Design of Efficient Artificial Enzymes Using Crystallographically Enhanced Conformational Sampling.

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing the catalytic efficiency of de novo enzymes by several orders of magnitude without relying on directed evolution and high-throughput screening. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models, with catalytic contacts present as designed and transition-state root-mean-square deviations of ≤0.65 Å. Our work shows how ensemble-based design can generate efficient artificial enzymes by exploiting the true conformational ensemble to design improved active sites.

Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling.

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.

Computational remodeling of an enzyme conformational landscape for altered substrate selectivity.

Structural plasticity of enzymes dictates their function. Yet, our ability to rationally remodel enzyme conformational landscapes to tailor catalytic properties remains limited. Here, we report a computational procedure for tuning conformational landscapes that is based on multistate design of hinge-mediated domain motions. Using this method, we redesign the conformational landscape of a natural aminotransferase to preferentially stabilize a less populated but reactive conformation and thereby increase catalytic efficiency with a non-native substrate, resulting in altered substrate selectivity. Steady-state kinetics of designed variants reveals activity increases with the non-native substrate of approximately 100-fold and selectivity switches of up to 1900-fold. Structural analyses by room-temperature X-ray crystallography and multitemperature nuclear magnetic resonance spectroscopy confirm that conformational equilibria favor the target conformation. Our computational approach opens the door to targeted alterations of conformational states and equilibria, which should facilitate the design of biocatalysts with customized activity and selectivity.

Origin of acetylcholine antagonism in ELIC, a bacterial pentameric ligand-gated ion channel.

ELIC is a prokaryotic homopentameric ligand-gated ion channel that is homologous to vertebrate nicotinic acetylcholine receptors. Acetylcholine binds to ELIC but fails to activate it, despite bringing about conformational changes indicative of activation. Instead, acetylcholine competitively inhibits agonist-activated ELIC currents. What makes acetylcholine an agonist in an acetylcholine receptor context, and an antagonist in an ELIC context, is not known. Here we use available structures and statistical coupling analysis to identify residues in the ELIC agonist-binding site that contribute to agonism. Substitution of these ELIC residues for their acetylcholine receptor counterparts does not convert acetylcholine into an ELIC agonist, but in some cases reduces the sensitivity of ELIC to acetylcholine antagonism. Acetylcholine antagonism can be abolished by combining two substitutions that together appear to knock out acetylcholine binding. Thus, making the ELIC agonist-binding site more acetylcholine receptor-like, paradoxically reduces the apparent affinity for acetylcholine, demonstrating that residues important for agonist binding in one context can be deleterious in another. These findings reinforce the notion that although agonism originates from local interactions within the agonist-binding site, it is a global property with cryptic contributions from distant residues. Finally, our results highlight an underappreciated mechanism of antagonism, where agonists with appreciable affinity, but negligible efficacy, present as competitive antagonists.

Generation of bright monomeric red fluorescent proteins via computational design of enhanced chromophore packing.

Red fluorescent proteins (RFPs) have found widespread application in chemical and biological research due to their longer emission wavelengths. Here, we use computational protein design to increase the quantum yield and thereby brightness of a dim monomeric RFP (mRojoA, quantum yield = 0.02) by optimizing chromophore packing with aliphatic residues, which we hypothesized would reduce torsional motions causing non-radiative decay. Experimental characterization of the top 10 designed sequences yielded mSandy1 (λ em = 609 nm, quantum yield = 0.26), a variant with equivalent brightness to mCherry, a widely used RFP. We next used directed evolution to further increase brightness, resulting in mSandy2 (λ em = 606 nm, quantum yield = 0.35), the brightest Discosoma sp. derived monomeric RFP with an emission maximum above 600 nm reported to date. Crystallographic analysis of mSandy2 showed that the chromophore p-hydroxybenzylidene moiety is sandwiched between the side chains of Leu63 and Ile197, a structural motif that has not previously been observed in RFPs, and confirms that aliphatic packing leads to chromophore rigidification. Our results demonstrate that computational protein design can be used to generate bright monomeric RFPs, which can serve as templates for the evolution of novel far-red fluorescent proteins.

Personalized oncology and BRAFK601N melanoma: model development, drug discovery, and clinical correlation.

