1
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Anderson DM, Jayanthi LP, Gosavi S, Meiering EM. Engineering the kinetic stability of a β-trefoil protein by tuning its topological complexity. Front Mol Biosci 2023; 10:1021733. [PMID: 36845544 PMCID: PMC9945329 DOI: 10.3389/fmolb.2023.1021733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 01/02/2023] [Indexed: 02/11/2023] Open
Abstract
Kinetic stability, defined as the rate of protein unfolding, is central to determining the functional lifetime of proteins, both in nature and in wide-ranging medical and biotechnological applications. Further, high kinetic stability is generally correlated with high resistance against chemical and thermal denaturation, as well as proteolytic degradation. Despite its significance, specific mechanisms governing kinetic stability remain largely unknown, and few studies address the rational design of kinetic stability. Here, we describe a method for designing protein kinetic stability that uses protein long-range order, absolute contact order, and simulated free energy barriers of unfolding to quantitatively analyze and predict unfolding kinetics. We analyze two β-trefoil proteins: hisactophilin, a quasi-three-fold symmetric natural protein with moderate stability, and ThreeFoil, a designed three-fold symmetric protein with extremely high kinetic stability. The quantitative analysis identifies marked differences in long-range interactions across the protein hydrophobic cores that partially account for the differences in kinetic stability. Swapping the core interactions of ThreeFoil into hisactophilin increases kinetic stability with close agreement between predicted and experimentally measured unfolding rates. These results demonstrate the predictive power of readily applied measures of protein topology for altering kinetic stability and recommend core engineering as a tractable target for rationally designing kinetic stability that may be widely applicable.
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Affiliation(s)
| | - Lakshmi P. Jayanthi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
| | - Elizabeth M. Meiering
- Department of Chemistry, University of Waterloo, Waterloo, ON, Canada,*Correspondence: Elizabeth M. Meiering,
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2
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Banerjee A, Gosavi S. Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease. J Phys Chem B 2023; 127:855-865. [PMID: 36689738 PMCID: PMC9883841 DOI: 10.1021/acs.jpcb.2c05917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/23/2022] [Indexed: 01/24/2023]
Abstract
The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.
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Affiliation(s)
- Arkadeep Banerjee
- Simons Centre for the Study
of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
| | - Shachi Gosavi
- Simons Centre for the Study
of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
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3
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Kumari K, Ravi Prakash J, Padinhateeri R. Heterogeneous interactions and polymer entropy decide organization and dynamics of chromatin domains. Biophys J 2022; 121:2794-2812. [PMID: 35672951 PMCID: PMC9382282 DOI: 10.1016/j.bpj.2022.06.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 04/28/2022] [Accepted: 06/01/2022] [Indexed: 11/02/2022] Open
Abstract
Chromatin is known to be organized into multiple domains of varying sizes and compaction. While these domains are often imagined as static structures, they are highly dynamic and show cell-to-cell variability. Since processes such as gene regulation and DNA replication occur in the context of these domains, it is important to understand their organization, fluctuation, and dynamics. To simulate chromatin domains, one requires knowledge of interaction strengths among chromatin segments. Here, we derive interaction-strength parameters from experimentally known contact maps and use them to predict chromatin organization and dynamics. Taking two domains on the human chromosome as examples, we investigate its three-dimensional organization, size/shape fluctuations, and dynamics of different segments within a domain, accounting for hydrodynamic effects. Considering different cell types, we quantify changes in interaction strengths and chromatin shape fluctuations in different epigenetic states. Perturbing the interaction strengths systematically, we further investigate how epigenetic-like changes can alter the spatio-temporal nature of the domains. Our results show that heterogeneous weak interactions are crucial in determining the organization of the domains. Computing effective stiffness and relaxation times, we investigate how perturbations in interactions affect the solid- and liquid-like nature of chromatin domains. Quantifying dynamics of chromatin segments within a domain, we show how the competition between polymer entropy and interaction energy influence the timescales of loop formation and maintenance of stable loops.
