Computational Insights for the Discovery of Non-ATP Competitive Inhibitors of MAP Kinases

Schnieders, Michael J.; Kaoud, Tamer S.; Cheng, Yan; Dalby, Kevin N.; Ren, Pengyu

doi:10.2174/138920012799362873

Cited by 12 publications

(21 citation statements)

References 94 publications

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“…In the past two decades, tremendous efforts have been made by both pharmaceutical companies and academic groups to identify and develop new potent and selective p38 α MAPK inhibitors, some of which have reached different stage of clinical trials. Furthermore, their mechanisms of action, kinase selectivity, crystallographic and computational studies, and pharmacological profiles have been extensively reviewed in the literature . Notwithstanding these promising results, multiple attempts to generate clinically useful p38 α MAPK inhibitors have generally failed, either due to toxicity or inadequate efficacy.…”

Section: Methodsmentioning

confidence: 99%

The Pyrazolobenzothiazine Core as a New Chemotype of p38 Alpha Mitogen‐Activated Protein Kinase Inhibitors

et al. 2015

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The identification, synthesis, biological activity, and binding mode prediction of a series of pyrazolobenzothiazines as novel p38α MAPK inhibitors are reported. Some of these compounds showed interesting activity in both p38α MAPK and TNF-α release assays. Derivative 6 emerged as the most interesting compound with IC50 (p38α) = 0.457 μm, IC50 (TNF-α) = 0.5 μm and a promising kinase selectivity profile. The obtained results strongly indicate the pyrazolobenzothiazine core as a new p38α inhibitor chemotype worthy of future chemical optimization efforts directed toward identifying a new generation of anti-inflammatory agents.

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Section: Methodsmentioning

confidence: 99%

The Pyrazolobenzothiazine Core as a New Chemotype of p38 Alpha Mitogen‐Activated Protein Kinase Inhibitors

et al. 2015

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“…63 Combining the polarizable AMOEBA force field with electrostatics evaluated using PME has been shown to improve macromolecular models from X-ray crystallography refinement in a variety of contexts. 64,77,[238][239][240] At high resolution (~1 Å or lower), the information contained within a polarizable atomic multipole force field can be used to formulate the electron density of the scattering model ( ), in addition to contributing chemical restraints ( ). 64,238 The importance of the prior chemical information contained in a polarizable force field is most significant when positioning parts of the model that are not discernable from the experimental electron density, as in the orientation of water hydrogen atoms 239 or secondary structure elements for mid-to-low resolution data sets (~3-4 Å).…”

Section: Continuum Solvents For Polarizable Biomolecular Solutesmentioning

confidence: 99%

Polarizable Force Fields for Biomolecular Modeling

Shi¹,

Ren²,

Schnieders³

et al. 2015

Reviews in Computational Chemistry

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110

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Classical electrostatics models that take into account polarization appeared as early as the 1950s. Barker in his 1953 paper "Statistical Mechanics of Interacting Dipoles" discussed the electrostatic energy of molecules in terms of "permanent and induced dipoles". 13 Currently, polarizable models generally fall into three categories: those based on induced point dipoles, 9, 14-23 the classical Drude oscillators, 24-26 and fluctuating charges. 27-30 More sophisticated force fields that are "electronic structure-based" 31, 32 or use "machine learning methods" 33 also exist, but incur higher computational costs. Discussions of the advantages and disadvantages of each model and their applications will be presented in the following sections. Compared to fixed charge models, the polarizable models are still in a relatively early stage. Only in the past decade or so has there been a systematic effort to develop general polarizable force fields for molecular modeling. A number of reviews have been published to discuss various aspects of polarizable force fields and their development. 9, 34-40 Here, we focus on the recent development and applications of different polarizable force fields. We begin with a brief introduction to the basic principles and formulae underlying alternative models. Next, the recent progress of several well-developed polarizable force fields is reviewed. Finally, applications of polarizable models to a range of molecular systems, including water and other small molecules, ion solvation, peptides, proteins and lipid systems are presented.

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“…The crystal structure of the marketed kinase inhibitors with the drug molecule in situ has been solved and modelling techniques and experimental work are pursuing non‐competitive inhibitors (Schnieders et al ., ). The ability to bring together genome analysis of kinases and their mutations with molecular biology, cell biochemistry, crystallography, fragment‐based drug design and direct measurement of kinase inhibition in biopsies from the human tumour was a reflection of the growing power of translational medicine at the convergence point of many disciplines (Schwartz and Murray, ).…”

Section: Fortunately the Era Of Brickdust Had Its Successes Particulmentioning

confidence: 97%

Lost in Translation (LiT): IUPHAR Review 6

Dollery

2014

British J Pharmacology

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Translational medicine is a roller coaster with occasional brilliant successes and a large majority of failures. Lost in Translation 1 (‘LiT1’), beginning in the 1950s, was a golden era built upon earlier advances in experimental physiology, biochemistry and pharmacology, with a dash of serendipity, that led to the discovery of many new drugs for serious illnesses. LiT2 saw the large‐scale industrialization of drug discovery using high‐throughput screens and assays based on affinity for the target molecule. The links between drug development and university sciences and medicine weakened, but there were still some brilliant successes. In LiT3, the coverage of translational medicine expanded from molecular biology to drug budgets, with much greater emphasis on safety and official regulation. Compared with R&D expenditure, the number of breakthrough discoveries in LiT3 was disappointing, but monoclonal antibodies for immunity and inflammation brought in a new golden era and kinase inhibitors such as imatinib were breakthroughs in cancer. The pharmaceutical industry is trying to revive the LiT1 approach by using phenotypic assays and closer links with academia. LiT4 faces a data explosion generated by the genome project, GWAS, ENCODE and the ‘omics’ that is in danger of leaving LiT4 in a computerized cloud. Industrial laboratories are filled with masses of automated machinery while the scientists sit in a separate room viewing the results on their computers. Big Data will need Big Thinking in LiT4 but with so many unmet medical needs and so many new opportunities being revealed there are high hopes that the roller coaster will ride high again.

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Computational Insights for the Discovery of Non-ATP Competitive Inhibitors of MAP Kinases

Cited by 12 publications

References 94 publications

The Pyrazolobenzothiazine Core as a New Chemotype of p38 Alpha Mitogen‐Activated Protein Kinase Inhibitors

The Pyrazolobenzothiazine Core as a New Chemotype of p38 Alpha Mitogen‐Activated Protein Kinase Inhibitors

Polarizable Force Fields for Biomolecular Modeling

Lost in Translation (LiT): IUPHAR Review 6

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