1
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Kutlu Y, Axel G, Kolodny R, Ben-Tal N, Haliloglu T. Reused Protein Segments Linked to Functional Dynamics. Mol Biol Evol 2024; 41:msae184. [PMID: 39226145 PMCID: PMC11412252 DOI: 10.1093/molbev/msae184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 08/10/2024] [Accepted: 08/26/2024] [Indexed: 09/05/2024] Open
Abstract
Protein space is characterized by extensive recurrence, or "reuse," of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.
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Affiliation(s)
- Yiğit Kutlu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey
| | - Gabriel Axel
- School of Neurobiology, Biochemistry & Biophysics, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Rachel Kolodny
- Department of Computer Science, University of Haifa, Haifa, Israel
| | - Nir Ben-Tal
- School of Neurobiology, Biochemistry & Biophysics, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Turkan Haliloglu
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey
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2
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Moldovean-Cioroianu NS. Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches. Int J Mol Sci 2024; 25:6789. [PMID: 38928495 PMCID: PMC11204371 DOI: 10.3390/ijms25126789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 06/13/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024] Open
Abstract
Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.
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Affiliation(s)
- Nastasia Sanda Moldovean-Cioroianu
- Institute of Materials Science, Bioinspired Materials and Biosensor Technologies, Kiel University, Kaiserstraße 2, 24143 Kiel, Germany;
- Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, RO-400084 Cluj-Napoca, Romania
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3
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Zhao H, Yu J, Weng G, Yu J, Wang E, Gao J, Liu H, Hou T, Wang Z, Kang Y. Structural view on the role of the TRD loop in regulating DNMT3A activity: a molecular dynamics study. Phys Chem Chem Phys 2022; 24:15791-15801. [PMID: 35758413 DOI: 10.1039/d2cp02031a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
DNA methyltransferase 3A (DNMT3A) has been regarded as a potential epigenetic target for the development of cancer therapeutics. A number of DNMT3A inhibitors have been reported, but most of them do not have good potency, high selectivity and/or low cytotoxicity. It has been suggested that a non-conserved region around the target recognition domain (TRD) loop is implicated in the DNMT3A activity under the allosteric regulation of the ATRX-DNMT3-DNMT3L (ADD) domain, but the molecular mechanism of the regulation of the TRD loop on the DNMT3A activity needs to be elucidated. In this study, based on the reported crystal structures, the dynamics of the TRD loop in different multimerization with/without the bound guest molecule, namely the ADD domain or the DNA molecule, was investigated using conventional molecular dynamics (MD) and umbrella sampling simulations. The simulation results illustrate that the TRD loop exhibits relatively higher flexibility than the other components in the whole catalytic domain (CD), which could be well stabilized into different local minima through the binding with either the ADD domain or the DNA molecule by forming tight hydrogen-bond and salt-bridge networks involving distinct residues. Moreover, the movement of the TRD loop away from the catalytic loop upon activation could be triggered simply by the detachment of the ADD domain, but not necessarily induced by the ADD domain relocation on the CD. All these dynamic structural details could be a supplement to the previously reported crystal structure, which underlines the importance of the structural flexibility for the critical residues in the TRD loop, arousing more interest in the rational design of novel DNMT3A inhibitors targeting this region.
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Affiliation(s)
- Hong Zhao
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China. .,Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, China
| | - Jie Yu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Gaoqi Weng
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Jiahui Yu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Ercheng Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Junbo Gao
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Huanxiang Liu
- Faculty of Applied Science, Macao Polytechnic University, Macao, SAR, China
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Zhe Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
| | - Yu Kang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
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4
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Man X, Li Q, Wang B, Zhang H, Zhang S, Li Z. DNMT3A and DNMT3B in Breast Tumorigenesis and Potential Therapy. Front Cell Dev Biol 2022; 10:916725. [PMID: 35620052 PMCID: PMC9127442 DOI: 10.3389/fcell.2022.916725] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 04/21/2022] [Indexed: 01/15/2023] Open
Abstract
Breast cancer has become a leading cause of cancer-related deaths in women worldwide. DNA methylation has been revealed to play an enormously important role in the development and progression of breast cancer. DNA methylation is regulated by DNA methyltransferases (DNMTs), including DNMT1, DNMT2, and DNMT3. DNMT3 family has three members: DNMT3A, DNMT3B, and DNMT3L. The roles and functions of DNMT1 in breast cancer have been well reviewed. In this article, the roles of DNMT3A and DNMT3B in breast tumorigenesis and development are reviewed. We also discuss the SNP and mutations of DNMT3A and DNMT3B in breast cancer. In addition, we summarize how DNMT3A and DNMT3B are regulated by non-coding RNAs and signaling pathways in breast cancer, and targeting the expression levels of DNMT3A and DNMT3B may be a promising therapeutic approach for breast cancer. This review will provide reference for further studies on the biological functions and molecular mechanisms of DNMT3A and DNMT3B in breast cancer.
