Roberto A. Chica

Iterative approach to computational enzyme design.

A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.

Generation of longer emission wavelength red fluorescent proteins using computationally designed libraries

The longer emission wavelengths of red fluorescent proteins (RFPs) make them attractive for whole-animal imaging because cells are more transparent to red light. Although several useful RFPs have been developed using directed evolution, the quest for further red-shifted and improved RFPs continues. Herein, we report a structure-based rational design approach to red-shift the fluorescence emission of RFPs. We applied a combined computational and experimental approach that uses computational protein design as an in silico prescreen to generate focused combinatorial libraries of mCherry mutants. The computational procedure helped us identify residues that could fulfill interactions hypothesized to cause red-shifts without destabilizing the protein fold. These interactions include stabilization of the excited state through H-bonding to the acylimine oxygen atom, destabilization of the ground state by hydrophobic packing around the charged phenolate, and stabilization of the excited state by a π-stacking interaction. Our methodology allowed us to identify three mCherry mutants (mRojoA, mRojoB, and mRouge) that display emission wavelengths > 630 nm, representing red-shifts of 20–26 nm. Moreover, our approach required the experimental screening of a total of ∼5,000 clones, a number several orders of magnitude smaller than those previously used to achieve comparable red-shifts. Additionally, crystal structures of mRojoA and mRouge allowed us to verify fulfillment of the interactions hypothesized to cause red-shifts, supporting their contribution to the observed red-shifts.

Tissue transglutaminase acylation: Proposed role of conserved active site Tyr and Trp residues revealed by molecular modeling of peptide substrate binding

Transglutaminases (TGases) catalyze the cross‐linking of peptides and proteins by the formation of γ‐glutamyl‐ε‐lysyl bonds. Given the implication of tissue TGase in various physiological disorders, development of specific tissue TGase inhibitors is of current interest. To aid in the design of peptide‐based inhibitors, a better understanding of the mode of binding of model peptide substrates to the enzyme is required. Using a combined kinetic/molecular modeling approach, we have generated a model for the binding of small acyl‐donor peptide substrates to tissue TGase from red sea bream. Kinetic analysis of various N‐terminally derivatized Gln‐Xaa peptides has demonstrated that many CBz‐Gln‐Xaa peptides are typical in vitro substrates with KM values between 1.9 mM and 9.4 mM, whereas Boc‐Gln‐Gly is not a substrate, demonstrating the importance of the CBz group for recognition. Our binding model of CBz‐Gln‐Gly on tissue TGase has allowed us to propose the following steps in the acylation of tissue TGase. First, the active site is opened by displacement of conserved W329. Second, the substrate Gln side chain enters the active site and is stabilized by hydrophobic interaction with conserved residue W236. Third, a hydrogen bond network is formed between the substrate Gln side chain and conserved residues Y515 and the acid‐base catalyst H332 that helps to orient and activate the γ‐carboxamide group for nucleophilic attack by the catalytic sulphur atom. Finally, an H‐bond with Y515 stabilizes the oxyanion formed during the reaction.

Multistate approaches in computational protein design

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.

Improving the accuracy of protein stability predictions with multistate design using a variety of backbone ensembles.

Multistate computational protein design (MSD) with backbone ensembles approximating conformational flexibility can predict higher quality sequences than single‐state design with a single fixed backbone. However, it is currently unclear what characteristics of backbone ensembles are required for the accurate prediction of protein sequence stability. In this study, we aimed to improve the accuracy of protein stability predictions made with MSD by using a variety of backbone ensembles to recapitulate the experimentally measured stability of 85 Streptococcal protein G domain β1 sequences. Ensembles tested here include an NMR ensemble as well as those generated by molecular dynamics (MD) simulations, by Backrub motions, and by PertMin, a new method that we developed involving the perturbation of atomic coordinates followed by energy minimization. MSD with the PertMin ensembles resulted in the most accurate predictions by providing the highest number of stable sequences in the top 25, and by correctly binning sequences as stable or unstable with the highest success rate (≈90%) and the lowest number of false positives. The performance of PertMin ensembles is due to the fact that their members closely resemble the input crystal structure and have low potential energy. Conversely, the NMR ensemble as well as those generated by MD simulations at 500 or 1000 K reduced prediction accuracy due to their low structural similarity to the crystal structure. The ensembles tested herein thus represent on‐ or off‐target models of the native protein fold and could be used in future studies to design for desired properties other than stability. Proteins 2014; 82:771–784.

