1
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Li Z, Song G, Zhu J, Mu J, Sun Y, Hong X, Choi T, Cui X, Chen HF. Excited-Ground-State Transition of the RNA Strand Slippage Mechanism Captured by the Base-Specific Force Field. J Chem Theory Comput 2024; 20:6082-6097. [PMID: 38980289 DOI: 10.1021/acs.jctc.4c00497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Excited-ground-state transition and strand slippage of RNA play key roles in transcription and translation of central dogma. Due to limitation of current experimental techniques, the dynamic structure ensembles of RNA remain inadequately understood. Molecular dynamics simulations offer a promising complementary approach, whose accuracy depends on the force field. Here, we develop the new version of RNA base-specific force field (BSFF2) to address underestimation of base pairing stability and artificial backbone conformations. Extensive evaluations on typical RNA systems have comprehensively confirmed the accuracy of BSFF2. Furthermore, BSFF2 demonstrates exceptional efficiency in de novo folding of tetraloops and reproducing base pair reshuffling transition between RNA excited and ground states. Then, we explored the RNA strand slippage mechanism with BSFF2. We conducted a comprehensive three-dimensional structural investigation into the strand slippage of the most complex r(G4C2)9 repeat element and presented the molecular details in the dynamic transition along with the underlying mechanism. Our results of capturing the strand slippage, excited-ground transition, de novo folding, and simulations for various typical RNA motifs indicate that BSFF2 should be one of valuable tools for dynamic conformation research and structure prediction of RNA, and a future contribution to RNA-targeted drug design as well as RNA therapy development.
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Affiliation(s)
- Zhengxin Li
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ge Song
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Junjie Zhu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yutong Sun
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xiaokun Hong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian 350116, China
| | - Taeyoung Choi
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xiaochen Cui
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
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2
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Hu Z, Sun T, Chen W, Nordenskiöld L, Lu L. Refined Bonded Terms in Coarse-Grained Models for Intrinsically Disordered Proteins Improve Backbone Conformations. J Phys Chem B 2024; 128:6492-6508. [PMID: 38950000 DOI: 10.1021/acs.jpcb.4c02823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Coarse-grained models designed for intrinsically disordered proteins and regions (IDP/Rs) usually omit some bonded potentials (e.g., angular and dihedral potentials) as a conventional strategy to enhance backbone flexibility. However, a notable drawback of this approach is the generation of inaccurate backbone conformations. Here, we addressed this problem by introducing residue-specific angular, refined dihedral, and correction map (CMAP) potentials, derived based on the statistics from a customized coil database. These bonded potentials were integrated into the existing Mpipi model, resulting in a new model, denoted as the "Mpipi+" model. Results show that the Mpipi+ model can improve backbone conformations. More importantly, it can markedly improve the secondary structure propensity (SSP) based on the experimental chemical shift and, consequently, succeed in capturing transient secondary structures. Moreover, the Mpipi+ model preserves the liquid-liquid phase separation (LLPS) propensities of IDPs.
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Affiliation(s)
- Zixin Hu
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
| | - Tiedong Sun
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
| | - Wenwen Chen
- UHL no. 05-01, Tan Chin Tuan Wing, Office of the President, University Hall, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
| | - Lars Nordenskiöld
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
| | - Lanyuan Lu
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
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3
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Saluja S, Lennon R. Exploring novel therapeutic opportunities for hypertension: a paradigm-shifting approach via integrative multiomic analysis, pioneering the path to precision medicine. J Hypertens 2024; 42:1147-1149. [PMID: 38818837 DOI: 10.1097/hjh.0000000000003738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Affiliation(s)
- Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester
- Division of Medicine and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester
| | - Rachel Lennon
- Wellcome Centre for Cell-Matrix Research, Division of Cell-Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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4
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Świderek K, Martí S, Arafet K, Moliner V. Computational study of the mechanism of a polyurethane esterase A (PueA) from Pseudomonas chlororaphis. Faraday Discuss 2024. [PMID: 38836643 DOI: 10.1039/d4fd00022f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
The effective management of plastic waste has become a global imperative, given our reliance on a linear model in which plastics are manufactured, used once, and then discarded. This has led to the pervasive accumulation of plastic debris in landfills and environmental contamination. Recognizing this issue, numerous initiatives are underway to address the environmental repercussions associated with plastic disposal. In this study, we investigate the possible molecular mechanism of polyurethane esterase A (PueA), which has been previously identified as responsible for the degradation of a polyester polyurethane (PU) sample in Pseudomonas chlororaphis, as an effort to develop enzymatic biodegradation solutions. After generating the unsolved 3D structure of the protein by AlphaFold2 from its known genome, the enzymatic hydrolysis of the same model PU compound previously used in experiments has been explored employing QM/MM molecular dynamics simulations. This required a preliminary analysis of the 3D structure of the apo-enzyme, identifying the putative active site, and the search for the optimal protein-substrate binding site. Finally, the resulting free energy landscape indicates that wild-type PueA can degrade PU chains, although with low-level activity. The reaction takes place by a characteristic four-step path of the serine hydrolases, involving an acylation followed by a diacylation step. Energetics and structural analysis of the evolution of the active site along the reaction suggests that PueA can be considered a promising protein scaffold for further development to achieve efficient biodegradation of PU.
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Affiliation(s)
- Katarzyna Świderek
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain.
| | - Sergio Martí
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain.
| | - Kemel Arafet
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain.
| | - Vicent Moliner
- BioComp Group, Institute of Advanced Materials (INAM), Universitat Jaume I, 12071 Castellón, Spain.
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5
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Mu J, Li Z, Zhang B, Zhang Q, Iqbal J, Wadood A, Wei T, Feng Y, Chen HF. Graphormer supervised de novo protein design method and function validation. Brief Bioinform 2024; 25:bbae135. [PMID: 38557677 PMCID: PMC10982952 DOI: 10.1093/bib/bbae135] [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: 10/07/2023] [Revised: 01/31/2024] [Accepted: 03/12/2024] [Indexed: 04/04/2024] Open
Abstract
Protein design is central to nearly all protein engineering problems, as it can enable the creation of proteins with new biological functions, such as improving the catalytic efficiency of enzymes. One key facet of protein design, fixed-backbone protein sequence design, seeks to design new sequences that will conform to a prescribed protein backbone structure. Nonetheless, existing sequence design methods present limitations, such as low sequence diversity and shortcomings in experimental validation of the designed functional proteins. These inadequacies obstruct the goal of functional protein design. To improve these limitations, we initially developed the Graphormer-based Protein Design (GPD) model. This model utilizes the Transformer on a graph-based representation of three-dimensional protein structures and incorporates Gaussian noise and a sequence random masks to node features, thereby enhancing sequence recovery and diversity. The performance of the GPD model was significantly better than that of the state-of-the-art ProteinMPNN model on multiple independent tests, especially for sequence diversity. We employed GPD to design CalB hydrolase and generated nine artificially designed CalB proteins. The results show a 1.7-fold increase in catalytic activity compared to that of the wild-type CalB and strong substrate selectivity on p-nitrophenyl acetate with different carbon chain lengths (C2-C16). Thus, the GPD method could be used for the de novo design of industrial enzymes and protein drugs. The code was released at https://github.com/decodermu/GPD.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
- Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, No.5 Yiheyuan Road, Beijing, 100871, China
| | - Zhengxin Li
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Bo Zhang
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Qi Zhang
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Jamshed Iqbal
- Centre for Advanced Drug Research, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, 22060, Pakistan
| | - Abdul Wadood
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, 23200, Pakistan
| | - Ting Wei
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Yan Feng
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
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6
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Choi T, Li Z, Song G, Chen HF. Comprehensive Comparison and Critical Assessment of RNA-Specific Force Fields. J Chem Theory Comput 2024; 20:2676-2688. [PMID: 38447040 DOI: 10.1021/acs.jctc.4c00066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Molecular dynamics simulations play a pivotal role in elucidating the dynamic behaviors of RNA structures, offering a valuable complement to traditional methods such as nuclear magnetic resonance or X-ray. Despite this, the current precision of RNA force fields lags behind that of protein force fields. In this work, we systematically compared the performance of four RNA force fields (ff99bsc0χOL3, AMBERDES, ff99OL3_CMAP1, AMBERMaxEnt) across diverse RNA structures. Our findings highlight significant challenges in maintaining stability, particularly with regard to cross-strand and cross-loop hydrogen bonds. Furthermore, we observed the limitations in accurately describing the conformations of nonhelical structural motif, terminal nucleotides, and also base pairing and base stacking interactions by the tested RNA force fields. The identified deficiencies in existing RNA force fields provide valuable insights for subsequent force field development. Concurrently, these findings offer recommendations for selecting appropriate force fields in RNA simulations.
