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Green biomanufacturing promoted by automatic retrobiosynthesis planning and computational enzyme design. Chin J Chem Eng 2022. [DOI: 10.1016/j.cjche.2021.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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2
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Lin M, Tan J, Xu Z, Huang J, Tian Y, Chen B, Wu Y, Tong Y, Zhu Y. Computational design of enhanced detoxification activity of a zearalenone lactonase from Clonostachys rosea in acidic medium. RSC Adv 2019; 9:31284-31295. [PMID: 35527979 PMCID: PMC9072336 DOI: 10.1039/c9ra04964a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 09/27/2019] [Indexed: 11/21/2022] Open
Abstract
Computational design of pH-activity profiles for enzymes is of great importance in industrial applications. In this research, a computational strategy was developed to engineer the pH-activity profile of a zearalenone lactonase (ZHD101) from Clonostachys rosea to promote its activity in acidic medium. The active site pK a values of ZHD101 were computationally designed by introducing positively charged lysine mutations on the enzyme surface, and the experimental results showed that two variants, M2(D157K) and M9(E171K), increased the catalytic efficiencies of ZHD101 modestly under acidic conditions. Moreover, two variants, M8(D133K) and M9(E171K), were shown to increase the turnover numbers by 2.73 and 2.06-fold with respect to wild type, respectively, though their apparent Michaelis constants were concomitantly increased. These results imply that the active site pK a value change might affect the pH-activity profile of the enzyme. Our computational strategy for pH-activity profile engineering considers protein stability; therefore, limited experimental validation is needed to discover beneficial mutations under shifted pH conditions.
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Affiliation(s)
- Min Lin
- Department of Chemical Engineering, Tsinghua University Beijing 100084 China
| | - Jian Tan
- Nutrition & Health Research Institute, China National Cereals, Oils and Foodstuffs Corporation (COFCO) Beijing 102209 China.,Beijing Key Lab of Nutrition, Health and Food Safety Beijing 102209 China.,Beijing Livestock Products Quality and Safety Source Control Engineering Technology Research Center Beijing 102209 China
| | - Zhaobin Xu
- Department of Chemical Engineering, Tsinghua University Beijing 100084 China
| | - Jin Huang
- Nutrition & Health Research Institute, China National Cereals, Oils and Foodstuffs Corporation (COFCO) Beijing 102209 China.,Beijing Key Lab of Nutrition, Health and Food Safety Beijing 102209 China.,Beijing Livestock Products Quality and Safety Source Control Engineering Technology Research Center Beijing 102209 China
| | - Ye Tian
- Department of Chemical Engineering, Tsinghua University Beijing 100084 China
| | - Bo Chen
- Nutrition & Health Research Institute, China National Cereals, Oils and Foodstuffs Corporation (COFCO) Beijing 102209 China.,Beijing Key Lab of Nutrition, Health and Food Safety Beijing 102209 China.,Beijing Livestock Products Quality and Safety Source Control Engineering Technology Research Center Beijing 102209 China
| | - Yandong Wu
- National Engineering Research Center of Corn Deep Processing Changchun 130033 Jilin China
| | - Yi Tong
- National Engineering Research Center of Corn Deep Processing Changchun 130033 Jilin China
| | - Yushan Zhu
- Department of Chemical Engineering, Tsinghua University Beijing 100084 China .,MOE Key Lab of Industrial Biocatalysis, Tsinghua University Beijing 100084 China
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3
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Xue J, Huang X, Zhu Y. Using molecular dynamics simulations to evaluate active designs of cephradine hydrolase by molecular mechanics/Poisson–Boltzmann surface area and molecular mechanics/generalized Born surface area methods. RSC Adv 2019; 9:13868-13877. [PMID: 35519543 PMCID: PMC9064048 DOI: 10.1039/c9ra02406a] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 04/30/2019] [Indexed: 11/30/2022] Open
Abstract
