Discover how computational methods are identifying plant-based compounds to fight tuberculosis by targeting the DHFR enzyme through in-silico drug discovery.
Tuberculosis (TB) is a disease that has haunted humanity for millennia, caused by the cunning pathogen Mycobacterium tuberculosis. Despite centuries of medical advances, TB remains a devastating global health crisis.
Ranking as the second leading infectious killer worldwide after COVID-19, TB claimed approximately 1.25 million lives in 2023 alone9 . The situation has deteriorated with the emergence of multi-drug resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains, which defy conventional treatments and pose a grave threat to global health security4 .
The search for new therapeutic solutions has led researchers down an unexpected path—back to nature, but with a technological twist. In laboratories worldwide, scientists are now performing digital experiments on computer-generated models of the tuberculosis bacterium, testing thousands of medicinal plant compounds without ever touching a petri dish. This innovative approach represents the cutting edge of drug discovery, where ancient botanical wisdom meets 21st-century computational power.
TB deaths in 2023
Leading infectious killer worldwide
To understand how these digital experiments work, we must first examine the bacterial weak point they target: an enzyme called dihydrofolate reductase, or DHFR. This enzyme serves as an essential lifeline for the tuberculosis bacterium, performing a critical function in its survival kit2 3 .
DHFR acts as a molecular factory worker in the folate metabolic pathway, catalyzing the NADPH-dependent reduction of dihydrofolate to tetrahydrofolate (THF)3 . This might sound like biochemical jargon, but its practical importance is straightforward: THF is indispensable for creating the building blocks of DNA and RNA8 . Without it, the bacterium cannot replicate its genetic material or multiply.
By blocking DHFR, we essentially starve the bacterium of its reproductive capacity, leading to cellular collapse and death3 .
This strategic approach is particularly appealing because it targets a fundamental process in bacterial cells while offering researchers a specific molecular structure to aim for with precision-designed therapeutics.
DNA Synthesis
RNA Synthesis
DHFR catalyzes the conversion of dihydrofolate to tetrahydrofolate, essential for DNA and RNA synthesis in bacterial cells.
The traditional drug discovery process is notoriously lengthy and expensive, often requiring 10-15 years and billions of dollars to bring a single medication to market. In-silico methods have dramatically accelerated this timeline by leveraging computational power to screen potential drug candidates before ever synthesizing them chemically3 8 .
"In-silico" simply means "performed on computer or via computer simulation." Think of it as a virtual laboratory where scientists can test thousands of compounds against a digital model of their target protein. The process typically involves several sophisticated techniques:
Researchers use specialized software to predict how small molecules (potential drugs) will interact with and bind to the target protein8 .
This involves computationally testing thousands or even millions of compounds from digital libraries to identify those with the strongest predicted affinity for the target3 .
Absorption, distribution, metabolism, excretion, and toxicity properties are predicted using algorithms to filter out compounds with undesirable characteristics early in the process8 .
These simulations test the stability of the protein-ligand complex over time, providing insights into how the interaction might hold up in a real biological environment3 .
Reduction in discovery time
A landmark 2025 study published in RSC Advances exemplifies the power of this approach3 8 . The research team embarked on an ambitious mission to identify novel DHFR inhibitors from a library of 1,026 drug-like molecules with known antibacterial properties.
The researchers obtained the three-dimensional crystal structure of M. tuberculosis DHFR (PDB ID: 1DG5) from the Protein Data Bank. They then prepared the protein for docking by removing water molecules and optimizing the structure8 .
The investigators collected antibacterial compounds from the ChEMBL database, creating a diverse virtual library to screen8 .
Using AutoDock Vina and the Schrodinger Suite, the team computationally "tested" each compound by docking it into the active site of DHFR. The software calculated binding affinities—a measure of how tightly each compound interacts with the target8 .
Promising candidates were analyzed for desirable pharmaceutical properties using the SwissADME platform, which predicts factors such as solubility, absorption, and metabolic stability8 .
The most promising complexes underwent 100 nanosecond molecular dynamics simulations to confirm the stability of the interactions under conditions mimicking the cellular environment8 .