Nerve Agent Hydrolysis Activity Designed into a Human Drug Metabolism Enzyme

Organophosphorus (OP) nerve agents are potent suicide inhibitors of the essential neurotransmitter-regulating enzyme acetylcholinesterase. Due to their acute toxicity, there is significant interest in developing effective countermeasures to OP poisoning. Here we impart nerve agent hydrolysis activity into the human drug metabolism enzyme carboxylesterase 1. Using crystal structures of the target enzyme in complex with nerve agent as a guide, a pair of histidine and glutamic acid residues were designed proximal to the enzymes native catalytic triad. The resultant variant protein demonstrated significantly increased rates of reactivation following exposure to sarin, soman, and cyclosarin. Importantly, the addition of these residues did not alter the high affinity binding of nerve agents to this protein. Thus, using two amino acid substitutions, a novel enzyme was created that efficiently converted a group of hemisubstrates, compounds that can start but not complete a reaction cycle, into bona fide substrates. Such approaches may lead to novel countermeasures for nerve agent poisoning.

Discovery of Substrates for a SET Domain Lysine Methyltransferase Predicted by Multistate Computational Protein Design

Characterization of lysine methylation has proven challenging despite its importance in biological processes such as gene transcription, protein turnover, and cytoskeletal organization. In contrast to other key posttranslational modifications, current proteomics techniques have thus far shown limited success at characterizing methyl-lysine residues across the cellular landscape. To complement current biochemical characterization methods, we developed a multistate computational protein design procedure to probe the substrate specificity of the protein lysine methyltransferase SMYD2. Modeling of substrate-bound SMYD2 identified residues important for substrate recognition and predicted amino acids necessary for methylation. Peptide- and protein- based substrate libraries confirmed that SMYD2 activity is dictated by the motif [LFM]-1-K(∗)-[AFYMSHRK]+1-[LYK]+2 around the target lysine K(∗). Comprehensive motif-based searches and mutational analysis further established four additional substrates of SMYD2. Our methodology paves the way to systematically predict and validate posttranslational modification sites while simultaneously pairing them with their associated enzymes.

Bioanalysis for Biocatalysis: Multiplexed Capillary Electrophoresis–Mass Spectrometry Assay for Aminotransferase Substrate Discovery and Specificity Profiling

In this work, we introduce an entirely automated enzyme assay based on capillary electrophoresis coupled to electrospray ionization mass spectrometry termed MINISEP-MS for multiple interfluent nanoinjections-incubation-separation-enzyme profiling using mass spectrometry. MINISEP-MS requires only nanoliters of reagent solutions and uses the separation capillary as a microreactor, allowing multiple substrates to be assayed simultaneously. The method can be used to rapidly profile the substrate specificity of any enzyme and to measure steady-state kinetics in an automated fashion. We used the MINISEP-MS assay to profile the substrate specificity of three aminotransferases (E. coli aspartate aminotransferase, E. coli branched-chain amino acid aminotransferase, and Bacillus sp. YM-1 D-amino acid aminotransferase) for 33 potential amino acid substrates and to measure steady-state kinetics. Using MINISEP-MS, we were able to recapitulate the known substrate specificities and to discover new amino acid substrates for these industrially relevant enzymes. Additionally, we were able to measure the apparent K(M) and k(cat) parameters for amino acid donor substrates of these aminotransferases. Because of its many advantages, the MINISEP-MS assay has the potential of becoming a useful tool for researchers aiming to identify or create novel enzymes for specific biocatalytic applications.

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 β1. 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.

A high-throughput assay for screening L- or D-amino acid specific aminotransferase mutant libraries.

Aminotransferases are pyridoxal phosphate-dependent enzymes whose potential for the biocatalytic production of enantiopure amino acids is increasingly recognized. Because of this, there is a growing interest in engineering them to alter their substrate specificity and to increase their catalytic activity. Here, we report the development of a high-throughput assay for screening α-ketoglutarate-dependent aminotransferase mutant libraries. To achieve this, we exploited the L-glutamate dehydrogenase coupled assay that has previously been shown to allow for aminotransferase activity to be monitored in vitro. We adapted this assay to allow screening of mutant libraries of either L- or D-amino acid specific aminotransferases in a continuous fashion. This assay requiring clarified cell lysates is reproducible, rapid, and sensitive because it allowed for the identification of a catalytically active mutant of Bacillus sp. YM-1 D-amino acid aminotransferase displaying a decrease in k(cat)/K(M) of more than two orders of magnitude. In addition, this assay allowed us to discover a mutant of Escherichia coli branched-chain amino acid aminotransferase, F36W, which is approximately 60-fold more specific toward the natural substrate L-leucine than L-phenylalanine as compared with wild type. This result demonstrates the potential of our assay for the discovery of mutant aminotransferases displaying altered substrate specificity, an important goal of enzyme engineering.