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Affiliation(s)
- Taeyoung Choi
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhengxin Li
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ge Song
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
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7
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Di Prima D, Reinholdt P, Kongsted J. Color Tuning in Bovine Rhodopsin through Polarizable Embedding. J Phys Chem B 2024. [PMID: 38489248 DOI: 10.1021/acs.jpcb.3c07891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
Bovine rhodopsin is among the most studied proteins in the rhodopsin family. Its primary activation mechanism is the photoisomerization of 11-cis retinal, triggered by the absorption of a UV-visible photon. Different mutants of the same rhodopsin show different absorption wavelengths due to the influence of the specific amino acid residues forming the cavity in which the retinal chromophore is embedded, and rhodopsins activated at different wavelengths are, for example, exploited in the field of optogenetics. In this letter, we present a procedure for systematically investigating color tuning in models of bovine rhodopsin and a set of its mutants embedded in a membrane bilayer. Vertical excitation energy calculations were carried out with the polarizable embedding potential for describing the environment surrounding the chromophore. We show that polarizable embedding outperformed regular electrostatic embedding in determining both the vertical excitation energies and associated oscillator strengths of the systems studied.
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Affiliation(s)
- Duccio Di Prima
- Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Peter Reinholdt
- Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Jacob Kongsted
- Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense M DK-5230, Denmark
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8
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Zhu J, Li Z, Tong H, Lu Z, Zhang N, Wei T, Chen HF. Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling. Brief Bioinform 2023; 25:bbad429. [PMID: 38018910 PMCID: PMC10783862 DOI: 10.1093/bib/bbad429] [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: 08/14/2023] [Revised: 09/21/2023] [Accepted: 11/05/2023] [Indexed: 11/30/2023] Open
Abstract
The biological function of proteins is determined not only by their static structures but also by the dynamic properties of their conformational ensembles. Numerous high-accuracy static structure prediction tools have been recently developed based on deep learning; however, there remains a lack of efficient and accurate methods for exploring protein dynamic conformations. Traditionally, studies concerning protein dynamics have relied on molecular dynamics (MD) simulations, which incur significant computational costs for all-atom precision and struggle to adequately sample conformational spaces with high energy barriers. To overcome these limitations, various enhanced sampling techniques have been developed to accelerate sampling in MD. Traditional enhanced sampling approaches like replica exchange molecular dynamics (REMD) and frontier expansion sampling (FEXS) often follow the MD simulation approach and still cost a lot of computational resources and time. Variational autoencoders (VAEs), as a classic deep generative model, are not restricted by potential energy landscapes and can explore conformational spaces more efficiently than traditional methods. However, VAEs often face challenges in generating reasonable conformations for complex proteins, especially intrinsically disordered proteins (IDPs), which limits their application as an enhanced sampling method. In this study, we presented a novel deep learning model (named Phanto-IDP) that utilizes a graph-based encoder to extract protein features and a transformer-based decoder combined with variational sampling to generate highly accurate protein backbones. Ten IDPs and four structured proteins were used to evaluate the sampling ability of Phanto-IDP. The results demonstrate that Phanto-IDP has high fidelity and diversity in the generated conformation ensembles, making it a suitable tool for enhancing the efficiency of MD simulation, generating broader protein conformational space and a continuous protein transition path.
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Affiliation(s)
- Junjie Zhu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhengxin Li
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Haowei Tong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhouyu Lu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ningjie Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ting Wei
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
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9
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Djulbegovic M, Taylor Gonzalez DJ, Antonietti M, Uversky VN, Shields CL, Karp CL. Intrinsic disorder may drive the interaction of PROS1 and MERTK in uveal melanoma. Int J Biol Macromol 2023; 250:126027. [PMID: 37506796 PMCID: PMC11182630 DOI: 10.1016/j.ijbiomac.2023.126027] [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: 11/28/2022] [Revised: 07/23/2023] [Accepted: 07/25/2023] [Indexed: 07/30/2023]
Abstract
BACKGROUND Class 2 uveal melanomas are associated with the inactivation of the BRCA1 ((breast cancer type 1 susceptibility protein)-associated protein 1 (BAP1)) gene. Inactivation of BAP1 promotes the upregulation of vitamin K-dependent protein S (PROS1), which interacts with the tyrosine-protein kinase Mer (MERTK) receptor on M2 macrophages to induce an immunosuppressive environment. METHODS We simulated the interaction of PROS1 with MERTK with ColabFold. We evaluated PROS1 and MERTK for the presence of intrinsically disordered protein regions (IDPRs) and disorder-to-order (DOT) regions to understand their protein-protein interaction (PPI). We first evaluated the structure of each protein with AlphaFold. We then analyzed specific sequence-based features of the PROS1 and MERTK with a suite of bioinformatics tools. RESULTS With high-resolution, moderate confidence, we successfully modeled the interaction between PROS1 and MERTK (predicted local distance difference test score (pDLLT) = 70.68). Our structural analysis qualitatively demonstrated IDPRs (i.e., spaghetti-like entities) in PROS1 and MERK. PROS1 was 23.37 % disordered, and MERTK was 23.09 % disordered, classifying them as moderately disordered and flexible proteins. PROS1 was significantly enriched in cysteine, the most order-promoting residue (p-value <0.05). Our IUPred analysis demonstrated that there are two disorder-to-order transition (DOT) regions in PROS1. MERTK was significantly enriched in proline, the most disorder-promoting residue (p-value <0.05), but did not contain DOT regions. Our STRING analysis demonstrated that the PPI network between PROS1 and MERTK is more complex than their assumed one-to-one binding (p-value <2.0 × 10-6). CONCLUSION Our findings present a novel prediction for the interaction between PROS1 and MERTK. Our findings show that PROS1 and MERTK contain elements of intrinsic disorder. PROS1 has two DOT regions that are attractive immunotherapy targets. We recommend that IDPRs and DOT regions found in PROS1 and MERTK should be considered when developing immunotherapies targeting this PPI.
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Affiliation(s)
- Mak Djulbegovic
- Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA
| | | | | | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | - Carol L Shields
- Ocular Oncology Service, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, PA, USA
| | - Carol L Karp
- Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA.
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10
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Pan Z, Mu J, Chen HF. Balanced Three-Point Water Model OPC3-B for Intrinsically Disordered and Ordered Proteins. J Chem Theory Comput 2023; 19:4837-4850. [PMID: 37452752 DOI: 10.1021/acs.jctc.3c00297] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Intrinsically disordered proteins (IDPs) play a critical role in many biological processes. Due to the inherent structural flexibility of IDPs, experimental methods present significant challenges for sampling their conformational information at the atomic level. Therefore, molecular dynamics (MD) simulations have emerged as the primary tools for modeling IDPs whose accuracy depend on force field and water model. To enhance the accuracy of physical modeling of IDPs, several force fields have been developed. However, current water models lack precision and underestimate the interaction between water molecules and proteins. Here, we used Monte-Carlo re-weighting method to re-parameterize a three-point water model based on OPC3 for IDPs (named OPC3-B). We benchmarked the performance of OPC3-B compared with nine different water models for 10 IDPs and three ordered proteins. The results indicate that the performance of OPC3-B is better than other water models for both IDPs and ordered proteins. At the same time, OPC3-B possess the power of transferability with other force field to simulate IDPs. This newly developed water model can be used to insight into the research of sequence-disordered-function paradigm for IDPs.
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Affiliation(s)
- Zhengsong Pan
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Center for Bioinformation Technology, Shanghai 200235, China
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11
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Saurabh S, Nadendla K, Purohit SS, Sivakumar PM, Cetinel S. Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm. ACS OMEGA 2023; 8:9729-9747. [PMID: 36969402 PMCID: PMC10034788 DOI: 10.1021/acsomega.2c07708] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.
