Computational approaches for protein engineering and design
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Computational approaches for protein engineering and design
Interesting papers on computational (in-silico) approaches for protein engineering and design.
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Ising Model Reprogramming of a Repeat Protein's Equilibrium Unfolding Pathway

Ising Model Reprogramming of a Repeat Protein's Equilibrium Unfolding Pathway | Computational approaches for protein engineering and design | Scoop.it

J Mol Biol. 2016 Mar 4. pii: S0022-2836(16)00138-8. doi: 10.1016/j.jmb.2016.02.022. [Epub ahead of print]


C. Millership, J.J. Phillips, E.R.G. Main


Abstract


Repeat proteins are formed from units of 20–40 aa that stack together into quasi one-dimensional non-globular structures. This modular repetitive construction means that, unlike globular proteins, a repeat protein's equilibrium folding and thus thermodynamic stability can be analysed using linear Ising models. Typically, homozipper Ising models have been used. These treat the repeat protein as a series of identical interacting subunits (the repeated motifs) that couple together to form the folded protein. However, they cannot describe subunits of differing stabilities.

Here we show that a more sophisticated heteropolymer Ising model can be constructed and fitted to two new helix deletion series of consensus tetratricopeptide repeat proteins (CTPRs). This analysis, showing an asymmetric spread of stability between helices within CTPR ensembles, coupled with the Ising model's predictive qualities was then used to guide reprogramming of the unfolding pathway of a variant CTPR protein. The designed behaviour was engineered by introducing destabilising mutations that increased the thermodynamic asymmetry within a CTPR ensemble. The asymmetry caused the terminal α-helix to thermodynamically uncouple from the rest of the protein and preferentially unfold. This produced a specific, highly populated stable intermediate with a putative dimerisation interface. As such it is the first step in designing repeat proteins with function regulated by a conformational switch.

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Converting bulk sugars into prebiotics: semi-rational design of a transglucosylase with controlled selectivity

Converting bulk sugars into prebiotics: semi-rational design of a transglucosylase with controlled selectivity | Computational approaches for protein engineering and design | Scoop.it

Tom Verhaeghe,   Karel De Winter,   Magali Berland,   Rob De Vreese,   Matthias D'hooghe,   Bernard Offmann and   Tom Desmet  


Chem. Commun., 2016, Accepted Manuscript


DOI: 10.1039/C5CC09940D


Despite the growing importance of prebiotics in nutrition and gastroenterology, their structural variety is currently still very limited. The lack of straightforward procedures to gain new products in sufficient amounts often hampers application testing and further development. Although the enzyme sucrose phosphorylase can be used to produce the rare disaccharide kojiobiose (α-1,2-glucobiose) from the bullk sugars sucrose and glucose, the target compound is only a side product that is difficult to isolate. Accordingly, for this biocatalyst to become economically attractive, the formation of other glucobioses should be avoided and therefore we applied semi-rational mutagenesis and low-throughput screening, which resulted in a double mutant (L341I_Q345S) with a selectivity of 95% for kojibiose. That way, an efficient and scalable production process with a yield of 74% could be established, and with a simple yeast treatment and crystallization step over hundred grams of highly pure kojibiose (>99.5%) was obtained.

Bernard Offmann's insight:

Enzymatic synthesis of kojibiose from sucrose.

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Direct Calculation of Protein Fitness Landscapes through Computational Protein Design.

Biophys J. 2016 Jan 5;110(1):75-84. doi: 10.1016/j.bpj.2015.11.029.

http://www.sciencedirect.com/science/article/pii/S0006349515012126

 

Au L, Green DF.

