Computational structure-based redesign of enzyme activity.
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ABSTRACT:
SUBMITTER: Chen CY
PROVIDER: S-EPMC2645347 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationDisruption of protein-protein interactions can mitigate antibody recognition of therapeutic proteins, yield monomeric forms of oligomeric proteins, and elucidate signaling mechanisms, among other applications. While designing affinity-enhancing mutations remains generally quite challenging, both statistically and physically based computational methods can precisely identify affinity-reducing mutations. In order to leverage this ability to design variants of a target protein with disrupted interactions, we developed the DisruPPI protein design method (DISRUpting Protein-Protein Interactions) to optimize combinations of mutations simultaneously for both disruption and stability, so that incorporated disruptive mutations do not inadvertently affect the target protein adversely.ResultsTwo existing methods for predicting mutational effects on binding, FoldX and INT5, were demonstrated to be quite precise in selecting disruptive mutations from the SKEMPI and AB-Bind databases of experimentally determined changes in binding free energy. DisruPPI was implemented to use an INT5-based disruption score integrated with an AMBER-based stability assessment and was applied to disrupt protein interactions in a set of different targets representing diverse applications. In retrospective evaluation with three different case studies, comparison of DisruPPI-designed variants to published experimental data showed that DisruPPI was able to identify more diverse interaction-disrupting and stability-preserving variants more efficiently and effectively than previous approaches. In prospective application to an interaction between enhanced green fluorescent protein (EGFP) and a nanobody, DisruPPI was used to design five EGFP variants, all of which were shown to have significantly reduced nanobody binding while maintaining function and thermostability. This demonstrates that DisruPPI may be readily utilized for effective removal of known epitopes of therapeutically relevant proteins.Availability and implementationDisruPPI is implemented in the EpiSweep package, freely available under an academic use license.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:OptZyme is a new computational procedure for designing improved enzymatic activity (i.e., kcat or kcat/KM) with a novel substrate. The key concept is to use transition state analogue compounds, which are known for many reactions, as proxies for the typically unknown transition state structures. Mutations that minimize the interaction energy of the enzyme with its transition state analogue, rather than with its substrate, are identified that lower the transition state formation energy barrier. Using Escherichia coli β-glucuronidase as a benchmark system, we confirm that KM correlates (R(2) = 0.960) with the computed interaction energy between the enzyme and the para-nitrophenyl- β, D-glucuronide substrate, kcat/KM correlates (R(2) = 0.864) with the interaction energy of the transition state analogue, 1,5-glucarolactone, and kcat correlates (R(2) = 0.854) with a weighted combination of interaction energies with the substrate and transition state analogue. OptZyme is subsequently used to identify mutants with improved KM, kcat, and kcat/KM for a new substrate, para-nitrophenyl- β, D-galactoside. Differences between the three libraries reveal structural differences that underpin improving KM, kcat, or kcat/KM. Mutants predicted to enhance the activity for para-nitrophenyl- β, D-galactoside directly or indirectly create hydrogen bonds with the altered sugar ring conformation or its substituents, namely H162S, L361G, W549R, and N550S.
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Project description:The escalating demand for biocatalysts in pharmaceutical and biochemical applications underscores the critical imperative to enhance enzyme activity and durability under high denaturant concentrations. Nevertheless, the development of a practical computational redesign protocol for improving enzyme tolerance to denaturants is challenging due to the limitations of relying solely on model-driven approaches to adequately capture denaturant-enzyme interactions. In this study, we introduce an enzyme redesign strategy termed GRAPE_DA, which integrates multiple data-driven and model-driven computational methods to mitigate the sampling biases inherent in a single approach and comprehensively predict beneficial mutations on both the protein surface and backbone. To illustrate the methodology's effectiveness, we applied it to engineer a peptidylamidoglycolate lyase, resulting in a variant exhibiting up to a 24-fold increase in peptide C-terminal amidation activity under 2.5 M guanidine hydrochloride. We anticipate that this integrated engineering strategy will facilitate the development of enzymatic peptide synthesis and functionalization under denaturing conditions and highlight the role of engineering surface residues in governing protein stability.
