Name: Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors (Video) | JoVE Journal
Uploaded: 2025-05-09T12:40:00.000+00:00
Duration: 10 min 29 s
Description: Discover computer-aided drug design for HIV treatment using molecular dynamics and high-performance computing. This method identifies Enumerated Etravirine as a promising NNRTI therapeutic agent.

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5 minutes

The authors would like to thank the Centre for High-Performance Computing (CHPC) for providing computational resources and the Department of Chemical Science at the University of Johannesburg.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The DFT26 method was used to analyze the electronic properties and stability of various pyrimidine derivatives, which is not the case in similar studies. The use of DFT allows for a deeper understanding of the molecular interactions at the quantum level, enhancing the design process of NNRTIs. In this study, we selected six NNRTIs with unknown activity values. We retrieved their molecular structures from the PubChem database and conducted geometric optimization using the Minnesota 15 Local (MN15-L)32 functional and 6-31++G (d,p)2 basis set in the Gaussian 16 revision C0133 quantum mechanics software package. To set up simulation input files, we used GaussView 6.026. The quantum structures were then docked into the active site of the HIV-1 protein. 
The study utilized a QSAR approach51, which is tailored to predict the biological activity of NNRTIs based on their chemical structure. This model is generated using a dataset of 94 dihydrofuro[3,4-d] pyrimidine derivatives, enabling the identification of key functional groups that influence antiviral activity. Incorporating a robust QSAR model is a crucial advancement, as it helps filter compounds early in the design process, enhancing the efficacy of drug discovery. 
The predicted activities of the new compounds were considered, and the docking scores were validated. The advanced molecular docking technique explored the binding interactions between NNRTIs and the HIV-1 reverse transcriptase enzyme. This was complemented by molecular dynamics simulations over an extended period (200 ns), providing insight into the stability and behavior of the drug-protein complexes under physiological conditions. Molecular dynamics52 validated the findings from docking studies. By simulating the behavior of drug-enzyme complexes over time, we can assess the dynamic stability and interactions that may not be captured in static docking studies53. This approach provides a more realistic assessment of how NNRTIs may perform in biological systems. The simulations showed that Etravirine produced RMSD fluctuations of approximately 4.5 &#197;, while the enumerated Etravirine gave RMSD fluctuations of 3.5 &#197;. There were various similarities between Etravirine and enumerated Etravirine, with the enumerated compound possessing enhanced amino acid interactions within the protein's active site. The lower RMSD, improved amino acid interactions, and highest binding free energy all suggest that the enumerated Etravirine could serve as a viable alternative for HIV/AIDS treatment.
The use of enumeration techniques54 to generate stereoisomers and perform isostere scanning is a noteworthy aspect of this research. This method allows researchers to explore a wider chemical space for potential NNRTIs by systematically modifying existing structures, which can lead to the discovery of compounds with improved efficacy and reduced resistance.
The research integrates HOMO-LUMO analysis derived from quantum mechanical calculations to evaluate the reactivity and stability of the compounds. This aspect is often overlooked in similar studies55, yet it provides valuable insights into electronic properties that can influence biological activity
Using the MMGBSA method in this study to estimate binding free energies of the enumerated NNRTIs as potential HIV-1 reverse transcriptase (RT) inhibitors present a novel aspect that enhances the significance and potential impact of this work on HIV treatment development. 
