Unveiling Potent Inhibitors for Schistosomiasis Through Ligand-based Drug Design, Molecular Docking, Molecular Dynamics Simulations and Pharmacokinetics Predictions
Saudatu Chinade Ja’afaru, Adamu Uzairu, Imren Bayil, Muhammed Sani Sallau, George Iloegbulam Ndukwe, Muhammad Tukur Ibrahim, Abu Tayab Moin, A. K. M. Moniruzzaman Mollah, Nurul Absar
Abstract
Schistosomiasis is a neglected tropical disease which imposes a considerable and enduring impact on affected regions, leading to persistent morbidity, hindering child development, diminishing productivity, and imposing economic burdens. Due to the emergence of drug resistance and limited management options, there is need to develop additional effective inhibitors for schistosomiasis. In view of this, quantitative structure-activity relationship studies, molecular docking, molecular dynamics simulations, drug-likeness and pharmacokinetics predictions were applied to 39 Schistosoma mansoni Thioredoxin Glutathione Reductase (SmTGR) inhibitors. The chosen QSAR model demonstrated robust statistical parameters, including an R2 of 0.798, R2adj of 0.767, Q2cv of 0.681, LOF of 0.930, R2test of 0.776, and cR2p of 0.746, confirming its reliability. The most active derivative (compound 40) was identified as a lead candidate for the development of new potential non-covalent inhibitors through ligand-based design. Subsequently, 12 novel compounds (40a-40l) were designed with enhanced anti-schistosomiasis activity and binding affinity. Molecular docking studies revealed strong and stable interactions, including hydrogen bonding, between the designed compounds and the target receptor.
Introduction
Schistosomiasis, a prevalent human parasitic infection, represents a significant global health challenge, impacting more than 200 million individuals in developing countries [1–4]. The disease is prevalent across sub-Saharan Africa, parts of South America, the Caribbean, the Middle East, and Southeast Asia [5]. Schistosomiasis exacts a heavy toll, causing approximately 280,000 deaths yearly [4]. Chronic infections of schistosomiasis can severely damage organs like the liver, spleen, and urinary tract and increase the risk of bladder cancer and infertility as reported by Silvestri V. and coworkers, along with many other researchers [6–8]. The predominant therapeutic approach for schistosomiasis relies on a single drug, Praziquantel (PZQ), which is administered extensively to combat the disease’s impact [9]. Despite its widespread use, PZQ’s effectiveness is compromised by several factors, including its exclusive activity against certain Schistosome species and the potential emergence of drug-resistant parasites [10–12]. Moreover, the absence of a reliable alternative to PZQ underscores a critical limitation in current treatment options. Hence, it is necessary to explore more potential inhibitors for Schistosomiasis.
Materials and methods
2.1 Dataset collection, preparations, structure determination and optimization
The dataset was downloaded from ChEMBL (https://www.ebi.ac.uk/chembl) and included experimental data for Schistosoma mansoni as a target (target ID: CHEMBL6110). The dataset was screened and filtered to select compounds suitable for the QSAR study and was rigorously cleaned to eliminate duplicates and resolve discrepancies (S1 Table) [34]. Compounds with incomplete or inconsistent activity values were eliminated and data authenticity was verified to maintain data quality and integrity [35]. The biological activities, initially recorded as IC50 in nanomolar (nM), were transformed into pIC50 to achieve data linearity and uniformity throughout the dataset [36]. Following the filtration process, the dataset was reduced from the initial count of 57 compounds to 49, which were subsequently employed for further analysis.
Results
3.1 QSAR analysis
Four distinctive QSAR models were generated utilizing the GFA technique, all passing internal validation (shown below) as proposed by Umar Abdullahi Bello and co-workers [43]. Numerous researchers have employed the GFA approach in model building due to its flexibility and non-linear modeling capacity [67–69]. Aligning with benchmarks values in Table 1, only two of the created models satisfied the requirements for external validation against the test set compounds [70]. Among the models generated, model 2 emerged as the most suitable for predicting the inhibitory activities of the compounds and was chosen for further studies.
Discussion
The metabolism assessment shows predictions indicating that all but one of the twelve compounds are potential substrates for CYP3A4, which could enhance their bioavailability and reduce elimination rates [95]. However, none of the compounds were predicted to be CYP3A4 inhibitors, therefore minimizing the risk of drug-drug interactions and preserving therapeutic efficacy [96]. Total clearance significantly influences the bioavailability and half-life of drug molecules, determining appropriate dose sizes and regimens [97]. The projected total clearance of the designed compounds indicated a moderate level, with log(CLtot) ranging between 0.310 and 0.690. This suggests that the compounds could be reasonably cleared from the bloodstream by the liver [98]. Furthermore, an assessment of toxicity and skin sensitization for the proposed compounds, revealed their non-toxic nature and favorable physicochemical and pharmacokinetic ADMET properties (Table 8). In summary, these outcomes suggest that the proposed compounds have the potential to act as inhibitors for Schistosoma mansoni and could be considered for use in schistosomiasis treatment.
Conclusion
An in-silico modeling exploration was conducted on a set of 49 derivatives functioning as inhibitors against SmTGR. This study utilized QSAR, molecular docking, molecular dynamics, drug likeness and ADMET properties analyses. The reliability and predictive capability of the developed QSAR models were evaluated through statistically validation parameters. The molecular docking analysis elucidated the inhibition mechanism of the SmTGR receptor by the chosen template scaffold (compound 40), demonstrating interactions through conventional hydrogen bonding, hydrophobic interactions, and electrostatic interactions with the active residues in the binding cavity. The findings from the QSAR modeling and docking analyses guided the design of 12 new derivatives (40a-40l) with improved activities and binding potentials. Molecular dynamics simulations 100 ns, affirmed the stability of the two best-designed molecules (40d and 40j), within the binding cavity of the SmTGR receptor. Analysis of Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) plots indicated minimal fluctuations, supporting system stability as corroborated by molecular docking results. MM-PBSA calculations of binding free energy (ΔGbind) further validated the stability of the complexes, with 40j emerging as the most promising among the newly designed compounds.
Citation: Ja’afaru SC, Uzairu A, Bayil I, Sallau MS, Ndukwe GI, Ibrahim MT, et al. (2024) Unveiling potent inhibitors for schistosomiasis through ligand-based drug design, molecular docking, molecular dynamics simulations and pharmacokinetics predictions. PLoS ONE 19(6): e0302390. https://doi.org/10.1371/journal.pone.0302390
Editor: Peter Mbugua Njogu, University of Nairobi, KENYA
Received: January 29, 2024; Accepted: April 2, 2024; Published: June 26, 2024
Copyright: © 2024 Ja’afaru et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302390#abstract0