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Affiliation(s)
- Suman Saurabh
- Molecular
Sciences Research Hub, Department of Chemistry, Imperial College London, London W12 0BZ, U.K.
| | - Karthik Nadendla
- Center
for Misfolding Diseases, Yusuf Hamied Department of Chemistry, Lensfield
Road, University of Cambridge, Cambridge CB2 1EW, U.K.
| | - Shubh Sanket Purohit
- Department
of Clinical Haematology, Sahyadri Superspeciality
Hospital, Pune, Maharashtra 411038, India
| | - Ponnurengam Malliappan Sivakumar
- Institute
of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
- School
of Medicine and Pharmacy, Duy Tan University, Da Nang 550000, Vietnam
- Nanotechnology
Research and Application Center (SUNUM), Sabanci University, Istanbul 34956, Turkey
| | - Sibel Cetinel
- Nanotechnology
Research and Application Center (SUNUM), Sabanci University, Istanbul 34956, Turkey
- Faculty of
Engineering and Natural Sciences, Molecular Biology, Genetics and
Bioengineering Program, Sabanci University, Istanbul 34956, Turkey
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12
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Li T, Hendrix E, He Y. Simple and Effective Conformational Sampling Strategy for Intrinsically Disordered Proteins Using the UNRES Web Server. J Phys Chem B 2023; 127:2177-2186. [PMID: 36827446 DOI: 10.1021/acs.jpcb.2c08945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Intrinsically disordered proteins (IDPs) contain more charged amino acids than folded proteins, resulting in a lack of hydrophobic core(s) and a tendency to adopt rapidly interconverting structures rather than well-defined structures. The structural heterogeneity of IDPs, encoded by the amino acid sequence, is closely related to their unique roles in biological pathways, which require them to interact with different binding partners. Recently, Robustelli and co-workers have demonstrated that a balanced all-atom force field can be used to sample heterogeneous structures of disordered proteins ( Proc. Natl. Acad. Sci. U.S.A. 2018, 115, E4758-E4766). However, such a solution requires extensive computational resources, such as Anton supercomputers. Here, we propose a simple and effective solution to sample the conformational space of IDPs using a publicly available web server, namely, the UNited-RESidue (UNRES) web server. Our proposed solution requires no investment in computational resources and no prior knowledge of UNRES. UNRES Replica Exchange Molecular Dynamics (REMD) simulations were carried out on a set of eight disordered proteins at temperatures spanning from 270 to 430 K. Utilizing the latest UNRES force field designed for structured proteins, with proper selections of temperatures, we were able to produce comparable results to all-atom force fields as reported in work done by Robustelli and co-workers. In addition, NMR observables and the radius of gyration calculated from UNRES ensembles were directly compared with the experimental data to further evaluate the accuracy of the UNRES model at all temperatures. Our results suggest that carrying out the UNRES simulations at optimal temperatures using the UNRES web server can be a good alternative to sample heterogeneous structures of IDPs.
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Affiliation(s)
- Tongtong Li
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Emily Hendrix
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Yi He
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States.,Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87131, United States
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13
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Song G, Zhong B, Zhang B, Rehman AU, Chen HF. Phosphorylation Modification Force Field FB18CMAP Improving Conformation Sampling of Phosphoproteins. J Chem Inf Model 2023; 63:1602-1614. [PMID: 36800279 DOI: 10.1021/acs.jcim.3c00112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Phosphorylation of proteins plays an important regulatory role at almost all levels of cellular organization. Molecular dynamics (MD) simulation is a promising tool to reveal the mechanism of how phosphorylation regulates many key biological processes at the atomistic level. MD simulation accuracy depends on force field precision, while the current force fields for phospho-amino acids have resulted in notable inconsistency with experimental data. Here, a new force field parameter (named FB18CMAP) is generated by fitting against quantum mechanics (QM) energy in aqueous solution with φ/ψ dihedral potential-energy surfaces optimized using CMAP parameters. MD simulations of phosphorylated dipeptides, intrinsically disordered proteins (IDPs), and ordered (folded) proteins show that FB18CMAP can mimic NMR observables and structural characteristics of phosphorylated dipeptides and proteins more accurately than the FB18 force field. These findings suggest that FB18CMAP performs well in both the simulation of ordered and disordered states of phosphorylated proteins.
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Affiliation(s)
- Ge Song
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bozitao Zhong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bo Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ashfaq Ur Rehman
- Departments of Molecular Biology and Biochemistry, University of California, Irvine, California 92697, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Center for Bioinformation Technology, Shanghai 200240, China
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14
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Park J, Lee HS, Kim H, Choi JM. Conformational landscapes of artificial peptides predicted by various force fields: are we ready to simulate β-amino acids? Phys Chem Chem Phys 2023; 25:7466-7476. [PMID: 36848062 DOI: 10.1039/d2cp05998c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer's complex structure-function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.
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Affiliation(s)
- Jihye Park
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 34141, Republic of Korea.
| | - Hee-Seung Lee
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 34141, Republic of Korea. .,Center for Multiscale Chiral Architectures, KAIST, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Hyungjun Kim
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 34141, Republic of Korea.
| | - Jeong-Mo Choi
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Geumjeong-gu, Busan 46241, Republic of Korea.
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15
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Moore SJ, Deplazes E, Mancera RL. Influence of force field choice on the conformational landscape of rat and human islet amyloid polypeptide. Proteins 2023; 91:338-353. [PMID: 36163697 PMCID: PMC10092333 DOI: 10.1002/prot.26432] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 02/04/2023]
Abstract
Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein (IDP) whose abnormal aggregation into toxic soluble oligomers and insoluble amyloid fibrils is a pathological feature in type-2 diabetes. Rat IAPP (rIAPP) differs from hIAPP by only six amino acids yet has a reduced tendency to aggregate or form fibrils. The structures of the monomeric forms of IAPP are difficult to characterize due to their intrinsically disordered nature. Molecular dynamics simulations can provide a detailed characterization of the monomeric forms of rIAPP and hIAPP in near-physiological conditions. In this work, the conformational landscapes of rIAPP and hIAPP as a function of secondary structure content were predicted using well-tempered bias exchange metadynamics simulations. Several combinations of commonly used biomolecular force fields and water models were tested. The predicted conformational preferences of both rIAPP and hIAPP are typical of IDPs, exhibiting dominant random coil structures but showing a low propensity for transient α-helical conformations. Predicted nuclear magnetic resonance Cα chemical shifts reveal different preferences with each force field towards certain conformations, with AMBERff99SBnmr2/TIP4Pd showing the best agreement with the experiment. Comparisons of secondary structure content demonstrate residue-specific differences between hIAPP and rIAPP that may reflect their different aggregation propensities.
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Affiliation(s)
- Sandra J Moore
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia
| | - Evelyne Deplazes
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia.,School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Ricardo L Mancera
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia
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16
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Hong X, Song K, Rahman MU, Wei T, Zhang Y, Da LT, Chen HF. Phosphorylation Regulation Mechanism of β2 Integrin for the Binding of Filamin Revealed by Markov State Model. J Chem Inf Model 2023; 63:605-618. [PMID: 36607244 DOI: 10.1021/acs.jcim.2c01177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Leukocyte adhesion deficiency-1 (LAD-1) disorder is a severe immunodeficiency syndrome caused by deficiency or mutation of β2 integrin. The phosphorylation on threonine 758 of β2 integrin acts as a molecular switch inhibiting the binding of filamin. However, the switch mechanism of site-specific phosphorylation at the atom level is still poorly understood. To resolve the regulation mechanism, all-atom molecular dynamics simulation and Markov state model were used to study the dynamic regulation pathway of phosphorylation. Wild type system possessed lower binding free energy and fewer number of states than the phosphorylated system. Both systems underwent local disorder-to-order conformation conversion when achieving steady states. To reach steady states, wild type adopted less number of transition paths/shortest path according to the transition path theory than the phosphorylated system. The underlying phosphorylated regulation pathway was from P1 to P0 and then P4 state, and the main driving force should be hydrogen bond and hydrophobic interaction disturbing the secondary structure of phosphorylated states. These studies will shed light on the pathogenesis of LAD-1 disease and lay a foundation for drug development.
