1
|
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]
|
2
|
Tavares D, van der Meer JR. Ribose-Binding Protein Mutants With Improved Interaction Towards the Non-natural Ligand 1,3-Cyclohexanediol. Front Bioeng Biotechnol 2021; 9:705534. [PMID: 34368100 PMCID: PMC8343135 DOI: 10.3389/fbioe.2021.705534] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/29/2021] [Indexed: 01/08/2023] Open
Abstract
Bioreporters consist of genetically modified living organisms that respond to the presence of target chemical compounds by production of an easily measurable signal. The central element in a bioreporter is a sensory protein or aptamer, which, upon ligand binding, modifies expression of the reporter signal protein. A variety of naturally occurring or modified versions of sensory elements has been exploited, but it has proven to be challenging to generate elements that recognize non-natural ligands. Bacterial periplasmic binding proteins have been proposed as a general scaffold to design receptor proteins for non-natural ligands, but despite various efforts, with only limited success. Here, we show how combinations of randomized mutagenesis and reporter screening improved the performance of a set of mutants in the ribose binding protein (RbsB) of Escherichia coli, which had been designed based on computational simulations to bind the non-natural ligand 1,3-cyclohexanediol (13CHD). Randomized mutant libraries were constructed that used the initially designed mutants as scaffolds, which were cloned in an appropriate E. coli bioreporter system and screened for improved induction of the GFPmut2 reporter fluorescence in presence of 1,3-cyclohexanediol. Multiple rounds of library screening, sorting, renewed mutagenesis and screening resulted in 4.5-fold improvement of the response to 1,3-cyclohexanediol and a lower detection limit of 0.25 mM. All observed mutations except one were located outside the direct ligand-binding pocket, suggesting they were compensatory and helping protein folding or functional behavior other than interaction with the ligand. Our results thus demonstrate that combinations of ligand-binding-pocket redesign and randomized mutagenesis can indeed lead to the selection and recovery of periplasmic-binding protein mutants with non-natural compound recognition. However, current lack of understanding of the intermolecular movement and ligand-binding in periplasmic binding proteins such as RbsB are limiting the rational production of further and better sensory mutants.
Collapse
Affiliation(s)
- Diogo Tavares
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | |
Collapse
|
3
|
Mignon D, Druart K, Michael E, Opuu V, Polydorides S, Villa F, Gaillard T, Panel N, Archontis G, Simonson T. Physics-Based Computational Protein Design: An Update. J Phys Chem A 2020; 124:10637-10648. [DOI: 10.1021/acs.jpca.0c07605] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- David Mignon
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Karen Druart
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Eleni Michael
- Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus
| | - Vaitea Opuu
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Savvas Polydorides
- Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus
| | - Francesco Villa
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Thomas Gaillard
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Nicolas Panel
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| | - Georgios Archontis
- Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus
| | - Thomas Simonson
- Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France
| |
Collapse
|
4
|
Huang X, Pearce R, Zhang Y. Toward the Accuracy and Speed of Protein Side-Chain Packing: A Systematic Study on Rotamer Libraries. J Chem Inf Model 2019; 60:410-420. [PMID: 31851497 DOI: 10.1021/acs.jcim.9b00812] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Protein rotamers refer to the conformational isomers taken by the side-chains of amino acids to accommodate specific structural folding environments. Since accurate modeling of atomic interactions is difficult, rotamer information collected from experimentally solved protein structures is often used to guide side-chain packing in protein folding and sequence design studies. Many rotamer libraries have been built in the literature but there is little quantitative guidance on which libraries should be chosen for different structural modeling studies. Here, we performed a comparative study of six widely used rotamer libraries and systematically examined their suitability for protein folding and sequence design in four aspects: (1) side-chain match accuracy, (2) side-chain conformation prediction, (3) de novo protein sequence design, and (4) computational time cost. We demonstrated that, compared to the backbone-dependent rotamer libraries (BBDRLs), the backbone-independent rotamer libraries (BBIRLs) generated conformations that more closely matched the native conformations due to the larger number of rotamers in the local rotamer search spaces. However, more practically, using an optimized physical energy function incorporated into a simulated annealing Monte Carlo searching scheme, we showed that utilization of the BBDRLs could result in higher accuracies in side-chain prediction and higher sequence recapitulation rates in protein design experiments. Detailed data analyses showed that the major advantage of BBDRLs lies in the energy term derived from the rotamer probabilities that are associated with the individual backbone torsion angle subspaces. This term is important for distinguishing between amino acid identities as well as the rotamer conformations of an amino acid. Meanwhile, the backbone torsion angle subspace-specific rotamer search drastically speeds up the searching time, despite the significantly larger number of total rotamers in the BBDRLs. These results should provide important guidance for the development and selection of rotamer libraries for practical protein design and structure prediction studies.