PURPOSE: Mutations in BRAF are the most prominent activating mutations in melanoma and are increasingly recognized in other cancers. There is currently no accepted treatment regimen for patients with mutant BRAFK601N melanoma, and the study of melanoma driven by BRAF mutations at the 601 locus is lacking due to a paucity of cellular model systems. Therefore, we sought to better understand the treatment and clinical approach to patients with mutant BRAFK601N melanoma and subsequently develop a novel personalized oncology platform for rare or treatment-refractory cancers. METHODS: We developed and characterized the first patient-derived, naturally occurring BRAFK601N melanoma model, described herein as OHRI-MEL-13, and assessed efficacy using the Prestwick Chemical Library and select targeted therapeutics. RESULTS: OHRI-MEL-13 exhibits loss of heterozygosity of BRAF, closely mimics the original tumor's gene expression profile, is tumorigenic in immune-deficient murine models, and is available for public accession through American Type Culture Collection. We present in silico modeling data, which illustrates the therapeutic failure of BRAFV600E-targeted therapies in BRAFK601N mutants. Our platform elucidated a unique role for MEK inhibition with cobimetinib, which resulted in short-term clinical success by reducing the metastatic burden. CONCLUSION: Our model of BRAFK601N-activated melanoma was developed, thoroughly characterized, and made available for public accession. This model served to demonstrate the feasibility of a novel personalized oncology platform that could be optimized at an institutional level for rare variant or treatment-refractory cancers. We also demonstrate the clinical utility of monotherapy MEK inhibition in a case of BRAFK601N melanoma.

Genetically Encoded Fluorescent Biosensor for Rapid Detection of Protein Expression.

Fluorescent proteins are widely used as fusion tags to detect protein expression in vivo. To become fluorescent, these proteins must undergo chromophore maturation, a slow process with a half-time of 5 to >30 min that causes delays in real-time detection of protein expression. Here, we engineer a genetically encoded fluorescent biosensor to enable detection of protein expression within seconds in live bacteria. This sensor for transiently expressed proteins (STEP) is based on a fully matured but dim green fluorescent protein in which pre-existing fluorescence increases 11-fold in vivo following the specific and rapid binding of a protein tag (Kd 120 nM, kon 1.7 × 105 M-1 s-1). In live E. coli cells, our STEP biosensor enables detection of protein expression twice as fast as the use of standard fluorescent protein fusions. Our biosensor opens the door to the real-time study of short timescale processes in live cells with high spatiotemporal resolution.

Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico.

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 146 M-1s-1). We observe that catalytic residues are increasingly rigidified, the active site becomes better pre-organized, and its entrance is widened. Based on these observations, we engineer HG4, an efficient biocatalyst (kcat/KM 103,000 M-1s-1) containing key first and second-shell mutations found during evolution. HG4 structures reveal that its active site is pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

Origin of conformational dynamics in a globular protein.

Protein structures are dynamic, undergoing motions that can play a vital role in function. However, the link between primary sequence and conformational dynamics remains poorly understood. Here, we studied how conformational dynamics can arise in a globular protein by evaluating the impact of individual core-residue substitutions in DANCER-3, a streptococcal protein G domain ß1 variant that we previously designed to undergo a specific mode of conformational exchange that has never been observed in the wild-type protein. Using a combination of solution NMR experiments and molecular dynamics simulations, we demonstrate that only two mutations are necessary to create this conformational exchange, and that these mutations work synergistically, with one destabilizing the native structure and the other allowing two new conformational states to be accessed on the energy landscape. Overall, our results show how dynamics can appear in a stable globular fold, a critical step in the molecular evolution of dynamics-linked functions.

Structural Determinants of the Stereoinverting Activity of Pseudomonas stutzeri d-Phenylglycine Aminotransferase.

Aromatic d-amino acids are key precursors for the production of many small molecule therapeutics. Therefore, the development of biocatalytic methods for their synthesis is of great interest. An enzyme that has great potential as a biocatalyst for the synthesis of d-amino acids is the stereoinverting d-phenylglycine aminotransferase (DPAT) from Pseudomonas stutzeri ST-201. This enzyme catalyzes a unique l to d transamination reaction that produces d-phenylglycine and α-ketoglutarate from benzoylformate and l-glutamate, via a mechanism that is poorly understood. Here, we present the crystal structure of DPAT, which shows that the enzyme folds into a two-domain structure representative of class III aminotransferases. Guided by the crystal structure, we performed saturation mutagenesis to probe the substrate binding pockets of the enzyme. These experiments helped us identify two arginine residues (R34 and R407), one in each binding pocket, that are essential to catalysis. Together with kinetic analyses using a library of amino acid substrates, our mutagenesis and structural studies allow us to propose a binding model that explains the dual l/d specificity of DPAT. Our kinetic analyses also demonstrate that DPAT can catalyze the transamination of ß- and γ-amino acids, reclassifying this enzyme as an ω-aminotransferase. Collectively, our studies highlight that the DPAT active site is amenable to protein engineering for expansion of its substrate scope, which offers the opportunity to generate new biocatalysts for the synthesis of a variety of valuable optically pure d-amino acids from inexpensive and abundant l-amino acids.