The poor predictive accuracy of current computational enzyme design methods has led to low success rates of producing highly active variants that target non-natural substrates. In this report, a quantitative assessment approach based on molecular dynamics (MD) simulations was developed to eliminate false-positive enzyme designs at the computational stage. Taking cephradine hydrolase as an example, the apparent Michaelis binding constant (Km) and catalytic efficiency (kcat/Km) of designed variants were correlated with binding free energies and activation energy barriers, respectively, as calculated by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) methods with explicit water considered based on general MD simulation protocols. The correlation results showed that both the MM/GBSA and MM/PBSA methods with a protein dielectric constant (εp = 4) could rank the variants well based on the predicted binding free energies between enzyme and the substrate. Furthermore, the activation energy barriers calculated by the MM/PBSA method with an εp = 24 correlated well with kcat/Km. Thus, false-positive variants obtained by the enzyme design program PRODA were eliminated prior to experimentation. Therefore, MD simulation-based quantitative assessment of designed variants greatly enhanced the predictive accuracy of computational enzyme design tools and should facilitate the construction of artificial enzymes with high catalytic activities toward non-natural substrates. A quantitative assessment method for computational enzyme design was developed to rank the active designs of cephradine hydrolase based on molecular dynamics simulation.![]()
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Affiliation(s)
- Jing Xue
- Department of Chemical Engineering
- Tsinghua University
- Beijing 100084
- China
| | - Xiaoqiang Huang
- Department of Chemical Engineering
- Tsinghua University
- Beijing 100084
- China
| | - Yushan Zhu
- Department of Chemical Engineering
- Tsinghua University
- Beijing 100084
- China
- MOE Key Lab for Industrial Biocatalysis
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4
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Computational design of thermostable mutants for cephalosporin C acylase from Pseudomonas strain SE83. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.05.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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5
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Setiawan D, Brender J, Zhang Y. Recent advances in automated protein design and its future challenges. Expert Opin Drug Discov 2018; 13:587-604. [PMID: 29695210 DOI: 10.1080/17460441.2018.1465922] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered: The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.
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Affiliation(s)
- Dani Setiawan
- a Department of Computational Medicine and Bioinformatics , University of Michigan , Ann Arbor , MI , USA
| | - Jeffrey Brender
- b Radiation Biology Branch , Center for Cancer Research, National Cancer Institute - NIH , Bethesda , MD , USA
| | - Yang Zhang
- a Department of Computational Medicine and Bioinformatics , University of Michigan , Ann Arbor , MI , USA.,c Department of Biological Chemistry , University of Michigan , Ann Arbor , MI , USA
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6
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Computational design of variants for cephalosporin C acylase from Pseudomonas strain N176 with improved stability and activity. Appl Microbiol Biotechnol 2016; 101:621-632. [PMID: 27557716 DOI: 10.1007/s00253-016-7796-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Revised: 07/16/2016] [Accepted: 08/05/2016] [Indexed: 01/06/2023]
Abstract
In this report, redesigning cephalosporin C acylase from the Pseudomonas strain N176 revealed that the loss of stability owing to the introduced mutations at the active site can be recovered by repacking the nearby hydrophobic core regions. Starting from a quadruple mutant M31βF/H57βS/V68βA/H70βS, whose decrease in stability is largely owing to the mutation V68βA at the active site, we employed a computational enzyme design strategy that integrated design both at hydrophobic core regions for stability enhancement and at the active site for activity improvement. Single-point mutations L154βF, Y167βF, L180βF and their combinations L154βF/L180βF and L154βF/Y167βF/L180βF were found to display improved stability and activity. The two-point mutant L154βF/L180βF increased the protein melting temperature (T m) by 11.7 °C and the catalytic efficiency V max/K m by 57 % compared with the values of the starting quadruple mutant. The catalytic efficiency of the resulting sixfold mutant M31βF/H57βS/V68βA/H70βS/L154βF/L180βF is recovered to become comparable to that of the triple mutant M31βF/H57βS/H70βS, but with a higher T m. Further experiments showed that single-point mutations L154βF, L180βF, and their combination contribute no stability enhancement to the triple mutant M31βF/H57βS/H70βS. These results verify that the lost stability because of mutation V68βA at the active site was recovered by introducing mutations L154βF and L180βF at hydrophobic core regions. Importantly, mutation V68βA in the six-residue mutant provides more space to accommodate the bulky side chain of cephalosporin C, which could help in designing cephalosporin C acylase mutants with higher activities and the practical one-step enzymatic route to prepare 7-aminocephalosporanic acid at industrial-scale levels.
