1
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Ranganathan S, Liu J, Shakhnovich E. Enzymatic metabolons dramatically enhance metabolic fluxes of low-efficiency biochemical reactions. Biophys J 2023; 122:4555-4566. [PMID: 37915170 PMCID: PMC10719048 DOI: 10.1016/j.bpj.2023.10.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/18/2023] [Accepted: 10/30/2023] [Indexed: 11/03/2023] Open
Abstract
In this work, we investigate how spatial proximity of enzymes belonging to the same pathway (metabolon) affects metabolic flux. Using off-lattice Langevin dynamics simulations in tandem with a stochastic reaction-diffusion protocol and a semi-analytical reaction-diffusion model, we systematically explored how strength of protein-protein interactions, catalytic efficiency, and protein-ligand interactions affect metabolic flux through the metabolon. Formation of a metabolon leads to a greater speedup for longer pathways and especially for reaction-limited enzymes, whereas, for fully optimized diffusion-limited enzymes, the effect is negligible. Notably, specific cluster architectures are not a prerequisite for enhancing reaction flux. Simulations uncover the crucial role of optimal nonspecific protein-ligand interactions in enhancing catalytic efficiency of a metabolon. Our theory implies, and bioinformatics analysis confirms, that longer catalytic pathways are enriched in less optimal enzymes, whereas most diffusion-limited enzymes populate shorter pathways. Our findings point toward a plausible evolutionary strategy where enzymes compensate for less-than-optimal efficiency by increasing their local concentration in the clustered state.
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Affiliation(s)
- Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Junlang Liu
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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2
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Axelrod S, Shakhnovich E, Gómez-Bombarelli R. Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. J Chem Inf Model 2023; 63:5794-5802. [PMID: 37671878 DOI: 10.1021/acs.jcim.3c00484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2023]
Abstract
Light-activated drugs are a promising way to localize biological activity and minimize side effects. However, their development is complicated by the numerous photophysical and biological properties that must be simultaneously optimized. To accelerate the design of photoactive drugs, we describe a procedure that combines ligand-protein docking with chemical property prediction based on machine learning (ML). We apply this procedure to 58 proteins and 9000 photo-drug candidates based on azobenzene cis-trans isomerism. We find that most proteins display a preference for trans isomers over cis and that the binding affinities of nominally active/inactive pairs are in fact highly correlated. These findings have significant value for photopharmacology research, and reinforce the need for virtual screening to identify compounds with rare desirable properties. Further, we combine our procedure with quantum chemical validation to identify promising candidates for the photoactive inhibition of PARP1, an enzyme that is over-expressed in cancer cells. The top compounds are predicted to have long-lived active forms, differential bioactivity, and absorption in the near-infrared therapeutic window.
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Affiliation(s)
- Simon Axelrod
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Rafael Gómez-Bombarelli
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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3
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Ranganathan S, Dasmeh P, Furniss S, Shakhnovich E. Phosphorylation sites are evolutionary checkpoints against liquid-solid transition in protein condensates. Proc Natl Acad Sci U S A 2023; 120:e2215828120. [PMID: 37155880 PMCID: PMC10193986 DOI: 10.1073/pnas.2215828120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 03/30/2023] [Indexed: 05/10/2023] Open
Abstract
Assemblies of multivalent RNA-binding protein fused in sarcoma (FUS) can exist in the functional liquid-like state as well as less dynamic and potentially toxic amyloid- and hydrogel-like states. How could then cells form liquid-like condensates while avoiding their transformation to amyloids? Here, we show how posttranslational phosphorylation can provide a "handle" that prevents liquid-solid transition of intracellular condensates containing FUS. Using residue-specific coarse-grained simulations, for 85 different mammalian FUS sequences, we show how the number of phosphorylation sites and their spatial arrangement affect intracluster dynamics preventing conversion to amyloids. All atom simulations further confirm that phosphorylation can effectively reduce the β-sheet propensity in amyloid-prone fragments of FUS. A detailed evolutionary analysis shows that mammalian FUS PLDs are enriched in amyloid-prone stretches compared to control neutrally evolved sequences, suggesting that mammalian FUS proteins evolved to self-assemble. However, in stark contrast to proteins that do not phase-separate for their function, mammalian sequences have phosphosites in close proximity to these amyloid-prone regions. These results suggest that evolution uses amyloid-prone sequences in prion-like domains to enhance phase separation of condensate proteins while enriching phosphorylation sites in close proximity to safeguard against liquid-solid transitions.
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Affiliation(s)
- Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA02138
| | - Pouria Dasmeh
- Center for Human Genetics, Marburg University, Marburg35033, Germany
| | - Seth Furniss
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA02138
- Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, OxfordOX1 3QZ, United Kingdom
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA02138
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4
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Axelrod S, Shakhnovich E, Gómez-Bombarelli R. Thermal Half-Lives of Azobenzene Derivatives: Virtual Screening Based on Intersystem Crossing Using a Machine Learning Potential. ACS Cent Sci 2023; 9:166-176. [PMID: 36844486 PMCID: PMC9951306 DOI: 10.1021/acscentsci.2c00897] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Indexed: 05/27/2023]
Abstract
Molecular photoswitches are the foundation of light-activated drugs. A key photoswitch is azobenzene, which exhibits trans-cis isomerism in response to light. The thermal half-life of the cis isomer is of crucial importance, since it controls the duration of the light-induced biological effect. Here we introduce a computational tool for predicting the thermal half-lives of azobenzene derivatives. Our automated approach uses a fast and accurate machine learning potential trained on quantum chemistry data. Building on well-established earlier evidence, we argue that thermal isomerization proceeds through rotation mediated by intersystem crossing, and incorporate this mechanism into our automated workflow. We use our approach to predict the thermal half-lives of 19,000 azobenzene derivatives. We explore trends and trade-offs between barriers and absorption wavelengths, and open-source our data and software to accelerate research in photopharmacology.
