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Wang Y, Li C, Zheng X. Markov State Models Reveal How Folding Kinetics Influence Absorption Spectra of Foldamers. J Chem Theory Comput 2024. [PMID: 38900275 DOI: 10.1021/acs.jctc.4c00202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Self-assembly of platinum(II) complex foldamers is an essential approach to fabricate advanced luminescent materials. However, a comprehensive understanding of folding kinetics and their absorption spectra remains elusive. By constructing Markov state models (MSMs) from large-scale molecular dynamics simulations, we reveal that two largely similar dinuclear alknylplatinum(II) terpyridine foldamers, Pt-PEG and Pt-PE with slightly different bridges, exhibit distinctive folding kinetics. Particularly, Pt-PEG bears bridge-dominant, plane-dominant, and cooperative pathways, while Pt-PE only prefers the plane-dominant pathway. Such preference originates from their difference in intrabridge electrostatic interactions, leading to contrastive distributions of metastable states. We also found that the bridge-dominant pathway for Pt-PEG becomes more favorable when lowering the temperature. Interestingly, based on the comprehensive conformation ensembles from our MSMs, we reveal the conformation-dependent absorption spectra of Pt-PEG and Pt-PE. Our theoretical spectra not only align with experimental results but also reveal the contributions of diverse conformations to the overall absorption bands explicitly, facilitating the rational design of stimuli-responsive smart luminescent molecules.
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Affiliation(s)
- Yijia Wang
- Key Laboratory of Cluster Science of Ministry of Education, Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials, Key Laboratory of Medicinal Molecule Science and Pharmaceutics Engineering of Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Chu Li
- Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Xiaoyan Zheng
- Key Laboratory of Cluster Science of Ministry of Education, Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials, Key Laboratory of Medicinal Molecule Science and Pharmaceutics Engineering of Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, China
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2
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Xi K, Zhu L. Automated Path Searching Reveals the Mechanism of Hydrolysis Enhancement by T4 Lysozyme Mutants. Int J Mol Sci 2022; 23:ijms232314628. [PMID: 36498954 PMCID: PMC9736071 DOI: 10.3390/ijms232314628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/16/2022] [Accepted: 11/19/2022] [Indexed: 11/25/2022] Open
Abstract
Bacteriophage T4 lysozyme (T4L) is a glycosidase that is widely applied as a natural antimicrobial agent in the food industry. Due to its wide applications and small size, T4L has been regarded as a model system for understanding protein dynamics and for large-scale protein engineering. Through structural insights from the single conformation of T4L, a series of mutations (L99A,G113A,R119P) have been introduced, which have successfully raised the fractional population of its only hydrolysis-competent excited state to 96%. However, the actual impact of these substitutions on its dynamics remains unclear, largely due to the lack of highly efficient sampling algorithms. Here, using our recently developed travelling-salesman-based automated path searching (TAPS), we located the minimum-free-energy path (MFEP) for the transition of three T4L mutants from their ground states to their excited states. All three mutants share a three-step transition: the flipping of F114, the rearrangement of α0/α1 helices, and final refinement. Remarkably, the MFEP revealed that the effects of the mutations are drastically beyond the expectations of their original design: (a) the G113A substitution not only enhances helicity but also fills the hydrophobic Cavity I and reduces the free energy barrier for flipping F114; (b) R119P barely changes the stability of the ground state but stabilizes the excited state through rarely reported polar contacts S117OG:N132ND2, E11OE1:R145NH1, and E11OE2:Q105NE2; (c) the residue W138 flips into Cavity I and further stabilizes the excited state for the triple mutant L99A,G113A,R119P. These novel insights that were unexpected in the original mutant design indicated the necessity of incorporating path searching into the workflow of rational protein engineering.
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3
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Protein Function Analysis through Machine Learning. Biomolecules 2022; 12:biom12091246. [PMID: 36139085 PMCID: PMC9496392 DOI: 10.3390/biom12091246] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/22/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022] Open
Abstract
Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein–ligand binding, including allosteric effects, protein–protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.