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Affiliation(s)
- Kiran Kumari
- IITB-Monash Research Academy, Indian Institute of Technology Bombay, Mumbai, Maharashtra, 400076, India; Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra 400076, India; Department of Chemical Engineering, Monash University, Melbourne, VIC 3800, Australia.
| | - J Ravi Prakash
- Department of Chemical Engineering, Monash University, Melbourne, VIC 3800, Australia.
| | - Ranjith Padinhateeri
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra 400076, India.
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4
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Yadahalli S, Jayanthi LP, Gosavi S. A Method for Assessing the Robustness of Protein Structures by Randomizing Packing Interactions. Front Mol Biosci 2022; 9:849272. [PMID: 35832734 PMCID: PMC9271847 DOI: 10.3389/fmolb.2022.849272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/27/2022] [Indexed: 12/02/2022] Open
Abstract
Many single-domain proteins are not only stable and water-soluble, but they also populate few to no intermediates during folding. This reduces interactions between partially folded proteins, misfolding, and aggregation, and makes the proteins tractable in biotechnological applications. Natural proteins fold thus, not necessarily only because their structures are well-suited for folding, but because their sequences optimize packing and fit their structures well. In contrast, folding experiments on the de novo designed Top7 suggest that it populates several intermediates. Additionally, in de novo protein design, where sequences are designed for natural and new non-natural structures, tens of sequences still need to be tested before success is achieved. Both these issues may be caused by the specific scaffolds used in design, i.e., some protein scaffolds may be more tolerant to packing perturbations and varied sequences. Here, we report a computational method for assessing the response of protein structures to packing perturbations. We then benchmark this method using designed proteins and find that it can identify scaffolds whose folding gets disrupted upon perturbing packing, leading to the population of intermediates. The method can also isolate regions of both natural and designed scaffolds that are sensitive to such perturbations and identify contacts which when present can rescue folding. Overall, this method can be used to identify protein scaffolds that are more amenable to whole protein design as well as to identify protein regions which are sensitive to perturbations and where further mutations should be avoided during protein engineering.
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Affiliation(s)
| | | | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India
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5
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Neelamraju S, Wales DJ, Gosavi S. Protein energy landscape exploration with structure-based models. Curr Opin Struct Biol 2020; 64:145-151. [DOI: 10.1016/j.sbi.2020.07.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 06/30/2020] [Accepted: 07/15/2020] [Indexed: 12/11/2022]
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6
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Gershenson A, Gosavi S, Faccioli P, Wintrode PL. Successes and challenges in simulating the folding of large proteins. J Biol Chem 2020; 295:15-33. [PMID: 31712314 PMCID: PMC6952611 DOI: 10.1074/jbc.rev119.006794] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.
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Affiliation(s)
- Anne Gershenson
- Department of Biochemistry and Molecular Biology, University of Massachusetts, Amherst, Massachusetts 01003; Molecular and Cellular Biology Graduate Program, University of Massachusetts, Amherst, Massachusetts 01003.
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore-560065, India.
| | - Pietro Faccioli
- Dipartimento di Fisica, Universitá degli Studi di Trento, 38122 Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, 38123 Povo (Trento), Italy.
| | - Patrick L Wintrode
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland 21201.
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7
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Neelamraju S, Wales DJ, Gosavi S. Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins. J Chem Inf Model 2019; 59:1703-1708. [PMID: 30977648 DOI: 10.1021/acs.jcim.9b00007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Coarse-grained Go̅-like models, based on the principle of minimal frustration, provide valuable insight into fundamental questions in the field of protein folding and dynamics. In conjunction with commonly used molecular dynamics (MD) simulations, energy landscape exploration methods like discrete path sampling (DPS) with Go̅-like models can provide quantitative details of the thermodynamics and kinetics of proteins. Here we present Go-kit, a software that facilitates the setup of MD and DPS simulations of several flavors of Go̅-like models. Go-kit is designed for use with MD (GROMACS) and DPS (PATHSAMPLE) simulation engines that are open source. The Go-kit code is written in python2.7 and is also open source. A case study for the ribosomal protein S6 is discussed to illustrate the utility of the software, which is available at https://github.com/gokit1/gokit .