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Affiliation(s)
- Simon Axelrod
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts02138, United States
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts02139, United States
| | - Eugene Shakhnovich
- Department
of Chemistry and Chemical Biology, Harvard
University, Cambridge, Massachusetts02138, United States
| | - Rafael Gómez-Bombarelli
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts02139, United States
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5
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Kraay C, Serebryany E, Ranganathan S, Shakhnovich E. Investigating the mechanism of suppression of human γD-crystallin aggregation by myo-inositol. Biophys J 2023; 122:337a. [PMID: 36783703 DOI: 10.1016/j.bpj.2022.11.1878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023] Open
Affiliation(s)
- Constance Kraay
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
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6
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Serebryany E, Chowdhury S, Woods C, Thorn DC, Watson NE, McClelland A, Klevit R, Shakhnovich E. A native chemical chaperone in the human eye lens suppresses redox-dependent lens crystallin misfolding. Biophys J 2023; 122:337a. [PMID: 36783704 DOI: 10.1016/j.bpj.2022.11.1879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023] Open
Affiliation(s)
- Eugene Serebryany
- Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Sourav Chowdhury
- Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | - David C Thorn
- Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Nicki E Watson
- Center for Nanoscale Systems, Harvard University, Cambridge, MA, USA
| | - Arthur McClelland
- Center for Nanoscale Systems, Harvard University, Cambridge, MA, USA
| | - Rachel Klevit
- Biochemistry, University of Washington, Seattle, WA, USA
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7
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Axelrod S, Shakhnovich E, Gómez-Bombarelli R. Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. Nat Commun 2022; 13:3440. [PMID: 35705543 PMCID: PMC9200747 DOI: 10.1038/s41467-022-30999-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 05/23/2022] [Indexed: 12/31/2022] Open
Abstract
Light-induced chemical processes are ubiquitous in nature and have widespread technological applications. For example, photoisomerization can allow a drug with a photo-switchable scaffold such as azobenzene to be activated with light. In principle, photoswitches with desired photophysical properties like high isomerization quantum yields can be identified through virtual screening with reactive simulations. In practice, these simulations are rarely used for screening, since they require hundreds of trajectories and expensive quantum chemical methods to account for non-adiabatic excited state effects. Here we introduce a diabatic artificial neural network (DANN), based on diabatic states, to accelerate such simulations for azobenzene derivatives. The network is six orders of magnitude faster than the quantum chemistry method used for training. DANN is transferable to azobenzene molecules outside the training set, predicting quantum yields for unseen species that are correlated with experiment. We use the model to virtually screen 3100 hypothetical molecules, and identify novel species with high predicted quantum yields. The model predictions are confirmed using high-accuracy non-adiabatic dynamics. Our results pave the way for fast and accurate virtual screening of photoactive compounds.
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Affiliation(s)
- Simon Axelrod
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA.,Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Rafael Gómez-Bombarelli
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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8
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Ranganathan S, Shakhnovich E. The physics of liquid-to-solid transitions in multi-domain protein condensates. Biophys J 2022; 121:2751-2766. [PMID: 35702028 DOI: 10.1016/j.bpj.2022.06.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 04/21/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022] Open
Abstract
Many RNA-binding proteins (RBPs) that assemble into membraneless organelles have a common architecture including disordered prion-like domain (PLD) and folded RNA-binding domain (RBD). An enrichment of PLD within the condensed phase gives rise to formation, on longer time scales, of amyloid-like fibrils (aging). In this study, we employ coarse-grained Langevin dynamics simulations to explore the physical basis for the structural diversity in condensed phases of multi-domain RBPs. We discovered a highly cooperative first-order transition between disordered structures and an ordered phase whereby chains of PLD organize in fibrils with high nematic orientational order. An interplay between homodomain (PLD-PLD) and heterodomain (PLD-RBD) interactions results in variety of structures with distinct spatial architectures. Interestingly, the different structural phases also exhibit vastly different intracluster dynamics of proteins, with diffusion coefficients 5 times (disordered structures) to 50 times (ordered structures) lower than that of the dilute phase. Cooperativity of this liquid-solid transition makes fibril formation highly malleable to mutations or post-translational modifications. Our results provide a mechanistic understanding of how multi-domain RBPs could form assemblies with distinct structural and material properties.
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Affiliation(s)
- Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
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9
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Zhang Y, Chowdhury S, Rodrigues JV, Shakhnovich E. Development of antibacterial compounds that constrain evolutionary pathways to resistance. eLife 2021; 10:64518. [PMID: 34279221 PMCID: PMC8331180 DOI: 10.7554/elife.64518] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 07/13/2021] [Indexed: 01/27/2023] Open
Abstract
Antibiotic resistance is a worldwide challenge. A potential approach to block resistance is to simultaneously inhibit WT and known escape variants of the target bacterial protein. Here, we applied an integrated computational and experimental approach to discover compounds that inhibit both WT and trimethoprim (TMP) resistant mutants of E. coli dihydrofolate reductase (DHFR). We identified a novel compound (CD15-3) that inhibits WT DHFR and its TMP resistant variants L28R, P21L and A26T with IC50 50–75 µM against WT and TMP-resistant strains. Resistance to CD15-3 was dramatically delayed compared to TMP in in vitro evolution. Whole genome sequencing of CD15-3-resistant strains showed no mutations in the target folA locus. Rather, gene duplication of several efflux pumps gave rise to weak (about twofold increase in IC50) resistance against CD15-3. Altogether, our results demonstrate the promise of strategy to develop evolution drugs - compounds which constrain evolutionary escape routes in pathogens.
