1
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Gunasinghe KJ, Rahman T, Chee Wezen X. Unraveling the Behavior of Intrinsically Disordered Protein c-Myc: A Study Utilizing Gaussian-Accelerated Molecular Dynamics. ACS OMEGA 2024; 9:2250-2262. [PMID: 38250404 PMCID: PMC10795134 DOI: 10.1021/acsomega.3c05822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 11/02/2023] [Accepted: 11/21/2023] [Indexed: 01/23/2024]
Abstract
The protein c-Myc is a transcription factor that remains largely intrinsically disordered and is known to be involved in various biological processes and is overexpressed in various cancers, making it an attractive drug target. However, intrinsically disordered proteins such as c-Myc do not show funnel-like basins in their free-energy landscapes; this makes their druggability a challenge. For the first time, we propose a heterodimer model of c-Myc/Max in full length in this work. We used Gaussian-accelerated molecular dynamics (GaMD) simulations to explore the behavior of c-Myc and its various regions, including the transactivation domain (TAD) and the basic helix-loop-helix-leucine-zipper (bHLH-Zipper) motif in three different conformational states: (a) monomeric c-Myc, (b) c-Myc when bound to its partner protein, Max, and (c) when Max was removed after binding. We analyzed the GaMD trajectories using root-mean-square deviation (RMSD), radius of gyration, root-mean-square fluctuation, and free-energy landscape (FEL) calculations to elaborate the behaviors of these regions. The results showed that the monomeric c-Myc structure showed a higher RMSD fluctuation as compared with the c-Myc/Max heterodimer in the bHLH-Zipper motif. This indicated that the bHLH-Zipper motif of c-Myc is more stable when it is bound to Max. The TAD region in both monomeric and Max-bound states showed similar plasticity in terms of RMSD. We also conducted residue decomposition calculations and showed that the c-Myc and Max interaction could be driven mainly by electrostatic interactions and the residues Arg299, Ile403, and Leu420 seemed to play important roles in the interaction. Our work provides insights into the behavior of c-Myc and its regions that could support the development of drugs that target c-Myc and other intrinsically disordered proteins.
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Affiliation(s)
| | - Taufiq Rahman
- Department
of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, United Kingdom
| | - Xavier Chee Wezen
- Faculty
of Engineering, Computing and Science, Swinburne
University of Technology Sarawak, Kuching 93350, Malaysia
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2
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Wang X, Lin DH, Yan Y, Wang AH, Liao J, Meng Q, Yang WQ, Zuo H, Hua MM, Zhang F, Zhu H, Zhou H, Huang TY, He R, Li G, Tan YQ, Shi HJ, Gou LT, Li D, Wu L, Zheng Y, Fu XD, Li J, Liu R, Li GH, Liu MF. The PIWI-specific insertion module helps load longer piRNAs for translational activation essential for male fertility. SCIENCE CHINA. LIFE SCIENCES 2023:10.1007/s11427-023-2390-5. [PMID: 37335463 DOI: 10.1007/s11427-023-2390-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 06/07/2023] [Indexed: 06/21/2023]
Abstract
PIWI-clade proteins harness piRNAs of 24-33 nt in length. Of great puzzles are how PIWI-clade proteins incorporate piRNAs of different sizes and whether the size matters to PIWI/piRNA function. Here we report that a PIWI-Ins module unique in PIWI-clade proteins helps define the length of piRNAs. Deletion of PIWI-Ins in Miwi shifts MIWI to load with shorter piRNAs and causes spermiogenic failure in mice, demonstrating the functional importance of this regulatory module. Mechanistically, we show that longer piRNAs provide additional complementarity to target mRNAs, thereby enhancing the assembly of the MIWI/eIF3f/HuR super-complex for translational activation. Importantly, we identify a c.1108C>T (p.R370W) mutation of HIWI (human PIWIL1) in infertile men and demonstrate in Miwi knock-in mice that this genetic mutation impairs male fertility by altering the property of PIWI-Ins in selecting longer piRNAs. These findings reveal a critical role of PIWI-Ins-ensured longer piRNAs in fine-tuning MIWI/piRNA targeting capacity, proven essential for spermatid development and male fertility.