Collapse
|
5
|
Tavares D, Reimer A, Roy S, Joublin A, Sentchilo V, van der Meer JR. Computational redesign of the Escherichia coli ribose-binding protein ligand binding pocket for 1,3-cyclohexanediol and cyclohexanol. Sci Rep 2019; 9:16940. [PMID: 31729460 PMCID: PMC6858440 DOI: 10.1038/s41598-019-53507-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 10/31/2019] [Indexed: 01/24/2023] Open
Abstract
Bacterial periplasmic-binding proteins have been acclaimed as general biosensing platform, but their range of natural ligands is too limited for optimal development of chemical compound detection. Computational redesign of the ligand-binding pocket of periplasmic-binding proteins may yield variants with new properties, but, despite earlier claims, genuine changes of specificity to non-natural ligands have so far not been achieved. In order to better understand the reasons of such limited success, we revisited here the Escherichia coli RbsB ribose-binding protein, aiming to achieve perceptible transition from ribose to structurally related chemical ligands 1,3-cyclohexanediol and cyclohexanol. Combinations of mutations were computationally predicted for nine residues in the RbsB binding pocket, then synthesized and tested in an E. coli reporter chassis. Two million variants were screened in a microcolony-in-bead fluorescence-assisted sorting procedure, which yielded six mutants no longer responsive to ribose but with 1.2-1.5 times induction in presence of 1 mM 1,3-cyclohexanediol, one of which responded to cyclohexanol as well. Isothermal microcalorimetry confirmed 1,3-cyclohexanediol binding, although only two mutant proteins were sufficiently stable upon purification. Circular dichroism spectroscopy indicated discernable structural differences between these two mutant proteins and wild-type RbsB. This and further quantification of periplasmic-space abundance suggested most mutants to be prone to misfolding and/or with defects in translocation compared to wild-type. Our results thus affirm that computational design and library screening can yield RbsB mutants with recognition of non-natural but structurally similar ligands. The inherent arisal of protein instability or misfolding concomitant with designed altered ligand-binding pockets should be overcome by new experimental strategies or by improved future protein design algorithms.
Collapse
Affiliation(s)
- Diogo Tavares
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Artur Reimer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
- Novartis, 4056, Basel, Switzerland
| | - Shantanu Roy
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Aurélie Joublin
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Vladimir Sentchilo
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Jan Roelof van der Meer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
| |
Collapse
|
6
|
Chowdhury R, Maranas CD. From directed evolution to computational enzyme engineering—A review. AIChE J 2019. [DOI: 10.1002/aic.16847] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Ratul Chowdhury
- Department of Chemical Engineering The Pennsylvania State University University Park Pennsylvania
| | - Costas D. Maranas
- Department of Chemical Engineering The Pennsylvania State University University Park Pennsylvania
| |
Collapse
|
7
|
Löffler P, Schmitz S, Hupfeld E, Sterner R, Merkl R. Rosetta:MSF: a modular framework for multi-state computational protein design. PLoS Comput Biol 2017; 13:e1005600. [PMID: 28604768 PMCID: PMC5484525 DOI: 10.1371/journal.pcbi.1005600] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Revised: 06/26/2017] [Accepted: 05/27/2017] [Indexed: 12/20/2022] Open
Abstract
Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design. Protein engineering, i. e. the targeted modification or design of proteins has tremendous potential for medical and industrial applications. One generally applicable strategy for protein engineering is rational protein design: based on detailed knowledge of structure and function, computer programs like Rosetta propose the sequence of a protein possessing the desired properties. So far, most computer protocols have used rigid structures for design, which is a simplification because a protein’s structure is more accurately specified by a conformational ensemble. We have now implemented a framework for computational protein design that allows certain design protocols of Rosetta to make use of multiple design states like structural ensembles. An in silico assessment simulating ligand-binding design showed that this new approach generates more reliably native-like sequences than a single-state approach. As a proof-of-concept, we introduced de novo retro-aldolase activity into a scaffold protein and characterized nine variants experimentally, all of which were catalytically active.
Collapse
Affiliation(s)
- Patrick Löffler
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany
| | - Samuel Schmitz
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany
| | - Enrico Hupfeld
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany
| | - Reinhard Sterner
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany
| | - Rainer Merkl
- Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany
- * E-mail:
| |
Collapse
|
8
|
Small Molecule-Induced Domain Swapping as a Mechanism for Controlling Protein Function and Assembly. Sci Rep 2017; 7:44388. [PMID: 28287617 PMCID: PMC5347425 DOI: 10.1038/srep44388] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 02/07/2017] [Indexed: 12/22/2022] Open
Abstract
Domain swapping is the process by which identical proteins exchange reciprocal segments to generate dimers. Here we introduce induced domain swapping (INDOS) as a mechanism for regulating protein function. INDOS employs a modular design consisting of the fusion of two proteins: a recognition protein that binds a triggering molecule, and a target protein that undergoes a domain swap in response to binding of the triggering ligand. The recognition protein (FK506 binding protein) is inserted into functionally-inactivated point mutants of two target proteins (staphylococcal nuclease and ribose binding protein). Binding of FK506 to the FKBP domain causes the target domain to first unfold, then refold via domain swap. The inactivating mutations become ‘swapped out’ in the dimer, increasing nuclease and ribose binding activities by 100-fold and 15-fold, respectively, restoring them to near wild-type values. INDOS is intended to convert an arbitrary protein into a functional switch, and is the first example of rational design in which a small molecule is used to trigger protein domain swapping and subsequent activation of biological function.
Collapse
|
9
|
Ha JH, Karchin JM, Walker-Kopp N, Castañeda CA, Loh SN. Engineered Domain Swapping as an On/Off Switch for Protein Function. ACTA ACUST UNITED AC 2016; 22:1384-93. [PMID: 26496687 DOI: 10.1016/j.chembiol.2015.09.007] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 09/01/2015] [Accepted: 09/02/2015] [Indexed: 11/25/2022]
Abstract
Domain swapping occurs when identical proteins exchange segments in reciprocal fashion. Natural swapping mechanisms remain poorly understood, and engineered swapping has the potential for creating self-assembling biomaterials that encode for emergent functions. We demonstrate that induced swapping can be used to regulate the function of a target protein. Swapping is triggered by inserting a "lever" protein (ubiquitin) into one of four loops of the ribose binding protein (RBP) target. The lever splits the target, forcing RBP to refold in trans to generate swapped oligomers. Identical RBP-ubiquitin fusions form homo-swapped complexes with the ubiquitin domain acting as the hinge. Surprisingly, some pairs of non-identical fusions swap more efficiently with each other than they do with themselves. Nuclear magnetic resonance experiments reveal that the hinge of these hetero-swapped complexes maps to a region of RBP distant from both ubiquitins. This design is expected to be applicable to other proteins to convert them into functional switches.