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Affiliation(s)
- Yanmin Zhang
- School of Science, China Pharmaceutical University, Nanjing, China.,Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Sourav Chowdhury
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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10
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Abstract
Membraneless organelles (MLOs) are spatiotemporally regulated structures that concentrate multivalent proteins or RNA, often in response to stress. The proteins enriched within MLOs are often classified as high-valency "scaffolds" or low-valency "clients", with the former being associated with a phase-separation promoting role. In this study, we employ a minimal model for P-body components, with a defined protein-protein interaction network, to study their phase separation at biologically realistic low protein concentrations. Without RNA, multivalent proteins can assemble into solid-like clusters only in the regime of high concentration and stable interactions. RNA molecules promote cluster formation in an RNA-length-dependent manner, even in the regime of weak interactions and low protein volume fraction. Our simulations reveal that long RNA chains act as superscaffolds that stabilize large RNA-protein clusters by recruiting low-valency proteins within them while also ensuring functional "liquid-like" turnover of components. Our results suggest that RNA-mediated phase separation could be a plausible mechanism for spatiotemporally regulated phase separation in the cell.
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Affiliation(s)
- Srivastav Ranganathan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
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11
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Bhattacharyya S, Bershtein S, Adkar B, Woodard J, Shakhnovich E. Metabolic response to point mutations reveals principles of modulation of
in vivo
enzyme activity and phenotype. FASEB J 2021. [DOI: 10.1096/fasebj.2021.35.s1.01916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | - Bharat Adkar
- Chemistry & Chemical BiologyHarvard UniversityCambridgeMA
| | - Jaie Woodard
- Chemistry & Chemical BiologyHarvard UniversityCambridgeMA
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12
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Serebryany E, Shakhnovich E. High-Throughput Disulfide Scanning of In Vivo Protein Conformations. Biophys J 2021. [DOI: 10.1016/j.bpj.2020.11.921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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13
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Serebryany E, Jacobs WM, Razban R, Shakhnovich E. Catalysis of Aggregation by Interface Opening and Disulfide Exchange in Cataract-Associated Variants of Human Gamma-D Crystallin. Biophys J 2020. [DOI: 10.1016/j.bpj.2019.11.1192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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14
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Hu R, Rodrigues JV, Pradeep Waduge J, Yamazaki H, Cressiot B, Chishti Y, Makowski L, Yu D, Shakhnovich E, Zhao Q, Wanunu M. Differential Enzyme Flexibility Probed Using Solid-State Nanopores. ACS Nano 2018; 12:4494-4502. [PMID: 29630824 PMCID: PMC9016714 DOI: 10.1021/acsnano.8b00734] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Enzymes and motor proteins are dynamic macromolecules that coexist in a number of conformations of similar energies. Protein function is usually accompanied by a change in structure and flexibility, often induced upon binding to ligands. However, while measuring protein flexibility changes between active and resting states is of therapeutic significance, it remains a challenge. Recently, our group has demonstrated that breadth of signal amplitudes in measured electrical signatures as an ensemble of individual protein molecules is driven through solid-state nanopores and correlates with protein conformational dynamics. Here, we extend our study to resolve subtle flexibility variation in dihydrofolate reductase mutants from unlabeled single molecules in solution. We first demonstrate using a canonical protein system, adenylate kinase, that both size and flexibility changes can be observed upon binding to a substrate that locks the protein in a closed conformation. Next, we investigate the influence of voltage bias and pore geometry on the measured electrical pulse statistics during protein transport. Finally, using the optimal experimental conditions, we systematically study a series of wild-type and mutant dihydrofolate reductase proteins, finding a good correlation between nanopore-measured protein conformational dynamics and equilibrium bulk fluorescence probe measurements. Our results unequivocally demonstrate that nanopore-based measurements reliably probe conformational diversity in native protein ensembles.
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Affiliation(s)
- Rui Hu
- State Key Laboratory for Mesoscopic Physics and Electron Microscopy Laboratory, School of Physics, Peking University, Beijing 100871, People’s Republic of China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, People’s Republic of China
| | - João V. Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - J Pradeep Waduge
- Department of Physics, Northeastern University, Boston, Massachusetts 02115, United States
| | - Hirohito Yamazaki
- Department of Physics, Northeastern University, Boston, Massachusetts 02115, United States
| | - Benjamin Cressiot
- Department of Physics, Northeastern University, Boston, Massachusetts 02115, United States
| | - Yasmin Chishti
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Lee Makowski
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Dapeng Yu
- State Key Laboratory for Mesoscopic Physics and Electron Microscopy Laboratory, School of Physics, Peking University, Beijing 100871, People’s Republic of China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, People’s Republic of China
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Qing Zhao
- State Key Laboratory for Mesoscopic Physics and Electron Microscopy Laboratory, School of Physics, Peking University, Beijing 100871, People’s Republic of China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, People’s Republic of China
- Corresponding Authors:.,
| | - Meni Wanunu
- Department of Physics, Northeastern University, Boston, Massachusetts 02115, United States
- Corresponding Authors:.,
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15
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Srinivasan B, Rodrigues JV, Tonddast-Navaei S, Shakhnovich E, Skolnick J. Correction to Rational Design of Novel Allosteric Dihydrofolate Reductase Inhibitors Showing Antibacterial Effects on Drug-Resistant Escherichia coli Escape Variants. ACS Chem Biol 2018; 13:1407. [PMID: 29688000 DOI: 10.1021/acschembio.7b00759] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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16
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Srinivasan B, Rodrigues JV, Tonddast-Navaei S, Shakhnovich E, Skolnick J. Rational Design of Novel Allosteric Dihydrofolate Reductase Inhibitors Showing Antibacterial Effects on Drug-Resistant Escherichia coli Escape Variants. ACS Chem Biol 2017; 12:1848-1857. [PMID: 28525268 DOI: 10.1021/acschembio.7b00175] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
In drug discovery, systematic variations of substituents on a common scaffold and bioisosteric replacements are often used to generate diversity and obtain molecules with better biological effects. However, this could saturate the small-molecule diversity pool resulting in drug resistance. On the other hand, conventional drug discovery relies on targeting known pockets on protein surfaces leading to drug resistance by mutations of critical pocket residues. Here, we present a two-pronged strategy of designing novel drugs that target unique pockets on a protein's surface to overcome the above problems. Dihydrofolate reductase, DHFR, is a critical enzyme involved in thymidine and purine nucleotide biosynthesis. Several classes of compounds that are structural analogues of the substrate dihydrofolate have been explored for their antifolate activity. Here, we describe 10 novel small-molecule inhibitors of Escherichia coli DHFR, EcDHFR, belonging to the stilbenoid, deoxybenzoin, and chalcone family of compounds discovered by a combination of pocket-based virtual ligand screening and systematic scaffold hopping. These inhibitors show a unique uncompetitive or noncompetitive inhibition mechanism, distinct from those reported for all known inhibitors of DHFR, indicative of binding to a unique pocket distinct from either substrate or cofactor-binding pockets. Furthermore, we demonstrate that rescue mutants of EcDHFR, with reduced affinity to all known classes of DHFR inhibitors, are inhibited at the same concentration as the wild-type. These compounds also exhibit antibacterial activity against E. coli harboring the drug-resistant variant of DHFR. This discovery is the first report on a novel class of inhibitors targeting a unique pocket on EcDHFR.
