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 (/ 125 M s) and KE70 (/ 57 M s), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently.

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 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 (/ 125 M s) and KE70 (/ 57 M s), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently.

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.

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.

Generation of bright monomeric red fluorescent proteins 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.

Personalized oncology and BRAF 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 BRAF 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 BRAF melanoma and subsequently develop a novel personalized oncology platform for rare or treatment-refractory cancers.

Genetically Encoded Fluorescent Biosensor for Rapid Detection of Protein Expression.

Fluorescent proteins are widely used as fusion tags to detect protein expression . 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.

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 (k/K 146 Ms).

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 β1 variant that we previously designed to undergo a specific mode of conformational exchange that has never been observed in the wild-type protein.

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.

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.

Selective α-Synuclein Knockdown in Monoamine Neurons by Intranasal Oligonucleotide Delivery: Potential Therapy for Parkinson's Disease.

Progressive neuronal death in brainstem nuclei and widespread accumulation of α-synuclein are neuropathological hallmarks of Parkinson's disease (PD). Reduction of α-synuclein levels is therefore a potential therapy for PD. However, because α-synuclein is essential for neuronal development and function, α-synuclein elimination would dramatically impact brain function.

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.

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.

Brighter Red Fluorescent Proteins by Rational Design of Triple-Decker Motif.

Red fluorescent proteins (RFPs) are used extensively in chemical biology research as fluorophores for live cell imaging, as partners in FRET pairs, and as signal transducers in biosensors. For all of these applications, brighter RFP variants are desired. Here, we used rational design to increase the quantum yield of monomeric RFPs in order to improve their brightness.

Prediction of Stable Globular Proteins Using Negative Design with Non-native Backbone Ensembles.

Accurate predictions of protein stability have great potential to accelerate progress in computational protein design, yet the correlation of predicted and experimentally determined stabilities remains a significant challenge. To address this problem, we have developed a computational framework based on negative multistate design in which sequence energy is evaluated in the context of both native and non-native backbone ensembles. This framework was validated experimentally with the design of ten variants of streptococcal protein G domain β1 that retained the wild-type fold, and showed a very strong correlation between predicted and experimental stabilities (R(2) = 0.