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Affiliation(s)
- Sridhar Neelamraju
- Simons Centre for the Study of Living Machines , National Centre for Biological Sciences, Tata Institute of Fundamental Research , Bellary Road , Bangalore 560065 , India.,University Chemical Laboratories , University of Cambridge , Lensfield Road , Cambridge CB2 1EW , U.K
| | - David J Wales
- University Chemical Laboratories , University of Cambridge , Lensfield Road , Cambridge CB2 1EW , U.K
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines , National Centre for Biological Sciences, Tata Institute of Fundamental Research , Bellary Road , Bangalore 560065 , India
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8
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Neelamraju S, Gosavi S, Wales DJ. Energy Landscape of the Designed Protein Top7. J Phys Chem B 2018; 122:12282-12291. [DOI: 10.1021/acs.jpcb.8b08499] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Sridhar Neelamraju
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka 560065, India
- University Chemical Laboratories, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka 560065, India
| | - David J. Wales
- University Chemical Laboratories, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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9
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Bruno da Silva F, Contessoto VG, de Oliveira VM, Clarke J, Leite VBP. Non-Native Cooperative Interactions Modulate Protein Folding Rates. J Phys Chem B 2018; 122:10817-10824. [DOI: 10.1021/acs.jpcb.8b08990] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Fernando Bruno da Silva
- Department of Physics, Institute of Biosciences, Humanities and Exact Sciences, São Paulo State University (UNESP), São José do Rio Preto - São Paulo 15054-000, Brazil
| | - Vinícius G. Contessoto
- Brazilian Bioethanol Science and Technology Laboratory - CTBE, Campinas - São Paulo 13083-100, Brazil
| | - Vinícius M. de Oliveira
- Department of Physics, Institute of Biosciences, Humanities and Exact Sciences, São Paulo State University (UNESP), São José do Rio Preto - São Paulo 15054-000, Brazil
| | - Jane Clarke
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Vitor B. P. Leite
- Department of Physics, Institute of Biosciences, Humanities and Exact Sciences, São Paulo State University (UNESP), São José do Rio Preto - São Paulo 15054-000, Brazil
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10
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Terse VL, Gosavi S. The Sensitivity of Computational Protein Folding to Contact Map Perturbations: The Case of Ubiquitin Folding and Function. J Phys Chem B 2018; 122:11497-11507. [PMID: 30234303 DOI: 10.1021/acs.jpcb.8b07409] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Ubiquitin is a small model protein, commonly used in protein folding experiments and simulations. We simulated ubiquitin using a well-tested structure-based model coarse-grained to a Cα level (Cα-SBM) and found that the simulated folding route did not agree with the experimentally observed one. Simulating the Cα-SBM with a cutoff contact map, instead of a screened contact map, switched the folding route with the new route matching the experimental route. Thus, the simulated folding of ubiquitin is sensitive to contact map definition. The screened contact map, which is used in folding simulations because it captures protein folding cooperativity, removes contacts in which the atoms in contact are occluded by a third atom and is less sensitive to the value of the cutoff distance in well-packed regions of the protein. In sparsely packed regions, the larger cutoff distance creates bridging contacts between atoms which are separated by voids. Such contacts do not seem to affect the folding of most proteins, including those of the ubiquitin fold. However, the surface of ubiquitin has several protruding functional side chains which naturally create bridging contacts. Together, our results show that subtle structural features of a protein that may not be apparent by mere observation can be identified by comparing folding simulations of SBMs in which these features are differently encoded. When such structural features are preserved for functional reasons, differences in computational folding can be leveraged to identify functional features. Notably, such features are accessible to a gradation of SBMs even in commonly studied proteins such as ubiquitin.