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Affiliation(s)
- Xin Wang
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Di-Hang Lin
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yue Yan
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - An-Hui Wang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiaoyang Liao
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Qian Meng
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
| | - Wen-Qing Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Heng Zuo
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Min-Min Hua
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
- NHC Key Lab of Reproduction Regulation (Shanghai Institute for Biomedical and Pharmaceutical Technologies), Fudan University, Shanghai, 200032, China
| | - Fengjuan Zhang
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hongwen Zhu
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
| | - Hu Zhou
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
| | - Tian-Yu Huang
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Rui He
- Key Laboratory of Fertility Preservation and Maintenance of Ministry of Education, School of Basic Medical Sciences, Ningxia Medical University, Yinchuan, 750004, China
| | - Guangyong Li
- Department of Urology, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, 750004, China
| | - Yue-Qiu Tan
- Institute of Reproductive and Stem Cell Engineering, College of Basic of Medicine, Central South University, Changsha, 410000, China
| | - Hui-Juan Shi
- NHC Key Lab of Reproduction Regulation (Shanghai Institute for Biomedical and Pharmaceutical Technologies), Fudan University, Shanghai, 200032, China
| | - Lan-Tao Gou
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Dangsheng Li
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ligang Wu
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yonggang Zheng
- Department of Physiology, Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Xiang-Dong Fu
- Westlake Laboratory of Life Sciences and Biomedicine, School of Life Sciences, Westlake University, Hangzhou, 310024, China
| | - Jinsong Li
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Rujuan Liu
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
| | - Guo-Hui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Mo-Fang Liu
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China.
- State Key Laboratory of Molecular Biology, State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
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3
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Rahimi K, Piaggi PM, Zerze GH. Comparison of On-the-Fly Probability Enhanced Sampling and Parallel Tempering Combined with Metadynamics for Atomistic Simulations of RNA Tetraloop Folding. J Phys Chem B 2023. [PMID: 37196167 DOI: 10.1021/acs.jpcb.3c00117] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Atomistic simulations with reliable models are extremely useful in providing exquisitely detailed pictures of biomolecular phenomena that are not always accessible to experiments. One such biomolecular phenomenon is RNA folding, which often requires exhaustive simulations with combined advanced sampling techniques. In this work, we employed the multithermal-multiumbrella on-the-fly probability enhanced sampling (MM-OPES) technique and compared it against combined parallel tempering and metadynamics simulations. We found that MM-OPES simulations were successful in reproducing the free energy surfaces from combined parallel tempering and metadynamics simulations. Importantly, we also investigated a wide range of temperature sets (minimum and maximum temperatures) for MM-OPES simulations in order to identify some guidelines for deciding the temperature limits for an accurate and efficient exploration of the free energy landscapes. We found that most temperature sets yielded almost the same accuracy in reproducing the free energy surface at the ambient conditions as long as (i) the maximum temperature is reasonably high, (ii) the temperature at which we run the simulation is reasonably high (in our simulations, running temperature is defined as [minimum temperature + maximum temperature]/2), and (iii) the effective sample size at the temperature of interest is statistically reasonable. In terms of the computational cost, all MM-OPES simulations were nearly 4 times less costly than the combined parallel tempering and metadynamics simulations. We concluded that the demanding combined parallel tempering and metadynamics simulations can safely be replaced with approximately 4 times less costly MM-OPES simulations (with carefully selected temperature limits) to obtain the same information.
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Affiliation(s)
- Kosar Rahimi
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204, United States
| | - Pablo M Piaggi
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Gül H Zerze
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204, United States
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4
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Kasavajhala K, Simmerling C. Exploring the Transferability of Replica Exchange Structure Reservoirs to Accelerate Generation of Ensembles for Alternate Hamiltonians or Protein Mutations. J Chem Theory Comput 2023; 19:1931-1944. [PMID: 36861842 PMCID: PMC10658647 DOI: 10.1021/acs.jctc.3c00005] [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] [Indexed: 03/03/2023]
Abstract
Generating precise ensembles is commonly a prerequisite to understand the energetics of biological processes using Molecular Dynamics (MD) simulations. Previously, we have shown how unweighted reservoirs built from high temperature MD simulations can accelerate convergence of Boltzmann-weighted ensembles by at least 10× with the Reservoir Replica Exchange MD (RREMD) method. Therefore, in this work, we explore whether an unweighted structure reservoir generated with one Hamiltonian (solute force field plus solvent model) can be reused to quickly generate accurately weighted ensembles for Hamiltonians other than the one that was used to generate the reservoir. We also extended this methodology to rapidly estimate the effects of mutations on peptide stability by using a reservoir of diverse structures obtained from wild-type simulations. These results suggest that structures generated via fast methods such as coarse-grained models or structures predicted by Rosetta or deep learning approaches could be integrated into a reservoir to accelerate generation of ensembles using more accurate representations.