The application of MMGBSA in this study provides a more accurate estimation of the binding free energies for the enumerated Etravirine compared to its counterpart. By calculating binding free energy values, the study quantitatively assesses the binding affinity of enumerated Etravirine, which was considerably higher (9.133 kcal/mol) than that of standard Etravirine. This level of detail in binding energy calculations allows for a more nuanced understanding of how structural modifications can influence the efficacy of NNRTIs, which is often lacking in similar studies that may rely solely on qualitative assessments. 
The reported &#916;GCovalent value of 1.477 kcal/mol further indicates the strength of the interaction for the enumerated compound. The comparative approach is innovative as it not only identifies a promising candidate but also situates it within the broader context of existing therapies, providing a benchmark for future NNRTI development. 
The comparison shown in Table 8 also indicates that enumerated Etravirine can be a potential compound to be used as an alternative ART as its binding free energy of (&#916;Gbind) is the highest as compared to Etravirine, HBY56, Etravirine, and their enumerated counterparts. 
Our study's results could significantly impact the development of novel therapeutic agents for HIV infection. Additionally, this approach may allow for identifying the most promising anti-HIV candidate. These findings may pave the way for the rational design of novel HIV-1 NNRTIs.
The incorporation of MMGBSA in conjunction with other computational methods (like molecular docking, QSAR modeling, and molecular dynamics simulations) enhances the robustness of the findings. This integrated approach allows for a comprehensive evaluation of the compounds, from structural optimization to dynamic behavior in a biological context. Such a methodology is relatively novel in NNRTI research, where studies often focus on isolated methods without a holistic view of the drug design process. The research highlights several promising outcomes and an enhanced understanding of the molecular interactions between NNRTIs and the reverse transcriptase enzyme, which can inform future drug design efforts.
While other studies in the field of NNRTI development often focus on single computational methods or basic docking analyses, this research stands out by combining quantum chemical calculations with molecular dynamics and QSAR modelling, employing a systematic enumeration approach that expands the potential chemical space for NNRTIs, and utilizing a comprehensive in-silico framework that not only predicts binding affinities but also assesses the stability and dynamics of drug-enzyme interactions.
Overall, the novelty of this research lies in its multifaceted approach, leveraging advanced computational techniques to address the challenges of drug resistance in HIV treatment, thereby paving the way for the development of more effective NNRTIs. The findings underscore the potential for developing more effective NNRTIs that can overcome the limitations of current therapies.
Some future applications of the approach described in this protocol include the following. 
Integration with machine learning
Future studies could integrate MMGBSA with machine learning algorithms to improve the predictive power of binding free energy estimates. By training models on large datasets, researchers could enhance the accuracy and reliability of predictions, enabling better identification of promising NNRTI candidates.
Application in fragment-based drug design
MMGBSA can be effectively utilized in fragment-based drug design, where small molecular fragments are optimized to improve binding affinity. This approach could lead to the identification of novel NNRTIs with enhanced potency and selectivity against HIV-1.
Exploration of drug resistance mechanisms
The technique can be applied to study the binding interactions of NNRTIs with mutant strains of HIV-1. By comparing binding free energies of NNRTIs against both wild-type and resistant variants, researchers can gain insights into the mechanisms of drug resistance and inform the design of next-generation inhibitors.
Evaluation of pharmacokinetic properties
MMGBSA can also be employed to evaluate the pharmacokinetic properties of NNRTIs, such as solubility and permeability. By understanding how these properties correlate with binding affinity, researchers can optimize drug candidates for better therapeutic profiles.