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Affiliation(s)
- Bharath Srinivasan
- Center
for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, Georgia 30332, United States
| | - João V. Rodrigues
- Department
of Chemistry and Chemical Biology, Harvard University, 12 Oxford
Street, Cambridge, Massachusetts 02138, United States
| | - Sam Tonddast-Navaei
- Center
for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, Georgia 30332, United States
| | - Eugene Shakhnovich
- Department
of Chemistry and Chemical Biology, Harvard University, 12 Oxford
Street, Cambridge, Massachusetts 02138, United States
| | - Jeffrey Skolnick
- Center
for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, Georgia 30332, United States
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17
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Zhou Q, Sun X, Xia X, Fan Z, Luo Z, Zhao S, Shakhnovich E, Liang H. Exploring the Mutational Robustness of Nucleic Acids by Searching Genotype Neighborhoods in Sequence Space. J Phys Chem Lett 2017; 8:407-414. [PMID: 28045264 DOI: 10.1021/acs.jpclett.6b02769] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
To assess the mutational robustness of nucleic acids, many genome- and protein-level studies have been performed, where nucleic acids are treated as genetic information carriers and transferrers. However, the molecular mechanisms through which mutations alter the structural, dynamic, and functional properties of nucleic acids are poorly understood. Here we performed a SELEX in silico study to investigate the fitness distribution of the l-Arm-binding aptamer genotype neighborhoods. Two novel functional genotype neighborhoods were isolated and experimentally verified to have comparable fitness as the wild-type. The experimental aptamer fitness landscape suggests the mutational robustness is strongly influenced by the local base environment and ligand-binding mode, whereas bases distant from the binding pocket provide potential evolutionary pathways to approach the global fitness maximum. Our work provides an example of successful application of SELEX in silico to optimize an aptamer and demonstrates the strong sensitivity of mutational robustness to the site of genetic variation.
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Affiliation(s)
- Qingtong Zhou
- iHuman Institute, ShanghaiTech University , Shanghai 201210, China
| | - Xianbao Sun
- CAS Key Laboratory of Soft Matter Chemistry, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Polymer Science and Engineering, Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China , Hefei, Anhui 230026, China
| | - Xiaole Xia
- Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University , Wuxi, Jiangsu 214122, China
| | - Zhou Fan
- iHuman Institute, ShanghaiTech University , Shanghai 201210, China
- Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- University of Chinese Academy of Sciences , Beijing 100049, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
| | - Zhaofeng Luo
- School of Life Science, University of Science and Technology of China , Hefei, Anhui 230026, China
| | - Suwen Zhao
- iHuman Institute, ShanghaiTech University , Shanghai 201210, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States
| | - Haojun Liang
- CAS Key Laboratory of Soft Matter Chemistry, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Polymer Science and Engineering, Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China , Hefei, Anhui 230026, China
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18
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19
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Zhou Q, Xia X, Luo Z, Liang H, Shakhnovich E. Searching the Sequence Space for Potent Aptamers Using SELEX in Silico. J Chem Theory Comput 2015; 11:5939-46. [PMID: 26642994 DOI: 10.1021/acs.jctc.5b00707] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
To isolate functional nucleic acids that bind to defined targets with high affinity and specificity, which are known as aptamers, the systematic evolution of ligands by exponential enrichment (SELEX) methodology has emerged as the preferred approach. Here, we propose a computational approach, SELEX in silico, that allows the sequence space to be more thoroughly explored regarding binding of a certain target. Our approach consists of two steps: (i) secondary structure-based sequence screening, which aims to collect the sequences that can form a desired RNA motif as an enhanced initial library, followed by (ii) sequence enrichment regarding target binding by molecular dynamics simulation-based virtual screening. Our SELEX in silico method provided a practical computational solution to three key problems in aptamer sequence searching: design of nucleic acid libraries, knowledge of sequence enrichment, and identification of potent aptamers. Six potent theophylline-binding aptamers, which were isolated by SELEX in silico from a sequence space containing 4(13) sequences, were experimentally verified to bind theophylline with high affinity: Kd ranging from 0.16 to 0.52 μM, compared with the dissociation constant of the original aptamer-theophylline, 0.32 μM. These results demonstrate the significant potential of SELEX in silico as a new method for aptamer discovery and optimization.