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Affiliation(s)
- Vishram L Terse
- Simons Centre for the Study of Living Machines , National Centre for Biological Sciences , Tata Institute of Fundamental Research, Bangalore 560065 , India
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines , National Centre for Biological Sciences , Tata Institute of Fundamental Research, Bangalore 560065 , India
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11
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Wang Y, Tian P, Boomsma W, Lindorff-Larsen K. Monte Carlo Sampling of Protein Folding by Combining an All-Atom Physics-Based Model with a Native State Bias. J Phys Chem B 2018; 122:11174-11185. [DOI: 10.1021/acs.jpcb.8b06335] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Yong Wang
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
| | - Pengfei Tian
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Wouter Boomsma
- Department of Computer Science, University of Copenhagen, 2100 Copenhagen Ø, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark
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12
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Cheng C, Wu J, Liu G, Shi S, Chen T. Effects of Non-native Interactions on Frustrated Proteins Folding under Confinement. J Phys Chem B 2018; 122:7654-7667. [DOI: 10.1021/acs.jpcb.8b04147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Chenqian Cheng
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an 710127, P. R. China
| | - Jing Wu
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an 710127, P. R. China
| | - Gaoyuan Liu
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an 710127, P. R. China
| | - Suqing Shi
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an 710127, P. R. China
| | - Tao Chen
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an 710127, P. R. China
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13
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Mandalaparthy V, Sanaboyana VR, Rafalia H, Gosavi S. Exploring the effects of sparse restraints on protein structure prediction. Proteins 2017; 86:248-262. [DOI: 10.1002/prot.25438] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 11/20/2017] [Accepted: 11/29/2017] [Indexed: 01/06/2023]
Affiliation(s)
- Varun Mandalaparthy
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road; Bangalore 560065 India
| | - Venkata Ramana Sanaboyana
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road; Bangalore 560065 India
| | - Hitesh Rafalia
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road; Bangalore 560065 India
- Manipal University, Madhav Nagar; Manipal 576104 India
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road; Bangalore 560065 India
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14
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Wu J, Chen G, Zhang Z, Zhang P, Chen T. The low populated folding intermediate of a mutant of the Fyn SH3 domain identified by a simple model. Phys Chem Chem Phys 2017; 19:22321-22328. [DOI: 10.1039/c7cp04139j] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The low populated on-pathway folding intermediate of the A39V/N53P/V55L Fyn SH3 domain is captured by a native-centric model augmented by sequence-dependent nonnative hydrophobic interactions.
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Affiliation(s)
- Jing Wu
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education
- College of Chemistry and Materials Science
- Northwest University
- Xi'an
- P. R. China
| | - Guojun Chen
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education
- College of Chemistry and Materials Science
- Northwest University
- Xi'an
- P. R. China
| | - Zhuqing Zhang
- College of Life Sciences
- University of Chinese Academy of Sciences
- Beijing
- P. R. China
| | - Ping Zhang
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education
- College of Chemistry and Materials Science
- Northwest University
- Xi'an
- P. R. China
| | - Tao Chen
- Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of the Ministry of Education
- College of Chemistry and Materials Science
- Northwest University
- Xi'an
- P. R. China
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15
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Mascarenhas NM, Gosavi S. Understanding protein domain-swapping using structure-based models of protein folding. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2016; 128:113-120. [PMID: 27867057 PMCID: PMC7127520 DOI: 10.1016/j.pbiomolbio.2016.09.013] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2016] [Revised: 09/05/2016] [Accepted: 09/26/2016] [Indexed: 02/05/2023]
Abstract
In domain-swapping, two or more identical protein monomers exchange structural elements and fold into dimers or multimers whose units are structurally similar to the original monomer. Domain-swapping is of biotechnological interest because inhibiting domain-swapping can reduce disease-causing fibrillar protein aggregation. To achieve such inhibition, it is important to understand both the energetics that stabilize the domain-swapped structure and the protein dynamics that enable the swapping. Structure-based models (SBMs) encode the folded structure of the protein in their potential energy functions. SBMs have been successfully used to understand diverse aspects of monomer folding. Symmetrized SBMs model interactions between two identical protein chains using only intra-monomer interactions. Molecular dynamics simulations of such symmetrized SBMs have been used to correctly predict the domain-swapped structure and to understand the mechanism of domain-swapping. Here, we review such models and illustrate that monomer topology determines key aspects of domain-swapping. However, in some proteins, specifics of local energetic interactions modulate domain-swapping and these need to be added to the symmetrized SBMs. We then summarize some general principles of the mechanism of domain-swapping that emerge from the symmetrized SBM simulations. Finally, using our own results, we explore how symmetrized SBMs could be used to design domain-swapping in proteins.