 

Abstract

Naturally selected amino-acid sequences or experimentally derived ones are often the basis for understanding how protein three-dimensional conformation and function are determined by primary structure. Such sequences for a protein family comprise only a small fraction of all possible variants, however, representing the fitness landscape with limited scope. Explicitly sampling and characterizing alternative, unexplored protein sequences would directly identify fundamental reasons for sequence robustness (or variability), and we demonstrate that computational methods offer an efficient mechanism toward this end, on a large scale. The dead-end elimination and A∗ search algorithms were used here to find all low-energy single mutant variants, and corresponding structures of a G-protein heterotrimer, to measure changes in structural stability and binding interactions to define a protein fitness landscape. We established consistency between these algorithms with known biophysical and evolutionary trends for amino-acid substitutions, and could thus recapitulate known protein side-chain interactions and predict novel ones.

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How mutational epistasis impairs predictability in protein evolution and design.

Protein Sci. 2016 Jan 12. doi: 10.1002/pro.2876. [Epub ahead of print]

 

Charlotte M. Miton, Nobuhiko Tokuriki

 

Significance Statement: Epistasis, that is, non-additive mutational effects, constrains the adaptive evolution of proteins, yet we lack a consensus view of its extent. To address this need, we performed a systematic survey of mutational epistasis occurring within nine adaptive enzyme trajectories. Of particular importance to protein engineering, our results quantify the unpredictability of functional mutations and emphasize the need to incorporate epistasis for the accurate prediction of mutational effects.

Abstract

There has been much debate about the extent to which mutational epistasis, that is, the dependence of the outcome of a mutation on the genetic background, constrains evolutionary trajectories. The degree of unpredictability introduced by epistasis, due to the non-additivity of functional effects, strongly hinders the strategies developed in protein design and engineering. While many studies have addressed this issue through systematic characterization of evolutionary trajectories within individual enzymes, the field lacks a consensus view on this matter. In this work, we performed a comprehensive analysis of epistasis by analyzing the mutational effects from nine adaptive trajectories toward new enzymatic functions. We quantified epistasis by comparing the effect of mutations occurring between two genetic backgrounds: the starting enzyme (for example, wild type) and the intermediate variant on which the mutation occurred during the trajectory. We found that most trajectories exhibit positive epistasis, in which the mutational effect is more beneficial when it occurs later in the evolutionary trajectory. Approximately half (49%) of functional mutations were neutral or negative on the wild-type background, but became beneficial at a later stage in the trajectory, indicating that these functional mutations were not predictable from the initial starting point. While some cases of strong epistasis were associated with direct interaction between residues, many others were caused by long-range indirect interactions between mutations. Our work highlights the prevalence of epistasis in enzyme adaptive evolution, in particular positive epistasis, and suggests the necessity of incorporating mutational epistasis in protein engineering and design to create highly efficient catalysts.

Bernard Offmann's insight:

Beautiful paper from Tokuriki in Protein Science journal ! Must read.

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Rational design of α-helical tandem repeat proteins with closed architectures : Nature : Nature Publishing Group

Rational design of α-helical tandem repeat proteins with closed architectures : Nature : Nature Publishing Group | Computational approaches for protein engineering and design | Scoop.it
Tandem repeat proteins, which are formed by repetition of modular units of protein sequence and structure, play important biological roles as macromolecular binding and scaffolding domains, enzymes, and building blocks for the assembly of fibrous materials. The modular nature of repeat proteins enables the rapid construction and diversification of extended binding surfaces by duplication and recombination of simple building blocks. The overall architecture of tandem repeat protein structures—which is dictated by the internal geometry and local packing of the repeat building blocks—is highly diverse, ranging from extended, super-helical folds that bind peptide, DNA, and RNA partners, to closed and compact conformations with internal cavities suitable for small molecule binding and catalysis. Here we report the development and validation of computational methods for de novo design of tandem repeat protein architectures driven purely by geometric criteria defining the inter-repeat geometry, without reference to the sequences and structures of existing repeat protein families. We have applied these methods to design a series of closed α-solenoid repeat structures (α-toroids) in which the inter-repeat packing geometry is constrained so as to juxtapose the amino (N) and carboxy (C) termini; several of these designed structures have been validated by X-ray crystallography. Unlike previous approaches to tandem repeat protein engineering, our design procedure does not rely on template sequence or structural information taken from natural repeat proteins and hence can produce structures unlike those seen in nature. As an example, we have successfully designed and validated closed α-solenoid repeats with a left-handed helical architecture that—to our knowledge—is not yet present in the protein structure database.
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From David Baker's group, a second Nature paper in same week !!! 