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4
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Wang L, Song K, Yu J, Da LT. Computational investigations on target-site searching and recognition mechanisms by thymine DNA glycosylase during DNA repair process. Acta Biochim Biophys Sin (Shanghai) 2022; 54:796-806. [PMID: 35593467 PMCID: PMC9828053 DOI: 10.3724/abbs.2022050] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
DNA glycosylase, as one member of DNA repair machineries, plays an essential role in correcting mismatched/damaged DNA nucleotides by cleaving the N-glycosidic bond between the sugar and target nucleobase through the base excision repair (BER) pathways. Efficient corrections of these DNA lesions are critical for maintaining genome integrity and preventing premature aging and cancers. The target-site searching/recognition mechanisms and the subsequent conformational dynamics of DNA glycosylase, however, remain challenging to be characterized using experimental techniques. In this review, we summarize our recent studies of sequential structural changes of thymine DNA glycosylase (TDG) during the DNA repair process, achieved mostly by molecular dynamics (MD) simulations. Computational simulations allow us to reveal atomic-level structural dynamics of TDG as it approaches the target-site, and pinpoint the key structural elements responsible for regulating the translocation of TDG along DNA. Subsequently, upon locating the lesions, TDG adopts a base-flipping mechanism to extrude the mispaired nucleobase into the enzyme active-site. The constructed kinetic network model elucidates six metastable states during the base-extrusion process and suggests an active role of TDG in flipping the intrahelical nucleobase. Finally, the molecular mechanism of product release dynamics after catalysis is also summarized. Taken together, we highlight to what extent the computational simulations advance our knowledge and understanding of the molecular mechanism underlying the conformational dynamics of TDG, as well as the limitations of current theoretical work.
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Affiliation(s)
- Lingyan Wang
- Key Laboratory of Systems Biomedicine (Ministry of Education)Shanghai Center for Systems BiomedicineShanghai Jiao Tong UniversityShanghai200240China
| | - Kaiyuan Song
- Key Laboratory of Systems Biomedicine (Ministry of Education)Shanghai Center for Systems BiomedicineShanghai Jiao Tong UniversityShanghai200240China
| | - Jin Yu
- Department of Physics and AstronomyDepartment of ChemistryNSF-Simons Center for Multiscale Cell Fate ResearchUniversity of CaliforniaIrvineCA92697USA
| | - Lin-Tai Da
- Key Laboratory of Systems Biomedicine (Ministry of Education)Shanghai Center for Systems BiomedicineShanghai Jiao Tong UniversityShanghai200240China,Correspondence address. Tel: +86-21-34207348; E-mail:
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5
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Zhu L, Jiang H, Cao S, Unarta IC, Gao X, Huang X. Critical role of backbone coordination in the mRNA recognition by RNA induced silencing complex. Commun Biol 2021; 4:1345. [PMID: 34848812 PMCID: PMC8632932 DOI: 10.1038/s42003-021-02822-7] [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: 05/17/2021] [Accepted: 10/26/2021] [Indexed: 01/02/2023] Open
Abstract
Despite its functional importance, the molecular mechanism underlying target mRNA recognition by Argonaute (Ago) remains largely elusive. Based on extensive all-atom molecular dynamics simulations, we constructed quasi-Markov State Model (qMSM) to reveal the dynamics during recognition at position 6-7 in the seed region of human Argonaute 2 (hAgo2). Interestingly, we found that the slowest mode of motion therein is not the gRNA-target base-pairing, but the coordination of the target phosphate groups with a set of positively charged residues of hAgo2. Moreover, the ability of Helix-7 to approach the PIWI and MID domains was found to reduce the effective volume accessible to the target mRNA and therefore facilitate both the backbone coordination and base-pair formation. Further mutant simulations revealed that alanine mutation of the D358 residue on Helix-7 enhanced a trap state to slow down the loading of target mRNA. Similar trap state was also observed when wobble pairs were introduced in g6 and g7, indicating the role of Helix-7 in suppressing non-canonical base-paring. Our study pointed to a general mechanism for mRNA recognition by eukaryotic Agos and demonstrated the promise of qMSM in investigating complex conformational changes of biomolecular systems.
