Binding Studies and Lead Generation of Pteridin-7(8H)-one Derivatives Targeting FLT3

Ghosh, Suparna; Cho, Seung Joo

doi:10.3390/ijms23147696

Cited by 3 publications

(3 citation statements)

References 37 publications

(38 reference statements)

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“…Figure 4 a shows the generalized thermodynamic cycle of the relative binding free energy derivation scheme. In the earlier studies [ 23 , 24 ], we used an absolute binding free energy estimate in the modeling study of kinase inhibitors and found a satisfactory correlation between the experimental and computed binding free energies. Although, the calculated binding free energies were overestimated in comparison to the corresponding experimental values.…”

Section: Resultsmentioning

confidence: 89%

Three-Dimensional-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Ghosh

Cho

2023

Molecules

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Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK-targeting inhibitors using three-dimensional structure–activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure–activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (∆∆GRBFEA→B) terms of analogous ligands were estimated using alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. Overall, the results suggested that using ML and physics-based hybrid approaches could be useful in synergy for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

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Section: Resultsmentioning

confidence: 89%

Three-Dimensional-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Ghosh

Cho

2023

Molecules

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“…Figure 4a shows the generalized thermodynamic cycle of the relative binding free energy derivation scheme. In the earlier studies [36,37], we used an absolute binding free energy estimate in the modeling study of kinase inhibitors and found a satisfactory correlation between the experimental and computed binding free energies, despite the high numerical approximation. Since the entire ligand needs to be perturbed (interactions off or on) corresponding to its surroundings, which requires a large number of λ intermediate states and simulation time.…”

Section: Relative Binding Affinity Estimationmentioning

confidence: 92%

3D-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Ghosh¹,

Cho²

2022

Preprint

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Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK targeting inhibitors using 3-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using the MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (〖∆∆G〗_RBFE^(A→B)) values of analogous ligands were estimated using the alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. The overall results using ML and physics-based hybrid approaches could be useful for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

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“…GROMACS 2019.5 22 was used for the MD simulation study using Amber ff99SB force field according to our previous studies 23,24 . ACEPYPE 25 was used to parameterize the ligand molecules with AM1‐BCC charges.…”

Section: Methodsmentioning

confidence: 99%

Comparative binding affinity analysis of dual CDK2/FLT3 inhibitors

Ghosh

Cho

2022

Bulletin Korean Chem Soc

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Selective inhibition of cyclin‐dependent kinase 2 (CDK2) using small molecules is gaining popularity for the treatment of certain types of acute myeloid leukemia (AML). In this study, we used different molecular modeling techniques to investigate the structure–activity relationship (SAR) and binding modalities of dual CDK2/FLT3 inhibitors. The key chemical characteristics of the 3H‐pyrazolo[4,3‐f]quinoline derivatives were highlighted as descriptive colored contours using comparative molecular similarity analysis (CoMSIA). Modifying chemical groups in existing compounds along these contours could improve CDK2 selectivity over FMS‐like tyrosine kinase 3 (FLT3). We determined the ligand affinities for CDK2 by estimating the binding free energy using molecular mechanics generalized Born surface area (MM‐GBSA) and umbrella sampling (US) simulations. Reasonable correlations were found between the computed and experimental binding energies, suggesting that MM‐GBSA and US can be used to reliably predict the binding affinities of new compounds in the more potent CDK2 drug development process.

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Binding Studies and Lead Generation of Pteridin-7(8H)-one Derivatives Targeting FLT3

Cited by 3 publications

References 37 publications

Three-Dimensional-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Three-Dimensional-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

3D-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Comparative binding affinity analysis of dual CDK2/FLT3 inhibitors

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