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Affiliation(s)
- Xiaxia Man
- Department of Oncologic Gynecology, the First Hospital of Jilin University, Jilin, China
| | - Qi Li
- State and Local Joint Engineering Laboratory for Animal Models of Human Diseases, Academy of Translational Medicine, the First Hospital of Jilin University, Jilin, China
| | - Baogang Wang
- Department of Cardiac Surgery, the First Hospital of Jilin University, Jilin, China
| | - He Zhang
- Department of Oncologic Gynecology, the First Hospital of Jilin University, Jilin, China
| | - Songling Zhang
- Department of Oncologic Gynecology, the First Hospital of Jilin University, Jilin, China
| | - Ziyi Li
- State and Local Joint Engineering Laboratory for Animal Models of Human Diseases, Academy of Translational Medicine, the First Hospital of Jilin University, Jilin, China
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5
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Xiao F, Zhou Z, Song X, Gan M, Long J, Verkhivker G, Hu G. Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation. PLoS Comput Biol 2022; 18:e1010009. [PMID: 35320273 PMCID: PMC8979438 DOI: 10.1371/journal.pcbi.1010009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/04/2022] [Accepted: 03/10/2022] [Indexed: 11/18/2022] Open
Abstract
Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control, mild and severe HPP phenotypes. Molecular dynamics simulations coupled with protein structure network analysis were employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and the developed machine learning model suggested that the topological network parameters could serve as a robust indicator of severe mutations. The results indicated that the severity of disease-associated mutations is often linked with mutation-induced modulation of allosteric communications in the protein. This study suggested that ALPL mutations associated with mild and more severe HPPs can exert markedly distinct effects on the protein stability and long-range network communications. By linking the disease phenotypes with dynamic and allosteric molecular signatures, the proposed integrative computational approach enabled to characterize and quantify the allosteric effects of ALPL mutations and role of allostery in the pathogenesis of HPPs.
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Affiliation(s)
- Fei Xiao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Ziyun Zhou
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Xingyu Song
- Department of Chemistry, Multiscale Research Institute of Complex Systems and Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Mi Gan
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Jie Long
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Gennady Verkhivker
- Department of Computational and Data Sciences, Chapman University, One University Drive, Orange, California, United States of America
- Department of Biomedical and Pharmaceutical Sciences, Chapman University Pharmacy School 9401 Jeronimo Rd, Irvine, California, United States of America
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
- * E-mail:
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6
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein-Protein Interfaces, How and Why? Molecules 2022; 27:1841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein-protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein-protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein-protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein-protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
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7
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Jurkowska RZ, Jeltsch A. Enzymology of Mammalian DNA Methyltransferases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1389:69-110. [DOI: 10.1007/978-3-031-11454-0_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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8
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Pacini L, Dorantes-Gilardi R, Vuillon L, Lesieur C. Mapping Function from Dynamics: Future Challenges for Network-Based Models of Protein Structures. Front Mol Biosci 2021; 8:744646. [PMID: 34708077 PMCID: PMC8543124 DOI: 10.3389/fmolb.2021.744646] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/19/2021] [Indexed: 11/25/2022] Open
Abstract
Proteins fulfill complex and diverse biological functions through the controlled atomic motions of their structures (functional dynamics). The protein composition is given by its amino-acid sequence, which was assumed to encode the function. However, the discovery of functional sequence variants proved that the functional encoding does not come down to the sequence, otherwise a change in the sequence would mean a change of function. Likewise, the discovery that function is fulfilled by a set of structures and not by a unique structure showed that the functional encoding does not come down to the structure either. That leaves us with the possibility that a set of atomic motions, achievable by different sequences and different structures, encodes a specific function. Thanks to the exponential growth in annual depositions in the Protein Data Bank of protein tridimensional structures at atomic resolutions, network models using the Cartesian coordinates of atoms of a protein structure as input have been used over 20 years to investigate protein features. Combining networks with experimental measures or with Molecular Dynamics (MD) simulations and using typical or ad-hoc network measures is well suited to decipher the link between protein dynamics and function. One perspective is to consider static structures alone as alternatives to address the question and find network measures relevant to dynamics that can be subsequently used for mining and classification of dynamic sequence changes functionally robust, adaptable or faulty. This way the set of dynamics that fulfill a function over a diversity of sequences and structures will be determined.