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De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy | Computational approaches for protein engineering and design | Scoop.it

Po-Ssu Huang,Kaspar Feldmeier,Fabio Parmeggiani,D Alejandro Fernandez Velasco,Birte Höcker& David Baker

 

Abstract

 

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain–backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes.

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Another impressive achievement from David Baker's group...

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Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm.

J Mol Model. 2015 Aug;21(8):2742. doi: 10.1007/s00894-015-2742-x. Epub 2015 Jul 11.Tian Y1, Huang X, Zhu Y. 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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Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression.

Protein Sci. 2015 Jul 15. doi: 10.1002/pro.2748. [Epub ahead of print] Bale JB, Park RU, Liu Y, Gonen S, Gonen T, Cascio D, King NP, Yeates TO, Baker D. Abstract

 

We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids. The structure is found to match the computational design model with atomic-level accuracy, providing further validation of the design approach and demonstrating a simple and potentially general means of improving the yield of designed protein nanomaterials.

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Another very nice protein design paper from David Baker's group !

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Prediction of protein folding rates from simplified secondary structure alphabet.

J Theor Biol. 2015 Aug 4. pii: S0022-5193(15)00369-0. doi: 10.1016/j.jtbi.2015.07.024. [Epub ahead of print] Huang JT, Wang T, Huang SR, Li X. AbstractProtein folding is a very complicated and highly cooperative dynamic process. However, the folding kinetics is likely to depend more on a few key structural features. Here we find that secondary structures can determine folding rates of only large, multi-state folding proteins and fails to predict those for small, two-state proteins. The importance of secondary structures for protein folding is ordered as: extended β strand>α helix>bend>turn>undefined secondary structure>310 helix>isolated β strand>π helix. Only the first three secondary structures, extended β strand, α helix and bend, can achieve a good correlation with folding rates. This suggests that the rate-limiting step of protein folding would depend upon the formation of regular secondary structures and the buckling of chain. The reduced secondary structure alphabet provides a simplified description for the machine learning applications in protein design.
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Interesting theoretical insight.

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Engineering Transcriptional Regulator Effector Specificity using Computational Design and In Vitro Rapid Prototyping: Developing a Vanillin Sensor.

ACS Synth Biol. 2015 Aug 11. [Epub ahead of print] de Los Santos EL, Meyerowitz JT, Mayo SL, Murray RM.Abstract

The pursuit of circuits and metabolic pathways of increasing complexity and robustness in synthetic biology will require engineering new regulatory tools. Feedback control based on relevant molecules, including toxic intermediates and environmental signals, would enable genetic circuits to react appropriately to changing conditions. In this work, variants of qacR, a tetR family repressor, were generated by computational protein design and screened in a cell-free transcription-translation (TX-TL) system for responsiveness to a new targeted effector. The modified repressors target vanillin, a growth-inhibiting small molecule found in lignocellulosic hydrolysates and other industrial processes. Promising candidates from the in vitro screen were further characterized in vitro and in vivo in a gene circuit. The screen yielded two qacR mutants that respond to vanillin both in vitro and in vivo. While the mutants exhibit some toxicity to cells, presumably due to off-target effects, they are prime starting points for directed evolution towards vanillin sensors with the specifications required for use in a dynamic control loop. We believe this process, a combination of the generation of variants coupled with in vitro screening, can serve as a framework for designing new sensors for other target compounds.

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Design of symmetric TIM barrel proteins from first principles.

Nagarajan D, Deka G, Rao M.