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Affiliation(s)
- Xiaokun Hong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Kaiyuan Song
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Mueed Ur Rahman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Ting Wei
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Yan Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Lin-Tai Da
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai200240, China
- Shanghai Center for Bioinformation Technology, Shanghai200240, China
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17
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Ji X, Liu H, Zhang Y, Chen J, Chen HF. Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning. J Chem Inf Model 2023; 63:362-374. [PMID: 36533639 DOI: 10.1021/acs.jcim.2c01501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabetes, and other diseases. Experimental methods can hardly capture the ensemble of diverse conformations for IDPs. Molecular dynamics (MD) simulations can sample continuous conformations that might provide a valuable complement to experimental data. However, the accuracy of MD simulations depends on the quality of force field. In particular, the evolutionary conservation and coevolution of IDPs introduce that current force fields could not precisely reproduce the conformation of IDPs. In order to improve the performance of force field, deep learning and reweighting methods were used to automatically generate personal force field parameters for intrinsically disordered and ordered proteins. At first, the deep learning method predicted more accuracy φ/ψ dihedral of residue than the previous method. Then, reweighting optimized the personal force field parameters for each residue. Finally, typical representative systems such as IDPs, structure protein, and fast-folding protein were used to evaluate this force field. The results indicate that two personal force field parameters (named PPFF1 and PPFF1_af2) could better reproduce the experimental observables than ff03CMAP force field. In summary, this strategy will provide feasibility for the development of precise personal force fields.
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Affiliation(s)
- Xiaoyue Ji
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China
| | - Yangpeng Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China
| | - Jun Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China.,Shanghai Center for Bioinformation Technology, Shanghai200235, China
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18
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Li M, Wang Y, Guo C, Wang S, Zheng L, Bu Y, Ding K. The claim of primacy of human gut Bacteroides ovatus in dietary cellobiose degradation. Gut Microbes 2023; 15:2227434. [PMID: 37349961 PMCID: PMC10291918 DOI: 10.1080/19490976.2023.2227434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 06/14/2023] [Indexed: 06/24/2023] Open
Abstract
A demonstration of cellulose degrading bacterium from human gut changed our view that human cannot degrade the cellulose. However, investigation of cellulose degradation by human gut microbiota on molecular level has not been completed so far. We showed here, using cellobiose as a model that promoted the growth of human gut key members, such as Bacteroides ovatus (BO), to clarify the molecular mechanism. Our results showed that a new polysaccharide utilization locus (PUL) from BO was involved in the cellobiose capturing and degradation. Further, two new cellulases BACOVA_02626GH5 and BACOVA_02630GH5 on the cell surface performed the degradation of cellobiose into glucose were determined. The predicted structures of BACOVA_02626GH5 and BACOVA_02630GH5 were highly homologous with the cellulase from soil bacteria, and the catalytic residues were highly conservative with two glutamate residues. In murine experiment, we observed cellobiose reshaped the composition of gut microbiota and probably modified the metabolic function of bacteria. Taken together, our findings further highlight the evidence of cellulose can be degraded by human gut microbes and provide new insight in the field of investigation on cellulose.
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Affiliation(s)
- Meixia Li
- Glycochemistry and Glycobiology Lab, Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Yeqing Wang
- Glycochemistry and Glycobiology Lab, Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Ciliang Guo
- Glycochemistry and Glycobiology Lab, Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China
- University of Chinese Academy of Science, Beijing, P. R. China
| | | | | | - Yifan Bu
- Zelixir Biotech, Shanghai, P. R. China
| | - Kan Ding
- Glycochemistry and Glycobiology Lab, Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China
- University of Chinese Academy of Science, Beijing, P. R. China
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Science, SSIP Healthcare and Medicine Demonstration Zone, Zhongshan, P. R. China
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19
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Pedersen KB, Flores-Canales JC, Schiøtt B. Predicting molecular properties of α-synuclein using force fields for intrinsically disordered proteins. Proteins 2023; 91:47-61. [PMID: 35950933 PMCID: PMC10087257 DOI: 10.1002/prot.26409] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/17/2022] [Accepted: 07/12/2022] [Indexed: 12/29/2022]
Abstract
Independent force field validation is an essential practice to keep track of developments and for performing meaningful Molecular Dynamics simulations. In this work, atomistic force fields for intrinsically disordered proteins (IDP) are tested by simulating the archetypical IDP α-synuclein in solution for 2.5 μs. Four combinations of protein and water force fields were tested: ff19SB/OPC, ff19SB/TIP4P-D, ff03CMAP/TIP4P-D, and a99SB-disp/TIP4P-disp, with four independent repeat simulations for each combination. We compare our simulations to the results of a 73 μs simulation using the a99SB-disp/TIP4P-disp combination, provided by D. E. Shaw Research. From the trajectories, we predict a range of experimental observations of α-synuclein and compare them to literature data. This includes protein radius of gyration and hydration, intramolecular distances, NMR chemical shifts, and 3 J-couplings. Both ff19SB/TIP4P-D and a99SB-disp/TIP4P-disp produce extended conformational ensembles of α-synuclein that agree well with experimental radius of gyration and intramolecular distances while a99SB-disp/TIP4P-disp reproduces a balanced α-synuclein secondary structure content. It was found that ff19SB/OPC and ff03CMAP/TIP4P-D produce overly compact conformational ensembles and show discrepancies in the secondary structure content compared to the experimental data.
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Affiliation(s)
| | | | - Birgit Schiøtt
- Department of Chemistry, Aarhus University, Aarhus C, Denmark.,Interdisciplinary Nanoscience Center, Aarhus University, Aarhus C, Denmark
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20
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Jiang Y, Chen HF. Performance evaluation of the balanced force field ff03CMAP for intrinsically disordered and ordered proteins. Phys Chem Chem Phys 2022; 24:29870-29881. [PMID: 36468450 DOI: 10.1039/d2cp04501j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Intrinsically disordered proteins (IDPs) have been found to be closely associated with various human diseases. Because IDPs have no fixed tertiary structure under physiological conditions, current experimental methods, such as X-ray spectroscopy, NMR, and CryoEM, cannot capture all the dynamic conformations. Molecular dynamics simulation is an useful tool that is widely used to study the conformer distributions of IDPs and has become an important complementary tool for experimental methods. However, the accuracy of MD simulations directly depends on utilizing a precise force field. Recently a CMAP optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of IDPs and folded proteins. In order to further evaluate the performance, more types of disordered and ordered proteins were used to test the ability for conformer sampling. The results showed that simulated chemical shifts, J-coupling, and Rg distribution with the ff03CMAP force field were in better agreement with NMR measurements and were more accurate than those with the ff03 force field. The sampling conformations by ff03CMAP were more diverse than those of ff03. At the same time, ff03CMAP could stabilize the conformers of the ordered proteins. These findings indicate that ff03CMAP can be widely used to sample diverse conformers for proteins, including the intrinsically disordered regions.
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Affiliation(s)
- Yuxin Jiang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. .,Shanghai Center for Bioinformation Technology, 200240, Shanghai, China
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21
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Cui X, Liu H, Chen HF. Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization. J Chem Inf Model 2022; 62:4970-4982. [PMID: 36178373 DOI: 10.1021/acs.jcim.2c00835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.
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Affiliation(s)
- Xiaochen Cui
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China
| | - Hao Liu
- Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai200240, China.,Shanghai Center for Bioinformation Technology, Shanghai200235, China
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22
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Balanced Force Field ff03CMAP Improving the Dynamics Conformation Sampling of Phosphorylation Site. Int J Mol Sci 2022; 23:ijms231911285. [PMID: 36232586 PMCID: PMC9569523 DOI: 10.3390/ijms231911285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/08/2022] [Accepted: 09/11/2022] [Indexed: 11/30/2022] Open
Abstract
Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins.
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23
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Base-specific RNA force field improving the dynamics conformation of nucleotide. Int J Biol Macromol 2022; 222:680-690. [PMID: 36167105 DOI: 10.1016/j.ijbiomac.2022.09.183] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/02/2022] [Accepted: 09/19/2022] [Indexed: 11/23/2022]
Abstract
RNA plays a key role in numerous biological processes. Traditional experimental methods have difficulties capturing the structure and dynamic conformation of RNA. Thus, Molecular dynamic simulations (MDs) has become an essential complementary for RNA experiment. However, state-of-the-art RNA force fields have two major limitations of overestimation base stacking propensity and generation of a high ratio of intercalated conformations. Therefore, a two-step strategy was used to optimize the parameters of ff99bsc0χOL3 (named BSFF1) to improve these limitations, which as well adjusted the unbonded parameters of nucleobase heavy atoms and added ζ/α grid-based energy correction map energy term with reweighting. MD simulations of tetranucleotides indicate that BSFF1 can significantly decrease the ratio of intercalated conformations. Tests of single-strand RNA and kink-turn show that BSFF1 force field can reproduce more accurate conformers than ff99bsc0χOL3 force field. BSFF1 can also stabilize the conformers of duplex and riboswitch. The successful ab initio folding of tetraloop further supports the performance of BSFF1. These findings confirm that the newly developed force field BSFF1 can improve the conformer sampling of RNA.