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Affiliation(s)
- Lizhe Zhu
- Warshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong, 518172, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Hanlun Jiang
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- Department of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA
| | - Siqin Cao
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Ilona Christy Unarta
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Xin Gao
- Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
| | - Xuhui Huang
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
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Tian J, Wang L, Da LT. Atomic resolution of short-range sliding dynamics of thymine DNA glycosylase along DNA minor-groove for lesion recognition. Nucleic Acids Res 2021; 49:1278-1293. [PMID: 33469643 PMCID: PMC7897493 DOI: 10.1093/nar/gkaa1252] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 12/10/2020] [Accepted: 12/15/2020] [Indexed: 02/06/2023] Open
Abstract
Thymine DNA glycosylase (TDG), as a repair enzyme, plays essential roles in maintaining the genome integrity by correcting several mismatched/damaged nucleobases. TDG acquires an efficient strategy to search for the lesions among a vast number of cognate base pairs. Currently, atomic-level details of how TDG translocates along DNA as it approaches the lesion site and the molecular mechanisms of the interplay between TDG and DNA are still elusive. Here, by constructing the Markov state model based on hundreds of molecular dynamics simulations with an integrated simulation time of ∼25 μs, we reveal the rotation-coupled sliding dynamics of TDG along a 9 bp DNA segment containing one G·T mispair. We find that TDG translocates along DNA at a relatively faster rate when distant from the lesion site, but slows down as it approaches the target, accompanied by deeply penetrating into the minor-groove, opening up the mismatched base pair and significantly sculpturing the DNA shape. Moreover, the electrostatic interactions between TDG and DNA are found to be critical for mediating the TDG translocation. Notably, several uncharacterized TDG residues are identified to take part in regulating the conformational switches of TDG occurred in the site-transfer process, which warrants further experimental validations.
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Affiliation(s)
- Jiaqi Tian
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Lingyan Wang
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Lin-Tai Da
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
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7
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Hou X, Sun JP, Ge L, Liang X, Li K, Zhang Y, Fang H. Inhibition of striatal-enriched protein tyrosine phosphatase by targeting computationally revealed cryptic pockets. Eur J Med Chem 2020; 190:112131. [PMID: 32078861 PMCID: PMC7163917 DOI: 10.1016/j.ejmech.2020.112131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 01/21/2020] [Accepted: 02/06/2020] [Indexed: 11/21/2022]
Abstract
Cryptic pockets, which are not apparent in crystallographic structures, provide promising alternatives to traditional binding sites for drug development. However, identifying cryptic pockets is extremely challenging and the therapeutic potential of cryptic pockets remains unclear. Here, we reported the discovery of novel inhibitors for striatal-enriched protein tyrosine phosphatase (STEP), a potential drug target for multiple neuropsychiatric disorders, based on cryptic pocket detection. By combining the use of molecular dynamics simulations and fragment-centric topographical mapping, we identified transiently open cryptic pockets and identified 12 new STEP inhibition scaffolds through structure-based virtual screening. Site-directed mutagenesis verified the binding of ST3 with the predicted cryptic pockets. Moreover, the most potent and selective inhibitors could modulate the phosphorylation of both ERK1/2 and Pyk2 in PC12 cells.
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Affiliation(s)
- Xuben Hou
- Department of Medicinal Chemistry and Key Laboratory of Chemical Biology of Natural Products (MOE), School of Pharmaceutical Science, Shandong University, Jinan, Shandong, 250012, China; Department of Chemistry, New York University, New York, NY, 10003, United States
| | - Jin-Peng Sun
- Key Laboratory Experimental Teratology of the Ministry of Education and Department of Biochemistry and Molecular Biology, School of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Lin Ge
- Key Laboratory Experimental Teratology of the Ministry of Education and Department of Biochemistry and Molecular Biology, School of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Xiao Liang
- Department of Medicinal Chemistry and Key Laboratory of Chemical Biology of Natural Products (MOE), School of Pharmaceutical Science, Shandong University, Jinan, Shandong, 250012, China
| | - Kangshuai Li
- Key Laboratory Experimental Teratology of the Ministry of Education and Department of Biochemistry and Molecular Biology, School of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Yingkai Zhang
- Department of Chemistry, New York University, New York, NY, 10003, United States; NYU-ECNU Center for Computational Chemistry, New York University-Shanghai, Shanghai, 200122, China
| | - Hao Fang
- Department of Medicinal Chemistry and Key Laboratory of Chemical Biology of Natural Products (MOE), School of Pharmaceutical Science, Shandong University, Jinan, Shandong, 250012, China.