BMC Biochem. 2015 Aug 12;16(1):18. doi: 10.1186/s12858-015-0047-4

 

ABSTRACT

 

BACKGROUND: 

Computational protein design is a rapidly maturing field within structural biology, with the goal of designing proteins with custom structures and functions. Such proteins could find widespread medical and industrial applications. Here, we have adapted algorithms from the Rosetta software suite to design much larger proteins, based on ideal geometric and topological criteria. Furthermore, we have developed techniques to incorporate symmetry into designed structures. For our first design attempt, we targeted the (α/β)8 TIM barrel scaffold. We gained novel insights into TIM barrel folding mechanisms from studying natural TIM barrel structures, and from analyzing previous TIM barrel design attempts.

 

METHODS: 

Computational protein design and analysis was performed using the Rosetta software suite and custom scripts. Genes encoding all designed proteins were synthesized and cloned on the pET20-b vector. Standard circular dichroism and gel chromatographic experiments were performed to determine protein biophysical characteristics. 1D NMR and 2D HSQC experiments were performed to determine protein structural characteristics.

 

RESULTS: 

Extensive protein design simulations coupled with ab initio modeling yielded several all-atom models of ideal, 4-fold symmetric TIM barrels. Four such models were experimentally characterized. The best designed structure (Symmetrin-1) contained a polar, histidine-rich pore, forming an extensive hydrogen bonding network. Symmetrin-1 was easily expressed and readily soluble. It showed circular dichroism spectra characteristic of well-folded alpha/beta proteins. Temperature melting experiments revealed cooperative and reversible unfolding, with a Tm of 44 °C and a Gibbs free energy of unfolding (ΔG°) of 8.0 kJ/mol. Urea denaturing experiments confirmed these observations, revealing a Cm of 1.6 M and a ΔG° of 8.3 kJ/mol. Symmetrin-1 adopted a monomeric conformation, with an apparent molecular weight of 32.12 kDa, and displayed well resolved 1D-NMR spectra. However, the HSQC spectrum revealed somewhat molten characteristics.

 

CONCLUSIONS: 

Despite the detection of molten characteristics, the creation of a soluble, cooperatively folding protein represents an advancement over previous attempts at TIM barrel design. Strategies to further improve Symmetrin-1 are elaborated. Our techniques may be used to create other large, internally symmetric proteins.

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Nice paper from scientist from leading Indian Institute of Science (Bangalore, India).

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Computational strategies for the design of new enzymatic functions.

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Proteochemometric Modeling of the Antigen-Antibody Interaction: New Fingerprints for Antigen, Antibody and Epitope-Paratope Interaction

Proteochemometric Modeling of the Antigen-Antibody Interaction: New Fingerprints for Antigen, Antibody and Epitope-Paratope Interaction | Computational approaches for protein engineering and design | Scoop.it
Despite the high specificity between antigen and antibody binding, similar epitopes can be recognized or cross-neutralized by paratopes of antibody with different binding affinities.

Via Krishan Maggon
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Krishan Maggon 's curator insight, April 23, 2015 5:11 AM

Citation: Qiu T, Xiao H, Zhang Q, Qiu J, Yang Y, et al. (2015) Proteochemometric Modeling of the Antigen-Antibody Interaction: New Fingerprints for Antigen, Antibody and Epitope-Paratope Interaction. PLoS ONE 10(4): e0122416. doi:10.1371/journal.pone.0122416

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Effect of ELP Sequence and Fusion Protein Design on Concentrated Solution Self-Assembly.