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Affiliation(s)
- Koushik Kasavajhala
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
| | - Carlos Simmerling
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
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5
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Fan Y, Xia W, Ma C, Huang Y, Li S, Wang X, Qian C, Chen K, Liu D. Recent advances of computational studies on bioethanol to light olefin reactions using zeolite and metal oxide catalysts. Chem Eng Sci 2023. [DOI: 10.1016/j.ces.2023.118532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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6
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Souza FR, Moura PG, Costa RKM, Silva RS, Pimentel AS. Absolute binding free energies of mucroporin and its analog mucroporin-M1 with the heptad repeat 1 domain and RNA-dependent RNA polymerase of SARS-CoV-2. J Biomol Struct Dyn 2022:1-12. [PMID: 35993479 DOI: 10.1080/07391102.2022.2114014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The peptide Mucroporin and its analog Mucroporin-M1 were studied using the molecular docking and molecular dynamics simulation of their complexation with two protein targets, the Heptad Repeat 1 (HR1) domain and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The molecular docking of the peptide-protein complexes was performed using the glowworm swarm optimization algorithm. The lowest energy poses were submitted to molecular dynamics simulation. Then, the binding free energies of Mucroporin and its analog Mucroporin-M1 with these two protein targets were calculated using the Multistate Bennett Acceptance Ratio (MBAR) method. It was verified that the peptides/HR1 domain complex showed stability in the interaction site determined by molecular docking. It was also found that Mucroporin-M1 has a much higher affinity than Mucroporin to the HR1 protein target. The peptides showed similar stability and affinity at the NTP binding site in the RdRp protein. Additional experimental studies are needed to confirm the antiviral activity of Mucroporin-M1 and a possible mechanism of action against SARS-CoV-2. However, here we indicate that Mucroporin-M1 may have potential antiviral activity against the HR1 domain with the possibility for further peptide optimization.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Felipe Rodrigues Souza
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Paloma Guimarães Moura
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | | | - Rudielson Santos Silva
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - André Silva Pimentel
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
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7
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Hsu CH, Chen YJ, Yang CN. An order-to-disorder structural switch regulates HIF-1 transcription through S247 phosphorylation in the HIF1α PAS-B domain. Comput Biol Med 2022; 149:106006. [PMID: 36027865 DOI: 10.1016/j.compbiomed.2022.106006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 08/11/2022] [Accepted: 08/14/2022] [Indexed: 11/18/2022]
Abstract
Hypoxia-inducible factor 1 (HIF-1), a transcriptional activator that mediates cellular responses to hypoxic stress, is essential for tumor progression. It is a heterodimer comprising HIF1α and HIF1β, with multiple interfaces among their PAS-A, PAS-B, and bHLH domains. HIF1β is also known as aryl hydrocarbon receptor nuclear translocator (ARNT). Casein kinase 1δ-dependent phosphorylation of the solvent-front residue S247 on the HIF1α PAS-B domain interrupts HIF1α-ARNT complex formation and reduces HIF-1 transcription activity. However, S247 is involved in neither HIF1α-ARNT complex formation nor stabilization of the relative orientation between the HIF1α PAS-A and PAS-B domains. To uncover the underlying allosteric mechanism, we conducted Gaussian accelerated molecular dynamics simulations and identified two distinct conformations of the pS247-carrying HIF1α PAS-B domain: H291-in and H291-out. The H291-in structure can associate with the HIF1α PAS-A domain and form a V-shaped pouch to accommodate the ARNT PAS-A domain, but it cannot associate with the ARNT PAS-B domain. By contrast, the H291-out structure can bind to the ARNT PAS-B domain, but its association with the HIF1α PAS-A domain leads to an unsuitable relative orientation to accommodate the ARNT PAS-A domain. Both conformations were also collected in parallel simulations of the unphosphorylated PAS-B domain. Both structures manage to associate with the ARNT PAS-B and HIF1α PAS-A domains; thus, they are adequate for HIF1α-ARNT complex formation. The domain-domain contact pattern in a phosphorylated variant is shuffled by an order-to-disorder structural switch, triggered by the newly formed K251-pS247 interaction.
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Affiliation(s)
- Chia-Hung Hsu
- Department of Internal Medicine, Zuoying Branch of Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
| | - Ya-Jyun Chen
- Institute of Precision Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Chia-Ning Yang
- Institute of Precision Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan.