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Da LT, Lin M. Opening dynamics of HIV-1 gp120 upon receptor binding is dictated by a key hydrophobic core. Phys Chem Chem Phys 2019; 21:26003-26016. [PMID: 31764922 DOI: 10.1039/c9cp04613e] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
HIV-1 entry is mediated firstly by the molecular recognition between the viral glycoprotein gp120 and its receptor CD4 on host T-cells. As a key antigen that can be targeted by neutralizing antibodies, gp120 has been a focus for extensive studies with efforts to understand its structural properties and conformational dynamics upon receptor binding. An atomistic-level revelation of gp120 opening dynamics activated by CD4, however, is still unknown. Here, by constructing a Markov State Model (MSM) based on hundreds of Molecular Dynamics (MD) simulations with an aggregated simulation time of ∼20 microseconds (μs), we identify the key metastable states of gp120 during its opening dynamics upon CD4 binding. The MSM provides a clear dynamic model whereby the identified metastable states coexist and can reach an equilibrium. More importantly, a hydrophobic core flanked by variable loops (V1V2 and V3) and the β20/21 region plays an essential role in triggering the gp120 opening. Any destabilizing effects introduced into the hydrophobic core, therefore, can be expected to promote transition of gp120 to an open state. Moreover, the variable loops demonstrate high flexibilities in fully open gp120. In particular, the V3 region is capable of exploring both closed and open conformations, even with the V1/V2 loops largely adopting an open form. In addition, the bridging sheet formation in gp120 is likely induced by the incoming co-receptor/antibody recognitions, since the V1/V2 structure is highly heterogeneous so that the bridging-sheet formed conformation is not the most populated state. Our studies provide deep insights into the dynamic features of gp120 and its molecular recognitions to the broadly neutralizing antibodies, which guides future attempts to design more effective gp120 immunogens.
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Affiliation(s)
- Lin-Tai Da
- Key Laboratory of System Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China.
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Tian J, Liu F, Xu Z, Shi J, Liang T, Zhang Y, Da LT. Regulatory Role of One Critical Catalytic Loop of Polypeptide N-Acetyl-Galactosaminyltransferase-2 in Substrate Binding and Catalysis during Mucin-Type O-Glycosylation. ACS Catal 2019. [DOI: 10.1021/acscatal.9b03782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Jiaqi Tian
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Feng Liu
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Zhijue Xu
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Jingjing Shi
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Tao Liang
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Yan Zhang
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Lin-Tai Da
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
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Da LT, Yu J. Base-flipping dynamics from an intrahelical to an extrahelical state exerted by thymine DNA glycosylase during DNA repair process. Nucleic Acids Res 2019; 46:5410-5425. [PMID: 29762710 PMCID: PMC6009601 DOI: 10.1093/nar/gky386] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 04/30/2018] [Indexed: 12/17/2022] Open
Abstract
Thymine DNA glycosylase (TDG) is a DNA repair enzyme that excises a variety of mismatched or damaged nucleotides (nts), e.g. dU, dT, 5fC and 5caC. TDG is shown to play essential roles in maintaining genome integrity and correctly programming epigenetic modifications through DNA demethylation. After locating the lesions, TDG employs a base-flipping strategy to recognize the damaged nucleobases, whereby the interrogated nt is extruded from the DNA helical stack and binds into the TDG active site. The dynamic mechanism of the base-flipping process at an atomistic resolution, however, remains elusive. Here, we employ the Markov State Model (MSM) constructed from extensive all-atom molecular dynamics (MD) simulations to reveal the complete base-flipping process for a G.T mispair at a tens of microsecond timescale. Our studies identify critical intermediates of the mispaired dT during its extrusion process and reveal the key TDG residues involved in the inter-state transitions. Notably, we find an active role of TDG in promoting the intrahelical nt eversion, sculpturing the DNA backbone, and penetrating into the DNA minor groove. Three additional TDG substrates, namely dU, 5fC, and 5caC, are further tested to evaluate the substituent effects of various chemical modifications of the pyrimidine ring on base-flipping dynamics.