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Affiliation(s)
- Nahren Manuel Mascarenhas
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India.
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16
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Sikosek T, Krobath H, Chan HS. Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches. PLoS Comput Biol 2016; 12:e1004960. [PMID: 27253392 PMCID: PMC4890782 DOI: 10.1371/journal.pcbi.1004960] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 05/04/2016] [Indexed: 11/18/2022] Open
Abstract
Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein’s folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the GA all-α and GB α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between GA and GB. In agreement with experiment, we observe conformational switching from GA to GB upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp GA/GB switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches. The biological functions of globular proteins are intimately related to their folded structures and their associated conformational fluctuations. Evolution of new structures is an important avenue to new functions. Although many mutations do not change the folded state, experiments indicate that a single amino acid substitution can lead to a drastic change in the folded structure. The physics of this switch-like behavior remains to be elucidated. Here we develop a computational model for the relevant physical forces, showing that mutations can lead to new folds by passing through intermediate sequences where the old and new folds occur with varying probabilities. Our approach helps provide a general physical account of conformational switching in evolution and mutational effects on conformational dynamics.
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Affiliation(s)
- Tobias Sikosek
- Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Heinrich Krobath
- Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hue Sun Chan
- Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
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17
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Balabanova L, Golotin V, Podvolotskaya A, Rasskazov V. Genetically modified proteins: functional improvement and chimeragenesis. Bioengineered 2015. [PMID: 26211369 DOI: 10.1080/21655979.2015.1075674] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Abstract
This review focuses on the emerging role of site-specific mutagenesis and chimeragenesis for the functional improvement of proteins in areas where traditional protein engineering methods have been extensively used and practically exhausted. The novel path for the creation of the novel proteins has been created on the farther development of the new structure and sequence optimization algorithms for generating and designing the accurate structure models in result of x-ray crystallography studies of a lot of proteins and their mutant forms. Artificial genetic modifications aim to expand nature's repertoire of biomolecules. One of the most exciting potential results of mutagenesis or chimeragenesis finding could be design of effective diagnostics, bio-therapeutics and biocatalysts. A sampling of recent examples is listed below for the in vivo and in vitro genetically improvement of various binding protein and enzyme functions, with references for more in-depth study provided for the reader's benefit.