Effect of ELP Sequence and Fusion Protein Design on Concentrated Solution Self-Assembly. | Computational approaches for protein engineering and design | Scoop.it
Guokui Qin, Paola M. Perez, Carolyn E. Mills, and Bradley D. Olsen

Biomacromolecules. 2016 Mar 1. [Epub ahead of print]

Abstract 

Fusion proteins provide a facile route for the purification and self-assembly of biofunctional protein block copolymers into complex nanostructures; however, the use of biochemical synthesis techniques introduces unexplored variables into the design of the structures. Using model fusion constructs of the red fluorescent protein mCherry and the coil-like protein elastin-like polypeptide (ELP), it is shown that the molar mass and hydrophobicity of the ELP sequence have a large effect on the propensity of a fusion to form well-ordered nanostructures, even when the ELP is in the low temperature, highly solvated state. In contrast, the presence of a 6xHis purification tag has little effect on self-assembly, and the order of blocks in the construct (N-terminal vs C-terminal) only has a significant effect on the nanostructure when the conjugates are heated above the transition temperature of the ELP block. These results indicate that for a sufficiently hydrophobic and high molar mass ELP block, there is a great deal of design latitude in the construction of fusion protein block copolymers for self-assembling nanomaterials.
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De Novo Proteins with Life-Sustaining Functions are Structurally Dynamic. - PubMed - NCBI

J Mol Biol. 2015 Dec 18. pii: S0022-2836(15)00699-3. doi: 10.1016/j.jmb.2015.12.008. [Epub ahead of print]

 

Murphy GS, Greisman JB, Hecht MH.

Abstract

Designing and producing novel proteins that fold into stable structures and provide essential biological functions are key goals in synthetic biology. In initial steps toward achieving these goals, we constructed a combinatorial library of de novo proteins designed to fold into 4-helix bundles. As described previously, screening this library for sequences that function in vivo to rescue conditionally lethal mutants of E. coli (auxotrophs) yielded several de novo sequences, termed SynRescue proteins, which rescued four different E. coli auxotrophs. In an effort to understand the structural requirements necessary for auxotroph rescue, we investigated the biophysical properties of the SynRescue proteins, using both computational and experimental approaches. Results from circular dichroism, size exclusion chromatography, and NMR demonstrate that the SynRescue proteins are α-helical and relatively stable. Surprisingly, however, they do not form well-ordered structures. Instead, they form dynamic structures that fluctuate between monomeric and dimeric states. These findings show that a well-ordered structure is not a prerequisite for life-sustaining functions, and suggest that dynamic structures may have been important in the early evolution of protein function.

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Another interesting paper from Michael H. Hecht.

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A De Novo Protein Confers Copper Resistance in Escherichia Coli. - PubMed - NCBI

Protein Sci. 2016 Jan 8. doi: 10.1002/pro.2871. [Epub ahead of print]

 

Hoegler KJ, Hecht MH

Abstract

To survive environmental challenges, biological systems rely on proteins that were selected by evolution to function in particular cellular and environmental settings. With the advent of protein design and synthetic biology, it is now possible to construct novel proteins that are not biased by eons of selection in natural hosts. The availability of these sequences prompts us to ask whether natural biological organisms can use naïve - non-biological - proteins to enhance fitness in stressful environments. To address this question, we transformed a library of DNA sequences encoding ∼1.5 × 106 binary patterned de novo proteins into E. coli, and selected for sequences that enable growth in concentrations of copper that would otherwise be toxic. Several novel sequences were discovered, and one of them, called Construct K (ConK), was studied in detail. Cells expressing ConK accumulate approximately 50% less copper than control cells. The function of ConK does not involve an oxidase, nor does it require two of the best characterized copper efflux systems. However, the ability of ConK to rescue cells from toxic concentrations of copper does require an active proton motive force. Further selections for growth in higher concentrations of copper led to the laboratory evolution of variants of ConK with enhanced levels of activity in vivo. These studies demonstrate that novel proteins, unbiased by evolutionary history in the natural world, can enhance the fitness of biological systems. This article is protected by copyright. All rights reserved.

© 2016 The Protein Society.

Bernard Offmann's insight:

Another interesting paper from Michael H. Hecht on the topic of protein design published in Protein Science journal from Protein Society. 