Collapse
Affiliation(s)
- Jeung-Hoi Ha
- Department of Biochemistry and Molecular Biology, State University of New York Upstate Medical University, 750 East Adams Street, Syracuse, NY 13210, USA
| | - Joshua M Karchin
- Department of Biochemistry and Molecular Biology, State University of New York Upstate Medical University, 750 East Adams Street, Syracuse, NY 13210, USA
| | - Nancy Walker-Kopp
- Department of Biochemistry and Molecular Biology, State University of New York Upstate Medical University, 750 East Adams Street, Syracuse, NY 13210, USA
| | - Carlos A Castañeda
- Departments of Biology and Chemistry, Syracuse University, 111 College Place, Syracuse, NY 13244, USA
| | - Stewart N Loh
- Department of Biochemistry and Molecular Biology, State University of New York Upstate Medical University, 750 East Adams Street, Syracuse, NY 13210, USA.
| |
Collapse
|
10
|
Druart K, Palmai Z, Omarjee E, Simonson T. Protein:Ligand binding free energies: A stringent test for computational protein design. J Comput Chem 2015; 37:404-15. [PMID: 26503829 DOI: 10.1002/jcc.24230] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Revised: 10/01/2015] [Accepted: 10/02/2015] [Indexed: 01/29/2023]
Abstract
A computational protein design method is extended to allow Monte Carlo simulations where two ligands are titrated into a protein binding pocket, yielding binding free energy differences. These provide a stringent test of the physical model, including the energy surface and sidechain rotamer definition. As a test, we consider tyrosyl-tRNA synthetase (TyrRS), which has been extensively redesigned experimentally. We consider its specificity for its substrate l-tyrosine (l-Tyr), compared to the analogs d-Tyr, p-acetyl-, and p-azido-phenylalanine (ac-Phe, az-Phe). We simulate l- and d-Tyr binding to TyrRS and six mutants, and compare the structures and binding free energies to a more rigorous "MD/GBSA" procedure: molecular dynamics with explicit solvent for structures and a Generalized Born + Surface Area model for binding free energies. Next, we consider l-Tyr, ac- and az-Phe binding to six other TyrRS variants. The titration results are sensitive to the precise rotamer definition, which involves a short energy minimization for each sidechain pair to help relax bad contacts induced by the discrete rotamer set. However, when designed mutant structures are rescored with a standard GBSA energy model, results agree well with the more rigorous MD/GBSA. As a third test, we redesign three amino acid positions in the substrate coordination sphere, with either l-Tyr or d-Tyr as the ligand. For two, we obtain good agreement with experiment, recovering the wildtype residue when l-Tyr is the ligand and a d-Tyr specific mutant when d-Tyr is the ligand. For the third, we recover His with either ligand, instead of wildtype Gln.
Collapse
Affiliation(s)
- Karen Druart
- Laboratoire De Biochimie (UMR CNRS 7654), Department of Biology, Ecole Polytechnique, Palaiseau, France
| | - Zoltan Palmai
- Laboratoire De Biochimie (UMR CNRS 7654), Department of Biology, Ecole Polytechnique, Palaiseau, France
| | - Eyaz Omarjee
- Laboratoire De Biochimie (UMR CNRS 7654), Department of Biology, Ecole Polytechnique, Palaiseau, France
| | - Thomas Simonson
- Laboratoire De Biochimie (UMR CNRS 7654), Department of Biology, Ecole Polytechnique, Palaiseau, France
| |
Collapse
|
11
|
Tobin PH, Richards DH, Callender RA, Wilson CJ. Protein engineering: a new frontier for biological therapeutics. Curr Drug Metab 2015; 15:743-56. [PMID: 25495737 DOI: 10.2174/1389200216666141208151524] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Revised: 11/27/2014] [Accepted: 12/07/2014] [Indexed: 12/14/2022]
Abstract
Protein engineering holds the potential to transform the metabolic drug landscape through the development of smart, stimulusresponsive drug systems. Protein therapeutics are a rapidly expanding segment of Food and Drug Administration approved drugs that will improve clinical outcomes over the long run. Engineering of protein therapeutics is still in its infancy, but recent general advances in protein engineering capabilities are being leveraged to yield improved control over both pharmacokinetics and pharmacodynamics. Stimulus- responsive protein therapeutics are drugs which have been designed to be metabolized under targeted conditions. Protein engineering is being utilized to develop tailored smart therapeutics with biochemical logic. This review focuses on applications of targeted drug neutralization, stimulus-responsive engineered protein prodrugs, and emerging multicomponent smart drug systems (e.g., antibody-drug conjugates, responsive engineered zymogens, prospective biochemical logic smart drug systems, drug buffers, and network medicine applications).
Collapse
Affiliation(s)
| | | | | | - Corey J Wilson
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520-8286, USA.
| |
Collapse
|
12
|
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.