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Affiliation(s)
- Qingtong Zhou
- Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States
| | - Xiaole Xia
- Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States.,Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University , Wuxi, Jiangsu 214122, People's Republic of China
| | | | | | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States
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Bershtein S, Choi JM, Bhattacharyya S, Budnik B, Shakhnovich E. Systems-level response to point mutations in a core metabolic enzyme modulates genotype-phenotype relationship. Cell Rep 2015; 11:645-56. [PMID: 25892240 DOI: 10.1016/j.celrep.2015.03.051] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2015] [Revised: 02/20/2015] [Accepted: 03/23/2015] [Indexed: 11/18/2022] Open
Abstract
Linking the molecular effects of mutations to fitness is central to understanding evolutionary dynamics. Here, we establish a quantitative relation between the global effect of mutations on the E. coli proteome and bacterial fitness. We created E. coli strains with specific destabilizing mutations in the chromosomal folA gene encoding dihydrofolate reductase (DHFR) and quantified the ensuing changes in the abundances of 2,000+ E. coli proteins in mutant strains using tandem mass tags with subsequent LC-MS/MS. mRNA abundances in the same E. coli strains were also quantified. The proteomic effects of mutations in DHFR are quantitatively linked to phenotype: the SDs of the distributions of logarithms of relative (to WT) protein abundances anticorrelate with bacterial growth rates. Proteomes hierarchically cluster first by media conditions, and within each condition, by the severity of the perturbation to DHFR function. These results highlight the importance of a systems-level layer in the genotype-phenotype relationship.
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Affiliation(s)
- Shimon Bershtein
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA; Department of Life Sciences, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 8410501, Israel
| | - Jeong-Mo Choi
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA
| | - Sanchari Bhattacharyya
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA
| | - Bogdan Budnik
- MSPRL, Center of Systems Biology, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.
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Liberles DA, Teichmann SA, Bahar I, Bastolla U, Bloom J, Bornberg-Bauer E, Colwell LJ, de Koning APJ, Dokholyan NV, Echave J, Elofsson A, Gerloff DL, Goldstein RA, Grahnen JA, Holder MT, Lakner C, Lartillot N, Lovell SC, Naylor G, Perica T, Pollock DD, Pupko T, Regan L, Roger A, Rubinstein N, Shakhnovich E, Sjölander K, Sunyaev S, Teufel AI, Thorne JL, Thornton JW, Weinreich DM, Whelan S. The interface of protein structure, protein biophysics, and molecular evolution. Protein Sci 2012; 21:769-85. [PMID: 22528593 PMCID: PMC3403413 DOI: 10.1002/pro.2071] [Citation(s) in RCA: 140] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Revised: 03/22/2012] [Accepted: 03/23/2012] [Indexed: 12/20/2022]
Abstract
Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.
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Affiliation(s)
- David A Liberles
- Department of Molecular Biology, University of WyomingLaramie, Wyoming 82071
| | - Sarah A Teichmann
- MRC Laboratory of Molecular BiologyHills Road, Cambridge CB2 0QH, United Kingdom
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of PittsburghPittsburgh, Pennsylvania 15213
| | - Ugo Bastolla
- Bioinformatics Unit. Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Universidad Autonoma de Madrid28049 Cantoblanco Madrid, Spain
| | - Jesse Bloom
- Division of Basic Sciences, Fred Hutchinson Cancer Research CenterSeattle, Washington 98109
| | - Erich Bornberg-Bauer
- Evolutionary Bioinformatics Group, Institute for Evolution and Biodiversity, University of MuensterGermany
| | - Lucy J Colwell
- MRC Laboratory of Molecular BiologyHills Road, Cambridge CB2 0QH, United Kingdom
| | - A P Jason de Koning
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of ColoradoAurora, Colorado
| | - Nikolay V Dokholyan
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel HillNorth Carolina 27599
| | - Julian Echave
- Escuela de Ciencia y Tecnología, Universidad Nacional de San MartínMartín de Irigoyen 3100, 1650 San Martín, Buenos Aires, Argentina
| | - Arne Elofsson
- Department of Biochemistry and Biophysics, Center for Biomembrane Research, Stockholm Bioinformatics Center, Science for Life Laboratory, Swedish E-science Research Center, Stockholm University106 91 Stockholm, Sweden
| | - Dietlind L Gerloff
- Biomolecular Engineering Department, University of CaliforniaSanta Cruz, California 95064
| | - Richard A Goldstein
- Division of Mathematical Biology, National Institute for Medical Research (MRC)Mill Hill, London NW7 1AA, United Kingdom
| | - Johan A Grahnen
- Department of Molecular Biology, University of WyomingLaramie, Wyoming 82071
| | - Mark T Holder
- Department of Ecology and Evolutionary Biology, University of KansasLawrence, Kansas 66045
| | - Clemens Lakner
- Bioinformatics Research Center, North Carolina State UniversityRaleigh, North Carolina 27695
| | - Nicholas Lartillot
- Département de Biochimie, Faculté de Médecine, Université de MontréalMontréal, QC H3T1J4, Canada
| | - Simon C Lovell
- Faculty of Life Sciences, University of ManchesterManchester M13 9PT, United Kingdom
| | - Gavin Naylor
- Department of Biology, College of CharlestonCharleston, South Carolina 29424
| | - Tina Perica
- MRC Laboratory of Molecular BiologyHills Road, Cambridge CB2 0QH, United Kingdom
| | - David D Pollock
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of ColoradoAurora, Colorado
| | - Tal Pupko
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv UniversityTel Aviv, Israel
| | - Lynne Regan
- Department of Molecular Biophysics and Biochemistry, Yale UniversityNew Haven 06511
| | - Andrew Roger
- Department of Biochemistry and Molecular Biology, Dalhousie UniversityHalifax, NS, Canada
| | - Nimrod Rubinstein
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv UniversityTel Aviv, Israel
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard UniversityCambridge, Massachusetts 02138
| | - Kimmen Sjölander
- Department of Bioengineering, University of CaliforniaBerkeley, Berkeley, California 94720