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Protein backbone ensemble generation explores the local structural space of unseen natural homologs. - PubMed - NCBI

Bioinformatics. 2016 Jan 18. pii: btw001. [Epub ahead of print]

 

Abstract
MOTIVATION: 

Mutations in homologous proteins affect changes in the backbone conformation that involve a complex interplay of forces which are difficult to predict. Protein design algorithms need to anticipate these backbone changes in order to accurately calculate the energy of the structure given an amino acid sequence, without knowledge of the final, designed sequence. This is related to the problem of predicting small changes in the backbone between highly similar sequences.

RESULTS: 

We explored the ability of the Rosetta suite of protein design tools to move the backbone from its position in one structure (template) to its position in a close homologous structure (target) as a function of the diversity of a backbone ensemble constructed using the template structure, the percent sequence identity between the template and target, and the size of local zone being considered in the ensemble. We describe a pareto front in the likelihood of moving the backbone toward the target as a function of ensemble diversity and zone size. The equations and protocols presented here will be useful for protein design.

AVAILABILITY: 

PyRosetta scripts available at www.bioinfo.rpi.edu/bystrc/downloads.html#ensemble CONTACT: bystrc@rpi.edu.

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Very interesting paper from Bystroff.

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Exploring the repeat protein universe through computational protein design

Exploring the repeat protein universe through computational protein design | Computational approaches for protein engineering and design | Scoop.it

A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix–loop–helix–loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95 °C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5 Å. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering.

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This is simply another brilliant paper from David Baker.

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Discriminating between stabilizing and destabilizing protein design mutations via recombination and simulation.

Protein Eng Des Sel. 2015 Aug;28(8):259-67. doi: 10.1093/protein/gzv030. Epub 2015 Jun 15.Johnson LB, Gintner LP, Park S, Snow CD. Abstract

Accuracy of current computational protein design (CPD) methods is limited by inherent approximations in energy potentials and sampling. These limitations are often used to qualitatively explain design failures; however, relatively few studies provide specific examples or quantitative details that can be used to improve future CPD methods. Expanding the design method to include a library of sequences provides data that is well suited for discriminating between stabilizing and destabilizing design elements. Using thermophilic endoglucanase E1 from Acidothermus cellulolyticus as a model enzyme, we computationally designed a sequence with 60 mutations. The design sequence was rationally divided into structural blocks and recombined with the wild-type sequence. Resulting chimeras were assessed for activity and thermostability. Surprisingly, unlike previous chimera libraries, regression analysis based on one- and two-body effects was not sufficient for predicting chimera stability. Analysis of molecular dynamics simulations proved helpful in distinguishing stabilizing and destabilizing mutations. Reverting to the wild-type amino acid at destabilized sites partially regained design stability, and introducing predicted stabilizing mutations in wild-type E1 significantly enhanced thermostability. The ability to isolate stabilizing and destabilizing elements in computational design offers an opportunity to interpret previous design failures and improve future CPD methods.

Bernard Offmann's insight:

Nice paper from Christophe Snow at Colorado State University (http://cbe.colostate.edu/pages/Chris_Snow.html). Met with him while he was in Caltech as Jane Coffin Childs Fellow and a KAUST Research Fellow.

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Specific GFP-binding artificial proteins (αRep): a new tool for in vitro to live cell applications.

Biosci Rep. 2015 Jun 12;35(4). pii: e00223. doi: 10.1042/BSR20150080.Chevrel A, Urvoas A, de la Sierra-Gallay IL, Aumont-Nicaise M, Moutel S, Desmadril M, Perez F, Gautreau A, van Tilbeurgh H, Minard P, Valerio-Lepiniec M.Abstract