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8
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Li L, Liu J, Li X, Tang Y, Shi C, Zhang X, Cui Y, Wang L, Xu W. Influencing factors and characterization methods of nanoparticles regulating amyloid aggregation. SOFT MATTER 2022; 18:3278-3290. [PMID: 35437550 DOI: 10.1039/d1sm01704g] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Human disorders associated with amyloid aggregation, such as Alzheimer's disease and Parkinson's disease, afflict the lives of millions worldwide. When peptides and proteins in the body are converted to amyloids, which have a tendency to aggregate, the toxic oligomers produced during the aggregation process can trigger a range of diseases. Nanoparticles (NPs) have been found to possess surface effects that can modulate the amyloid aggregation process and they have potential application value in the treatment of diseases related to amyloid aggregation and fibrillary tangles. In this review, we discuss recent progress relating to studies of nanoparticles that regulate amyloid aggregation. The review focuses on the factors influencing this regulation, which are important as guidelines for the future design of NPs for the treatment of amyloid aggregation. We describe the characterization methods that have been utilized so far in such studies. This review provides research information and characterization methods for the rational design of NPs, which should result in therapeutic strategies for amyloid diseases.
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Affiliation(s)
- Lingyi Li
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Jianhui Liu
- Yantai Center of Ecology and Environment Monitoring of Shandong Province, Yantai 264025, China
| | - Xinyue Li
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Yuanhan Tang
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Changxin Shi
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Xin Zhang
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Yuming Cui
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
| | - Linlin Wang
- State Key Laboratory of Long-Acting and Targeting Drug Delivery System, Shandong Luye Pharmaceutical Co., Ltd, Yantai 264000, China.
| | - Wenlong Xu
- School of Chemistry and Materials Science, Ludong University, Yantai 264025, China.
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9
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González-Fernández C, Bringas E, Oostenbrink C, Ortiz I. In silico investigation and surmounting of Lipopolysaccharide barrier in Gram-Negative Bacteria: How far has molecular dynamics Come? Comput Struct Biotechnol J 2022; 20:5886-5901. [PMID: 36382192 PMCID: PMC9636410 DOI: 10.1016/j.csbj.2022.10.039] [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: 08/26/2022] [Revised: 10/24/2022] [Accepted: 10/24/2022] [Indexed: 11/29/2022] Open
Abstract
Lipopolysaccharide (LPS), a main component of the outer membrane of Gram-negative bacteria, has crucial implications on both antibiotic resistance and the overstimulation of the host innate immune system. Fighting against these global concerns calls for the molecular understanding of the barrier function and immunostimulatory ability of LPS. Molecular dynamics (MD) simulations have become an invaluable tool for uncovering important findings in LPS research. While the reach of MD simulations for investigating the immunostimulatory ability of LPS has been already outlined, little attention has been paid to the role of MD simulations for exploring its barrier function and synthesis. Herein, we give an overview about the impact of MD simulations on gaining insight into the shield role and synthesis pathway of LPS, which have attracted considerable attention to discover molecules able to surmount antibiotic resistance, either circumventing LPS defenses or disrupting its synthesis. We specifically focus on the enhanced sampling and free energy calculation methods that have been combined with MD simulations to address such research. We also highlight the use of special-purpose MD supercomputers, the importance of appropriate LPS and ions parameterization to obtain reliable results, and the complementary views that MD and wet-lab experiments provide. Thereby, this work, which covers the last five years of research, apart from outlining the phenomena and strategies that are being explored, evidences the valuable insights that are gained by MD, which may be useful to advance antibiotic design, and what the prospects of this in silico method could be in LPS research.
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Affiliation(s)
- Cristina González-Fernández
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Eugenio Bringas
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Chris Oostenbrink
- Institute for Molecular Modeling and Simulation, BOKU – University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria
| | - Inmaculada Ortiz
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
- Corresponding author.
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10
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Shi X, Lin X, Luo R, Wu S, Li L, Zhao ZJ, Gong J. Dynamics of Heterogeneous Catalytic Processes at Operando Conditions. JACS AU 2021; 1:2100-2120. [PMID: 34977883 PMCID: PMC8715484 DOI: 10.1021/jacsau.1c00355] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Indexed: 05/02/2023]
Abstract
The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions-so-called operando modeling-is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.