| | - Shamil Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School77 Avenue Louis Pasteur, Boston, Massachusetts 02115
| | - Ashley I Teufel
- Department of Molecular Biology, University of WyomingLaramie, Wyoming 82071
| | - Jeffrey L Thorne
- Bioinformatics Research Center, North Carolina State UniversityRaleigh, North Carolina 27695
| | - Joseph W Thornton
- Howard Hughes Medical Institute and Institute for Ecology and Evolution, University of OregonEugene, Oregon 97403
- Department of Human Genetics, University of ChicagoChicago, Illinois 60637
- Department of Ecology and Evolution, University of ChicagoChicago, Illinois 60637
| | - Daniel M Weinreich
- Department of Ecology and Evolutionary Biology, and Center for Computational Molecular Biology, Brown UniversityProvidence, Rhode Island 02912
| | - Simon Whelan
- Faculty of Life Sciences, University of ManchesterManchester M13 9PT, United Kingdom
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Shakhnovich E, Chelnokova E, Pashenko N, Kerbikov O. 37 Multiple successive surgery and chemotherapy helped to dramatically prolong life in patient with bladder cancer. Crit Rev Oncol Hematol 2011. [DOI: 10.1016/s1040-8428(11)70056-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
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Shakhnovich E, Kolganov A. 22 Surgery and multiple successive chemotherapy helped to achieve a sustainable remission in patient with advanced MALT lymphoma. EJC Suppl 2010. [DOI: 10.1016/s1359-6349(10)70693-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Affiliation(s)
- J. William Lee
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Tomasz Zemojtel
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Germany
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
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Lam AR, Borreguero JM, Ding F, Dokholyan NV, Buldyrev SV, Stanley HE, Shakhnovich E. Parallel folding pathways in the SH3 domain protein. J Mol Biol 2007; 373:1348-60. [PMID: 17900612 DOI: 10.1016/j.jmb.2007.08.032] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2006] [Revised: 08/06/2007] [Accepted: 08/14/2007] [Indexed: 11/16/2022]
Abstract
The transition-state ensemble (TSE) is the set of protein conformations with an equal probability to fold or unfold. Its characterization is crucial for an understanding of the folding process. We determined the TSE of the src-SH3 domain protein by using extensive molecular dynamics simulations of the Go model and computing the folding probability of a generated set of TSE candidate conformations. We found that the TSE possesses a well-defined hydrophobic core with variable enveloping structures resulting from the superposition of three parallel folding pathways. The most preferred pathway agrees with the experimentally determined TSE, while the two least preferred pathways differ significantly. The knowledge of the different pathways allows us to design the interactions between amino acids that guide the protein to fold through the least preferred pathway. This particular design is akin to a circular permutation of the protein. The finding motivates the hypothesis that the different experimentally observed TSEs in homologous proteins and circular permutants may represent potentially available pathways to the wild-type protein.
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Affiliation(s)
- A R Lam
- Center for Polymer Studies, Department of Physics, Boston University, Boston, MA 02215, USA.
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Abstract
The mechanical unfolding of proteins under a stretching force has an important role in living systems and is a logical extension of the more general protein folding problem. Recent advances in experimental methodology have allowed the stretching of single molecules, thus rendering this process ripe for computational study. We use all-atom Monte Carlo simulation with a Gō-type potential to study the mechanical unfolding pathway of ubiquitin. A detailed, robust, well-defined pathway is found, confirming existing results in this vein though using a different model. Additionally, we identify the protein's fundamental stabilizing secondary structure interactions in the presence of a stretching force and show that this fundamental stabilizing role does not persist in the absence of mechanical stress. The apparent success of simulation methods in studying ubiquitin's mechanical unfolding pathway indicates their potential usefulness for future study of the stretching of other proteins and the relationship between protein structure and the response to mechanical deformation.
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Affiliation(s)
- Ariel Kleiner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA
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Affiliation(s)
- Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA.
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Zhang Y, Hubner IA, Arakaki AK, Shakhnovich E, Skolnick J. On the origin and highly likely completeness of single-domain protein structures. Proc Natl Acad Sci U S A 2006; 103:2605-10. [PMID: 16478803 PMCID: PMC1413790 DOI: 10.1073/pnas.0509379103] [Citation(s) in RCA: 140] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The size and origin of the protein fold universe is of fundamental and practical importance. Analyzing randomly generated, compact sticky homopolypeptide conformations constructed in generic simplified and all-atom protein models, all have similar folds in the library of solved structures, the Protein Data Bank, and conversely, all compact, single-domain protein structures in the Protein Data Bank have structural analogues in the compact model set. Thus, both sets are highly likely complete, with the protein fold universe arising from compact conformations of hydrogen-bonded, secondary structures. Because side chains are represented by their Cbeta atoms, these results also suggest that the observed protein folds are insensitive to the details of side-chain packing. Sequence specificity enters both in fine-tuning the structure and thermodynamically stabilizing a given fold with respect to the set of alternatives. Scanning the models against a three-dimensional active-site library, close geometric matches are frequently found. Thus, the presence of active-site-like geometries also seems to be a consequence of the packing of compact, secondary structural elements. These results have significant implications for the evolution of protein structure and function.