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24
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Zhang ZL, Chen C, Qu SY, Ding Q, Xu Q. Unexpected Dynamic Binding May Rescue the Binding Affinity of Rivaroxaban in a Mutant of Coagulation Factor X. Front Mol Biosci 2022; 9:877170. [PMID: 35601826 PMCID: PMC9117642 DOI: 10.3389/fmolb.2022.877170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
A novel coagulation factor X (FX) Tyr319Cys mutation (Y99C as chymotrypsin numbering) was identified in a patient with severe bleeding. Unlike the earlier reported Y99A mutant, this mutant can bind and cleave its specific chromogenetic substrate at a normal level, suggesting an intact binding pocket. Here, using molecular dynamics simulations and MM-PBSA calculations on a FX-rivaroxaban (RIV) complex, we confirmed a much stronger binding of RIV in Y99C than in Y99A on a molecular level, which is actually the average result of multiple binding poses in dynamics. Detailed structural analyses also indicated the moderate flexibility of the 99-loop and the importance of the flexible side chain of Trp215 in the different binding poses. This case again emphasizes that binding of ligands may not only be a dynamic process but also a dynamic state, which is often neglected in drug design and screening based on static X-ray structures. In addition, the computational results somewhat confirmed our hypothesis on the activated Tyr319Cys FX (Y99C FXa) with an impaired procoagulant function to bind inhibitors of FXa and to be developed into a potential reversal agent for novel oral anticoagulants (NOAC).
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Affiliation(s)
- Zhi-Li Zhang
- State Key Laboratory of Microbial Metabolism & Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Changming Chen
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Si-Ying Qu
- State Key Laboratory of Microbial Metabolism & Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Qiulan Ding
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Collaborative Innovation Center of Hematology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Qiulan Ding, ; Qin Xu,
| | - Qin Xu
- State Key Laboratory of Microbial Metabolism & Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Qiulan Ding, ; Qin Xu,
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25
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Rahman MU, Song K, Da LT, Chen HF. Early aggregation mechanism of Aβ 16-22 revealed by Markov state models. Int J Biol Macromol 2022; 204:606-616. [PMID: 35134456 DOI: 10.1016/j.ijbiomac.2022.02.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/24/2022] [Accepted: 02/01/2022] [Indexed: 12/19/2022]
Abstract
Aβ16-22 is believed to have critical role in early aggregation of full length amyloids that are associated with the Alzheimer's disease and can aggregate to form amyloid fibrils. However, the early aggregation mechanism is still unsolved. Here, multiple long-term molecular dynamics simulations combining with Markov state model were used to probe the early oligomerization mechanism of Aβ16-22 peptides. The identified dimeric form adopted either globular random-coil or extended β-strand like conformations. The observed dimers of these variants shared many overall conformational characteristics but differed in several aspects at detailed level. In all cases, the most common type of secondary structure was intermolecular antiparallel β-sheets. The inter-state transitions were very frequent ranges from few to hundred nanoseconds. More strikingly, those states which contain fraction of β secondary structure and significant amount of extended coiled structures, therefore exposed to the solvent, were majorly participated in aggregation. The assembly of low-energy dimers, in which the peptides form antiparallel β sheets, occurred by multiple pathways with the formation of an obligatory intermediates. We proposed that these states might facilitate the Aβ16-22 aggregation through a significant component of the conformational selection mechanism, because they might increase the aggregates population by promoting the inter-chain hydrophobic and the hydrogen bond contacts. The formation of early stage antiparallel β sheet structures is critical for oligomerization, and at the same time provided a flat geometry to seed the ordered β-strand packing of the fibrils. Our findings hint at reorganization of this part of the molecule as a potentially critical step in Aβ aggregation and will insight into early oligomerization for large β amyloids.
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Affiliation(s)
- Mueed Ur Rahman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kaiyuan Song
- Key Laboratory of System Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Lin-Tai Da
- Key Laboratory of System Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China; Shanghai Center for Bioinformation Technology, Shanghai, 200235, China.
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26
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Chen J, Liu H, Cui X, Li Z, Chen HF. RNA-Specific Force Field Optimization with CMAP and Reweighting. J Chem Inf Model 2022; 62:372-385. [PMID: 35021622 DOI: 10.1021/acs.jcim.1c01148] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
RNA plays a key role in a variety of cell activities. However, it is difficult to capture its structure dynamics by the traditional experimental methods because of the inherent limitations. Molecular dynamics simulation has become a valuable complement to the experimental methods. Previous studies have indicated that the current force fields cannot accurately reproduce the conformations and structural dynamics of RNA. Therefore, an RNA-specific force field was developed to improve the conformation sampling of RNA. The distribution of ζ/α dihedrals of tetranucleotides was optimized by a reweighting method, and the grid-based energy correction map (CMAP) term was first introduced into the Amber RNA force field of ff99bsc0χOL3, named ff99OL3_CMAP1. Extensive validations of tetranucleotides and tetraloops show that ff99OL3_CMAP1 can significantly decrease the population of an incorrect structure, increase the consistency between the simulation results and experimental values for tetranucleotides, and improve the stability of tetraloops. ff99OL3_CMAP1 can also precisely reproduce the conformation of a duplex and riboswitches. These findings confirm that the newly developed force field ff99OL3_CMAP1 can improve the conformer sampling of RNA.
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Affiliation(s)
- Jun Chen
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 20024 Shanghai, China
| | - Hao Liu
- Institute of Natural Sciences, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Xiaochen Cui
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 20024 Shanghai, China
| | - Zhengxin Li
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 20024 Shanghai, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 20024 Shanghai, China.,Shanghai Center for Bioinformation Technology, 200240 Shanghai, China
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Mu J, Zhou J, Gong Q, Xu Q. An allosteric regulation mechanism of Arabidopsis Serine/Threonine kinase 1 (SIK1) through phosphorylation. Comput Struct Biotechnol J 2022; 20:368-379. [PMID: 35035789 PMCID: PMC8749016 DOI: 10.1016/j.csbj.2021.12.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/23/2021] [Accepted: 12/23/2021] [Indexed: 11/21/2022] Open
Abstract
The Arabidopsis Serine/Threonine Kinase 1 (SIK1) is a Sterile 20 (STE20)/Hippo orthologue that is also categorized as a Mitogen-Activated Protein Kinase Kinase Kinase Kinase (MAP4K). Like its animal and fungi orthologues, SIK1 is required for cell cycle exit, cell expansion, polarity establishment, as well as pathogenic response. The catalytic activity of SIK1, like other MAPKs, is presumably regulated by its phosphorylation states. Since no crystal structure for SIK1 has been reported yet, we built structural models for SIK1 kinase domain in different phosphorylation states with different pocket conformation to see how this kinase may be regulated. Using computational structural biology methods, we outlined a conduction path in which a phosphorylation site on the A-loop regulates the catalytic activity of SIK1 by controlling the closing or opening of the catalytic pocket at the G-loop. Furthermore, with analyses on the dynamic motions and in vitro kinase assay, we confirmed that three key residues in this conduction path, Lys278, Glu295, and Arg370, are indeed important for the kinase activity of SIK1. Since these residues are conserved in all STE20 kinases examined, the regulatory mechanism that we discovered may be common in STE20 kinases.
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28
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Co NT, Li MS, Krupa P. Computational Models for the Study of Protein Aggregation. Methods Mol Biol 2022; 2340:51-78. [PMID: 35167070 DOI: 10.1007/978-1-0716-1546-1_4] [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] [Indexed: 06/14/2023]
Abstract
Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.
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Affiliation(s)
- Nguyen Truong Co
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
- Institute for Computational Science and Technology, Ho Chi Minh City, Vietnam
| | - Pawel Krupa
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland.
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29
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Nguyen PH, Derreumaux P. Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation. Methods Mol Biol 2022; 2340:175-196. [PMID: 35167075 DOI: 10.1007/978-1-0716-1546-1_9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein aggregation can lead to well-defined structures that are functional, but is also the cause of the death of neuron cells in many neurodegenerative diseases. The complexity of the molecular events involved in the aggregation kinetics of amyloid proteins and the transient and heterogeneous characters of all oligomers prevent high-resolution structural experiments. As a result, computer simulations have been used to determine the atomic structures of amyloid proteins at different association stages as well as to understand fibril dissociation. In this chapter, we first review the current computer simulation methods used for aggregation with some atomistic and coarse-grained results aimed at better characterizing the early formed oligomers and amyloid fibril formation. Then we present the applications of non-equilibrium molecular dynamics simulations to comprehend the dissociation of protein assemblies.