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Affiliation(s)
- Xiangcheng Shi
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
- Joint
School of National University of Singapore and Tianjin University,
International Campus of Tianjin University, Fuzhou 350207, China
| | - Xiaoyun Lin
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
| | - Ran Luo
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
| | - Shican Wu
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
| | - Lulu Li
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
| | - Zhi-Jian Zhao
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
| | - Jinlong Gong
- Key
Laboratory for Green Chemical Technology of Ministry of Education,
School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Collaborative
Innovation Center of Chemical Science and Engineering, Tianjin 300072, China
- Joint
School of National University of Singapore and Tianjin University,
International Campus of Tianjin University, Fuzhou 350207, China
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11
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Luo S, Zhao X, Wang Y, Duan L. Theoretical investigating mechanisms of drug-resistance generated by mutation-induced changes in influenza viruses. CHINESE J CHEM PHYS 2021. [DOI: 10.1063/1674-0068/cjcp2110193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Song Luo
- School of Physics and Electronics, Shandong Normal University, Jinan, 250014, China
| | - Xiaoyu Zhao
- School of Physics and Electronics, Shandong Normal University, Jinan, 250014, China
| | - Yihui Wang
- School of Physics and Electronics, Shandong Normal University, Jinan, 250014, China
| | - Lili Duan
- School of Physics and Electronics, Shandong Normal University, Jinan, 250014, China
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12
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González-Fernández C, Basauri A, Fallanza M, Bringas E, Oostenbrink C, Ortiz I. Fighting Against Bacterial Lipopolysaccharide-Caused Infections through Molecular Dynamics Simulations: A Review. J Chem Inf Model 2021; 61:4839-4851. [PMID: 34559524 PMCID: PMC8549069 DOI: 10.1021/acs.jcim.1c00613] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
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Lipopolysaccharide
(LPS) is the primary component of the outer
leaflet of Gram-negative bacterial outer membranes. LPS elicits an
overwhelming immune response during infection, which can lead to life-threatening
sepsis or septic shock for which no suitable treatment is available
so far. As a result of the worldwide expanding multidrug-resistant
bacteria, the occurrence and frequency of sepsis are expected to increase;
thus, there is an urge to develop novel strategies for treating bacterial
infections. In this regard, gaining an in-depth understanding about
the ability of LPS to both stimulate the host immune system and interact
with several molecules is crucial for fighting against LPS-caused
infections and allowing for the rational design of novel antisepsis
drugs, vaccines and LPS sequestration and detection methods. Molecular
dynamics (MD) simulations, which are understood as being a computational
microscope, have proven to be of significant value to understand LPS-related
phenomena, driving and optimizing experimental research studies. In
this work, a comprehensive review on the methods that can be combined
with MD simulations, recently applied in LPS research, is provided.
We focus especially on both enhanced sampling methods, which enable
the exploration of more complex systems and access to larger time
scales, and free energy calculation approaches. Thereby, apart from
outlining several strategies for surmounting LPS-caused infections,
this work reports the current state-of-the-art of the methods applied
with MD simulations for moving a step forward in the development of
such strategies.
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Affiliation(s)
- Cristina González-Fernández
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Arantza Basauri
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Marcos Fallanza
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Eugenio Bringas
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
| | - Chris Oostenbrink
- Institute for Molecular Modeling and Simulation, BOKU - University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria
| | - Inmaculada Ortiz
- Department of Chemical and Biomolecular Engineering, ETSIIT, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
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13
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Walker CC, Meek GA, Fobe TL, Shirts MR. Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure. J Chem Theory Comput 2021; 17:6018-6035. [PMID: 34495659 DOI: 10.1021/acs.jctc.1c00528] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1-1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Moreover, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.
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Affiliation(s)
- Christopher C Walker
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Garrett A Meek
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Theodore L Fobe
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Michael R Shirts
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
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14
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Gong X, Zhang Y, Chen J. Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions. Biomolecules 2021; 11:1416. [PMID: 34680048 PMCID: PMC8533332 DOI: 10.3390/biom11101416] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/22/2021] [Accepted: 09/24/2021] [Indexed: 11/16/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) are highly prevalent and play important roles in biology and human diseases. It is now also recognized that many IDPs remain dynamic even in specific complexes and functional assemblies. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for a mechanistic understanding of IDPs in biology, diseases, and therapeutics. Here, we provide an in-depth review of recent advances in the multi-scale simulation of disordered protein states, with a particular emphasis on the development and application of advanced sampling techniques for studying IDPs. These techniques are critical for adequate sampling of the manifold functionally relevant conformational spaces of IDPs. Together with dramatically improved protein force fields, these advanced simulation approaches have achieved substantial success and demonstrated significant promise towards the quantitative and predictive modeling of IDPs and their dynamic interactions. We will also discuss important challenges remaining in the atomistic simulation of larger systems and how various coarse-grained approaches may help to bridge the remaining gaps in the accessible time- and length-scales of IDP simulations.