ProtaBank: A repository for protein design and engineering data.

We present ProtaBank, a repository for storing, querying, analyzing, and sharing protein design and engineering data in an actively maintained and updated database. ProtaBank provides a format to describe and compare all types of protein mutational data, spanning a wide range of properties and techniques. It features a user-friendly web interface and programming layer that streamlines data deposition and allows for batch input and queries. The database schema design incorporates a standard format for reporting protein sequences and experimental data that facilitates comparison of results across different data sets. A suite of analysis and visualization tools are provided to facilitate discovery, to guide future designs, and to benchmark and train new predictive tools and algorithms. ProtaBank will provide a valuable resource to the protein engineering community by storing and safeguarding newly generated data, allowing for fast searching and identification of relevant data from the existing literature, and exploring correlations between disparate data sets. ProtaBank invites researchers to contribute data to the database to make it accessible for search and analysis. ProtaBank is available at https://protabank.org.

Rational design of proteins that exchange on functional timescales.

Proteins are intrinsically dynamic molecules that can exchange between multiple conformational states, enabling them to carry out complex molecular processes with extreme precision and efficiency. Attempts to design novel proteins with tailored functions have mostly failed to yield efficiencies matching those found in nature because standard methods do not allow the design of exchange between necessary conformational states on a functionally relevant timescale. Here we developed a broadly applicable computational method to engineer protein dynamics that we term meta-multistate design. We used this methodology to design spontaneous exchange between two novel conformations introduced into the global fold of Streptococcal protein G domain ß1. The designed proteins, named DANCERs, for dynamic and native conformational exchangers, are stably folded and switch between predicted conformational states on the millisecond timescale. The successful introduction of defined dynamics on functional timescales opens the door to new applications requiring a protein to spontaneously access multiple conformational states.

Multistate Computational Protein Design with Backbone Ensembles.

The ability of computational protein design (CPD) to identify protein sequences possessing desired characteristics in vast sequence spaces makes it a highly valuable tool in the protein engineering toolbox. CPD calculations are typically performed using a single-state design (SSD) approach in which amino-acid sequences are optimized on a single protein structure. Although SSD has been successfully applied to the design of numerous protein functions and folds, the approach can lead to the incorrect rejection of desirable sequences because of the combined use of a fixed protein backbone template and a set of rigid rotamers. This fixed backbone approximation can be addressed by using multistate design (MSD) with backbone ensembles. MSD improves the quality of predicted sequences by using ensembles approximating conformational flexibility as input templates instead of a single fixed protein structure. In this chapter, we present a step-by-step guide to the implementation and analysis of MSD calculations with backbone ensembles. Specifically, we describe ensemble generation with the PertMin protocol, execution of MSD calculations for recapitulation of Streptococcal protein G domain ß1 mutant stability, and analysis of computational predictions by sequence binning. Furthermore, we provide a comparison between MSD and SSD calculation results and discuss the benefits of multistate approaches to CPD.

Structure-guided rational design of red fluorescent proteins: towards designer genetically-encoded fluorophores.

Red fluorescent proteins (RFPs) have become an integral part of modern biological research due to their longer excitation and emission wavelengths. Protein engineering efforts have improved many key properties of RFPs for their practical use in imaging. Even so, continued engineering is required to overcome the shortcomings of the red chromophore and create RFPs with photophysical properties rivalling those of their optimized green and yellow counterparts. Here, we highlight recent examples of structure-guided rational design of RFPs to improve brightness, monomerization, maturation, and photostability, and discuss possible pathways for the future engineering of designer RFPs tailored to specific applications.

Turning a Negative into a Positive: Conversion of a Homodimer into a Heterodimer Using Negative State Repertoires.

In this issue of Structure, Leaver-Fay et al. (2016) engineer bispecific antibodies using multistate computational protein design with negative state repertoires. In combination with additional mutations selected rationally, they produced antibodies that assembled as heterodimers with up to 93% purity.