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Affiliation(s)
- Lorenza Pacini
- Ecole Centrale de Lyon, Ampère, UMR5005, Univ. Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Villeurbanne, France
- Institut Rhônalpin des Systèmes Complexes, IXXI-ENS-Lyon, Lyon, France
| | - Rodrigo Dorantes-Gilardi
- Institut Rhônalpin des Systèmes Complexes, IXXI-ENS-Lyon, Lyon, France
- USMB, CNRS, LAMA UMR5127, Le Bourget du Lac, France
| | | | - Claire Lesieur
- Ecole Centrale de Lyon, Ampère, UMR5005, Univ. Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Villeurbanne, France
- Institut Rhônalpin des Systèmes Complexes, IXXI-ENS-Lyon, Lyon, France
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9
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Zhu Y, Ye F, Zhou Z, Liu W, Liang Z, Hu G. Insights into Conformational Dynamics and Allostery in DNMT1-H3Ub/USP7 Interactions. Molecules 2021; 26:molecules26175153. [PMID: 34500587 PMCID: PMC8434485 DOI: 10.3390/molecules26175153] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 08/23/2021] [Accepted: 08/23/2021] [Indexed: 01/03/2023] Open
Abstract
DNA methyltransferases (DNMTs) including DNMT1 are a conserved family of cytosine methylases that play crucial roles in epigenetic regulation. The versatile functions of DNMT1 rely on allosteric networks between its different interacting partners, emerging as novel therapeutic targets. In this work, based on the modeling structures of DNMT1-ubiquitylated H3 (H3Ub)/ubiquitin specific peptidase 7 (USP7) complexes, we have used a combination of elastic network models, molecular dynamics simulations, structural residue perturbation, network modeling, and pocket pathway analysis to examine their molecular mechanisms of allosteric regulation. The comparative intrinsic and conformational dynamics analysis of three DNMT1 systems has highlighted the pivotal role of the RFTS domain as the dynamics hub in both intra- and inter-molecular interactions. The site perturbation and network modeling approaches have revealed the different and more complex allosteric interaction landscape in both DNMT1 complexes, involving the events caused by mutational hotspots and post-translation modification sites through protein-protein interactions (PPIs). Furthermore, communication pathway analysis and pocket detection have provided new mechanistic insights into molecular mechanisms underlying quaternary structures of DNMT1 complexes, suggesting potential targeting pockets for PPI-based allosteric drug design.
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Affiliation(s)
- Yu Zhu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; (Y.Z.); (Z.Z.); (W.L.)
| | - Fei Ye
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China;
| | - Ziyun Zhou
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; (Y.Z.); (Z.Z.); (W.L.)
| | - Wanlin Liu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; (Y.Z.); (Z.Z.); (W.L.)
| | - Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; (Y.Z.); (Z.Z.); (W.L.)
- Correspondence: (Z.L.); (G.H.)
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; (Y.Z.); (Z.Z.); (W.L.)
- Correspondence: (Z.L.); (G.H.)
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10
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Bourgeat L, Pacini L, Serghei A, Lesieur C. Experimental diagnostic of sequence-variant dynamic perturbations revealed by broadband dielectric spectroscopy. Structure 2021; 29:1419-1429.e3. [PMID: 34051139 DOI: 10.1016/j.str.2021.05.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 03/23/2021] [Accepted: 05/07/2021] [Indexed: 02/08/2023]
Abstract
Genetic diversity leads to protein robustness, adaptability, and failure. Some sequence variants are structurally robust but functionally disturbed because mutations bring the protein onto unfolding/refolding routes resulting in misfolding diseases (e.g., Parkinson). We assume dynamic perturbations introduced by mutations foster the alternative unfolding routes and test this possibility by comparing the unfolding dynamics of the heat-labile enterotoxin B pentamers and the cholera toxin B pentamers, two pentamers structurally and functionally related and robust to 17 sequence variations. The B-subunit thermal unfolding dynamics are monitored by broadband dielectric spectroscopy in nanoconfined and weakly hydrated conditions. Distinct dielectric signals reveal the different B-subunits unfolding dynamics. Combined with network analyses, the experiments pinpoint the role of three mutations A1T, E7D, and E102A, in diverting LTB5 to alternative unfolding routes that protect LTB5 from dissociation. Altogether, the methodology diagnoses dynamics faults that may underlie functional disorder, drug resistance, or higher virulence of sequence variants.
