Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach
Abstract
1. Introduction
2. Results and Discussion
2.1. Lead Compound Development
2.2. Molecular Dynamic Simulation
2.3. Lead Compound Optimization
2.3.1. Changing the Quinolone Scaffold
2.3.2. Other Changes to Improve Drug-like Properties
2.4. ADMET Property Prediction
3. Materials and Methods
3.1. Ligand Preparation
3.2. Protein Preparation
3.3. Receptor Grid Generation
3.4. Molecular Docking
3.5. Induced Fit Docking (IFD)
3.6. Molecular Dynamic Simulation
3.7. Pharmacology Parameters
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Compounds | IFD Score |
---|---|
Sildenafil | −765.04 |
Exisulind | −756.8 |
cGMP | −756.22 |
MS01 | −761.16 |
Compound ID | ΔG Energy (Kcal/mol) |
---|---|
MS25 | −14.729 |
MS18 | −14.441 |
MS23 | −13.984 |
MS01-Lead | −13.798 |
MS21 | −13.092 |
MS16 | −13.073 |
MS17 | −12.772 |
MS20 | −12.666 |
MS26 | −12.618 |
MS22 | −12.560 |
MS24 | −12.082 |
MS12 | −11.992 |
MS19 | −11.913 |
MS15 | −11.892 |
MS11 | −11.608 |
MS29 | −11.164 |
MS10 | −11.060 |
MS13 | −10.850 |
MS14 | −10.763 |
Sildenafil | −10.383 |
Exisulind | −9.895 |
cGMP | −9.798 |
MS28 | −8.749 |
MS27 | −7.952 |
Molecule | MW (g/mol) | Consensus Log p | Log S (ESOL) | TPSA | Fraction Csp3 | Verber #Violations | Lipinski #Violations | Bioavailability Score |
---|---|---|---|---|---|---|---|---|
MS01 | 497.56 | 4.62 | −5.26 | 112.68 | 0.1 | 0 | 0 | 0.56 |
MS10 | 470.54 | 4.35 | −5.23 | 108.5 | 0.11 | 0 | 0 | 0.56 |
MS11 | 485.55 | 4.04 | −4.76 | 108.92 | 0.14 | 0 | 0 | 0.56 |
MS12 | 471.52 | 4.57 | −5.34 | 105.85 | 0.11 | 0 | 0 | 0.56 |
MS13 | 471.53 | 3.98 | −4.96 | 121.39 | 0.12 | 0 | 0 | 0.56 |
MS14 | 470.54 | 4.31 | −5.20 | 108.50 | 0.11 | 0 | 0 | 0.55 |
MS15 | 469.55 | 4.83 | −5.54 | 95.61 | 0.11 | 0 | 0 | 0.56 |
MS16 | 522.61 | 4.86 | −5.87 | 118.73 | 0.10 | 1 | 0 | 0.56 |
MS17 | 511.59 | 4.96 | −5.5 | 112.68 | 0.13 | 0 | 2 | 0.56 |
MS18 | 523.6 | 5.05 | −5.68 | 112.68 | 0.16 | 0 | 2 | 0.56 |
MS19 | 498.55 | 3.81 | −4.84 | 138.7 | 0.07 | 0 | 0 | 0.56 |
MS20 | 568.64 | 4.24 | −5.29 | 125.15 | 0.19 | 0 | 1 | 0.56 |
MS21 | 567.65 | 3.41 | −3.67 | 127.95 | 0.19 | 0 | 1 | 0.55 |
MS22 | 498.55 | 3.82 | −4.59 | 125.57 | 0.11 | 0 | 0 | 0.56 |
MS23 | 498.55 | 3.9 | −4.59 | 125.57 | 0.11 | 0 | 0 | 0.56 |
MS24 | 498.55 | 3.96 | −4.62 | 125.57 | 0.11 | 0 | 0 | 0.56 |
MS25 | 565.56 | 5.65 | −6.13 | 112.68 | 0.13 | 0 | 2 | 0.56 |
MS26 | 565.56 | 5.62 | −6.13 | 112.68 | 0.13 | 0 | 2 | 0.56 |
MS27 | 572.67 | 5.75 | −6.46 | 104.48 | 0.09 | 0 | 2 | 0.17 |
MS28 | 558.69 | 6.28 | −7.12 | 87.41 | 0.11 | 0 | 2 | 0.17 |
MS29 | 586.7 | 5.79 | −6.43 | 104.48 | 0.11 | 0 | 2 | 0.17 |
Molecule | GI Absorption | BBB Permeant | Pgp Substrate | CYP1A2 Inhibitor | CYP2C19 Inhibitor | CYP2C9 Inhibitor | CYP2D6 Inhibitor | CYP3A4 Inhibitor | Log Kp (cm/s) |
---|---|---|---|---|---|---|---|---|---|
MS01 | Low | No | No | No | Yes | Yes | No | No | −6.84 |
MS10 | Low | No | No | No | Yes | Yes | No | No | −6.52 |
MS11 | Low | No | No | Yes | Yes | Yes | No | No | −7.17 |
MS12 | Low | No | No | No | Yes | Yes | No | No | −6.41 |
MS13 | Low | No | No | No | Yes | No | No | No | −6.85 |
MS14 | Low | No | No | No | Yes | Yes | No | No | −6.56 |
MS15 | Low | No | No | No | Yes | Yes | No | No | −6.16 |
MS16 | Low | No | No | No | No | No | No | No | −6.43 |
MS17 | Low | No | No | Yes | Yes | Yes | No | No | −6.67 |