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Affiliation(s)
- Phuong H Nguyen
- Laboratoire de Biochimie Théorique, UPR 9080, CNRS, Université de Paris, Paris, France
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Philippe Derreumaux
- Laboratoire de Biochimie Théorique, UPR 9080, CNRS, Université de Paris, Paris, France.
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France.
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30
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Mu J, Pan Z, Chen HF. Balanced Solvent Model for Intrinsically Disordered and Ordered Proteins. J Chem Inf Model 2021; 61:5141-5151. [PMID: 34546059 DOI: 10.1021/acs.jcim.1c00407] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Intrinsically disordered proteins (IDPs) have no fixed three-dimensional (3D) structures under physiological conditions, with the content being about 51% in human proteomics. IDPs are associated with many human diseases, such as cancer, diabetes, and neurodegenerative diseases. Because IDPs do not crystallize and have diverse conformers, traditional experimental methods such as crystallization and NMR can hardly capture their conformation ensemble and just provide average structural characters of IDPs. Therefore, molecular dynamics (MD) simulations become a valuable complement to the experimental data. However, the accuracy of molecular dynamics simulation for IDPs depends on the combination of force fields and solvent models. Recently, we released an environment-specific force field (ESFF1) for IDPs, which can well reproduce the local structural properties (such as J-coupling and secondary chemical shifts). However, there is still a large deviation for the radius of gyration (Rg). Therefore, a solvent model combined with ESFF1 is necessary to capture the local and global characters for IDPs and ordered proteins. Here, we investigated the underestimation or overestimation of the solvent interaction for four solvent models (TIP3P, TIP4P-Ew, TIP4P-D, OPC) under ESFF1 and found the important ε parameter of the solvent model to play a key role in scaling Rg. A near-linear relationship between the simulation Rg and the ε parameter was used to develop the new solvent model, named TIP4P-B. The results indicate that the simulated Rg with TIP4P-B is in better agreement with the experimental observations than the other four solvent models. Simultaneously, TIP4P-B can also maintain the advantages of the ESFF1 force field for the local structural properties. Additionally, TIP4P-B can successfully sample the conformation of ordered proteins. These findings confirm that TIP4P-B is a balanced solvent model and can improve sampling Rg performance for folded proteins and IDPs.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhengsong Pan
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.,MD Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Center for Bioinformation Technology, Shanghai 200235, China
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31
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Sacquin-Mora S, Prévost C. When Order Meets Disorder: Modeling and Function of the Protein Interface in Fuzzy Complexes. Biomolecules 2021; 11:1529. [PMID: 34680162 PMCID: PMC8533853 DOI: 10.3390/biom11101529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 11/30/2022] Open
Abstract
The degree of proteins structural organization ranges from highly structured, compact folding to intrinsic disorder, where each degree of self-organization corresponds to specific functions: well-organized structural motifs in enzymes offer a proper environment for precisely positioned functional groups to participate in catalytic reactions; at the other end of the self-organization spectrum, intrinsically disordered proteins act as binding hubs via the formation of multiple, transient and often non-specific interactions. This review focusses on cases where structurally organized proteins or domains associate with highly disordered protein chains, leading to the formation of interfaces with varying degrees of fuzziness. We present a review of the computational methods developed to provide us with information on such fuzzy interfaces, and how they integrate experimental information. The discussion focusses on two specific cases, microtubules and homologous recombination nucleoprotein filaments, where a network of intrinsically disordered tails exerts regulatory function in recruiting partner macromolecules, proteins or DNA and tuning the atomic level association. Notably, we show how computational approaches such as molecular dynamics simulations can bring new knowledge to help bridging the gap between experimental analysis, that mostly concerns ensemble properties, and the behavior of individual disordered protein chains that contribute to regulation functions.
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Affiliation(s)
- 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
| | - 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
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32
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Boopathi S, Poma AB, Garduño-Juárez R. An Overview of Several Inhibitors for Alzheimer's Disease: Characterization and Failure. Int J Mol Sci 2021; 22:10798. [PMID: 34639140 PMCID: PMC8509255 DOI: 10.3390/ijms221910798] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 10/01/2021] [Accepted: 10/03/2021] [Indexed: 01/04/2023] Open
Abstract
Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.
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Affiliation(s)
- Subramanian Boopathi
- Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico;
| | - Adolfo B. Poma
- Department of Biosystems and Soft Matter, Institute of Fundamental Technological Research Polish Academy of Science, Pawińskiego 5B, 02-106 Warsaw, Poland
- International Center for Research on Innovative Biobased Materials (ICRI-BioM)—International Research Agenda, Lodz University of Technology, Zeromskiego 116, 90-924 Lodz, Poland;
| | - Ramón Garduño-Juárez
- Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico;
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33
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Tian X, Liu H, Chen HF. Catalytic mechanism of butane anaerobic oxidation for alkyl-coenzyme M reductase. Chem Biol Drug Des 2021; 98:701-712. [PMID: 34328701 DOI: 10.1111/cbdd.13931] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/02/2021] [Accepted: 07/24/2021] [Indexed: 12/18/2022]
Abstract
Methane is among the most potent of the greenhouse gases, which plays a key role in global climate change. As an excellent carbon and energy source, methane can be utilized by anaerobic methane oxidizing archaea and aerobic methane oxidizing bacteria. The previous work shows that an anaerobic thermophilic enrichment culture composed of dense consortia of archaea and bacteria apparently uses partly similar pathways to oxidize the C4 hydrocarbon butane. However, the catalytic mechanism of butane anaerobic oxidation for alkyl-coenzyme M reductase is still unknown. Therefore, molecular dynamics (MD) simulation was used to investigate the dynamics differences of catalytic mechanism between methane coenzyme M reductase (MCR) and alkyl-coenzyme M reductase (ACR). At first, the binding pocket of ACR is larger than that of MCR. Then, the complex of butane and ACR is more stable than that of methane and ACR. Protein conformation cloud suggests that the position of methane is dynamics and methane escapes from the binding pocket of ACR during most of the simulation time, while butane tightly binds in the pocket of ACR. The hydrophobic interactions between butane and ACR are more and stronger than those between methane and ACR. At the same time, the binding free energy between butane and ACR is significantly lower than that between methane and ACR. The dynamics correlation network indicates that the transformation of information flow for ACR-butane is smoother than that for ACR-methane. The shortest pathway for ACR-butane is from Gln144, Ala141, Hie135, Ile133, Ala160, Arg206, Asp97, Met94, Tyr347 to Phe345 with synergistic effect for two butane molecules. This study can insight into the catalytic mechanism for butane/ACR complex.
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Affiliation(s)
- Xiaopian Tian
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Liu
- Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Center for Bioinformation Technology, Shanghai, China
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34
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Cui X, Liu H, Rehman AU, Chen HF. Extensive evaluation of environment-specific force field for ordered and disordered proteins. Phys Chem Chem Phys 2021; 23:12127-12136. [PMID: 34032235 DOI: 10.1039/d1cp01385h] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Intrinsically disordered proteins (IDPs) have no fixed tertiary structure under physiological conditions and are associated with many human diseases. Because IDPs have the characteristic of possessing diverse conformations, current experimental methods cannot capture all the conformations of IDPs. However, molecular dynamics simulation can sample these atomistically diverse conformations as a valuable complement to experimental data. To accurately describe the properties of IDPs, the environment-specific precise force field (ESFF1) was successfully released to reproduce the conformer character of ordered and disordered proteins. Here, three typical IDPs and thirteen folded proteins were used to further evaluate the performance of this force field. The results indicate that the NMR observables of ESFF1 better approach experimental data than do those of ff14SB for IDPs. The sampling conformations by ESFF1 are more diverse than those of ff14SB. For folded proteins, these force fields have comparable performances for reproducing conformers. Therefore, ESFF1 can be used to reveal the model of sequence-disorder-function for IDPs.