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Project description:As the spread of antibiotic resistant bacteria steadily increases, there is an urgent need for new antibacterial agents. Because fatty acid synthesis is only used for membrane biogenesis in bacteria, the enzymes in this pathway are attractive targets for antibacterial agent development. Acetyl-CoA carboxylase catalyzes the committed and regulated step in fatty acid synthesis. In bacteria, the enzyme is composed of three distinct protein components: biotin carboxylase, biotin carboxyl carrier protein, and carboxyltransferase. Fragment-based screening revealed that amino-oxazole inhibits biotin carboxylase activity and also exhibits antibacterial activity against Gram-negative organisms. In this report, we redesigned previously identified lead inhibitors to expand the spectrum of bacteria sensitive to the amino-oxazole derivatives by including Gram-positive species. Using 9,411 small organic building blocks, we constructed a diverse combinatorial library of 1.2×10⁸ amino-oxazole derivatives. A subset of 9×10⁶ of these compounds were subjected to structure-based virtual screening against seven biotin carboxylase isoforms using similarity-based docking by eSimDock. Potentially broad-spectrum antibiotic candidates were selected based on the consensus ranking by several scoring functions including non-linear statistical models implemented in eSimDock and traditional molecular mechanics force fields. The analysis of binding poses of the top-ranked compounds docked to biotin carboxylase isoforms suggests that: (1) binding of the amino-oxazole anchor is stabilized by a network of hydrogen bonds to residues 201, 202 and 204; (2) halogenated aromatic moieties attached to the amino-oxazole scaffold enhance interactions with a hydrophobic pocket formed by residues 157, 169, 171 and 203; and (3) larger substituents reach deeper into the binding pocket to form additional hydrogen bonds with the side chains of residues 209 and 233. These structural insights into drug-biotin carboxylase interactions will be tested experimentally in in vitro and in vivo systems to increase the potency of amino-oxazole inhibitors towards both Gram-negative as well as Gram-positive species.
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Project description:DNA polymerases have evolved to feature a highly conserved activity across the tree of life: formation of, without exception, internucleotidyl O-P linkages. Can this linkage selectivity be overcome by design to produce xenonucleic acids? Here, we report that the structure-guided redesign of an archaeal DNA polymerase, 9°N, exhibits a new activity undetectable in the wild-type enzyme: catalyzing the formation of internucleotidyl N-P linkages using 3'-NH2-ddNTPs. Replacing a metal-binding aspartate in the 9°N active site with asparagine was key to the emergence of this unnatural enzyme activity. MD simulations provided insights into how a single substitution enhances the productive positioning of a 3'-amino nucleophile in the active site. Further remodeling of the protein-nucleic acid interface in the finger subdomain yielded a quadruple-mutant variant (9°N-NRQS) displaying DNA-dependent NP-DNA polymerase activity. In addition, the engineered promiscuity of 9°N-NRQS was leveraged for one-pot synthesis of DNA─NP-DNA copolymers. This work sheds light on the molecular basis of substrate fidelity and latent promiscuity in enzymes.
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Project description:Edema factor (EF) toxin of Bacillus anthracis (NIAID category A), and several other toxins from NIAID category B Biodefense target bacteria are adenylyl cyclases or adenylyl cyclase agonists that catalyze the conversion of ATP to 3',5'-cyclic adenosine monophosphate (cAMP). We previously identified compound 1 (3-[(9-oxo-9H-fluorene-1-carbonyl)-amino]-benzoic acid), that inhibits EF activity in cultured mammalian cells, and reduces diarrhea caused by enterotoxigenic Escherichia coli (ETEC) at an oral dosage of 15?g/mouse. Here, molecular docking was used to predict improvements in potency and solubility of new derivatives of compound 1 in inhibiting edema toxin (ET)-catalyzed stimulation of cyclic AMP production in murine monocyte-macrophage cells (RAW 264.7). Structure-activity relationship (SAR) analysis of the bioassay results for 22 compounds indicated positions important for activity. Several derivatives demonstrated superior pharmacological properties compared to our initial lead compound, and are promising candidates to treat anthrax infections and diarrheal diseases induced by toxin-producing bacteria.
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Project description:Computational protein design relies on several approximations, including the use of fixed backbones and rotamers, to reduce protein design to a computationally tractable problem. However, allowing backbone and off-rotamer flexibility leads to more accurate designs and greater conformational diversity. Exhaustive sampling of this additional conformational space is challenging, and often impossible. Here, we report a computational method that utilizes a preselected library of native interactions to direct backbone flexibility to accommodate placement of these functional contacts. Using these native interaction modules, termed motifs, improves the likelihood that the interaction can be realized, provided that suitable backbone perturbations can be identified. Furthermore, it allows a directed search of the conformational space, reducing the sampling needed to find low energy conformations. We implemented the motif-based design algorithm in Rosetta, and tested the efficacy of this method by redesigning the substrate specificity of methionine aminopeptidase. In summary, native enzymes have evolved to catalyze a wide range of chemical reactions with extraordinary specificity. Computational enzyme design seeks to generate novel chemical activities by altering the target substrates of these existing enzymes. We have implemented a novel approach to redesign the specificity of an enzyme and demonstrated its effectiveness on a model system.
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