Collapse
Affiliation(s)
- Ye Tian
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, People's Republic of China
| | | | | |
Collapse
|
13
|
Roberts KE, Donald BR. Improved energy bound accuracy enhances the efficiency of continuous protein design. Proteins 2015; 83:1151-64. [PMID: 25846627 DOI: 10.1002/prot.24808] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 03/24/2015] [Indexed: 11/07/2022]
Abstract
Flexibility and dynamics are important for protein function and a protein's ability to accommodate amino acid substitutions. However, when computational protein design algorithms search over protein structures, the allowed flexibility is often reduced to a relatively small set of discrete side-chain and backbone conformations. While simplifications in scoring functions and protein flexibility are currently necessary to computationally search the vast protein sequence and conformational space, a rigid representation of a protein causes the search to become brittle and miss low-energy structures. Continuous rotamers more closely represent the allowed movement of a side chain within its torsional well and have been successfully incorporated into the protein design framework to design biomedically relevant protein systems. The use of continuous rotamers in protein design enables algorithms to search a larger conformational space than previously possible, but adds additional complexity to the design search. To design large, complex systems with continuous rotamers, new algorithms are needed to increase the efficiency of the search. We present two methods, PartCR and HOT, that greatly increase the speed and efficiency of protein design with continuous rotamers. These methods specifically target the large errors in energetic terms that are used to bound pairwise energies during the design search. By tightening the energy bounds, additional pruning of the conformation space can be achieved, and the number of conformations that must be enumerated to find the global minimum energy conformation is greatly reduced.
Collapse
Affiliation(s)
- Kyle E Roberts
- Department of Computer Science, Duke University, Durham, North Carolina
| | - Bruce R Donald
- Department of Computer Science, Duke University, Durham, North Carolina.,Department of Biochemistry, Duke University Medical Center, Durham, North Carolina.,Department of Chemistry, Duke University, Durham, North Carolina
| |
Collapse
|
14
|
Reimer A, Yagur-Kroll S, Belkin S, Roy S, van der Meer JR. Escherichia [corrected] coli ribose binding protein based bioreporters revisited. Sci Rep 2014; 4:5626. [PMID: 25005019 PMCID: PMC4088097 DOI: 10.1038/srep05626] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Accepted: 06/17/2014] [Indexed: 01/09/2023] Open
Abstract
Bioreporter bacteria, i.e., strains engineered to respond to chemical exposure by production of reporter proteins, have attracted wide interest because of their potential to offer cheap and simple alternative analytics for specified compounds or conditions. Bioreporter construction has mostly exploited the natural variation of sensory proteins, but it has been proposed that computational design of new substrate binding properties could lead to completely novel detection specificities at very low affinities. Here we reconstruct a bioreporter system based on the native Escherichia coli ribose binding protein RbsB and one of its computationally designed variants, reported to be capable of binding 2,4,6-trinitrotoluene (TNT). Our results show in vivo reporter induction at 50 nM ribose, and a 125 nM affinity constant for in vitro ribose binding to RbsB. In contrast, the purified published TNT-binding variant did not bind TNT nor did TNT cause induction of the E. coli reporter system.
Collapse
Affiliation(s)
- Artur Reimer
- Department of Fundamental Microbiology, University of Lausanne, Bâtiment Biophore, Quartier UNIL-Sorge 1015 Lausanne, Switzerland
| | - Sharon Yagur-Kroll
- Department of Plant and Environmental Sciences, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Shimshon Belkin
- Department of Plant and Environmental Sciences, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Shantanu Roy
- Department of Fundamental Microbiology, University of Lausanne, Bâtiment Biophore, Quartier UNIL-Sorge 1015 Lausanne, Switzerland
| | - Jan Roelof van der Meer
- Department of Fundamental Microbiology, University of Lausanne, Bâtiment Biophore, Quartier UNIL-Sorge 1015 Lausanne, Switzerland
| |
Collapse
|
15
|
An accurate binding interaction model in de novo computational protein design of interactions: If you build it, they will bind. J Struct Biol 2014; 185:136-46. [DOI: 10.1016/j.jsb.2013.03.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2012] [Revised: 03/15/2013] [Accepted: 03/21/2013] [Indexed: 01/07/2023]
|
16
|
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.
Collapse
Affiliation(s)
- Xiaoqiang Huang
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, People's Republic of China
| | | | | |
Collapse
|
17
|
Wijma HJ, Janssen DB. Computational design gains momentum in enzyme catalysis engineering. FEBS J 2013; 280:2948-60. [DOI: 10.1111/febs.12324] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Revised: 04/19/2013] [Accepted: 04/24/2013] [Indexed: 01/19/2023]
Affiliation(s)
- Hein J. Wijma
- Department of Biochemistry; Groningen Biomolecular Sciences and Biotechnology Institute; University of Groningen; The Netherlands
| | - Dick B. Janssen
- Department of Biochemistry; Groningen Biomolecular Sciences and Biotechnology Institute; University of Groningen; The Netherlands
| |
Collapse
|
18
|
Kiss G, Çelebi-Ölçüm N, Moretti R, Baker D, Houk KN. Computational enzyme design. Angew Chem Int Ed Engl 2013; 52:5700-25. [PMID: 23526810 DOI: 10.1002/anie.201204077] [Citation(s) in RCA: 370] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Indexed: 11/07/2022]
Abstract
Recent developments in computational chemistry and biology have come together in the "inside-out" approach to enzyme engineering. Proteins have been designed to catalyze reactions not previously accelerated in nature. Some of these proteins fold and act as catalysts, but the success rate is still low. The achievements and limitations of the current technology are highlighted and contrasted to other protein engineering techniques. On its own, computational "inside-out" design can lead to the production of catalytically active and selective proteins, but their kinetic performances fall short of natural enzymes. When combined with directed evolution, molecular dynamics simulations, and crowd-sourced structure-prediction approaches, however, computational designs can be significantly improved in terms of binding, turnover, and thermal stability.