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Affiliation(s)
- Lin-Tai Da
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai JiaoTong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Jin Yu
- Beijing Computational Science Research Center, Beijing 100193, China
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11
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Da LT, Shi Y, Ning G, Yu J. Dynamics of the excised base release in thymine DNA glycosylase during DNA repair process. Nucleic Acids Res 2019; 46:568-581. [PMID: 29253232 PMCID: PMC5778594 DOI: 10.1093/nar/gkx1261] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 12/06/2017] [Indexed: 01/09/2023] Open
Abstract
Thymine DNA glycosylase (TDG) initiates base excision repair by cleaving the N-glycosidic bond between the sugar and target base. After catalysis, the release of excised base is a requisite step to terminate the catalytic cycle and liberate the TDG for the following enzymatic reactions. However, an atomistic-level understanding of the dynamics of the product release process in TDG remains unknown. Here, by employing molecular dynamics simulations combined with the Markov State Model, we reveal the dynamics of the thymine release after the excision at microseconds timescale and all-atom resolution. We identify several key metastable states of the thymine and its dominant releasing pathway. Notably, after replacing the TDG residue Gly142 with tyrosine, the thymine release is delayed compared to the wild-type (wt) TDG, as supported by our potential of mean force (PMF) calculations. These findings warrant further experimental tests to potentially trap the excised base in the active site of TDG after the catalysis, which had been unsuccessful by previous attempts. Finally, we extended our studies to other TDG products, including the uracil, 5hmU, 5fC and 5caC bases in order to compare the product release for different targeting bases in the TDG–DNA complex.
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Affiliation(s)
- Lin-Tai Da
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai JiaoTong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Yi Shi
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai JiaoTong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Guodong Ning
- Technical Center of Erlianhot Entry-exit Inspection and Quarantine Bureau, 1266 Qianjin North Road, Erlianhot, Inner Mongolia, China
| | - Jin Yu
- Beijing Computational Science Research Center, Beijing 100193, China
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12
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Zhu L, Sheong FK, Cao S, Liu S, Unarta IC, Huang X. TAPS: A traveling-salesman based automated path searching method for functional conformational changes of biological macromolecules. J Chem Phys 2019; 150:124105. [DOI: 10.1063/1.5082633] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
- Lizhe Zhu
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- Warshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong 518172, China
| | - Fu Kit Sheong
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Siqin Cao
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Song Liu
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Ilona C. Unarta
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Xuhui Huang
- Department of Chemistry, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- Bioengineering Program, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
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13
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Peng JH, Wang W, Yu YQ, Gu HL, Huang X. Clustering algorithms to analyze molecular dynamics simulation trajectories for complex chemical and biological systems. CHINESE J CHEM PHYS 2018. [DOI: 10.1063/1674-0068/31/cjcp1806147] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Jun-hui Peng
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
| | - Wei Wang
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
| | - Ye-qing Yu
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
| | - Han-lin Gu
- Department of Mathematics, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
| | - Xuhui Huang
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
- Center of Systems Biology and Human Health, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
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14
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Zeng X, Li ZW, Zheng X, Zhu L, Sun ZY, Lu ZY, Huang X. Improving the productivity of monodisperse polyhedral cages by the rational design of kinetic self-assembly pathways. Phys Chem Chem Phys 2018; 20:10030-10037. [PMID: 29620122 DOI: 10.1039/c8cp00522b] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Hollow polyhedral cages hold great potential for application in nanotechnological and biomedical fields. Understanding the formation mechanism of these self-assembled structures could provide guidance for the rational design of the desired polyhedral cages. Here, by constructing kinetic network models from extensive coarse-grained molecular dynamics simulations, we elucidated the formation mechanism of the dodecahedral cage, which is formed by the self-assembly of patchy particles. We found that the dodecahedral cage is formed through increasing the aggregate size followed by structure rearrangement. Based on this mechanistic understanding, we improved the productivity of the dodecahedral cage through the rational design of the patch arrangement of patchy particles, which promotes the structural rearrangement process. Our results demonstrate that it should be a feasible strategy to achieve the rational design of the desired nanostructures via the kinetic analysis. We anticipate that this methodology could be extended to other self-assembly systems for the fabrication of functional nanomaterials.