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Affiliation(s)
- Xiping Gong
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
| | - Yumeng Zhang
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
| | - Jianhan Chen
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA 01003, USA
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15
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Weng JB, Liao CY, Li Y, Zhang DL, Li GH, Wang AH. Effect of protein dimerization on ion conductivity of gramicidin a channel studied using polarizable force field. CHINESE J CHEM PHYS 2021. [DOI: 10.1063/1674-0068/cjcp2103046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Jun-ben Weng
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Chen-yi Liao
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Yan Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Ding-lin Zhang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Guo-hui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - An-hui Wang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- State Key Laboratory of Fine Chemicals, School of Chemistry, Dalian University of Technology, Dalian 116024, China
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16
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Cao X, Tian P. "Dividing and Conquering" and "Caching" in Molecular Modeling. Int J Mol Sci 2021; 22:5053. [PMID: 34068835 PMCID: PMC8126232 DOI: 10.3390/ijms22095053] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/17/2022] Open
Abstract
Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.
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Affiliation(s)
- Xiaoyong Cao
- School of Life Sciences, Jilin University, Changchun 130012, China;
| | - Pu Tian
- School of Life Sciences, Jilin University, Changchun 130012, China;
- School of Artificial Intelligence, Jilin University, Changchun 130012, China
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17
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Zhong Q, Li G. Adaptively Iterative Multiscale Switching Simulation Strategy and Applications to Protein Folding and Structure Prediction. J Phys Chem Lett 2021; 12:3151-3162. [PMID: 33755493 DOI: 10.1021/acs.jpclett.1c00618] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Structure prediction is an important means to quickly understand new protein functions. However, the prediction of effects of proteins that have no detectable templates is still to be improved. Molecular dynamics simulation is supposed to be the primary research tool for structure predictions, but it still has limitations of huge computational cost in all-atom (AA) models and rough accuracy in coarse-grained (CG) models. We propose a universal multiscale simulation strategy named AIMS in which simulations can iteratively switch among multiple resolutions in order to adaptively trade off AA accuracy and CG high-efficiency. AIMS follows the idea of CG-guided enhanced sampling so that final results always keep AA accuracy. We successfully achieve four ab initio and four data-assisted protein structure predictions using AIMS. The prediction result is an ensemble rather than a structure and provides special insights on folding metastable states. AIMS is estimated to achieve a computational speed about 40 times faster than that of conventional AA simulations.
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Affiliation(s)
- Qinglu Zhong
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
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18
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Abstract
Every protein has a story-how it folds, what it binds, its biological actions, and how it misbehaves in aging or disease. Stories are often inferred from a protein's shape (i.e., its structure). But increasingly, stories are told using computational molecular physics (CMP). CMP is rooted in the principled physics of driving forces and reveals granular detail of conformational populations in space and time. Recent advances are accessing longer time scales, larger actions, and blind testing, enabling more of biology's stories to be told in the language of atomistic physics.
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Affiliation(s)
- Emiliano Brini
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Carlos Simmerling
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA
| | - Ken Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA. .,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Physics and Astronomy, Stony Brook University, Stony Brook, New NY 11794, USA
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19
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Kasavajhala K, Lam K, Simmerling C. Exploring Protocols to Build Reservoirs to Accelerate Temperature Replica Exchange MD Simulations. J Chem Theory Comput 2020; 16:7776-7799. [PMID: 33142060 DOI: 10.1021/acs.jctc.0c00513] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Temperature replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method for accelerating biomolecular simulations. During the past 2 decades, several variants of REMD have been developed to further improve the rate of conformational sampling of REMD. One such variant, reservoir REMD (RREMD), was shown to improve the rate of conformational sampling by around 5-20×. Despite the significant increase in the sampling speed, RREMD methods have not been widely used because of the difficulties in building the reservoir and also because of the code not being available on the graphics processing units (GPUs). In this work, we ported the Amber RREMD code onto GPUs making it 20× faster than the central processing unit code. Then, we explored protocols for building Boltzmann-weighted reservoirs as well as non-Boltzmann reservoirs and tested how each choice affects the accuracy of the resulting RREMD simulations. We show that, using the recommended protocols outlined here, RREMD simulations can accurately reproduce Boltzmann-weighted ensembles obtained by much more expensive conventional temperature-based REMD simulations, with at least 15× faster convergence rates even for larger proteins (>50 amino acids) compared to conventional REMD.