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7
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A fast loop-closure algorithm to accelerate residue matching in computational enzyme design. J Mol Model 2016; 22:49. [DOI: 10.1007/s00894-016-2915-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Accepted: 01/11/2016] [Indexed: 01/04/2023]
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8
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Simoncini D, Allouche D, de Givry S, Delmas C, Barbe S, Schiex T. Guaranteed Discrete Energy Optimization on Large Protein Design Problems. J Chem Theory Comput 2015; 11:5980-9. [DOI: 10.1021/acs.jctc.5b00594] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
| | - David Allouche
- INRA MIAT, UR 875, Castanet-Tolosan, 31326 Cedex, France
| | - Simon de Givry
- INRA MIAT, UR 875, Castanet-Tolosan, 31326 Cedex, France
| | - Céline Delmas
- INRA MIAT, UR 875, Castanet-Tolosan, 31326 Cedex, France
| | - Sophie Barbe
- Université de Toulouse; INSA, UPS, INP; LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France
- CNRS, UMR5504, F-31400 Toulouse, France
- INRA, UMR792 Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France
| | - Thomas Schiex
- INRA MIAT, UR 875, Castanet-Tolosan, 31326 Cedex, France
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9
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Tian Y, Huang X, Zhu Y. Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm. J Mol Model 2015; 21:191. [PMID: 26162695 DOI: 10.1007/s00894-015-2742-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2015] [Accepted: 06/24/2015] [Indexed: 01/06/2023]
Abstract
Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.
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Affiliation(s)
- Ye Tian
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, People's Republic of China
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10
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Li Q, Huang X, Zhu Y. Evaluation of active designs of cephalosporin C acylase by molecular dynamics simulation and molecular docking. J Mol Model 2014; 20:2314. [PMID: 24935111 DOI: 10.1007/s00894-014-2314-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Accepted: 05/19/2014] [Indexed: 01/04/2023]
Abstract
Optimization to identify the global minimum energy conformation sequence in in silico enzyme design is computationally non-deterministic polynomial-time (NP)-hard, with the search time growing exponentially as the number of design sites increases. This drawback forces the modeling of protein-ligand systems to adopt discrete amino acid rotamers and ligand conformers, as well as continuum solvent treatment of the environment; however, such compromises produce large numbers of false positives in sequence selection. In this report, cephalosporin acylase, which catalyzes the hydrolytic reaction of cephalosporin C to 7-aminocephalosporanic acid, was used to investigate the dynamic features of active-site-transition-state complex structures using molecular dynamics (MD) simulations to potentially eliminate false positives. The molecular docking between cephalosporin C and wild type acylase N176 and its eight mutants showed that the rate-limiting step in the hydrolytic reaction of cephalosporin C is the acylation process. MD simulations of the active-site-transition-state complex structures of the acylation processes for N176 and its eight mutants showed that the geometrical constraints between catalytic residues and small molecule transition states are always well maintained during the 20 ns simulation for mutants with higher activities, and more hydrogen bonds between binding residues and functional groups of the ligand side chain in the active pocket are formed for mutants with higher activities. The conformations of the ligand transition states were changed greatly after the simulation. This indicates that the hydrogen bond network between the ligand and protein could be improved to enhance the activity of cephalosporin C acylase in subsequent design.
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Affiliation(s)
- Qing Li
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, People's .Republic of China
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11
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Huang X, Han K, Zhu Y. Systematic optimization model and algorithm for binding sequence selection in computational enzyme design. Protein Sci 2013; 22:929-41. [PMID: 23649589 DOI: 10.1002/pro.2275] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2013] [Revised: 03/14/2013] [Accepted: 04/27/2013] [Indexed: 01/04/2023]
Abstract
A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions.
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Affiliation(s)
- Xiaoqiang Huang
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, People's Republic of China
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12
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Huang X, Yang J, Zhu Y. A solvated ligand rotamer approach and its application in computational protein design. J Mol Model 2012. [PMID: 23192355 DOI: 10.1007/s00894-012-1695-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The structure-based design of protein-ligand interfaces with respect to different small molecules is of great significance in the discovery of functional proteins. By statistical analysis of a set of protein-ligand complex structures, it was determined that water-mediated hydrogen bonding at the protein-ligand interface plays a crucial role in governing the binding between the protein and the ligand. Based on the novel statistic results, a solvated ligand rotamer approach was developed to explicitly describe the key water molecules at the protein-ligand interface and a water-mediated hydrogen bonding model was applied in the computational protein design context to complement the continuum solvent model. The solvated ligand rotamer approach produces only one additional solvated rotamer for each rotamer in the ligand rotamer library and does not change the number of side-chain rotamers at each protein design site. This has greatly reduced the total combinatorial number in sequence selection for protein design, and the accuracy of the model was confirmed by two tests. For the water placement test, 61% of the crystal water molecules were predicted correctly in five protein-ligand complex structures. For the sequence recapitulation test, 44.7% of the amino acid identities were recovered using the solvated ligand rotamer approach and the water-mediated hydrogen bonding model, while only 30.4% were recovered when the explicitly bound waters were removed. These results indicated that the developed solvated ligand rotamer approach is promising for functional protein design targeting novel protein-ligand interactions.
