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Alganem K, Hamoud AR, Creeden JF, Henkel ND, Imami AS, Joyce AW, Ryan V WG, Rethman JB, Shukla R, O'Donovan SM, Meller J, McCullumsmith R. The active kinome: The modern view of how active protein kinase networks fit in biological research. Curr Opin Pharmacol 2022; 62:117-129. [PMID: 34968947 PMCID: PMC9438800 DOI: 10.1016/j.coph.2021.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/21/2021] [Accepted: 11/12/2021] [Indexed: 02/03/2023]
Abstract
Biological regulatory networks are dynamic, intertwined, and complex systems making them challenging to study. While quantitative measurements of transcripts and proteins are key to investigate the state of a biological system, they do not inform the "active" state of regulatory networks. In consideration of that fact, "functional" proteomics assessments are needed to decipher active regulatory processes. Phosphorylation, a key post-translation modification, is a reversible regulatory mechanism that controls the functional state of proteins. Recent advancements of high-throughput protein kinase activity profiling platforms allow for a broad assessment of protein kinase networks in complex biological systems. In conjunction with sophisticated computational modeling techniques, these profiling platforms provide datasets that inform the active state of regulatory systems in disease models and highlight potential drug targets. Taken together, system-wide profiling of protein kinase activity has become a critical component of modern molecular biology research and presents a promising avenue for drug discovery.
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Affiliation(s)
- Khaled Alganem
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Abdul-Rizaq Hamoud
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Justin F Creeden
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Nicholas D Henkel
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Ali S Imami
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Alex W Joyce
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - William G Ryan V
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Jacob B Rethman
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Rammohan Shukla
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Sinead M O'Donovan
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA
| | - Jarek Meller
- Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH, USA; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, USA; Department of Pharmacology and System Biology, College of Medicine, University of Cincinnati, Cincinnati, OH, USA; Department of Electrical Engineering and Computer Science, College of Engineering and Applied Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Robert McCullumsmith
- Department of Neurosciences, University of Toledo College of Medicine, Toledo, OH, USA; Neurosciences Institute, ProMedica, Toledo, OH, USA.
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Liang JW, Li WQ, Nian QY, Xie SH, Yang L, Meng FH. Synthesis and identification of a novel skeleton of N-(pyridin-3-yl) proline as a selective CDK4/6 inhibitor with anti-breast cancer activities. Bioorg Chem 2021; 119:105547. [PMID: 34906858 DOI: 10.1016/j.bioorg.2021.105547] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/26/2021] [Accepted: 12/05/2021] [Indexed: 11/17/2022]
Abstract
CDK4/6 were attractive chemotherapeutic targets for the treatment of malignant tumors, CDK4/6 selective inhibitors have made outstanding contributions in the treatment of breast cancer. However, these inhibitors share a single skeleton of N-(pyridin-2-yl) pyrimidin-2-amine which cannot overcome the side effects in clinical application. In our previous study, an N'- acetylpyrrolidine-1-carbohydrazide was hit as the initial fragment by analyzing the active site characteristics of CDK6. Two series of N-(pyridin-3-yl) proline were obtained by fragment growth method. The QSAR study was carried out according to the in vitro activities data against CDK4/6, and two compounds 7c and 7p with potent inhibitory activities were found to interact with CDK4 in different binding conformation. They showed potential inhibition of cell proliferation against the breast cancer cell, and 7c exhibited promised anti-breast cancer effect in vivo.
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Affiliation(s)
- Jing-Wei Liang
- School of Pharmacy, China Medical University, Shen Yang, China
| | - Wan-Qiu Li
- School of Pharmacy, China Medical University, Shen Yang, China
| | - Qing-Yang Nian
- School of Pharmacy, China Medical University, Shen Yang, China
| | - Si-Hua Xie
- School of Pharmacy, China Medical University, Shen Yang, China
| | - Lulu Yang
- School of Pharmacy, China Medical University, Shen Yang, China
| | - Fan-Hao Meng
- School of Pharmacy, China Medical University, Shen Yang, China.
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Abstract
Allostery is a fundamental regulatory mechanism in the majority of biological processes of molecular machines. Allostery is well-known as a dynamic-driven process, and thus, the molecular mechanism of allosteric signal transmission needs to be established. Elastic network models (ENMs) provide efficient methods for investigating the intrinsic dynamics and allosteric communication pathways in proteins. In this chapter, two ENM methods including Gaussian network model (GNM) coupled with Markovian stochastic model, as well as the anisotropic network model (ANM), were introduced to identify allosteric effects in hemoglobins. Techniques on model parameters, scripting and calculation, analysis, and visualization are shown step by step.
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Liang Z, Verkhivker GM, Hu G. Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications. Brief Bioinform 2019; 21:815-835. [DOI: 10.1093/bib/bbz029] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 02/04/2019] [Accepted: 02/21/2019] [Indexed: 12/24/2022] Open
Abstract
Abstract
Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.
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Affiliation(s)
- Zhongjie Liang
- School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Gennady M Verkhivker
- Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, USA
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, USA
| | - Guang Hu
- School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
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Czemeres J, Buse K, Verkhivker GM. Atomistic simulations and network-based modeling of the Hsp90-Cdc37 chaperone binding with Cdk4 client protein: A mechanism of chaperoning kinase clients by exploiting weak spots of intrinsically dynamic kinase domains. PLoS One 2017; 12:e0190267. [PMID: 29267381 PMCID: PMC5739471 DOI: 10.1371/journal.pone.0190267] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Accepted: 11/21/2017] [Indexed: 12/31/2022] Open
Abstract
A fundamental role of the Hsp90 and Cdc37 chaperones in mediating conformational development and activation of diverse protein kinase clients is essential in signal transduction. There has been increasing evidence that the Hsp90-Cdc37 system executes its chaperoning duties by recognizing conformational instability of kinase clients and modulating their folding landscapes. The recent cryo-electron microscopy structure of the Hsp90-Cdc37-Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have combined atomistic simulations with protein stability and network-based rigidity decomposition analyses to characterize dynamic factors underlying allosteric mechanism of the chaperone-kinase cycle and identify regulatory hotspots that control client recognition. Through comprehensive characterization of conformational dynamics and systematic identification of stabilization centers in the unbound and client- bound Hsp90 forms, we have simulated key stages of the allosteric mechanism, in which Hsp90 binding can induce instability and partial unfolding of Cdk4 client. Conformational landscapes of the Hsp90 and Cdk4 structures suggested that client binding can trigger coordinated dynamic changes and induce global rigidification of the Hsp90 inter-domain regions that is coupled with a concomitant increase in conformational flexibility of the kinase client. This process is allosteric in nature and can involve reciprocal dynamic exchanges that exert global effect on stability of the Hsp90 dimer, while promoting client instability. The network-based rigidity analysis and emulation of thermal unfolding of the Cdk4-cyclin D complex and Hsp90-Cdc37-Cdk4 complex revealed weak spots of kinase instability that are present in the native Cdk4 structure and are targeted by the chaperone during client recruitment. Our findings suggested that this mechanism may be exploited by the Hsp90-Cdc37 chaperone to recruit and protect intrinsically dynamic kinase clients from degradation. The results of this investigation are discussed and interpreted in the context of diverse experimental data, offering new insights into mechanisms of chaperone regulation and binding.
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Affiliation(s)
- Josh Czemeres
- Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America
| | - Kurt Buse
- Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America
| | - Gennady M. Verkhivker
- Department of Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California, United States of America
- * E-mail:
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