sensitivity decreases across passages. If EC50 stably increases with passage, resistance selection may have occurred. If it is only a single fluctuation in efficacy, viral inoculum, cell status, drug stability, and batch differences should first be excluded.

(2) Target sequencing

Key drug targets such as polymerase, reverse transcriptase, integrase, protease, and neuraminidase should be examined. If reduced efficacy is accompanied by target mutations, the resistance mechanism is more strongly supported. If no target mutation is found, changes in host-dependent factors, viral adaptation, or non-target tolerance mechanisms should be further considered.

(3) Replicative fitness

Resistance mutations may reduce, maintain, or enhance viral replication capacity. If mutant viruses retain strong replication capacity, the resistant strain has expansion and transmission risk. If replication capacity is clearly reduced, the fitness cost of the resistance mutation should be evaluated.

(4) Result interpretation

Antiviral resistance cannot be judged solely by a single decrease in efficacy. Resistance mechanisms are supported only when stable EC50 shifts appear under drug pressure and are accompanied by target mutations or changes in replicative fitness.

7.4 Antiprotozoal Resistance

(1) Comparison between sensitive and resistant strains

Antiprotozoal resistance research should compare sensitive strains and resistant strains simultaneously. If a candidate is effective only against sensitive strains but shows clearly decreased efficacy against resistant strains, it should be cautiously positioned as a new antiprotozoal candidate.

(2) Drug uptake and transporters

Reduced drug uptake or transporter alterations can decrease the effective drug concentration inside parasites. If drug efflux or abnormal transport is consistent with reduced efficacy, transporter-related resistance should be considered.

(3) Target mutations and metabolic compensation

Target mutations can reduce drug binding ability, while metabolic compensation can bypass inhibited pathways. Antiprotozoal resistance analysis should correlate target sequencing, metabolic pathway changes, and efficacy shifts.

(4) Interpretation of combination therapy

If combination therapy restores sensitivity in resistant strains, the combination strategy may improve the resistance barrier. If the combination remains ineffective, target selection and drug entry into the parasite should be reassessed.

Table 4 Anti-Infective-Related Product Lines and Application Directions

Table 5 Representative Products for Anti-infective Research

The core of anti-infective research is to correlate pathogen targets, drug action stages, host injury, and resistance risk. Only when the drug action site, pathogen burden changes, host toxicity, and resistance evolution are described simultaneously can anti-infective experimental results have mechanistic interpretability and translational value.

References

[1] Dehghan Esmatabadi MJ, et al. Cell Mol Biol (Noisy-le-grand). 2017 Feb 28;63(2):40-48.

[2] Raymund R, et al. Mayo Clin Proc. 2011 Oct;86(10):1009-1026.

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