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Affiliation(s)
- Koushik Kasavajhala
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
| | - Kenneth Lam
- Molecular and Cellular Biology, Stony Brook University, Stony Brook, New York 11794, United States.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
| | - Carlos Simmerling
- Department of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
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20
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Wang A, Zhang Y, Chu H, Liao C, Zhang Z, Li G. Higher Accuracy Achieved for Protein-Ligand Binding Pose Prediction by Elastic Network Model-Based Ensemble Docking. J Chem Inf Model 2020; 60:2939-2950. [PMID: 32383873 DOI: 10.1021/acs.jcim.9b01168] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Molecular docking plays an indispensable role in predicting the receptor-ligand interactions in which the protein receptor is usually kept rigid, whereas the ligand is treated as being flexible. Because of the inherent flexibility of proteins, the binding pocket of apo receptors might undergo significant conformational rearrangement upon ligand binding, which limits the prediction accuracy of docking. Here, we present an iterative anisotropic network model (iterANM)-based ensemble docking approach, which generates multiple holo-like receptor structures starting from the apo receptor and incorporates protein flexibility into docking. In a validation data set consisting of 233 chemically diverse cyclin-dependent kinase 2 (CDK2) inhibitors, the iterANM-based ensemble docking achieves higher capacity to reproduce native-like binding poses compared with those using single apo receptor conformation or conformational ensemble from molecular dynamics simulations. The prediction success rate within the top5-ranked binding poses produced by the iterANM can further be improved through reranking with the molecular mechanics-Poisson-Boltzmann surface area method. In a smaller data set with 58 CDK2 inhibitors, the iterANM-based ensemble shows a higher success rate compared with the flexible receptor-based docking procedure AutoDockFR and other receptor conformation generation approaches. Further, an additional docking test consisting of 10 diverse receptor-ligand combinations shows that the iterANM is robustly applicable for different receptor structures. These results suggest the iterANM-based ensemble docking as an accurate, efficient, and practical framework to predict the binding mode of a ligand for receptors with flexibility.
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Affiliation(s)
- Anhui Wang
- State Key Laboratory of Fine Chemicals, School of Chemistry, Dalian University of Technology, Dalian 116024, China.,Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Yuebin Zhang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Huiying Chu
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Chenyi Liao
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Zhichao Zhang
- State Key Laboratory of Fine Chemicals, School of Chemistry, Dalian University of Technology, Dalian 116024, China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
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21
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Zhong Q, Li G. Arbitrary Resolution with Two Bead Types Coarse-Grained Strategy and Applications to Protein Recognition. J Phys Chem Lett 2020; 11:3263-3270. [PMID: 32251595 DOI: 10.1021/acs.jpclett.0c00750] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Molecular recognition is a fundamental step in essentially any biological process. However, the kinetic processes during association and dissociation are difficult to be efficiently sampled by direct all-atom molecular dynamics simulations because of the large spatial and temporal scales. Here we propose an arbitrary resolution with two bead types (ART) coarse-grained (CG) strategy that is adept in molecular recognition. ART is a universal user-customized CG strategy that can generate a system-specific CG force field anytime and be applied to any system with an arbitrary CG resolution according to research requirements. ART CG simulations can be very efficiently performed with implicit solvation in prevalent simulation packages and provide interfaces for any enhanced sampling method. We used three applications, HLA-HIV epitope recognition, barnase-barstar association, and trimeric TRAF2 self-assembly, to validate the feasibility of the ART CG strategy, its advantages in protein recognition, and its high performance in simulations. Regular CG simulations can successfully achieve valid protein recognitions without any prior bound structure.
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Affiliation(s)
- Qinglu Zhong
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
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22
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Sur-X, a novel peptide, kills colorectal cancer cells by targeting survivin-XIAP complex. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2020; 39:82. [PMID: 32381104 PMCID: PMC7203900 DOI: 10.1186/s13046-020-01581-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 04/22/2020] [Indexed: 12/12/2022]
Abstract
Background Survivin and XIAP are two important members of the inhibitor of apoptosis protein family and have been considered as potential targets for cancer treatment due to their overexpression in large variety of cancers including colorectal cancer. It has been reported that survivin and XIAP can synergistically inhibit apoptosis by forming survivin-XIAP complex. In this study, we aimed to design a peptide that targets the survivin-XIAP complex and elucidate its anticancer mechanisms in colorectal cancer cells. Methods We designed and synthetized Sur-X, the peptide targeting survivin-XIAP complex. The anticancer effects of Sur-X were evaluated both in vitro and in vivo. The underlying molecular mechanisms were also investigated. Results Sur-X exhibited potent inhibitory effects on four colorectal cancer cell lines HCT116, HCT15, RKO and HT29, but not on human peritoneal mesothelial cell line HMrSV5. Mechanistically, Sur-X induced Caspase 9-dependent intrinsic apoptosis in colorectal cancer cells by disrupting the survivin-XIAP complex and subsequently destabilizing survivin and XIAP. Interestingly, we found that Sur-X can also promote necroptosis. It was demonstrated that Sur-X destroyed the interaction between XIAP and TAB1 in the XIAP-TAB1-TAK1 complex, leading to the instability of TAK1, an endogenous necroptosis inhibitor. Subsequently, the accelerated degradation of TAK1 attenuated its inhibition on necroptosis in colorectal cancer cells. Moreover, knockdown of TAK1 restored the sensitivity of TAB1-overexpressing colorectal cancer cells to Sur-X-induced necroptosis. The in vivo pro-apoptotic effect of Sur-X was confirmed by the enhanced TUNEL staining and the decreased expression of survivin and XIAP in tumor tissues from xenograft mouse models. In addition, extensive necrosis and weaker MLKL expression in xenografts provided evidence for the in vivo pro-necroptotic effect of Sur-X. Conclusions Peptide Sur-X exhibits strong pro-apoptotic and pro-necroptotic effects in colorectal cancer cells and has a high clinical translation potential in the treatment of colorectal cancer.