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Affiliation(s)
- Laëtitia Bourgeat
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Univ Lyon, CNRS, IMP, 69622, Villeurbanne, France
| | - Lorenza Pacini
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Institut Rhônalpin des systèmes complexes, IXXI-ENS-Lyon, 69007, Lyon, France
| | | | - Claire Lesieur
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Institut Rhônalpin des systèmes complexes, IXXI-ENS-Lyon, 69007, Lyon, France.
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11
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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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12
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Wang Z, Ren J, Jin N, Liu X, Li X. Is Crocin a Potential Anti-tumor Candidate Targeting Microtubules? Computational Insights From Molecular Docking and Dynamics Simulations. Front Mol Biosci 2020; 7:586970. [PMID: 33251248 PMCID: PMC7674667 DOI: 10.3389/fmolb.2020.586970] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 10/13/2020] [Indexed: 12/27/2022] Open
Abstract
Although it is known crocin, a hydrophilic compound from the herbal plant Crocus sativus L., has promising antitumor activity, the detailed mechanism of its antitumor activity was not well understood. Recent experiments suggested tubulin as the primary target for the antitumor activity of crocin. However, due to a lack of crystal structure of tubulin bound with crocin, the exact binding mode and interaction between crocin and tubulin remains exclusive. In the present work, a computational study by integrating multiple conformation docking, molecular dynamics simulation as well as residue interaction network analysis was performed to investigate the molecular mechanism of crocin-tubulin interaction. By comparing the docking score, the most likely binding mode CRO_E1 were identified from 20 different binding modes of crocin in the vinca binding pockets. Further molecular dynamics simulation of CRO_E1 complex showed the binding of crocin is more stable than the inhibitor soblidotin and vinblastine. During the simulation course, an excessive number of hydrogen bonds were observed for the ligand crocin. The binding free energy of crocin-tubulin complex was calculated as -79.25 ± 7.24 kcal/mol, which is almost twice of the ligand soblidotin and vinblastine. By using energy decomposition, hot residues for CRO_E1 were identified as Gln11, Gln15, Thr72, Ser75, Pro173-Lys174-Val175-Ser176-Asp177, Tyr222, and Asn226 in the β-chain, and Asp245, Ala247-Leu248, Val250, Asn329, and Ile332 in the α-chain. Residue interaction network analysis also showed the importance of these hot residues in the interaction network of crocin-tubulin complex. In addition, a common residue motif Val175-Xxx176-Asp177 was discovered for all three bindings, suggesting its importance in future drug design. The study could provide valuable insights into the interaction between crocin and tubulin, and give suggestive clues for further experimental studies.
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Affiliation(s)
- Ze Wang
- Department of Pharmaceutical Sciences, Zunyi Medical University at Zhuhai Campus, Zhuhai, China
| | - Juan Ren
- Department of Pharmaceutical Sciences, Zunyi Medical University at Zhuhai Campus, Zhuhai, China
| | | | - Xingyi Liu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Xiaofei Li
- Department of Pharmaceutical Sciences, Zunyi Medical University at Zhuhai Campus, Zhuhai, China
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13
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Wingert B, Krieger J, Li H, Bahar I. Adaptability and specificity: how do proteins balance opposing needs to achieve function? Curr Opin Struct Biol 2020; 67:25-32. [PMID: 33053463 DOI: 10.1016/j.sbi.2020.08.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 08/30/2020] [Accepted: 08/30/2020] [Indexed: 12/14/2022]
Abstract
Many proteins select from a small repertoire of 3-dimensional folds retained over evolutional timescales and recruited for different functions, with changes in local structure and sequence to enable specificity. Recent studies have revealed the evolutionary constraints on protein dynamics to achieve function. The significance of protein dynamics in simultaneously satisfying conformational flexibility/malleability and stability/precision requirements becomes clear upon dissecting the spectrum of equilibrium motions accessible to fold families. Accessibility to highly conserved global modes of motions shared by family members, to low-to-intermediate-frequency modes that distinguish subfamilies and confer specificity, and to conserved high-frequency modes ensuring chemical precision and core stability underlies functional specialization while exploiting highly versatile folds. These design principles are illustrated for the family of PDZ domains.
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Affiliation(s)
- Bentley Wingert
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - James Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - Hongchun Li
- Research Center for Computer-Aided Drug Discovery at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA.
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Xiao F, Song X, Tian P, Gan M, Verkhivker GM, Hu G. Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding. J Chem Inf Model 2020; 60:3632-3647. [PMID: 32530640 DOI: 10.1021/acs.jcim.0c00447] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.