A family of artificial proteins, named αRep, based on a natural family of helical repeat was previously designed. αRep members are efficiently expressed, folded and extremely stable proteins. A large αRep library was constructed creating proteins with a randomized interaction surface. In the present study, we show that the αRep library is an efficient source of tailor-made specific proteins with direct applications in biochemistry and cell biology. From this library, we selected by phage display αRep binders with nanomolar dissociation constants against the GFP. The structures of two independent αRep binders in complex with the GFP target were solved by X-ray crystallography revealing two totally different binding modes. The affinity of the selected αReps for GFP proved sufficient for practically useful applications such as pull-down experiments. αReps are disulfide free proteins and are efficiently and functionally expressed in eukaryotic cells: GFP-specific αReps are clearly sequestrated by their cognate target protein addressed to various cell compartments. These results suggest that αRep proteins with tailor-made specificity can be selected and used in living cells to track, modulate or interfere with intracellular processes.

Bernard Offmann's insight:

Nice paper from Ph. Minard and people at I2BC in Orsay, Paris.

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Fast Gap-Free Enumeration of Conformations and Sequences for Protein Design.

Proteins. 2015 Aug 3. doi: 10.1002/prot.24870. [Epub ahead of print]Roberts KE, Gainza P, Hallen MA, Donald BRAbstract

Despite significant successes in structure-based computational protein design in recent years, protein design algorithms must be improved to increase the biological accuracy of new designs. Protein design algorithms search through an exponential number of protein conformations, protein ensembles, and amino acid sequences in an attempt to find globally optimal structures with a desired biological function. To improve the biological accuracy of protein designs, it is necessary to increase both the amount of protein flexibility allowed during the search and the overall size of the design, while guaranteeing that the lowest-energy structures and sequences are found. DEE/A*-based algorithms are the most prevalent provable algorithms in the field of protein design and can provably enumerate a gap-free list of low-energy protein conformations, which is necessary for ensemble-based algorithms that predict protein binding. We present two classes of algorithmic improvements to the A*algorithm that greatly increase the efficiency of A*. First, we analyze the effect of ordering the expansion of mutable residue positions within the A*tree and present a dynamic residue ordering that reduces the number of A*nodes that must be visited during the search. Second, we propose new methods to improve the conformational bounds used to estimate the energies of partial conformations during the A*search. The residue ordering techniques and improved bounds can be combined for additional increases in A*efficiency. Our enhancements enable all A*-based methods to more fully search protein conformation space, which will ultimately improve the accuracy of complex biomedically-relevant designs.

Bernard Offmann's insight:

Nice algorithm from Bruce Donald, a leader in structural bioinformatics  ! I think I'll be switching to their open source software.

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Antibody humanization by structure-based computational protein design.

MAbs. 2015 Aug 7:0. [Epub ahead of print] Choi Y, Hua C, Sentman CL, Ackerman ME, Bailey-Kellogg C.  Abstract

Antibodies derived from non-human sources must be modified for therapeutic use so as to mitigate undesirable immune responses. While complementarity-determining region (CDR) grafting-based humanization techniques have been successfully applied in many cases, it remains challenging to maintain the desired stability and antigen binding affinity upon grafting. We developed an alternative humanization approach called CoDAH ("Computationally-Driven Antibody Humanization") in which computational protein design methods directly select sets of amino acids to incorporate from human germline sequences to increase humanness while maintaining structural stability. Retrospective studies show that CoDAH is able to identify variants deemed beneficial according to both humanness and structural stability criteria, even for targets lacking crystal structures. Prospective application to TZ47, a murine anti-human B7H6 antibody, demonstrates the approach. Four diverse humanized variants were designed, and all possible unique VH/VL combinations were produced as full-length IgG1 antibodies. Soluble and cell surface expressed antigen binding assays showed that 75% (6 of 8) of the computationally designed VH/VL variants were successfully expressed and competed with the murine TZ47 for binding to B7H6 antigen. Furthermore, four of the six bound with an estimated KD within an order of magnitude of the original TZ47 antibody. In contrast, a traditional CDR-grafted variant could not be expressed. These results suggest that the computational protein design approach described here can be used to efficiently generate functional humanized antibodies and provide humanized templates for further affinity maturation.

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