Collapse
Affiliation(s)
- Gert Kiss
- Department of Chemistry and Biochemistry, University of California, Los Angeles, 607 Charles E. Young Dr. East, Los Angeles, CA 90095, USA
| | | | | | | | | |
Collapse
|
19
|
Kiss G, Çelebi-Ölçüm N, Moretti R, Baker D, Houk KN. Computerbasiertes Enzymdesign. Angew Chem Int Ed Engl 2013. [DOI: 10.1002/ange.201204077] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
20
|
Ha JH, Shinsky SA, Loh SN. Stepwise conversion of a binding protein to a fluorescent switch: application to Thermoanaerobacter tengcongensis ribose binding protein. Biochemistry 2013; 52:600-12. [PMID: 23302025 DOI: 10.1021/bi301105u] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Alternate frame folding (AFF) is a protein engineering methodology the purpose of which is to convert an ordinary binding protein into a molecular switch. The AFF modification entails duplicating an amino- or carboxy-terminal segment of the protein and appending it to the opposite end of the molecule. This duplication allows the protein to interconvert, in a ligand-dependent fashion, between two mutually exclusive native folds: the wild-type structure and a circularly permuted form. The fold shift can be detected by placement of extrinsic fluorophores at sites sensitive to the engineered conformational change. Here, we apply the AFF mechanism to create several ribose-sensing proteins derived from Thermoanaerobacter tengcongensis ribose binding protein. Our purpose is to systematically explore the parameters of the AFF design. These considerations include the site of circular permutation, the length and location of the duplicated segment, thermodynamic and kinetic optimization of the switching mechanism, and placement of extrinsic fluorophores. Three of the four AFF variants created here undergo the expected conformational shift and exhibit a ribose-dependent fluorescence change. The fourth construct fails to switch folds upon addition of ribose, likely because the circularly permuted form folds much more slowly than the nonpermuted form. This disparity apparently introduces a kinetic barrier that partitions the refolding molecules to the nonpermuted structure. The results of this study serve as a guideline for applying the AFF modification to other proteins of biomedical, diagnostic, and industrial interest.
Collapse
Affiliation(s)
- Jeung-Hoi Ha
- Department of Biochemistry and Molecular Biology, State University of New York Upstate Medical University, 750 East Adams Street, Syracuse, NY 13210, USA
| | | | | |
Collapse
|
21
|
Malisi C, Schumann M, Toussaint NC, Kageyama J, Kohlbacher O, Höcker B. Binding pocket optimization by computational protein design. PLoS One 2012; 7:e52505. [PMID: 23300688 PMCID: PMC3531388 DOI: 10.1371/journal.pone.0052505] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2012] [Accepted: 11/14/2012] [Indexed: 01/19/2023] Open
Abstract
Engineering specific interactions between proteins and small molecules is extremely useful for biological studies, as these interactions are essential for molecular recognition. Furthermore, many biotechnological applications are made possible by such an engineering approach, ranging from biosensors to the design of custom enzyme catalysts. Here, we present a novel method for the computational design of protein-small ligand binding named PocketOptimizer. The program can be used to modify protein binding pocket residues to improve or establish binding of a small molecule. It is a modular pipeline based on a number of customizable molecular modeling tools to predict mutations that alter the affinity of a target protein to its ligand. At its heart it uses a receptor-ligand scoring function to estimate the binding free energy between protein and ligand. We compiled a benchmark set that we used to systematically assess the performance of our method. It consists of proteins for which mutational variants with different binding affinities for their ligands and experimentally determined structures exist. Within this test set PocketOptimizer correctly predicts the mutant with the higher affinity in about 69% of the cases. A detailed analysis of the results reveals that the strengths of PocketOptimizer lie in the correct introduction of stabilizing hydrogen bonds to the ligand, as well as in the improved geometric complemetarity between ligand and binding pocket. Apart from the novel method for binding pocket design we also introduce a much needed benchmark data set for the comparison of affinities of mutant binding pockets, and that we use to asses programs for in silico design of ligand binding.
Collapse
Affiliation(s)
- Christoph Malisi
- Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Marcel Schumann
- Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Nora C. Toussaint
- Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Jorge Kageyama
- Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Oliver Kohlbacher
- Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Birte Höcker
- Max Planck Institute for Developmental Biology, Tübingen, Germany
- * E-mail:
| |
Collapse
|
22
|
Davey JA, Chica RA. Multistate approaches in computational protein design. Protein Sci 2012; 21:1241-52. [PMID: 22811394 DOI: 10.1002/pro.2128] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2012] [Revised: 07/04/2012] [Accepted: 07/12/2012] [Indexed: 11/10/2022]
Abstract
Computational protein design (CPD) is a useful tool for protein engineers. It has been successfully applied towards the creation of proteins with increased thermostability, improved binding affinity, novel enzymatic activity, and altered ligand specificity. Traditionally, CPD calculations search and rank sequences using a single fixed protein backbone template in an approach referred to as single-state design (SSD). While SSD has enjoyed considerable success, certain design objectives require the explicit consideration of multiple conformational and/or chemical states. Cases where a "multistate" approach may be advantageous over the SSD approach include designing conformational changes into proteins, using native ensembles to mimic backbone flexibility, and designing ligand or oligomeric association specificities. These design objectives can be efficiently tackled using multistate design (MSD), an emerging methodology in CPD that considers any number of protein conformational or chemical states as inputs instead of a single protein backbone template, as in SSD. In this review article, recent examples of the successful design of a desired property into proteins using MSD are described. These studies employing MSD are divided into two categories--those that utilized multiple conformational states, and those that utilized multiple chemical states. In addition, the scoring of competing states during negative design is discussed as a current challenge for MSD.