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Affiliation(s)
- Xiaochen Cui
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Ashfaq Ur Rehman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. and Shanghai Center for Bioinformation Technology, Shanghai, 200235, China
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Ploetz EA, Karunaweera S, Bentenitis N, Chen F, Dai S, Gee MB, Jiao Y, Kang M, Kariyawasam NL, Naleem N, Weerasinghe S, Smith PE. Kirkwood-Buff-Derived Force Field for Peptides and Proteins: Philosophy and Development of KBFF20. J Chem Theory Comput 2021; 17:2964-2990. [PMID: 33878263 DOI: 10.1021/acs.jctc.1c00075] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
A new classical nonpolarizable force field, KBFF20, for the simulation of peptides and proteins is presented. The force field relies heavily on the use of Kirkwood-Buff theory to provide a comparison of simulated and experimental Kirkwood-Buff integrals for solutes containing the functional groups common in proteins, thus ensuring intermolecular interactions that provide a good balance between the peptide-peptide, peptide-solvent, and solvent-solvent distributions observed in solution mixtures. In this way, it differs significantly from other biomolecular force fields. Further development and testing of the intermolecular potentials are presented here. Subsequently, rotational potentials for the ϕ/ψ and χ dihedral degrees of freedom are obtained by analysis of the Protein Data Bank, followed by small modifications to provide a reasonable balance between simulated and observed α and β percentages for small peptides. This, the first of two articles, describes in detail the philosophy and development behind KBFF20.
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Affiliation(s)
- Elizabeth A Ploetz
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Sadish Karunaweera
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Nikolaos Bentenitis
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Feng Chen
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Shu Dai
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Moon B Gee
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Yuanfang Jiao
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Myungshim Kang
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Nilusha L Kariyawasam
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | - Nawavi Naleem
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
| | | | - Paul E Smith
- Department of Chemistry, Kansas State University, 213 CBC Building, 1212 Mid-Campus Drive North, Manhattan, Kansas 66506, United States
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36
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Rosenberger D, Smith JS, Garcia AE. Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A Comparison. J Phys Chem B 2021; 125:3598-3612. [DOI: 10.1021/acs.jpcb.0c10401] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- David Rosenberger
- Los Alamos National Laboratory, Theoretical Division, Chemistry and Physics of Materials Group, Los Alamos, 87545 New Mexico, United States
- Los Alamos National Laboratory, Theoretical Division, Center for Nonlinear Studies, Los Alamos, 87545 New Mexico, United States
| | - Justin S. Smith
- Los Alamos National Laboratory, Theoretical Division, Chemistry and Physics of Materials Group, Los Alamos, 87545 New Mexico, United States
| | - Angel E. Garcia
- Los Alamos National Laboratory, Theoretical Division, Center for Nonlinear Studies, Los Alamos, 87545 New Mexico, United States
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37
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Nguyen PH, Ramamoorthy A, Sahoo BR, Zheng J, Faller P, Straub JE, Dominguez L, Shea JE, Dokholyan NV, De Simone A, Ma B, Nussinov R, Najafi S, Ngo ST, Loquet A, Chiricotto M, Ganguly P, McCarty J, Li MS, Hall C, Wang Y, Miller Y, Melchionna S, Habenstein B, Timr S, Chen J, Hnath B, Strodel B, Kayed R, Lesné S, Wei G, Sterpone F, Doig AJ, Derreumaux P. Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis. Chem Rev 2021; 121:2545-2647. [PMID: 33543942 PMCID: PMC8836097 DOI: 10.1021/acs.chemrev.0c01122] [Citation(s) in RCA: 386] [Impact Index Per Article: 128.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.
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Affiliation(s)
- Phuong H Nguyen
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Ayyalusamy Ramamoorthy
- Biophysics and Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Bikash R Sahoo
- Biophysics and Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Jie Zheng
- Department of Chemical & Biomolecular Engineering, The University of Akron, Akron, Ohio 44325, United States
| | - Peter Faller
- Institut de Chimie, UMR 7177, CNRS-Université de Strasbourg, 4 rue Blaise Pascal, 67000 Strasbourg, France
| | - John E Straub
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Laura Dominguez
- Facultad de Química, Departamento de Fisicoquímica, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
| | - Joan-Emma Shea
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - Nikolay V Dokholyan
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
- Department of Chemistry, and Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Alfonso De Simone
- Department of Life Sciences, Imperial College London, London SW7 2AZ, U.K
- Molecular Biology, University of Naples Federico II, Naples 80138, Italy
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc., Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, United States
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc., Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, United States
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Saeed Najafi
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics & Faculty of Applied Sciences, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
| | - Antoine Loquet
- Institute of Chemistry & Biology of Membranes & Nanoobjects, (UMR5248 CBMN), CNRS, Université Bordeaux, Institut Européen de Chimie et Biologie, 33600 Pessac, France
| | - Mara Chiricotto
- Department of Chemical Engineering and Analytical Science, University of Manchester, Manchester M13 9PL, U.K
| | - Pritam Ganguly
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - James McCarty
- Chemistry Department, Western Washington University, Bellingham, Washington 98225, United States
| | - Mai Suan Li
- Institute for Computational Science and Technology, SBI Building, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City 700000, Vietnam
- Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Carol Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Yifat Miller
- Department of Chemistry and The Ilse Katz Institute for Nanoscale Science & Technology, Ben-Gurion University of the Negev, Be'er Sheva 84105, Israel
| | | | - Birgit Habenstein
- Institute of Chemistry & Biology of Membranes & Nanoobjects, (UMR5248 CBMN), CNRS, Université Bordeaux, Institut Européen de Chimie et Biologie, 33600 Pessac, France
| | - Stepan Timr
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Jiaxing Chen
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
| | - Brianna Hnath
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
| | - Birgit Strodel
- Institute of Complex Systems: Structural Biochemistry (ICS-6), Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Rakez Kayed
- Mitchell Center for Neurodegenerative Diseases, and Departments of Neurology, Neuroscience and Cell Biology, University of Texas Medical Branch, Galveston, Texas 77555, United States
| | - Sylvain Lesné
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Guanghong Wei
- Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory for Computational Physical Science, Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200438, China
| | - Fabio Sterpone
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Andrew J Doig
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, U.K
| | - Philippe Derreumaux
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
- Laboratory of Theoretical Chemistry, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
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38
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Mu J, Liu H, Zhang J, Luo R, Chen HF. Recent Force Field Strategies for Intrinsically Disordered Proteins. J Chem Inf Model 2021; 61:1037-1047. [PMID: 33591749 PMCID: PMC8256680 DOI: 10.1021/acs.jcim.0c01175] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 20025, China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Molecular Engineering, Materials Science and Engineering, and Biomedical Engineering, University of California, Irvine, California 92697-3900, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
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39
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Rahman MU, Rehman AU, Arshad T, Chen HF. Disaggregation mechanism of prion amyloid for tweezer inhibitor. Int J Biol Macromol 2021; 176:510-519. [PMID: 33607137 DOI: 10.1016/j.ijbiomac.2021.02.094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 02/08/2021] [Accepted: 02/13/2021] [Indexed: 02/07/2023]
Abstract
The aggregation of amyloid has been an important event in the pathology of amyloidogenicity. A number of small molecules have been designed for Amyloidosis treatment. Molecular tweezer CLR01, a potential drug for misfolded β-amyloids inhibition, was reportedly bind directly to Lysine residues and interrupt oligomerization. However, the disaggregation mechanism of amyloid for this inhibitor is unclear. Here we used long timescale of molecular dynamic simulation to reveal the mechanism of disaggregation for pentamer prion amyloid. Molecular docking and molecular dynamics simulation demonstrate that CLR01 is attached with Lysine222 nitrogen by π-cation interaction of its nine aromatic rings and formation of salt bridge/hydrogen bond of one of the two rotatable peripheral anionic phosphate groups. Upon CLR01 binding, we found a major shifting occurs in initial conformation of the oligomer and stretch out the N-terminal chain A from the rest of the amyloid which seems to be the first stage of disaggregated the fibrils slowly yet efficiently. Moreover, the CLR01 remodelled the pentamer Prion220-272 into a compact structure which might be the resistant conformation for further oligomerization. Our work will contribute to better understand the interaction and deterioration mechanism of molecular tweezer for prions and similar amyloids, and offer significant insights into therapeutic development for Amyloidosis treatment.
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Affiliation(s)
- Mueed Ur Rahman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ashfaq Ur Rehman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Taaha Arshad
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Center for Bioinformation Technology, Shanghai 200235, China.
