Molecular modeling studies of pyrrolo[2,3-d]pyrimidin-4-amine derivatives as JAK1 inhibitors based on 3D-QSAR, molecular docking, molecular dynamics (MD) and MM-PBSA calculations

Keretsu, Seketoulie; Bhujbal, Swapnil P.; Cho, Seung Joo

doi:10.1080/07391102.2020.1714483

Cited by 16 publications

(6 citation statements)

References 46 publications

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“…Finally, unrestrained 50 ns production simulations were carried out for the systems at 310 K and 1 bar atmospheric pressure. The MD simulation procedure used here has been used in several protein–ligand interaction studies by our group and others 39 , 40 .…”

Section: Methodsmentioning

confidence: 99%

“…The non-polar energy term (G nonpolar ) includes both repulsive and attractive forces between the solute and solvent developed due to cavity (G cavity ) formation as well as the van der Waals interaction (G vdW ). This can be represented by the equation below 40 , 69 . …”

Section: Methodsmentioning

confidence: 99%

“…Computer-aided drug discovery (CADD) methodologies have emerged as powerful tools in the drug discovery process and have been used over the last decade to identify protein inhibitors and to study protein-drug interactions and protein–protein interactions 15 , 38 – 40 . Since the development of a candidate drug into an approved drug is a long and costly process, a combination of computational methodologies such as virtual screening, docking, molecular dynamics (MD) simulation, and binding free energy evaluation, serves as a promising alternative for identifying potential drug candidates from compound libraries 41 .…”

Section: Introductionmentioning

confidence: 99%

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Rational approach toward COVID-19 main protease inhibitors via molecular docking, molecular dynamics simulation and free energy calculation

Keretsu

Bhujbal

Cho

2020

Sci Rep

Self Cite

131

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In the rapidly evolving coronavirus disease (COVID-19) pandemic, repurposing existing drugs and evaluating commercially available inhibitors against druggable targets of the virus could be an effective strategy to accelerate the drug discovery process. The 3C-Like proteinase (3CLpro) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as an important drug target due to its role in viral replication. The lack of a potent 3CLpro inhibitor and the availability of the X-ray crystal structure of 3CLpro (PDB-ID 6LU7) motivated us to perform computational studies to identify commercially available potential inhibitors. A combination of modeling studies was performed to identify potential 3CLpro inhibitors from the protease inhibitor database MEROPS (https://www.ebi.ac.uk/merops/index.shtml). Binding energy evaluation identified key residues for inhibitor design. We found 15 potential 3CLpro inhibitors with higher binding affinity than that of an α-ketoamide inhibitor determined via X-ray structure. Among them, saquinavir and three other investigational drugs aclarubicin, TMC-310911, and faldaprevir could be suggested as potential 3CLpro inhibitors. We recommend further experimental investigation of these compounds.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Rational approach toward COVID-19 main protease inhibitors via molecular docking, molecular dynamics simulation and free energy calculation

Keretsu

Bhujbal

Cho

2020

Sci Rep

Self Cite

131

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“…According to clinical and experimental investigations, rheumatoid arthritis synovial response may be influenced by the JAK1-mediated cytokine (IFN and IL-6) signaling. As a result, inhibiting JAK1 is regarded as a significant therapeutic strategy for the successful treatment of rheumatoid arthritis ( Keretsu et al, 2021b ). Recently, it has been discovered that inhibiting JAK1 selectively may be an effective therapy option for patients suffering from autoimmune and hematological illnesses because of the role that altered JAK1 signaling plays in these conditions ( Kleppe et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches

et al. 2022

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JAK1 plays a significant role in the intracellular signaling by interacting with cytokine receptors in different types of cells and is linked to the pathogenesis of various cancers and in the pathology of the immune system. In this study, ligand-based pharmacophore modeling combined with virtual screening and molecular docking methods was incorporated to identify the potent and selective lead compounds for JAK1. Initially, the ligand-based pharmacophore models were generated using a set of 52 JAK1 inhibitors named C-2 methyl/hydroxyethyl imidazopyrrolopyridines derivatives. Twenty-seven pharmacophore models with five and six pharmacophore features were generated and validated using potency and selectivity validation methods. During potency validation, the Guner-Henry score was calculated to check the accuracy of the generated models, whereas in selectivity validation, the pharmacophore models that are capable of identifying selective JAK1 inhibitors were evaluated. Based on the validation results, the best pharmacophore models ADHRRR, DDHRRR, DDRRR, DPRRR, DHRRR, ADRRR, DDHRR, and ADPRR were selected and taken for virtual screening against the Maybridge, Asinex, Chemdiv, Enamine, Lifechemicals, and Zinc database to identify the new molecules with novel scaffold that can bind to JAK1. A total of 4,265 hits were identified from screening and checked for acceptable drug-like properties. A total of 2,856 hits were selected after ADME predictions and taken for Glide molecular docking to assess the accurate binding modes of the lead candidates. Ninety molecules were shortlisted based on binding energy and H-bond interactions with the important residues of JAK1. The docking results were authenticated by calculating binding free energy for protein–ligand complexes using the MM-GBSA calculation and induced fit docking methods. Subsequently, the cross-docking approach was carried out to recognize the selective JAK1 lead compounds. Finally, top five lead compounds that were potent and selective against JAK1 were selected and validated using molecular dynamics simulation. Besides, the density functional theory study was also carried out for the selected leads. Through various computational studies, we observed good potency and selectivity of these lead compounds when compared with the drug ruxolitinib. Compounds such as T5923555 and T5923531 were found to be the best and can be further validated using in vitro and in vivo methods.