Collapse
Affiliation(s)
- James A Davey
- Department of Chemistry, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | | |
Collapse
|
23
|
Lu WW, Huang RB, Wei YT, Meng JZ, Du LQ, Du QS. Statistical energy potential: reduced representation of Dehouck–Gilis–Rooman function by selecting against decoy datasets. Amino Acids 2012; 42:2353-61. [DOI: 10.1007/s00726-011-0977-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2010] [Accepted: 07/06/2011] [Indexed: 11/24/2022]
|
24
|
Li X, Fu Z, Merz KM. QM/MM refinement and analysis of protein bound retinoic acid. J Comput Chem 2012; 33:301-10. [PMID: 22108894 PMCID: PMC3240731 DOI: 10.1002/jcc.21978] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2011] [Revised: 09/13/2011] [Accepted: 09/28/2011] [Indexed: 11/12/2022]
Abstract
Retinoic acid (RA) is a vitamin A derivative, which modifies the appearance of fine wrinkles and roughness of facial skin and treats acne and activates gene transcription by binding to heterodimers of the retinoic acid receptor (RAR) and the retinoic X receptor (RXR). There are series of protein bound RA complexes available in the protein databank (PDB), which provides a broad range of information about the different bioactive conformations of RA. To gain further insights into the observed bioactive RA conformations we applied quantum mechanic (QM)/molecular mechanic (MM) approaches to re-refine the available RA protein-ligand complexes. MP2 complete basis set (CBS) extrapolations single energy calculations are also carried out for both the experimental conformations and QM optimized geometries of RA in the gas as well as solution phase. The results demonstrate that the re-refined structures show better geometries for RA than seen in the originally deposited PDB structures through the use of QMs for the ligand in the X-ray refinement procedure. QM/MM re-refined conformations also reduced the computed strain energies found in the deposited crystal conformations for RA. Finally, the dependence of ligand strain on resolution is analyzed. It is shown that ligand strain is not converged in our calculations and is likely an artifact of the typical resolutions employed to study protein-ligand complexes.
Collapse
Affiliation(s)
- Xue Li
- Department of Chemistry, Quantum Theory Project, University of Florida, Gainesville, Florida 32611, USA
| | | | | |
Collapse
|
25
|
Altshuler EP, Serebryanaya DV, Katrukha AG. Generation of recombinant antibodies and means for increasing their affinity. BIOCHEMISTRY (MOSCOW) 2011; 75:1584-605. [PMID: 21417996 DOI: 10.1134/s0006297910130067] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Highly specific interaction with foreign molecules is a unique feature of antibodies. Since 1975, when Keller and Milstein proposed the method of hybridoma technology and prepared mouse monoclonal antibodies, many antibodies specific to various antigens have been obtained. Recent development of methods for preparation of recombinant DNA libraries and in silico bioinformatics approaches for protein structure analysis makes possible antibody preparation using gene engineering approaches. The development of gene engineering methods allowed creating recombinant antibodies and improving characteristics of existing antibodies; this significantly extends the applicability of antibodies. By modifying biochemical and immunochemical properties of antibodies by changing their amino acid sequences it is possible to create antibodies with properties optimal for certain tasks. For example, application of recombinant technologies resulted in antibody preparation of high affinity significantly exceeding the initial affinity of natural antibodies. In this review we summarize information about the structure, modes of preparation, and application of recombinant antibodies and their fragments and also consider the main approaches used to increase antibody affinity.
Collapse
Affiliation(s)
- E P Altshuler
- Department of Biochemistry, Faculty of Biology, Lomonosov Moscow State University, Russia
| | | | | |
Collapse
|
26
|
Polydorides S, Amara N, Aubard C, Plateau P, Simonson T, Archontis G. Computational protein design with a generalized Born solvent model: application to Asparaginyl-tRNA synthetase. Proteins 2011; 79:3448-68. [PMID: 21563215 DOI: 10.1002/prot.23042] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2010] [Revised: 02/25/2011] [Accepted: 03/03/2011] [Indexed: 12/13/2022]
Abstract
Computational Protein Design (CPD) is a promising method for high throughput protein and ligand mutagenesis. Recently, we developed a CPD method that used a polar-hydrogen energy function for protein interactions and a Coulomb/Accessible Surface Area (CASA) model for solvent effects. We applied this method to engineer aspartyl-adenylate (AspAMP) specificity into Asparaginyl-tRNA synthetase (AsnRS), whose substrate is asparaginyl-adenylate (AsnAMP). Here, we implement a more accurate function, with an all-atom energy for protein interactions and a residue-pairwise generalized Born model for solvent effects. As a first test, we compute aminoacid affinities for several point mutants of Aspartyl-tRNA synthetase (AspRS) and Tyrosyl-tRNA synthetase and stability changes for three helical peptides and compare with experiment. As a second test, we readdress the problem of AsnRS aminoacid engineering. We compare three design criteria, which optimize the folding free-energy, the absolute AspAMP affinity, and the relative (AspAMP-AsnAMP) affinity. The sequences and conformations are improved with respect to our previous, polar-hydrogen/CASA study: For several designed complexes, the AspAMP carboxylate forms three interactions with a conserved arginine and a designed lysine, as in the active site of the AspRS:AspAMP complex. The conformations and interactions are well maintained in molecular dynamics simulations and the sequences have an inverted specificity, favoring AspAMP over AsnAMP. The method is not fully successful, since experimental measurements with the seven most promising sequences show that they do not catalyze at a detectable level the adenylation of Asp (or Asn) with ATP. This may be due to weak AspAMP binding and/or disruption of transition-state stabilization.