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40
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Caliskan M, Mandaci SY, Uversky VN, Coskuner-Weber O. Secondary structure dependence of amyloid-β(1-40) on simulation techniques and force field parameters. Chem Biol Drug Des 2021; 97:1100-1108. [PMID: 33580600 DOI: 10.1111/cbdd.13830] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/21/2021] [Accepted: 02/07/2021] [Indexed: 12/21/2022]
Abstract
Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α-synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid-β(1-40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid-β(1-40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence-based secondary structure predisposition of amyloid-β(1-40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid-β(1-40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*-ildn, charmm36m, and a99sb-disp parameters for the amyloid-β(1-40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.
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Affiliation(s)
- Murat Caliskan
- Molecular Biotechnology, Turkish-German University, Istanbul, Turkey
| | - Sunay Y Mandaci
- Molecular Biotechnology, Turkish-German University, Istanbul, Turkey
| | - Vladimir N Uversky
- Department of Molecular Medicine, USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.,Laboratory of New Methods in Biology, Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center "Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences", Pushchino, Russia
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41
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Wang W. Recent advances in atomic molecular dynamics simulation of intrinsically disordered proteins. Phys Chem Chem Phys 2021; 23:777-784. [PMID: 33355572 DOI: 10.1039/d0cp05818a] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Intrinsically disordered proteins (IDPs) play important roles in cellular functions. The inherent structural heterogeneity of IDPs makes the high-resolution experimental characterization of IDPs extremely difficult. Molecular dynamics (MD) simulation could provide the atomic-level description of the structural and dynamic properties of IDPs. This perspective reviews the recent progress in atomic MD simulation studies of IDPs, including the development of force fields and sampling methods, as well as applications in IDP-involved protein-protein interactions. The employment of large-scale simulations and advanced sampling techniques allows more accurate estimation of the thermodynamics and kinetics of IDP-mediated protein interactions, and the holistic landscape of the binding process of IDPs is emerging.
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Affiliation(s)
- Wenning Wang
- Department of Chemistry, Multiscale Research Institute of Complex Systems and Institute of Biomedical Sciences, Fudan University, Shanghai 200438, China.
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42
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Klein F, Barrera EE, Pantano S. Assessing SIRAH's Capability to Simulate Intrinsically Disordered Proteins and Peptides. J Chem Theory Comput 2021; 17:599-604. [PMID: 33411518 DOI: 10.1021/acs.jctc.0c00948] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
The challenges posed by intrinsically disordered proteins (IDPs) to atomistic and coarse-grained (CG) simulations are boosting efforts to develop and reparametrize current force fields. An assessment of the dynamical behavior of IDPs' and unstructured peptides with the CG SIRAH force field suggests that the current version achieves a fair description of IDPs' conformational flexibility. Moreover, we found a remarkable capability to capture the effect of point mutations in loosely structured peptides.
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Affiliation(s)
- Florencia Klein
- Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, CP 11400, Uruguay.,Graduate Program in Chemistry, Facultad de Química, Universidad de la República, Montevideo 11800, Uruguay
| | - Exequiel E Barrera
- Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, CP 11400, Uruguay.,Instituto de Histología y Embriología (IHEM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CC56, Universidad Nacional de Cuyo (UNCuyo), M5500 Mendoza, Argentina
| | - Sergio Pantano
- Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, CP 11400, Uruguay.,Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai 201210, China
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43
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Jagannathan NS, Hogue CWV, Tucker-Kellogg L. Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2. PLoS Comput Biol 2021; 17:e1008474. [PMID: 33406091 PMCID: PMC7787433 DOI: 10.1371/journal.pcbi.1008474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 10/27/2020] [Indexed: 11/22/2022] Open
Abstract
Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (RG) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation. Protein functions were originally believed to arise from ordered protein structures. This dogma was later challenged by the identification of intrinsically disordered proteins that lack specific structure. The functional roles of such proteins usually fell in two categories–exploiting the disorder for flexibility (like floppy connector), or imposing order upon binding to an external partner. In this study we explore the possibility of an alternative mechanism that harnesses disorder for function through regulated molecular crowding. Specifically, we use modeling to study two proteins involved in reshaping the cell membrane, Epsin and Eps15. We ask if they undergo binding-induced expansion, where binding of an external partner AP2 causes not a transition toward order, but rather an energetically favorable increase in propensity to occupy larger volumes. Our results show that Epsin tends to occupy a larger volume when bound to AP2, consistent with increased molecular crowding, which could help reshape the cell membrane. Such regulation of disorder via binding (without folding) opens hitherto unexplored avenues that cells might employ to harness disorder.
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Affiliation(s)
- N. Suhas Jagannathan
- Cancer & Stem Cell Biology, and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
| | - Christopher W. V. Hogue
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
- Mechanobiology Institute, National University of Singapore, Singapore
| | - Lisa Tucker-Kellogg
- Cancer & Stem Cell Biology, and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
- * E-mail:
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44
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Rahman MU, Rehman AU, Liu H, Chen HF. Comparison and Evaluation of Force Fields for Intrinsically Disordered Proteins. J Chem Inf Model 2020; 60:4912-4923. [PMID: 32816485 DOI: 10.1021/acs.jcim.0c00762] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Molecular dynamics (MD) simulations of six upgraded empirical force fields were compared and evaluated with short peptides, intrinsically disordered proteins, and folded proteins using trajectories of 1, 1.5, 5, or 10 μs (five replicates of 200 ns, 300 ns, 1 μs, or 2 μs) for each system. Previous studies have shown that different force fields, water models, simulation methods, and parameters can affect simulation outcomes. Here, the MD simulations were done in an explicit solvent with RS-peptide, HEWL19, HIV-rev, β amyloid (Aβ)-40, Aβ-42, phosphodiesterase-γ, CspTm, and ubiquitin using ff99IDPs, ff14IDPs, ff14IDPSFF, ff03w, CHARMM36m, and CHARMM22* force fields. The IDP ensembles generated by six all-atom empirical force fields were compared against NMR data. Despite using identical starting structures and simulation parameters, ensembles obtained with different force fields exhibit significant differences in NMR RMDs, secondary structure contents, and global properties such as the radius of gyration. The intrinsically disordered protein (IDP)-specific force fields could substantially reproduce the experimental observables in force field comparison: they have the lowest error in chemical shifts and J-couplings for short peptides/proteins, reasonably well for large IDPs and reasonably well with the radius of gyration. A high population of disorderness was observed in the IDP-specific force field for the IDP ensemble with a fraction of β sheets for β-amyloids. CHARMM22* performs better for many observables; however, it still has a preference toward the helicity for short peptides. The results of β-amyloid 42 starting from two different initial structures (Aβ421Z0Q and Aβ42model) were also compared with DSSP and NMR data. The results obtained with IDP-specific force fields within 2 μs simulation time are similar, even though starting from different structures. The current force fields perform equally well for folded proteins. The results of currently developed or modified force fields for IDPs are capable of enlightening the overall performance of the force field for disordered as well as folded proteins, thereby contributing to force field development.
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Affiliation(s)
- Mueed Ur Rahman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ashfaq Ur Rehman
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Center for Bioinformation Technology, Shanghai 200235, China
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45
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Song D, Liu H, Luo R, Chen HF. Environment-Specific Force Field for Intrinsically Disordered and Ordered Proteins. J Chem Inf Model 2020; 60:2257-2267. [PMID: 32227937 PMCID: PMC10449432 DOI: 10.1021/acs.jcim.0c00059] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The need for accurate and efficient force fields for modeling 3D structures of macrobiomolecules and in particular intrinsically disordered proteins (IDPs) has increased with recent findings to associate IDPs and human diseases. However, most conventional protein force fields and recent IDP-specific force fields are limited in reproducing accurate structural features of IDPs. Here, we present an environmental specific precise force field (ESFF1) based on CMAP corrections of 71 different sequence environments to improve the accuracy and efficiency of MD simulation for both IDPs and folded proteins. MD simulations of 84 different short peptides, IDPs, and structured proteins show that ESFF1 can accurately reproduce spectroscopic properties for different peptides and proteins whether they are disordered or ordered. The successful ab initio folding of five fast-folding proteins further supports the reliability of ESFF1. The extensive analysis documented here shows that ESFF1 is able to achieve a reasonable balance between ordered and disordered states in protein simulations.
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Affiliation(s)
- Dong Song
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Molecular Engineering, Materials Science and Engineering, and Biomedical Engineering, University of California, Irvine, California 92697-3900, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Center for Bioinformation Technology, Shanghai 200235, China
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