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“…Computer-aided drug discovery (CADD) methods have become popular in the drug discovery process and have been widely used in several drug discovery studies [29][30][31][32]. Taking advantage of the CADD techniques, our research group has performed several computational studies particularly in the area of kinase inhibitors [33][34][35][36]. Given the role of both c-KIT and PDGFRα in the tumorigenesis of GISTs, the computational study of the dual inhibitory mechanism of these kinases could provide valuable insight into developing more effective drugs against GISTs.…”

Section: Introductionmentioning

confidence: 99%

Molecular Modeling Study of c-KIT/PDGFRα Dual Inhibitors for the Treatment of Gastrointestinal Stromal Tumors

Keretsu

Ghosh

Cho

2020

IJMS

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Gastrointestinal stromal tumors (GISTs) are the most common Mesenchymal Neoplasm of the gastrointestinal tract. The tumorigenesis of GISTs has been associated with the gain-of-function mutation and abnormal activation of the stem cell factor receptor (c-KIT) and platelet-derived growth factor receptor alpha (PDGFRα) kinases. Hence, inhibitors that target c-KIT and PDGFRα could be a therapeutic option for the treatment of GISTs. The available approved c-KIT/PDGFRα inhibitors possessed low efficacy with off-target effects, which necessitated the development of potent inhibitors. We performed computational studies of 48 pyrazolopyridine derivatives that showed inhibitory activity against c-KIT and PDGFRα to study the structural properties important for inhibition of both the kinases. The derivative of phenylurea, which has high activities for both c-KIT (pIC50 = 8.6) and PDGFRα (pIC50 = 8.1), was used as the representative compound for the dataset. Molecular docking and molecular dynamics simulation (100 ns) of compound 14 was performed. Compound 14 showed the formation of hydrogen bonding with Cys673, Glu640, and Asp810 in c-KIT, and Cys677, Glu644, and Asp836 in PDGFRα. The results also suggested that Thr670/T674 substitution in c-KIT/PDGFRα induced conformational changes at the binding site of the receptors. Three-dimensional quantitative structure–activity relationship (3D-QSAR) models were developed based on the inhibitors. Contour map analysis showed that electropositive and bulky substituents at the para-position and the meta-position of the benzyl ring of compound 14 was favorable and may increase the inhibitory activity against both c-KIT and PDGFRα. Analysis of the results suggested that having bulky and hydrophobic substituents that extend into the hydrophobic pocket of the binding site increases the activity for both c-KIT and PDGFRα. Based on the contour map analysis, 50 compounds were designed, and the activities were predicted. An evaluation of binding free energy showed that eight of the designed compounds have potential binding affinity with c-KIT/PDGFRα. Absorption, distribution, metabolism, excretion and toxicity (ADMET) and synthetic feasibility tests showed that the designed compounds have reasonable pharmaceutical properties and synthetic feasibility. Further experimental study of the designed compounds is recommended. The structural information from this study could provide useful insight into the future development of c-KIT and PDGFRα inhibitors.

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Molecular modeling studies of pyrrolo[2,3-d]pyrimidin-4-amine derivatives as JAK1 inhibitors based on 3D-QSAR, molecular docking, molecular dynamics (MD) and MM-PBSA calculations

Cited by 16 publications

References 46 publications

Rational approach toward COVID-19 main protease inhibitors via molecular docking, molecular dynamics simulation and free energy calculation

Rational approach toward COVID-19 main protease inhibitors via molecular docking, molecular dynamics simulation and free energy calculation

Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches

Molecular Modeling Study of c-KIT/PDGFRα Dual Inhibitors for the Treatment of Gastrointestinal Stromal Tumors

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