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Affiliation(s)
- Yang Zhang
- *Center of Excellence in Bioinformatics, University at Buffalo, State University of New York, 901 Washington Street, Buffalo, NY 14203; and
| | - Isaac A. Hubner
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138
| | - Adrian K. Arakaki
- *Center of Excellence in Bioinformatics, University at Buffalo, State University of New York, 901 Washington Street, Buffalo, NY 14203; and
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138
| | - Jeffrey Skolnick
- *Center of Excellence in Bioinformatics, University at Buffalo, State University of New York, 901 Washington Street, Buffalo, NY 14203; and
- To whom correspondence should be sent at the present address:
Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250 14th Street NW, Atlanta, GA 30318. E-mail:
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Shakhnovich BE, Deeds E, Delisi C, Shakhnovich E. Protein structure and evolutionary history determine sequence space topology. Genome Res 2005; 15:385-92. [PMID: 15741509 PMCID: PMC551565 DOI: 10.1101/gr.3133605] [Citation(s) in RCA: 75] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2004] [Accepted: 11/23/2004] [Indexed: 11/24/2022]
Abstract
Understanding the observed variability in the number of homologs of a gene is a very important unsolved problem that has broad implications for research into coevolution of structure and function, gene duplication, pseudogene formation, and possibly for emerging diseases. Here, we attempt to define and elucidate some possible causes behind the observed irregularity in sequence space. We present evidence that sequence variability and functional diversity of a gene or fold family is influenced by quantifiable characteristics of the protein structure. These characteristics reflect the structural potential for sequence plasticity, i.e., the ability to accept mutation without losing thermodynamic stability. We identify a structural feature of a protein domain-contact density-that serves as a determinant of entropy in sequence space, i.e., the ability of a protein to accept mutations without destroying the fold (also known as fold designability). We show that (log) of average gene family size exhibits statistical correlation (R(2) > 0.9.) with contact density of its three-dimensional structure. We present evidence that the size of individual gene families are influenced not only by the designability of the structure, but also by evolutionary history, e.g., the amount of time the gene family was in existence. We further show that our observed statistical correlation between gene family size and contact density of the structure is valid on many levels of evolutionary divergence, i.e., not only for closely related sequence, but also for less-related fold and superfamily levels of homology.
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Shakhnovich BE, Harvey JM, Comeau S, Lorenz D, DeLisi C, Shakhnovich E. ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations. BMC Bioinformatics 2003; 4:34. [PMID: 12952559 PMCID: PMC194751 DOI: 10.1186/1471-2105-4-34] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2003] [Accepted: 09/02/2003] [Indexed: 11/12/2022] Open
Abstract
UNLABELLED The problem of functional annotation based on homology modeling is primary to current bioinformatics research. Researchers have noted regularities in sequence, structure and even chromosome organization that allow valid functional cross-annotation. However, these methods provide a lot of false negatives due to limited specificity inherent in the system. We want to create an evolutionarily inspired organization of data that would approach the issue of structure-function correlation from a new, probabilistic perspective. Such organization has possible applications in phylogeny, modeling of functional evolution and structural determination. ELISA (Evolutionary Lineage Inferred from Structural Analysis, http://romi.bu.edu/elisa) is an online database that combines functional annotation with structure and sequence homology modeling to place proteins into sequence-structure-function "neighborhoods". The atomic unit of the database is a set of sequences and structural templates that those sequences encode. A graph that is built from the structural comparison of these templates is called PDUG (protein domain universe graph). We introduce a method of functional inference through a probabilistic calculation done on an arbitrary set of PDUG nodes. Further, all PDUG structures are mapped onto all fully sequenced proteomes allowing an easy interface for evolutionary analysis and research into comparative proteomics. ELISA is the first database with applicability to evolutionary structural genomics explicitly in mind. AVAILABILITY The database is available at http://romi.bu.edu/elisa.
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Affiliation(s)
| | - John M Harvey
- BioInformatics Program, Boston University, Boston, MA, 02215, USA
| | - Steve Comeau
- BioInformatics Program, Boston University, Boston, MA, 02215, USA
| | - David Lorenz
- BioInformatics Program, Boston University, Boston, MA, 02215, USA
| | - Charles DeLisi
- BioInformatics Program, Boston University, Boston, MA, 02215, USA
| | - Eugene Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
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Gutman L, Shakhnovich E. Field theory and segmental alignment analysis for a solution of sequence disordered liquid crystalline polymers. J Chem Phys 2002. [DOI: 10.1063/1.1430743] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Jan Angerman H, Shakhnovich E. Dynamic charge-density correlation function in weakly charged polyampholyte globules. Phys Rev E Stat Nonlin Soft Matter Phys 2001; 64:041802. [PMID: 11690043 DOI: 10.1103/physreve.64.041802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2000] [Revised: 05/30/2001] [Indexed: 05/23/2023]
Abstract
We study solutions of statistically neutral polyampholyte chains containing a large fraction of neutral monomers. It is known that such solutions phase separate at very low concentrations, even if the quality of the solvent with respect to the neutral monomers is good. The precipitate is semidilute if the chains are weakly charged. This paper considers straight theta solvents and good solvents, and we calculate the dynamic charge density correlation function g(k,t) in the precipitate, using the quadratic approximation to the Martin-Siggia-Rose generating functional. It is convenient to express the results in terms of dimensionless space and time variables. Let xi be the blob size, and let tau be the characteristic time scale at the blob level. Define the dimensionless wave vector q=xik, and the dimensionless time s=t/tau. In the regime q<1, corresponding to length scales larger than the blob size, and 1<s<q(-4), corresponding to time scales in between the blob relaxation time and the relaxation time at scale q(-1), we find that the charge density fluctuations relax according to the power law g(q,s) approximately q(2)s(-1/2). This relaxation is qualitatively different from that of a neutral semidilute polymer solution. We expect our results to be valid for wave vectors q>0.1, where entanglements are unimportant.
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Affiliation(s)
- H Jan Angerman
- Department of Polymer Chemistry, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands
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Abstract
This review focuses on recent advances in understanding protein folding kinetics in the context of nucleation theory. We present basic concepts such as nucleation, folding nucleus, and transition state ensemble and then discuss recent advances and challenges in theoretical understanding of several key aspects of protein folding kinetics. We cover recent topology-based approaches as well as evolutionary studies and molecular dynamics approaches to determine protein folding nucleus and analyze other aspects of folding kinetics. Finally, we briefly discuss successful all-atom Monte-Carlo simulations of protein folding and conclude with a brief outlook for the future.