MS18 | Low | No | No | Yes | No | Yes | No | No | −6.6 |
MS19 | Low | No | No | No | Yes | No | No | No | −7.32 |
MS20 | Low | No | No | No | No | Yes | No | No | −7.6 |
MS21 | Low | No | Yes | No | No | Yes | No | No | −9.41 |
MS22 | Low | No | No | No | Yes | Yes | No | No | −7.61 |
MS23 | Low | No | No | No | Yes | Yes | No | No | −7.61 |
MS24 | Low | No | No | No | Yes | Yes | No | No | −7.58 |
MS25 | Low | No | No | Yes | No | No | No | No | −6.63 |
MS26 | Low | No | No | Yes | No | No | No | No | −6.63 |
MS27 | Low | No | No | No | No | No | No | No | −6.37 |
MS28 | Low | No | No | No | No | No | No | No | −5.46 |
MS29 | Low | No | No | Yes | No | No | No | Yes | −6.5 |
Molecule | LD50 mg/kg | Toxicity Class | Hepatotoxicity | Respiratory Toxicity | Carcinogenicity | Immunotoxicity | Mutagenicity | Cytotoxicity |
---|---|---|---|---|---|---|---|---|
MS01 | 800 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS10 | 1000 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS11 | 5000 | 5 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS12 | 1000 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS13 | 1000 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS14 | 264 | 3 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS15 | 264 | 3 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS16 | 264 | 3 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS17 | 800 | 4 | Active | Active | Inactive | Active | Inactive | Inactive |
MS18 | 800 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS19 | 800 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS20 | 300 | 3 | Inactive | Active | Inactive | Inactive | Inactive | Inactive |
MS21 | 300 | 3 | Inactive | Active | Inactive | Inactive | Inactive | Inactive |
MS22 | 264 | 3 | Active | Active | Inactive | Active | Inactive | Inactive |
MS23 | 264 | 3 | Active | Active | Inactive | Active | Inactive | Inactive |
MS24 | 800 | 4 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS25 | 264 | 3 | Active | Active | Inactive | Active | Inactive | Inactive |
MS26 | 264 | 3 | Active | Active | Inactive | Active | Inactive | Inactive |
MS27 | 20,000 | 6 | Active | Active | Inactive | Inactive | Inactive | Inactive |
MS28 | 264 | 3 | Inactive | Active | Inactive | Active | Inactive | Inactive |
MS29 | 200 | 3 | Inactive | Active | Inactive | Active | Inactive | Inactive |
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Oladeji, S.M.; Conteh, D.N.; Bello, L.A.; Adegboyega, A.E.; Shokunbi, O.S. Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach. Int. J. Mol. Sci. 2025, 26, 1937. https://doi.org/10.3390/ijms26051937
Oladeji SM, Conteh DN, Bello LA, Adegboyega AE, Shokunbi OS. Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach. International Journal of Molecular Sciences. 2025; 26(5):1937. https://doi.org/10.3390/ijms26051937
Chicago/Turabian StyleOladeji, Samson Marvellous, Deborah Ngozi Conteh, Lukman Abidemi Bello, Abayomi Emmanuel Adegboyega, and Oluwatosin Sarah Shokunbi. 2025. "Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach" International Journal of Molecular Sciences 26, no. 5: 1937. https://doi.org/10.3390/ijms26051937
APA StyleOladeji, S. M., Conteh, D. N., Bello, L. A., Adegboyega, A. E., & Shokunbi, O. S. (2025). Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach. International Journal of Molecular Sciences, 26(5), 1937. https://doi.org/10.3390/ijms26051937