Collapse
|
27
|
Morin A, Meiler J, Mizoue LS. Computational design of protein-ligand interfaces: potential in therapeutic development. Trends Biotechnol 2011; 29:159-66. [PMID: 21295366 DOI: 10.1016/j.tibtech.2011.01.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2010] [Revised: 12/22/2010] [Accepted: 01/05/2011] [Indexed: 01/16/2023]
Abstract
Computational design of protein-ligand interfaces finds optimal amino acid sequences within a small-molecule binding site of a protein for tight binding of a specific small molecule. It requires a search algorithm that can rapidly sample the vast sequence and conformational space, and a scoring function that can identify low energy designs. This review focuses on recent advances in computational design methods and their application to protein-small molecule binding sites. Strategies for increasing affinity, altering specificity, creating broad-spectrum binding, and building novel enzymes from scratch are described. Future prospects for applications in drug development are discussed, including limitations that will need to be overcome to achieve computational design of protein therapeutics with novel modes of action.
Collapse
Affiliation(s)
- Andrew Morin
- Departments of Chemistry, Pharmacology, and Biomedical Informatics, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, TN 37235, USA
| | | | | |
Collapse
|
28
|
Zheng Z, Dutton PL, Gunner MR. The measured and calculated affinity of methyl- and methoxy-substituted benzoquinones for the Q(A) site of bacterial reaction centers. Proteins 2010; 78:2638-54. [PMID: 20607696 DOI: 10.1002/prot.22779] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Quinones play important roles in mitochondrial and photosynthetic energy conversion acting as intramembrane, mobile electron, and proton carriers between catalytic sites in various electron transfer proteins. They display different affinity, selectivity, functionality, and exchange dynamics in different binding sites. The computational analysis of quinone binding sheds light on the requirements for quinone affinity and specificity. The affinities of 10 oxidized, neutral benzoquinones were measured for the high affinity Q(A) site in the detergent-solubilized Rhodobacter sphaeroides bacterial photosynthetic reaction center. Multiconformation Continuum Electrostatics was then used to calculate their relative binding free energies by grand canonical Monte Carlo sampling with a rigid protein backbone, flexible ligand, and side chain positions and protonation states. Van der Waals and torsion energies, Poisson-Boltzmann continuum electrostatics, and accessible surface area-dependent ligand-solvent interactions are considered. An initial, single cycle of GROMACS backbone optimization improves the match with experiment as do coupled-ligand and side-chain motions. The calculations match experiment with an root mean square deviation (RMSD) of 2.29 and a slope of 1.28. The affinities are dominated by favorable protein-ligand van der Waals rather than electrostatic interactions. Each quinone appears in a closely clustered set of positions. Methyl and methoxy groups move into the same positions as found for the native quinone. Difficulties putting methyls into methoxy sites are observed. Calculations using a solvent-accessible surface area-dependent implicit van der Waals interaction smoothed out small clashes, providing a better match to experiment with a RMSD of 0.77 and a slope of 0.97.
Collapse
Affiliation(s)
- Zhong Zheng
- Department of Physics, City College of New York, New York, New York 10031, USA
| | | | | |
Collapse
|
29
|
Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles. Proc Natl Acad Sci U S A 2010; 107:19838-43. [PMID: 21045132 DOI: 10.1073/pnas.1012985107] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology.
Collapse
|
30
|
Lassila JK. Conformational diversity and computational enzyme design. Curr Opin Chem Biol 2010; 14:676-82. [PMID: 20829099 PMCID: PMC2953567 DOI: 10.1016/j.cbpa.2010.08.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2010] [Revised: 08/06/2010] [Accepted: 08/06/2010] [Indexed: 11/22/2022]
Abstract
The application of computational protein design methods to the design of enzyme active sites offers potential routes to new catalysts and new reaction specificities. Computational design methods have typically treated the protein backbone as a rigid structure for the sake of computational tractability. However, this fixed-backbone approximation introduces its own special challenges for enzyme design and it contrasts with an emerging picture of natural enzymes as dynamic ensembles with multiple conformations and motions throughout a reaction cycle. This review considers the impact of conformational variation and dynamics on computational enzyme design and it highlights new approaches to addressing protein conformational diversity in enzyme design including recent advances in multi-state design, backbone flexibility, and computational library design.
Collapse
Affiliation(s)
- Jonathan K Lassila
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA.
| |
Collapse
|
31
|
Abstract
A long-standing goal of computational protein design is to create proteins similar to those found in Nature. One motivation is to harness the exquisite functional capabilities of proteins for our own purposes. The extent of similarity between designed and natural proteins also reports on how faithfully our models represent the selective pressures that determine protein sequences. As the field of protein design shifts emphasis from reproducing native-like protein structure to function, it has become important that these models treat the notion of specificity in molecular interactions. Although specificity may, in some cases, be achieved by optimization of a desired protein in isolation, methods have been developed to address directly the desire for proteins that exhibit specific functions and interactions.
Collapse
Affiliation(s)
- James J Havranek
- Department of Genetics, Washington University School of Medicine, St Louis, Missouri 63110, USA.