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23
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Battocchio G, González R, Rao AG, Schapiro I, Mroginski MA. Dynamic Properties of the Photosensory Domain of Deinococcus radiodurans Bacteriophytochrome. J Phys Chem B 2020; 124:1740-1750. [PMID: 31999119 DOI: 10.1021/acs.jpcb.0c00612] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Phytochromes are biological photoreceptors found in all kingdoms of life. Numerous physicochemical and spectroscopic studies of phytochromes have been carried out for many decades, both experimentally and computationally, with the main focus on the photoconversion mechanism involving a tetrapyrrole chromophore. In this computational work, we concentrate on the long-scale dynamic motion of the photosensory domain of Deinococcus radiodurans by means of classical all-atom molecular dynamics (MD) simulations. Conventional and accelerated MD methods in combination with two different force fields, CHARMM27 and AMBER ff14SB, are tested in long atomistic simulations to confront the dynamics of monomer and dimer forms. These calculations highlight dissimilar equilibrium conformations in aqueous solutions and, in turn, different large-scale dynamic behaviors of the monomer form vs the dimer form. While the phytochrome in a monomer form tends to close the cavity entailed between the GAF and PHY domains, the opposite trend is predicted for the phytochrome dimer, which opens up as a consequence of the formation of strong salt bridges between the PHY domains of two molecules in water.
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Affiliation(s)
- Giovanni Battocchio
- Institut für Chemie, Technische Universität Berlin, Sekr. PC 14, Strasse des 17. Juni 135, D-10623 Berlin, Germany
| | - Ronald González
- Institut für Chemie, Technische Universität Berlin, Sekr. PC 14, Strasse des 17. Juni 135, D-10623 Berlin, Germany
| | - Aditya G Rao
- Fritz Haber Center for Molecular Dynamics Research Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Igor Schapiro
- Fritz Haber Center for Molecular Dynamics Research Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Maria Andrea Mroginski
- Institut für Chemie, Technische Universität Berlin, Sekr. PC 14, Strasse des 17. Juni 135, D-10623 Berlin, Germany
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24
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Wang A, Zhang D, Li Y, Zhang Z, Li G. Large-Scale Biomolecular Conformational Transitions Explored by a Combined Elastic Network Model and Enhanced Sampling Molecular Dynamics. J Phys Chem Lett 2020; 11:325-332. [PMID: 31867970 DOI: 10.1021/acs.jpclett.9b03399] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Biomolecules often undergo large-scale conformational transitions when carrying out their functions. However, it is still challenging for conventional molecular dynamics simulations to provide adequate structural dynamics information to interpret associated mechanisms. Here, we present a combined elastic network model and enhanced sampling-based strategy (iterANM-IaMD) by adopting iterANM to construct initial conformation space and enhanced sampling IaMD to explore the free energy landscape along specific large-scale conformational transitions. We applied this strategy to three functionally and structurally distinct proteins (adenylate kinase, calmodulin, and p38α kinase), which undergo striking conformational change upon ligand binding. The simulation results for both free and ligand-bound proteins show qualitative and quantitative agreement with existing studies, suggesting iterANM-IaMD as an accurate and efficient tool to investigate structural dynamics involved in complicated biological processes. Our work also provides insights into the relationship between the dynamics and functionality of biomolecules.
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Affiliation(s)
- Anhui Wang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
- State Key Laboratory of Fine Chemicals, School of Chemistry , Dalian University of Technology , Dalian 116024 , China
| | - Dinglin Zhang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
| | - Yan Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
| | - Zhichao Zhang
- State Key Laboratory of Fine Chemicals, School of Chemistry , Dalian University of Technology , Dalian 116024 , China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , Dalian 116023 , China
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