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Affiliation(s)
- Larissa Balabanova
- a G.B. Elyakov Pacific Institute of Bioorganic Chemistry; Far Eastern Branch; Russian Academy of Science ; Vladivostok , Russia.,b Far Eastern Federal University ; Vladivostok , Russia
| | - Vasily Golotin
- a G.B. Elyakov Pacific Institute of Bioorganic Chemistry; Far Eastern Branch; Russian Academy of Science ; Vladivostok , Russia.,b Far Eastern Federal University ; Vladivostok , Russia
| | | | - Valery Rasskazov
- a G.B. Elyakov Pacific Institute of Bioorganic Chemistry; Far Eastern Branch; Russian Academy of Science ; Vladivostok , Russia
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Chen T, Chan HS. Native contact density and nonnative hydrophobic effects in the folding of bacterial immunity proteins. PLoS Comput Biol 2015; 11:e1004260. [PMID: 26016652 PMCID: PMC4446218 DOI: 10.1371/journal.pcbi.1004260] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 03/29/2015] [Indexed: 11/18/2022] Open
Abstract
The bacterial colicin-immunity proteins Im7 and Im9 fold by different mechanisms. Experimentally, at pH 7.0 and 10°C, Im7 folds in a three-state manner via an intermediate but Im9 folding is two-state-like. Accordingly, Im7 exhibits a chevron rollover, whereas the chevron arm for Im9 folding is linear. Here we address the biophysical basis of their different behaviors by using native-centric models with and without additional transferrable, sequence-dependent energies. The Im7 chevron rollover is not captured by either a pure native-centric model or a model augmented by nonnative hydrophobic interactions with a uniform strength irrespective of residue type. By contrast, a more realistic nonnative interaction scheme that accounts for the difference in hydrophobicity among residues leads simultaneously to a chevron rollover for Im7 and an essentially linear folding chevron arm for Im9. Hydrophobic residues identified by published experiments to be involved in nonnative interactions during Im7 folding are found to participate in the strongest nonnative contacts in this model. Thus our observations support the experimental perspective that the Im7 folding intermediate is largely underpinned by nonnative interactions involving large hydrophobics. Our simulation suggests further that nonnative effects in Im7 are facilitated by a lower local native contact density relative to that of Im9. In a one-dimensional diffusion picture of Im7 folding with a coordinate- and stability-dependent diffusion coefficient, a significant chevron rollover is consistent with a diffusion coefficient that depends strongly on native stability at the conformational position of the folding intermediate. In order to fold correctly, a globular protein must avoid being trapped in wrong, i.e., nonnative conformations. Thus a biophysical account of how attractive nonnative interactions are bypassed by some amino acid sequences but not others is key to deciphering protein structure and function. We examine two closely related bacterial immunity proteins, Im7 and Im9, that are experimentally known to fold very differently: Whereas Im9 folds directly, Im7 folds through a mispacked conformational intermediate. A simple model we developed accounts for their intriguingly different folding kinetics in terms of a balance between the density of native-promoting contacts and the hydrophobicity of local amino acid sequences. This emergent principle is extensible to other biomolecular recognition processes.
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Affiliation(s)
- Tao Chen
- Departments of Biochemistry, of Molecular Genetics, and of Physics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Hue Sun Chan
- Departments of Biochemistry, of Molecular Genetics, and of Physics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- * E-mail:
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Chen T, Song J, Chan HS. Theoretical perspectives on nonnative interactions and intrinsic disorder in protein folding and binding. Curr Opin Struct Biol 2014; 30:32-42. [PMID: 25544254 DOI: 10.1016/j.sbi.2014.12.002] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 12/02/2014] [Accepted: 12/02/2014] [Indexed: 11/29/2022]
Abstract
The diverse biological functions of intrinsically disordered proteins (IDPs) have markedly raised our appreciation of protein conformational versatility, whereas the existence of energetically favorable yet functional detrimental nonnative interactions underscores the physical limitations of evolutionary optimization. Here we survey recent advances in using biophysical modeling to gain insight into experimentally observed nonnative behaviors and IDP properties. Simulations of IDP interactions to date focus mostly on coupled folding-binding, which follows essentially the same organizing principle as the local-nonlocal coupling mechanism in cooperative folding of monomeric globular proteins. By contrast, more innovative theories of electrostatic and aromatic interactions are needed for the conceptually novel but less-explored 'fuzzy' complexes in which the functionally bound IDPs remain largely disordered.
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Affiliation(s)
- Tao Chen
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
| | - Jianhui Song
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
| | - Hue Sun Chan
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada.
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