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Affiliation(s)
- L Mirny
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
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Abstract
Here, we present statistical analysis of conservation profiles in families of homologous sequences for nine proteins whose folding nucleus was determined by protein engineering methods. We show that in all but one protein (AcP) folding nucleus residues are significantly more conserved than the rest of the protein. Two aspects of our study are especially important: (i) grouping of amino acid residues into classes according to their physical-chemical properties and (ii) proper normalization of amino acid probabilities that reflects the fact that evolutionary pressure to conserve some amino acid types may itself affect concentration of various amino acid types in protein families. Neglect of any of those two factors may make physical and biological "signals" from conservation profiles disappear.
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Affiliation(s)
- L Mirny
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, 02138, USA
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Shakhnovich E, Kussell E, Shimada J. Folding thermodynamics and kinetics in all-atom simulations. J Mol Graph Model 2000. [DOI: 10.1016/s1093-3263(00)80130-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Angerman HJ, Shakhnovich E. Freezing in polyampholytes globules: Influence of the long-range nature of the interaction. J Chem Phys 1999. [DOI: 10.1063/1.479356] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Abstract
The folding ability of a heteropolymer model for proteins subject to Monte Carlo dynamics on a simple cubic lattice is shown to be strongly correlated with the stability of the native state. We consider a number of estimates of the stability that can be determined without simulation, including the energy gap between the native state and the structurally dissimilar part of the spectrum (Z score) and, for sequences with fully compact native states, the gap in energy between the native and first excited fully compact states. These estimates are found to be more robust predictors of folding ability than a parameter sigma that requires simulation for its evaluation: sigma = 1 - Tf/Ttheta, where Tf is the temperature at which the fluctuation of an order parameter is at its maximum and Ttheta is the temperature at which the specific heat is at its maximum. We show that the interpretation of Ttheta as the collapse transition temperature is not correct in general and that the correlation between sigma and the folding ability arises from the fact that sigma is related to the energy gap (Z score).
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Affiliation(s)
- A R Dinner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
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Abstract
BACKGROUND Nucleation-growth theory predicts that fast-folding peptide sequences fold to their native structure via structures in a transition-state ensemble that share a small number of native contacts (the folding nucleus). Experimental and theoretical studies of proteins suggest that residues participating in folding nuclei are conserved among homologs. We attempted to determine if this is true in proteins with highly diverged sequences but identical folds (superfamilies). RESULTS We describe a strategy based on comparisons of residue conservation in natural superfamily sequences with simulated sequences (generated with a Monte-Carlo sequence design strategy) for the same proteins. The basic assumptions of the strategy were that natural sequences will conserve residues needed for folding and stability plus function, the simulated sequences contain no functional conservation, and nucleus residues make native contacts with each other. Based on these assumptions, we identified seven potential nucleus residues in ubiquitin superfamily members. Non-nucleus conserved residues were also identified; these are proposed to be involved in stabilizing native interactions. We found that all superfamily members conserved the same potential nucleus residue positions, except those for which the structural topology is significantly different. CONCLUSIONS Our results suggest that the conservation of the nucleus of a specific fold can be predicted by comparing designed simulated sequences with natural highly diverged sequences that fold to the same structure. We suggest that such a strategy could be used to help plan protein folding and design experiments, to identify new superfamily members, and to subdivide superfamilies further into classes having a similar folding mechanism.
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Affiliation(s)
- S W Michnick
- Département de biochime, Université de Montréal, Quebec.
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Gutman L, Shakhnovich E. Phase diagram analysis of random heteropolymers with composition specific and quenched cross-links. J Chem Phys 1998. [DOI: 10.1063/1.476847] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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47
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Tiana G, Broglia RA, Roman HE, Vigezzi E, Shakhnovich E. Folding and misfolding of designed proteinlike chains with mutations. J Chem Phys 1998. [DOI: 10.1063/1.475435] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Gutman L, Shakhnovich E. Frozen phases with re-entrant transition for random heteropolymers with composition specific and annealed cross-links. J Chem Phys 1997. [DOI: 10.1063/1.474136] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Abstract
Experimental and simulation studies show that small monomeric proteins fold in one kinetic step, which entails overcoming the free-energy barrier between the unfolded and the native protein through a transition state. Two models of transition state formation have been proposed: a 'nonspecific' one in which it depends on the formation of a sufficient number of native-like contacts regardless of what amino acids are involved, and a 'specific' one, in which it depends on formation of a specific subset of the native structure (a folding nucleus). The latter requires that some amino acids form most of their contacts in the transition state, whereas others only do so on reaching the native conformation. If so, mutations affecting the stability of the transition state nucleus should have a greater effect on the folding kinetics than mutations elsewhere, and the residues involved should be evolutionarily conserved. Lattice-model simulations and experiments suggest that such mutations exist. Here we present a method for determining the folding nucleus of a protein with known structure with two-state folding kinetics. This method is based on the alignment of many sequences designed to fold into the native conformation of a protein to identify the positions where amino acids are most conserved in designed sequences. The method is applied to chymotrypsin inhibitor 2 (CI2), a protein whose transition state has been previously studied by protein engineering. The involvement of residues in folding nucleus of CI2 is clearly correlated with their conservation in design, and the residues forming the nucleus are highly conserved in 23 natural sequences homologous to CI2.
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Affiliation(s)
- E Shakhnovich
- Harvard University, Department of Chemistry, Cambridge, Massachusetts 02138, USA
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Karplus M, Caflisch A, Săli A, Shakhnovich E. Protein dynamics: From the native to the unfolded state and back again. ACTA ACUST UNITED AC 1995. [DOI: 10.1007/bf00999578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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