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Affiliation(s)
- Xiaoqiang Huang
- Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
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13
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Designing electrostatic interactions in biological systems via charge optimization or combinatorial approaches: insights and challenges with a continuum electrostatic framework. Theor Chem Acc 2012. [DOI: 10.1007/s00214-012-1252-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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14
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Lei Y, Luo W, Zhu Y. A matching algorithm for catalytic residue site selection in computational enzyme design. Protein Sci 2011; 20:1566-75. [PMID: 21714026 DOI: 10.1002/pro.685] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2011] [Accepted: 06/07/2011] [Indexed: 11/07/2022]
Abstract
A loop closure-based sequential algorithm, PRODA_MATCH, was developed to match catalytic residues onto a scaffold for enzyme design in silico. The computational complexity of this algorithm is polynomial with respect to the number of active sites, the number of catalytic residues, and the maximal iteration number of cyclic coordinate descent steps. This matching algorithm is independent of a rotamer library that enables the catalytic residue to take any required conformation during the reaction coordinate. The catalytic geometric parameters defined between functional groups of transition state (TS) and the catalytic residues are continuously optimized to identify the accurate position of the TS. Pseudo-spheres are introduced for surrounding residues, which make the algorithm take binding into account as early as during the matching process. Recapitulation of native catalytic residue sites was used as a benchmark to evaluate the novel algorithm. The calculation results for the test set show that the native catalytic residue sites were successfully identified and ranked within the top 10 designs for 7 of the 10 chemical reactions. This indicates that the matching algorithm has the potential to be used for designing industrial enzymes for desired reactions.
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Affiliation(s)
- Yulin Lei
- Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
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15
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Fung HK, Welsh WJ, Floudas CA. Computational De Novo Peptide and Protein Design: Rigid Templates versus Flexible Templates. Ind Eng Chem Res 2008. [DOI: 10.1021/ie071286k] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Ho Ki Fung
- Department of Chemical Engineering, Princeton University, Princeton, New Jersey 08544-5263, and Department of Pharmacology, University of Medicine & Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School, and the Informatics Institute of UMDNJ, Piscataway, New Jersey 08854
| | - William J. Welsh
- Department of Chemical Engineering, Princeton University, Princeton, New Jersey 08544-5263, and Department of Pharmacology, University of Medicine & Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School, and the Informatics Institute of UMDNJ, Piscataway, New Jersey 08854
| | - Christodoulos A. Floudas
- Department of Chemical Engineering, Princeton University, Princeton, New Jersey 08544-5263, and Department of Pharmacology, University of Medicine & Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School, and the Informatics Institute of UMDNJ, Piscataway, New Jersey 08854
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Mutations affecting the oligomerization interface of G-protein-coupled receptors revealed by a novel de novo protein design framework. Biophys J 2008; 94:2470-81. [PMID: 18178645 DOI: 10.1529/biophysj.107.117622] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Specific functional and pharmacological properties have recently been ascribed to G-protein-coupled receptor (GPCR) dimers/oligomers. Because the association of two identical or two distinct GPCR monomers seems to be required to elicit receptor function, it is necessary to understand the exact nature of this interaction. We present here a novel method for de novo protein design and its application to the prediction of mutations that can stabilize or destabilize a GPCR dimer while maintaining the monomer's native fold. To test the efficacy of this new method, the dimer of the single-spanned transmembrane domain of glycophorin A was used as a model system. Experimental data from mutagenesis of the helix-helix interface are compared with computational predictions at that interface, and the model's results are found to be consistent with the experimental findings. A flexible template was developed for the rhodopsin homodimer at atomic resolution and used to predict sets of three and five mutations. The results are found to be consistent across eight case studies, with favored mutations at each position. Mutation sets predicted to be the most disruptive at the dimerization interface are found to be less specific to the flexible template than sets predicted to be less disruptive.
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