The virtual screening yielded exciting results, identifying three compounds with exceptional binding properties to DHFR:
| Compound ID | Binding Affinity (kcal/mol) | Comparison to Standard Drugs |
|---|---|---|
| CHEMBL577 | -10.2 | Superior to controls |
| CHEMBL161702 | -9.8 | Superior to controls |
| CHEMBL1770248 | -9.5 | Superior to controls |
| Trimethoprim (control) | -7.3 | Reference compound |
| Methotrexate (control) | -7.9 | Reference compound |
Remarkably, all three identified compounds outperformed the control drugs trimethoprim and methotrexate in both binding affinity and complex stability3 8 . The molecular dynamics simulations revealed that these compounds formed stable interactions with the DHFR active site, maintaining their position with minimal structural fluctuation throughout the simulation—a strong indicator of effective inhibition.
The virtual screening identified three standout compounds—CHEMBL577, CHEMBL161702, and CHEMBL1770248—that consistently outperformed established DHFR inhibitors in computational tests8 . What makes these findings particularly significant is that these compounds maintained their strong binding throughout the 100-nanosecond molecular dynamics simulations, suggesting they form stable and enduring interactions with the bacterial enzyme.
This stability is crucial for effective drug action, as a stable drug-target complex means prolonged inhibition of the enzyme's function. Additionally, ADMET predictions indicated that these compounds possess favorable drug-like properties, suggesting they would be well-absorbed, distributed appropriately in the body, and have acceptable toxicity profiles8 .
| Aspect | Conventional TB Drugs | Novel Plant-Based DHFR Inhibitors |
|---|---|---|
| Selectivity | Often affect human cells | Can be designed for bacterial specificity |
| Resistance | Increasing MDR/XDR-TB cases | Novel mechanisms may bypass resistance |
| Toxicity | Significant side effects | Potentially better safety profiles |
| Source | Synthetic or semi-synthetic | Natural origin with optimization |
The selective targeting of bacterial DHFR over the human version is particularly important. While human and bacterial DHFR perform similar functions, structural biologists have identified key differences in their active sites. The M. tuberculosis DHFR has a unique glycerol-binding motif not found in the human enzyme, providing a structural basis for designing selective inhibitors that minimize side effects5 .
The promising compounds identified through virtual screening join a growing list of plant-derived molecules with demonstrated anti-tubercular potential. Nature has long served as humanity's medicine cabinet, with approximately 80% of people in developing nations relying on traditional plant-based medicines for their primary healthcare needs4 .
Recent research has highlighted several medicinal plants with particular promise against tuberculosis:
A plant used in traditional medicine, has shown potent anti-tubercular activity in laboratory studies. Bioactive compounds isolated from this plant demonstrated multi-targeting effects against several essential M. tuberculosis enzymes, including DHFR, isocitrate lyase, and ATP synthase9 .
This multi-target action is particularly valuable against drug-resistant strains, as simultaneously attacking multiple bacterial systems makes it more difficult for the pathogen to develop resistance.
Plants like Costus speciosus, Cymbopogon citratus (lemongrass), and Tabernaemontana coronaria have also shown significant anti-mycobacterial activity in preliminary studies7 .
The rich chemical diversity of plants—including alkaloids, flavonoids, terpenes, and phenolic compounds—provides an extensive library of molecular structures that have evolved through millennia of biological warfare against pathogens.
Molecular docking software to predict compound binding
Comprehensive computational chemistry platform
Online tool for predicting drug absorption and metabolism
Curated database of bioactive molecules
Simulates protein-ligand interactions over time
The integration of computational approaches with ethnobotanical knowledge represents a paradigm shift in how we discover new treatments for ancient diseases like tuberculosis. The success of in-silico methods in identifying potent DHFR inhibitors from medicinal plants underscores the power of this combined approach.
While the identification of CHEMBL577, CHEMBL161702, and CHEMBL1770248 as promising DHFR inhibitors is encouraging, the researchers behind the study emphasize that these computational findings represent just the first step in a longer journey3 8 . The logical next steps involve wet-lab experiments to validate these computational predictions, beginning with enzyme inhibition assays and progressing to cell-based studies and eventually animal models.
"The promise of structural biology is that if we can see the molecular basis of disease, we can design a cure."
In the fight against tuberculosis, we're now witnessing how computer simulations are helping us see that molecular basis more clearly than ever, while nature's chemical library provides the raw materials for designing those cures. This powerful combination may well hold the key to finally defeating one of humanity's oldest and most adaptable microbial foes.