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Affiliation(s)
- Xiangze Zeng
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
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15
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Zeng X, Zhu L, Zheng X, Cecchini M, Huang X. Harnessing complexity in molecular self-assembly using computer simulations. Phys Chem Chem Phys 2018; 20:6767-6776. [PMID: 29479585 DOI: 10.1039/c7cp06181a] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In molecular self-assembly, hundreds of thousands of freely-diffusing molecules associate to form ordered and functional architectures in the absence of an actuator. This intriguing phenomenon plays a critical role in biology and has become a powerful tool for the fabrication of advanced nanomaterials. Due to the limited spatial and temporal resolutions of current experimental techniques, computer simulations offer a complementary strategy to explore self-assembly with atomic resolution. Here, we review recent computational studies focusing on both thermodynamic and kinetic aspects. As we shall see, thermodynamic approaches based on modeling and statistical mechanics offer initial guidelines to design nanostructures with modest computational effort. Computationally more intensive analyses based on molecular dynamics simulations and kinetic network models (KNMs) reach beyond it, opening the door to the rational design of self-assembly pathways. Current limitations of these methodologies are discussed. We anticipate that the synergistic use of thermodynamic and kinetic analyses based on computer simulations will provide an important contribution to the de novo design of self-assembly.
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Affiliation(s)
- Xiangze Zeng
- Department of Chemistry, Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
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16
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Affiliation(s)
- Brooke E. Husic
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
| | - Vijay S. Pande
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
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17
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Da LT, E C, Shuai Y, Wu S, Su XD, Yu J. T7 RNA polymerase translocation is facilitated by a helix opening on the fingers domain that may also prevent backtracking. Nucleic Acids Res 2017; 45:7909-7921. [PMID: 28575393 PMCID: PMC5737862 DOI: 10.1093/nar/gkx495] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 05/24/2017] [Indexed: 12/04/2022] Open
Abstract
Here, we studied the complete process of a viral T7 RNA polymerase (RNAP) translocation on DNA during transcription elongation by implementing extensive all-atom molecular dynamics (MD) simulations to construct a Markov state model (MSM). Our studies show that translocation proceeds in a Brownian motion, and the RNAP thermally transits among multiple metastable states. We observed non-synchronized backbone movements of the nucleic acid (NA) chains with the RNA translocation accomplished first, while the template DNA lagged. Notably, both the O-helix and Y-helix on the fingers domain play key roles in facilitating NA translocation through the helix opening. The helix opening allows a key residue Tyr639 to become inserted into the active site, which pushes the RNA–DNA hybrid forward. Another key residue, Phe644, coordinates the downstream template DNA motions by stacking and un-stacking with a transition nucleotide (TN) and its adjacent nucleotide. Moreover, the O-helix opening at pre-translocation (pre-trans) likely resists backtracking. To test this hypothesis, we computationally designed mutants of T7 RNAP by replacing the amino acids on the O-helix with counterpart residues from a mitochondrial RNAP that is capable of backtracking. The current experimental results support the hypothesis.
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Affiliation(s)
- Lin-Tai Da
- Beijing Computational Science Research Center, Beijing 100193, China.,Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai JiaoTong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Chao E
- Beijing Computational Science Research Center, Beijing 100193, China
| | - Yao Shuai
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Shaogui Wu
- Beijing Computational Science Research Center, Beijing 100193, China
| | - Xiao-Dong Su
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Jin Yu
- Beijing Computational Science Research Center, Beijing 100193, China
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18
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Wang W, Cao S, Zhu L, Huang X. Constructing Markov State Models to elucidate the functional conformational changes of complex biomolecules. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1343] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Wei Wang
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Siqin Cao
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Lizhe Zhu
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Xuhui Huang
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & ReconstructionThe Hong Kong University of Science and Technology Kowloon Hong Kong
- HKUST‐Shenzhen Research Institute Shenzhen China
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