1Kakinada Institute of Technological Sciences, Andhra Pradesh,533255
2Narasaraopeta Institute of Pharmaceutical Sciences, Palnadu, Andhra Pradesh, 533601
The increasing prevalence of opioid misuse and associated fatalities has highlighted an urgent need for safer analgesic alternatives. Synthetic narcotics such as morphine and fentanyl remain highly effective in clinical pain management but are associated with significant risks, including tolerance, dependence, and respiratory depression (Volkow et al., 2019). Natural alkaloids, derived from medicinal plants, possess diverse pharmacological properties and may provide novel therapeutic approaches with reduced abuse liability. In this study, computational docking and in silico pharmacological evaluations were performed on selected natural alkaloids—mitragynine, berberine, conolidine, noscapine, and papaverine—against ?-opioid (MOR), ?-opioid (KOR), and ?-opioid (DOR) receptors. Docking affinities and receptor-ligand interactions were compared to synthetic narcotics, including morphine, fentanyl, and oxycodone. Additionally, ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions were conducted to evaluate safety and drug-likeness. Results demonstrated that several alkaloids, particularly mitragynine and conolidine, exhibited strong receptor affinity with favorable pharmacokinetic properties. These findings support the hypothesis that natural alkaloids may serve as promising analgesic candidates, warranting further preclinical and clinical investigation.
1.1 The Opioid Crisis and the Need for Alternatives
Opioid analgesics, especially morphine, oxycodone, and fentanyl, are crucial for managing moderate to severe pain. However, over the past twenty years, there has been a sharp increase in opioid misuse, dependence, and overdose deaths (Kolodny et al., 2015). In the U.S., opioid overdoses caused more than 80,000 deaths in 2022 (CDC, 2023). Similar patterns are appearing worldwide, highlighting a global public health crisis. While opioids are effective pharmacologically, they also carry serious side effects, such as tolerance, physical dependence, respiratory depression, and gastrointestinal dysmotility (Pasternak and Pan, 2013). These issues call for the development of new analgesic drugs with better safety profiles.
1.2 Natural Alkaloids as Therapeutic Candidates
Alkaloids are nitrogen-containing secondary metabolites commonly found in plants. They exhibit a broad range of pharmacological effects, including analgesic, anti-inflammatory, antimalarial, and anticancer activities (Roberts and Wink, 1998). Historically, morphine, itself an alkaloid from Papaver somniferum, revolutionized pain treatment. More recently, plant-derived alkaloids such as mitragynine (from Mitragyna speciosa), conolidine (from Tabernaemontana divaricata), and noscapine (from Papaver somniferum) have attracted interest for their analgesic properties with potentially lower abuse liability (Kruegel and Grundmann, 2018; Tarselli et al., 2011).
Mitragynine, the major active compound in kratom, acts on μ-opioid receptors but displays partial agonist activity, potentially reducing the risk of respiratory depression (Varadi et al., 2016). Conolidine, a lesser-known alkaloid, exerts analgesic effects without significant opioid receptor binding, suggesting non-traditional pain pathways (Tarselli et al., 2011). Noscapine, while historically studied as an antitussive, has shown promise in anticancer and analgesic research (Ke et al., 2000).
1.3 Computational Pharmacology Approaches
The rise of computational pharmacology has transformed early-stage drug discovery. Molecular docking offers a rapid and cost-effective method for predicting ligand-receptor interactions and estimating binding affinities (Morris et al., 2009). Coupled with ADMET profiling, researchers can prioritize compounds with favorable drug-like properties before investing in resource-intensive laboratory and clinical studies (Daina et al., 2017). Such approaches have been widely applied to natural products in drug discovery pipelines (Ekins et al., 2007).
1.4 Aim of the Study
This study aims to evaluate the analgesic potential of selected natural alkaloids using computational docking and pharmacological profiling. Specifically, the objectives are:
2. MATERIALS AND METHODS
2.1 Selection of Compounds
Five natural alkaloids were selected based on literature evidence of analgesic or central nervous system activity: mitragynine, berberine, conolidine, noscapine, and papaverine. These compounds represent structurally diverse plant alkaloids with reported bioactivity in pain modulation or neuropharmacology (Kruegel and Grundmann, 2018; Tarselli et al., 2011).
As controls, three widely used synthetic narcotics were included: morphine, fentanyl, and oxycodone. Their well-characterized receptor interactions and clinical analgesic potency provided a benchmark for comparison (Pasternak and Pan, 2013).
Chemical structures were retrieved from PubChem in SDF format and optimized for docking by energy minimization using the MMFF94 force field in PyRx 0.8 (Dallakyan and Olson, 2015).
2.2 Protein Target Preparation
Crystal structures of human opioid receptors were obtained from the Protein Data Bank (PDB):
Proteins were prepared using AutoDock Tools by removing water molecules, adding missing hydrogens, and assigning Gasteiger charges. Binding pockets were defined based on co-crystallized ligands and literature data on opioid receptor active sites (Manglik et al., 2012).
2.3 Molecular Docking Procedure
Docking simulations were carried out using AutoDock Vina, which applies a gradient optimization method to predict binding free energy (Trott and Olson, 2010).
Docking poses were ranked by lowest binding free energy, and interaction analysis was performed with Discovery Studio Visualizer.
2.4 ADMET and Drug-Likeness Prediction
Pharmacokinetic and toxicity parameters were assessed using SwissADME (Daina et al., 2017), pkCSM (Pires et al., 2015), and ProTox-II (Banerjee et al., 2018). Evaluated properties included:
3. RESULTS
3.1 Docking Affinities
Table 1 summarizes binding affinities (ΔG, kcal/mol) of alkaloids and synthetic narcotics across the three receptors.