Despite remarkable strides in treatment, the grave global health menace of acquired immunodeficiency syndrome (AIDS), caused by human immunodeficiency virus-1 (HIV-1), remains a persistent threat1. Antiretroviral medications known as reverse transcriptase inhibitors, RTIs, are used to treat HIV infection. Reverse transcriptase, a viral deoxyribonucleic acid (DNA) polymerase enzyme essential for retrovirus replication, is inhibited by reverse transcriptase inhibitors (RTIs). Nucleoside reverse transcriptase inhibitors (NRTIs) and non-nucleotide reverse transcriptase inhibitors (NNRTIs) are the main RTIs2.
Highly active antiretroviral therapy (HAART), a combination of various antiviral medications, has emerged as the standard therapy for HIV, effectively controlling AIDS spread and transforming this once-fatal illness into a manageable chronic condition3. NNRTIs for HIV-1 are currently a significant part of the HAART regimen4. Antimicrobial resistance (AMR) is among the most critical global health threats, with an estimated 1,27 million fatalities5. As a result, there is an urgent need to troubleshoot AMR and identify novel antimicrobial agents. According to the World Health Organization (WHO), AMR has reached alarming levels in many parts of the world.
This poses a severe risk to achieving sustainable development goals, as it undermines food security, economic growth, and health security while also contributing to social and economic inequalities6. The prevalence of drug-resistant viruses is on the rise, even in antiretroviral medications designed to combat HIV. According to recent statistics, nearly 30 million people across the globe were taking antiretroviral therapy as of the end of 20227.
WHO conducted 30 surveys and discovered that in 21 of those surveys, more than 10% of individuals who began their first-line antiretroviral therapy had resistance to Nevirapine or Efavirenz8. Moreover, individuals with prior exposure to antiretroviral drugs are up to three times more likely to have resistance to NNRTIs than those without exposure9. Studies have revealed that a sizeable number of infants under 18 months of age who were newly diagnosed with HIV exhibited high rates of drug-resistant strains10,11. Shockingly, almost half of them had a - (NNRTI)-resistant strain even before starting the treatment. These findings underscore the need to expedite studies to design innovative HIV therapy.
The development of drug-resistant strains and undesirable side effects from prolonged use have unavoidably posed challenges to the clinical use of NNRTIs12. Initiating combination antiretroviral therapy (cART) extends the life expectancy of people living with HIV despite the potential for adverse side effects. These side effects encompass the risk of developing non-communicable diseases, including lipodystrophy, hyperlipidemia, reduced bone mineral density, elevated blood glucose level leading to type 2 diabetes mellitus, hypertension, an increased risk of stroke, and issues related to obesity13. Early diagnosis and prompt access to suitable medical care in the initial phase of HIV infection offer considerable advantages both from a clinical and public perspective. Timely initiation of ART and prophylaxis against opportunistic infections leads to a notable reduction in HIV-related illness and mortality.
The use of ART can also contribute to a decline in the potential for onward transmission of HIV by reducing the level of circulating HIV ribonucleic acid. Furthermore, addressing the treatment of other sexually transmitted diseases and co-infections can likewise diminish the probability of further HIV infection14. NNRTIs are amongst the optional treatment classes of inhibitors that interact with RT by binding to the allosteric region or site of HIV. This type of inhibition is commonly known as an uncompetitive inhibitor because the NNRTI does not bind at the active site of the substrate but rather on the outside. The effect alters the conformation of the substrate binding site, hindering the standard substrate from binding and leading to premature chain termination. Due to their reduced toxicity compared to NRTIs, simple structure, improved bioavailability over protease inhibitors, and excellent selectivity, NNRTIs have become the most attractive HIV inhibitors15. Therefore, the synthesis and design of novel NNRTIs are crucial from a pharmacokinetic perspective16,17.
NNRTIs are vital in HIV/AIDS treatment due to their strong efficacy and low toxicity. However, early NNRTIs like Nevirapine, Delavirdine, and Efavirenz encounter resistance from viral mutations in the NNRTI binding site18. These drugs, part of the diarylpyrimidine (DAPY) family, exhibit potent activity against various NNRTI strains, including those resistant to early NNRTIs19, likely owing to their molecular flexibility and higher resistance barrier against HIV-120,21. Despite their success, the high mutation rate in HIV-1 RT and the absence of intrinsic proofreading activity have led to new resistance profiles in patients using Etravirine and Rilpivirine22,23. These viral mutations differ from each other, as do those associated with early NNRTI drugs24. Over 50 structurally diverse classes of compounds have been identified as NNRTIs. Notably, six NNRTIs have obtained approval for the treatment of HIV-1. These approved agents encompass Nevirapine (NVP), Delavirdine (DLV), Efavirenz (EFV), Etravirine (ETR), Rilpivirine (RPV), and Doravirine (DOR). Figure 1 shows the chemical structures of these six approved NNRTI drugs25.
In a recent study26, DFT calculations and molecular docking suggest that lovastatin and simvastatin show potential as anti-coronavirus agents. Virtual screening identified five new FDA-approved candidate molecules similar to the efavirenz scaffold, with superior binding affinity in the active pocket of the COVID-19 main protease.
Soltan et al.27 carried out a similar study on the identification of novel molecules for improved binding capacity to HIV RT by employing a fragment-based strategy with FDA-approved drugs to design chemical derivatives. They specifically leveraged the structures of delavirdine, efavirenz, etravirine, and rilpivirine as foundational scaffolds. The drug-likeness of these derivatives was assessed through Swiss-ADME, followed by docking them into related crystal structures. The study concluded with the selection of compounds exhibiting superior binding affinities compared to their parent scaffolds, particularly noting a more pronounced improvement in derivatives designed from the second-generation NNRTIs, etravirine and rilpivirine. For instance, derivatives RPV01 and RPV15 showed significant enhancements in docked energy values over rilpivirine, indicating potential utility in targeting both wild-type and mutant forms of HIV RT.
Murugesan and coworkers28 conducted research propose various medicinal chemistry approaches to enhance the efficacy and minimize resistance in HIV treatment. The study employed molecular hybridization, bioisosteric replacement and high-throughput screening. In their study, they managed to identify novel NNRTI scaffolds with high potency against both wild-type and drug-resistance strains of HIV. They developed DAPY derivatives that exhibit excellent selectivity and low toxicity, with some compounds showing effective inhibition at nanomolar concentrations.
Lately, using computational tools alongside in-silico research has gained popularity due to its practical analysis of a drug&#39;s quantum chemical characteristics29. In this study, computer-aided drug design, density functional theory, qualitative structure-activity relationship, and molecular dynamics were applied to discover potent NNRTIs.

