Computer-aided discovery of aminopyridines as novel JAK2 inhibitors

Zhao, Chao; Yang, Suhui; Khadka, Daulat Bikram; Jin, Yifeng; Lee, Kyung‐Tae; Cho, Won‐Jea

doi:10.1016/j.bmc.2015.01.016

Cited by 8 publications

(5 citation statements)

References 29 publications

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“…13,14 Therefore JAK2 enzyme as a viable therapeutic target has become a hot spot in the field. [15][16][17] However, the four members of the JAK family (JAK1, JAK2, JAK3 and TYK2) are unique, multi-domain proteins consisting of seven distinct domains termed the JAK homology (JH1-JH7) domains. Herein, the JH1 domain with the catalytic protein tyrosine kinase (PTK) domain shares a high level of sequence identity.…”

Section: Introductionmentioning

confidence: 99%

Enhancing specificity in the Janus kinases: a study on the thienopyridine JAK2 selective mechanism combined molecular dynamics simulation

Peng

et al. 2016

Mol. BioSyst.

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The selective inhibition for JAK2 over the other JAK family kinases (JAK1, JAK3 and TYK2) has shared an immense challenge due to high conservatism. In this paper, the highly JAK2 selective mechanism of the thienopyridine derivative was identified at the molecular level, based on insights into the inhibitory effects of compound on four JAK kinases by molecular docking, molecular dynamic simulations, free energy calculation and decomposition. The results clearly indicated that the nonpolar contribution and the H-bond network in the hinge region played a critical selective role in stabilizing ligand JAK2, and the residues Glu930, Leu932 and Gly935 in JAK2 kinase were the key differences compared to the equivalence residues of JAK1, JAK3 and TYK2, which were further verified by simulating four complexes of JAK kinases with another highly selective thienopyridine JAK2 inhibitor . Finally, several novel molecules were designed according to above findings and further verified by the same comprehensive modeling protocol. The obtained results not only demonstrated the rationality of our models and analyses, but also suggested that the designed molecules with higher JAK2 selectivity and bioactivity potential would provide an update of JAK2 inhibitors.

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Section: Introductionmentioning

confidence: 99%

Enhancing specificity in the Janus kinases: a study on the thienopyridine JAK2 selective mechanism combined molecular dynamics simulation

Peng

et al. 2016

Mol. BioSyst.

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“…52 Molecular docking is computer technology for studying drug–target interactions and drug design based on structure. 53,54 For example, DesJarlais RL et al have successfully used molecular docking to design a new type of HIV-1 protease inhibitors; 55 Zhao et al used molecular docking to identify JAK2 inhibitors; 56 Mirza SB et al used molecular docking to screen non-structural protein 3 (NS3) against dengue virus and found five inhibitors that could reduce virus titers in HUH7 cells. 57 Therefore, the virtual screening method that we combine both the ligand-based machine learning method and the structure-based molecular docking is of great significance for the discovery and application of drugs.…”

Section: Discussionmentioning

confidence: 99%

Discovery of Cobimetinib as a novel A-FABP inhibitor using machine learning and molecular docking-based virtual screening

Yang

Chang

2022

RSC Adv.

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“…Despite what would seem to be eviscerating weaknesses, docking screens have been successfully prosecuted, discovering new ligands (Table ) − that are increasingly confirmed with detailed biophysics, from concentration–response curves to K i and K d values of binding, to the comparison of subsequent crystal structures to the docking predictions (Figure ). In blind, prospective comparisons with HTS against enzymes like HSP90, PTP-1B, β-lactamase, , and cruzain, , the docking “hit rates” (actives/tested) were 2–3 orders of magnitude better than for the empirical screen, and while HTS found docking false negatives, docking in its turn found false negatives from HTS.…”

Section: Pragmatic Success: Docking As a Screening Techniquementioning

confidence: 99%

Docking Screens for Novel Ligands Conferring New Biology

2016

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It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking’s greatest impact over the next few years.

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Computer-aided discovery of aminopyridines as novel JAK2 inhibitors

Cited by 8 publications

References 29 publications

Enhancing specificity in the Janus kinases: a study on the thienopyridine JAK2 selective mechanism combined molecular dynamics simulation

Enhancing specificity in the Janus kinases: a study on the thienopyridine JAK2 selective mechanism combined molecular dynamics simulation

Discovery of Cobimetinib as a novel A-FABP inhibitor using machine learning and molecular docking-based virtual screening

Docking Screens for Novel Ligands Conferring New Biology

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