Table 1. Docking scores (kcal/mol) of natural alkaloids and synthetic narcotics against opioid receptors.
|
Compound |
μ-Opioid (MOR) |
κ-Opioid (KOR) |
δ-Opioid (DOR) |
|
Mitragynine |
-9.1 |
-8.6 |
-8.3 |
|
Conolidine |
-8.7 |
-8.2 |
-7.9 |
|
-8.3 |
-8.1 |
-7.8 |
|
|
Noscapine |
-8.0 |
-7.7 |
-7.4 |
|
Papaverine |
-7.6 |
-7.4 |
-7.2 |
|
Morphine |
-9.4 |
-8.9 |
-8.5 |
|
Fentanyl |
-10.2 |
-9.6 |
-9.1 |
|
Oxycodone |
-8.8 |
-8.3 |
-8.0 |
Synthetic narcotics demonstrated the strongest binding, particularly fentanyl at MOR (−10.2 kcal/mol). However, mitragynine and conolidine showed comparable affinities, suggesting potential efficacy as analgesic ligands.
3.2 Receptor–Ligand Interaction Profiles
3.3 ADMET Predictions
Table 2. Pharmacokinetic and toxicity profiles of selected compounds.
|
Compound |
GI Absorption |
BBB Penetration |
Hepatotoxicity |
Mutagenicity |
Rule of Five |
|
Mitragynine |
High |
Yes |
No |
No |
Pass |
|
Conolidine |
High |
Yes |
No |
No |
Pass |
|
Berberine |
Low |
No |
Possible |
No |
Fail (MW>500) |
|
Noscapine |
Moderate |
Yes |
No |
No |
Pass |
|
Papaverine |
Moderate |
Yes |
No |
No |
Pass |
|
Morphine |
High |
Yes |
No |
No |
Pass |
|
Fentanyl |
High |
Yes |
Yes |
Possible |
Pass |
|
Oxycodone |
High |
Yes |
No |
No |
Pass |
3.4 Comparative Insights
4. DISCUSSION
4.1 Comparison of Natural Alkaloids with Synthetic Narcotics
The results demonstrate that certain natural alkaloids, particularly mitragynine and conolidine, display binding affinities at the μ-opioid receptor comparable to morphine and oxycodone. While fentanyl unsurprisingly exhibited the strongest binding across all three receptors, its high potency is closely linked to increased risks of respiratory depression and overdose mortality (Volkow et al., 2019).
In contrast, mitragynine’s partial agonist activity at MOR and ability to interact with KOR and DOR suggest a broader pharmacological profile that may confer analgesia with reduced risk of respiratory depression and dependence (Varadi et al., 2016). Similarly, conolidine has been reported to produce analgesic effects through atypical mechanisms, possibly involving atypical chemokine receptor 3 (ACKR3), further reducing its risk of opioid-like side effects (Mendis et al., 2019).
These findings align with earlier reports highlighting that natural products often interact with multiple biological pathways, offering polypharmacological benefits compared to single-target synthetic drugs (Harvey et al., 2015).
4.2 ADMET Insights and Drug-Likeness
Pharmacokinetic profiling revealed that mitragynine and conolidine possess favorable oral bioavailability and blood–brain barrier penetration, critical for central analgesic action. Importantly, both compounds passed Lipinski’s Rule of Five, indicating good drug-likeness (Lipinski et al., 2001).
Conversely, berberine displayed poor gastrointestinal absorption and potential hepatotoxicity, consistent with prior reports of its limited oral bioavailability (Liu et al., 2016). Although noscapine and papaverine exhibited moderate binding and acceptable ADMET profiles, their comparatively weaker affinities suggest limited potential as primary analgesics.
Synthetic opioids showed high BBB penetration and favorable absorption, but their toxicity predictions (particularly for fentanyl) highlight the clinical trade-off between potency and safety (Kalso et al., 2003).
4.3 Clinical Relevance and Safety Considerations
The opioid crisis has fueled a demand for safer analgesics. Natural alkaloids may provide a valuable alternative by:
However, potential risks must not be overlooked. For example, mitragynine has been associated with dependence in chronic kratom users, though at substantially lower risk compared to synthetic opioids (Henningfield et al., 2018). Thus, preclinical validation and clinical trials remain essential to confirm efficacy and safety.
4.4 Limitations of the Study
This research is limited by its in silico nature. While molecular docking and ADMET predictions provide valuable early insights, they cannot fully capture the complexities of biological systems. Limitations include:
Nevertheless, computational approaches serve as a cost-effective screening tool to prioritize candidates for further experimental research.
CONCLUSION
This study highlights the promise of natural alkaloids as safer alternatives to synthetic narcotics. Mitragynine and conolidine demonstrated strong opioid receptor binding, favorable pharmacokinetic properties, and reduced predicted toxicity compared to conventional narcotics such as fentanyl. These results suggest that natural alkaloids represent a valuable starting point for developing next-generation analgesics with lower abuse potential. While synthetic opioids remain highly potent, their associated risks underscore the need for natural product-derived scaffolds with improved safety. Future research should integrate computational findings with laboratory assays and clinical investigations to advance these compounds toward therapeutic application.
FUTURE PERSPECTIVES
By combining traditional pharmacognosy with modern computational pharmacology, novel plant-derived alkaloids may contribute significantly to the next generation of safer analgesics.
REFERENCES
Kumbha Ravindra, Ganta Lakshmana, Computational Docking and Pharmacological Evaluation of Natural Alkaloids as Safer Alternatives to Synthetic Narcotics, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 9, 3326-3332. https://doi.org/10.5281/zenodo.17223260
10.5281/zenodo.17223260