<table><tbody><tr><td>GaussView</td><td>GaussView</td><td></td><td>V6.1.1</td></tr><tr><td>KNIME&amp;nbsp;</td><td>KNIME</td><td></td><td>V4.7.1</td></tr><tr><td>Schrodinger Maestro V13.6</td><td>SCHRODINGER INC.</td><td></td><td>License release year 2023-2</td></tr></tbody></table>

quantitative structure-activity relationship, activity prediction, and molecular dynamics of non-nucleotide reverse transcriptase inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

The increasing incidence of HIV-1 drug resistance presents a challenge to the effectiveness of combination antiretroviral therapy, particularly in Southern Africa. The development of resistance to non-nucleotide reverse transcriptase inhibitors (NNRTIs) threatens the long-term success of antiretroviral therapy. In 2019, antimicrobial resistance directly accounted for an estimated 1.27 million deaths globally. This study employed an in-silico approach to investigate NNTRI drugs and their derivatives. Techniques used included density functional theory calculations, molecular docking, enumeration, quantitative structure-activity relationship (QSAR) analysis, molecular dynamics simulation (MDS), and molecular mechanics with generalized Born and surface area methods. The analysis focused on various pyrimidine derivatives and six NNRTI drugs, examining their interactions with the HIV-1 protein (PDB code 1HQU).
A QSAR model was developed to predict the biological activity of the six NNRTIs under investigation. Using 94 pyrimidine derivatives, the QSAR model achieved an R2 OF 0.822 and a Q2 of 0.815, indicating a high level of predictive accuracy.
MDS were conducted to assess the stability of various ligands and their newly developed alternatives, ensuring they remained bound to the protein&#39;s active site over a 200-nanosecond simulation timeframe. Etravirine exhibited root mean square deviation (RMSD) fluctuations of approximately 4.5 &#197;, while its enumerated derivatives showed RMSD fluctuations of 3.5 &#197;. Through molecular docking, MDS, and free energy computations, enumerated Etravirine demonstrated the best performance, with an activity value of 7.373 and a docking score of -10.517 kcal/mol. Furthermore, the calculated free energy of binding for enumerated Etravirine was -89.684 kcal/mol, outperforming other ligands under investigation. The significant improvement suggests that the modified Etravirine holds promising potential as a novel agent in antiretroviral therapy.
The obtained lower RMSD value, the enhanced amino acid interactions, and the highest binding free energy indicate that enumerated Etravirine could serve as a viable alternative for HIV/AIDS treatment.

This study used in-silico strategies to identify Enumerated Etravirine as a promising therapeutic agent for HIV. Our findings on molecular interactions and dynamics support the rational design of novel NNRTIs as possible HIV treatment alternatives.

The increasing incidence of HIV-1 drug resistance presents a challenge to the effectiveness of combination antiretroviral therapy, particularly in ...

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Source: Scarborough, R. J., et al. Evaluation of the Efficacy And Toxicity of RNAs Targeting HIV-1 Production for Use in Gene or Drug Therapy. J. Vis. Exp. (2016).This video demonstrates a reverse transcriptase (RT) assay to assess the effect of a test RNA on virus-like particle (VLP) production. Cells are co-transfected with plasmids, and RT activity is measured as a quantitative indicator of VLP output. A decrease in RT activity reflects suppression of viral gene expression by the test RNA.

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Discover computer-aided drug design for HIV treatment using molecular dynamics and high-performance computing. This method identifies Enumerated Etravirine as a promising NNRTI therapeutic agent.

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors (Video) | JoVE Journal

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

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