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Affiliation(s)
- Fei Xiao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Xingyu Song
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Peiyi Tian
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Mi Gan
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Gennady M Verkhivker
- Department of Computational and Data Sciences, Chapman University, One University Drive, Orange, California 92866, United States.,Department of Biomedical and Pharmaceutical Sciences, Chapman University Pharmacy School, 9401 Jeronimo Rd, Irvine, California 92618, United States
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
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15
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Liang Z, Zhu Y, Long J, Ye F, Hu G. Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s. Comput Struct Biotechnol J 2020; 18:749-764. [PMID: 32280430 PMCID: PMC7132064 DOI: 10.1016/j.csbj.2020.03.016] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 03/17/2020] [Accepted: 03/17/2020] [Indexed: 01/03/2023] Open
Abstract
Dynamics and allosteric potentials of the RFTS domain are proposed. Hinge sites located at the RFTS-CD interface are key regulators for inter-domain interactions. Network analysis reveals local allosteric networks and inter-domain communication pathways in DNMT1. A potential allosteric site at the TRD interface for DNMT1 is identified.
DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.
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Affiliation(s)
- Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Yu Zhu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Jie Long
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Fei Ye
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
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Role of protein-protein interactions in allosteric drug design for DNA methyltransferases. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2020; 121:49-84. [PMID: 32312426 DOI: 10.1016/bs.apcsb.2019.12.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
DNA methyltransferases (DNMTs) not only play key roles in epigenetic gene regulation, but also serve as emerging targets for several diseases, especially for cancers. Due to the multi-domains of DNMT structures, targeting allosteric sites of protein-protein interactions (PPIs) is becoming an attractive strategy in epigenetic drug discovery. This chapter aims to review the major contemporary approaches utilized for the drug discovery based on PPIs in different dimensions, from the enumeration of allosteric mechanism to the identification of allosteric pockets. These include the construction of protein structure networks (PSNs) based on molecular dynamics (MD) simulations, performing elastic network models (ENMs) and perturbation response scanning (PRS) calculation, the sequence-based conservation and coupling analysis, and the allosteric pockets identification. Furthermore, we complement this methodology by highlighting the role of computational approaches in promising practical applications for the computer-aided drug design, with special focus on two DNMTs, namely, DNMT1 and DNMT3A.
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Zhang Y, Doruker P, Kaynak B, Zhang S, Krieger J, Li H, Bahar I. Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior. Curr Opin Struct Biol 2019; 62:14-21. [PMID: 31785465 DOI: 10.1016/j.sbi.2019.11.002] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 10/31/2019] [Accepted: 11/04/2019] [Indexed: 12/13/2022]
Abstract
Allosteric behavior is central to the function of many proteins, enabling molecular machinery, metabolism, signaling and regulation. Recent years have shown that the intrinsic dynamics of allosteric proteins defined by their 3-dimensional architecture or by the topology of inter-residue contacts favors cooperative motions that bear close similarity to structural changes they undergo during their allosteric actions. These conformational motions are usually driven by energetically favorable or soft modes at the low frequency end of the mode spectrum, and they are evolutionarily conserved among orthologs. These observations brought into light evolutionary adaptation mechanisms that help maintain, optimize or regulate allosteric behavior as the evolution from bacterial to higher organisms introduces sequential heterogeneities and structural complexities.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - James Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Hongchun Li
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA; Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
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Yu J, Xie T, Wang Z, Wang X, Zeng S, Kang Y, Hou T. DNA methyltransferases: emerging targets for the discovery of inhibitors as potent anticancer drugs. Drug Discov Today 2019; 24:2323-2331. [PMID: 31494187 DOI: 10.1016/j.drudis.2019.08.006] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 07/18/2019] [Accepted: 08/09/2019] [Indexed: 12/21/2022]
Abstract
DNA methyltransferases (DNMTs) are a conserved family of cytosine methylases with crucial roles in epigenetic regulation. They have been considered as promising therapeutic targets for the epigenetic treatment of cancer. Therefore, DNMT inhibitors (DNMTis) have attracted considerable interest in recent years for the modulation of the aberrant DNA methylation pattern in a reversible way. In this review, we provide a structure-based overview of the therapeutic importance of DNMTs against different cancer types, and then summarize recently investigated DNMTis as well as their inhibitory mechanisms, focusing on recent advances in the development of DNMTis with specificity and/or selectivity using computational approaches.
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Affiliation(s)
- Jie Yu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Tianli Xie
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Zhe Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Xuwen Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Su Zeng
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Yu Kang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
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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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