| |
Collapse
|
32
|
Lopes A, Schmidt Am Busch M, Simonson T. Computational design of protein-ligand binding: modifying the specificity of asparaginyl-tRNA synthetase. J Comput Chem 2010; 31:1273-86. [PMID: 19862811 DOI: 10.1002/jcc.21414] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
A method for computational design of protein-ligand interactions is implemented and tested on the asparaginyl- and aspartyl-tRNA synthetase enzymes (AsnRS, AspRS). The substrate specificity of these enzymes is crucial for the accurate translation of the genetic code. The method relies on a molecular mechanics energy function and a simple, continuum electrostatic, implicit solvent model. As test calculations, we first compute AspRS-substrate binding free energy changes due to nine point mutations, for which experimental data are available; we also perform large-scale redesign of the entire active site of each enzyme (40 amino acids) and compare to experimental sequences. We then apply the method to engineer an increased binding of aspartyl-adenylate (AspAMP) into AsnRS. Mutants are obtained using several directed evolution protocols, where four or five amino acid positions in the active site are randomized. Promising mutants are subjected to molecular dynamics simulations; Poisson-Boltzmann calculations provide an estimate of the corresponding, AspAMP, binding free energy changes, relative to the native AsnRS. Several of the mutants are predicted to have an inverted binding specificity, preferring to bind AspAMP rather than the natural substrate, AsnAMP. The computed binding affinities are significantly weaker than the native, AsnRS:AsnAMP affinity, and in most cases, the active site structure is significantly changed, compared to the native complex. This almost certainly precludes catalytic activity. One of the designed sequences has a higher affinity and more native-like structure and may represent a valid candidate for Asp activity.
Collapse
Affiliation(s)
- Anne Lopes
- Laboratoire de Biochimie, Department of Biology, UMR CNRS 7654, Ecole Polytechnique, 91128 Palaiseau, France
| | | | | |
Collapse
|
33
|
Allen BD, Mayo SL. An efficient algorithm for multistate protein design based on FASTER. J Comput Chem 2010; 31:904-16. [PMID: 19637210 DOI: 10.1002/jcc.21375] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Most of the methods that have been developed for computational protein design involve the selection of side-chain conformations in the context of a single, fixed main-chain structure. In contrast, multistate design (MSD) methods allow sequence selection to be driven by the energetic contributions of multiple structural or chemical states simultaneously. This methodology is expected to be useful when the design target is an ensemble of related states rather than a single structure, or when a protein sequence must assume several distinct conformations to function. MSD can also be used with explicit negative design to suggest sequences with altered structural, binding, or catalytic specificity. We report implementation details of an efficient multistate design optimization algorithm based on FASTER (MSD-FASTER). We subjected the algorithm to a battery of computational tests and found it to be generally applicable to various multistate design problems; designs with a large number of states and many designed positions are completely feasible. A direct comparison of MSD-FASTER and multistate design Monte Carlo indicated that MSD-FASTER discovers low-energy sequences much more consistently. MSD-FASTER likely performs better because amino acid substitutions are chosen on an energetic basis rather than randomly, and because multiple substitutions are applied together. Through its greater efficiency, MSD-FASTER should allow protein designers to test experimentally better-scoring sequences, and thus accelerate progress in the development of improved scoring functions and models for computational protein design.
Collapse
Affiliation(s)
- Benjamin D Allen
- Division of Chemistry and Chemical Engineering, California Institute of Technology, MC 114-96, 1200 E. California Blvd., Pasadena, California 91125, USA
| | | |
Collapse
|
34
|
Evolution: a guide to perturb protein function and networks. Curr Opin Struct Biol 2010; 20:351-9. [PMID: 20444593 DOI: 10.1016/j.sbi.2010.04.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2010] [Accepted: 04/08/2010] [Indexed: 12/11/2022]
Abstract
Protein interactions give rise to networks that control cell fate in health and disease; selective means to probe these interactions are therefore of wide interest. We discuss here Evolutionary Tracing (ET), a comparative method to identify protein functional sites and to guide experiments that selectively block, recode, or mimic their amino acid determinants. These studies suggest, in principle, a scalable approach to perturb individual links in protein networks.
Collapse
|
35
|
Abstract
Computational design has been very successful in recent years: multiple novel ligand binding proteins as well as enzymes have been reported. We wanted to know in molecular detail how precise the predictions of the interactions of protein and ligands are. Therefore, we performed a structural analysis of a number of published receptors designed onto the periplasmic binding protein scaffold that were reported to bind to the new ligands with nano- to micromolar affinities. It turned out that most of these designed proteins are not suitable for structural studies due to instability and aggregation. However, we were able to solve the crystal structure of an arabinose binding protein designed to bind serotonin to 2.2 A resolution. While crystallized in the presence of an excess of serotonin, the protein is in an open conformation with no serotonin bound, although the side-chain conformations in the empty binding pocket are very similar to the conformations predicted. During subsequent characterization using isothermal titration calorimetry, CD, and NMR spectroscopy, no indication of binding could be detected for any of the tested designed receptors, whereas wild-type proteins bound their ligands as expected. We conclude that although the computational prediction of side-chain conformations appears to be working, it does not necessarily confer binding as expected. Hence, the computational design of ligand binding is not a solved problem and needs to be revisited.
Collapse
|
36
|
Hollett JW, Poirier RA. SEST: Simulated Electronic Structure Theory. J Chem Theory Comput 2009; 5:126-35. [PMID: 26609826 DOI: 10.1021/ct800433r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A novel approach to empirically modeling the electronic structure of molecules is introduced. The theory is based on relationships between molecular orbital energy components and the average distance between electrons and electrons and nuclei. The electron-electron and electron-nucleus distances are subsequently related to interatomic distances which provides a means for modeling the electronic structure of molecules. The general energy expression for a simulated electronic structure theory is defined, along with the functional form of the interatomic distance dependent energy functions. The theory is used to model the hydrogen molecule, the first-row hydrides, and ethane. The models, which have the correct RHF/6-31G(d) optimized geometries, also fit the RHF/6-31G(d) energy at equilibrium and the UHF/6-31G(d) energy at the bond dissociation limit as well as some vibrational frequencies.
Collapse
Affiliation(s)
- Joshua W Hollett
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland A1B 3X7, Canada
| | - Raymond A Poirier
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland A1B 3X7, Canada
| |
Collapse
|