Predicting Productive Binding Modes for Substrates and Carbocation Intermediates in Terpene SynthasesBornyl Diphosphate Synthase As a Representative Case

Terpene synthases comprise a family of enzymes that convert acyclic oligo-isoprenyl diphosphates to terpene natural products with complex, polycyclic carbon backbones via the generation and protection of carbocation intermediates. To accommodate this chemistry, terpene synthase active sites generally are lined with alkyl and aromatic, i.e., nonpolar, side chains. Predicting the correct, mechanistically relevant binding modes for entire terpene synthase reaction pathways remains an unsolved challenge. Here, we describe a method for identifying such modes: <i>TerDockin</i>, a series of protocols to predict the orientation of carbon skeletons of substrates and derived carbocations relative to the bound diphosphate group in terpene synthase active sites. Using this recipe for bornyl diphosphate synthase, we have predicted binding modes that are consistent with all current experimental observations, including the results of isotope labeling experiments and known stereoselectivity. In addition, the predicted binding modes recapitulate key findings of a seminal study involving more computationally demanding QM/MM molecular dynamics methods on part of this pathway. This work illustrates the value of the <i>TerDockin</i> approach as a starting point for more involved calculations and sets the stage for the rational engineering of this family of enzymes

Predicting Productive Binding Modes for Substrates and Carbocation Intermediates in Terpene SynthasesBornyl Diphosphate Synthase As a Representative Case

Terpene synthases comprise a family of enzymes that convert acyclic oligo-isoprenyl diphosphates to terpene natural products with complex, polycyclic carbon backbones via the generation and protection of carbocation intermediates. To accommodate this chemistry, terpene synthase active sites generally are lined with alkyl and aromatic, i.e., nonpolar, side chains. Predicting the correct, mechanistically relevant binding modes for entire terpene synthase reaction pathways remains an unsolved challenge. Here, we describe a method for identifying such modes: <i>TerDockin</i>, a series of protocols to predict the orientation of carbon skeletons of substrates and derived carbocations relative to the bound diphosphate group in terpene synthase active sites. Using this recipe for bornyl diphosphate synthase, we have predicted binding modes that are consistent with all current experimental observations, including the results of isotope labeling experiments and known stereoselectivity. In addition, the predicted binding modes recapitulate key findings of a seminal study involving more computationally demanding QM/MM molecular dynamics methods on part of this pathway. This work illustrates the value of the <i>TerDockin</i> approach as a starting point for more involved calculations and sets the stage for the rational engineering of this family of enzymes

Predicting Productive Binding Modes for Substrates and Carbocation Intermediates in Terpene SynthasesBornyl Diphosphate Synthase As a Representative Case

Terpene synthases comprise a family of enzymes that convert acyclic oligo-isoprenyl diphosphates to terpene natural products with complex, polycyclic carbon backbones via the generation and protection of carbocation intermediates. To accommodate this chemistry, terpene synthase active sites generally are lined with alkyl and aromatic, i.e., nonpolar, side chains. Predicting the correct, mechanistically relevant binding modes for entire terpene synthase reaction pathways remains an unsolved challenge. Here, we describe a method for identifying such modes: <i>TerDockin</i>, a series of protocols to predict the orientation of carbon skeletons of substrates and derived carbocations relative to the bound diphosphate group in terpene synthase active sites. Using this recipe for bornyl diphosphate synthase, we have predicted binding modes that are consistent with all current experimental observations, including the results of isotope labeling experiments and known stereoselectivity. In addition, the predicted binding modes recapitulate key findings of a seminal study involving more computationally demanding QM/MM molecular dynamics methods on part of this pathway. This work illustrates the value of the <i>TerDockin</i> approach as a starting point for more involved calculations and sets the stage for the rational engineering of this family of enzymes

Systematic Functional Analysis of Active-Site Residues in l‑Threonine Dehydrogenase from Thermoplasma volcanium

Enzymes have been through millions of years of evolution during which their active-site microenvironments are fine-tuned. Active-site residues are commonly conserved within protein families, indicating their importance for substrate recognition and catalysis. In this work, we systematically mutated active-site residues of l-threonine dehydrogenase from Thermoplasma volcanium and characterized the mutants against a panel of substrate analogs. Our results demonstrate that only a subset of these residues plays an essential role in substrate recognition and catalysis and that the native enzyme activity can be further enhanced roughly 4.6-fold by a single point mutation. Kinetic characterization of mutants on substrate analogs shows that l-threonine dehydrogenase possesses promiscuous activities toward other chemically similar compounds not previously observed. Quantum chemical calculations on the hydride-donating ability of these substrates also reveal that this enzyme did not evolve to harness the intrinsic substrate reactivity for enzyme catalysis. Our analysis provides insights into connections between the details of enzyme active-site structure and specific function. These results are directly applicable to rational enzyme design and engineering

Data_Sheet_1_Acid-active proteases to optimize dietary protein digestibility: a step towards sustainable nutrition.docx

IntroductionHistorically, prioritizing abundant food production often resulted in overlooking nutrient quality and bioavailability, however, environmental concerns have now propelled sustainable nutrition and health efficacy to the forefront of global attention. In fact, increasing demand for protein is the major challenge facing the food system in the 21st century with an estimation that 70% more food is needed by 2050. This shift has spurred interest in plant-based proteins for their sustainability and health benefits, but most alternative sources of protein are poorly digestible. There are two approaches to solve digestibility: improve the digestibility of food proteins or improve the digestive capacity of consumers. Enhancing nutrient digestibility and bioavailability across diverse protein sources is crucial, with proteases presenting a promising avenue. Research, inspired by the proteases of human breast milk, has demonstrated that exogenous microbial proteases can activate within the human digestive tract and substantially increase the digestion of targeted proteins that are otherwise difficult to fully digest.MethodsHere, we introduce the use of an acid-active family of bacterial proteases (S53) to improve the digestibility and nutritional quality of a variety of protein sources, evaluated using the INFOGEST 2.0 protocol.ResultsResults from in vitro digestibility indicate that the most effective protease in the S53 family substantially improves the digestibility of an array of animal and plant-derived proteins—soy, pea, chickpea, rice, casein, and whey. On average, this protease elevated protein digestibility by 115% during the gastric phase and by 15% in the intestinal phase, based on the degree of hydrolysis.DiscussionThe widespread adoption of these proteases has the potential to enhance nutritional value and contribute to food security and sustainability. This approach would complement ongoing efforts to improve proteins in the food supply, increase the quality of more sustainable protein sources and aid in the nourishment of patients with clinically compromised, fragile intestines and individuals like older adults and high-performance athletes who have elevated protein needs.</p

Thermal stability and kinetic constants for 129 variants of a family 1 glycoside hydrolase reveal that enzyme activity and stability can be separately designed

<div><p>Accurate modeling of enzyme activity and stability is an important goal of the protein engineering community. However, studies seeking to evaluate current progress are limited by small data sets of quantitative kinetic constants and thermal stability measurements. Here, we report quantitative measurements of soluble protein expression in <i>E</i>. <i>coli</i>, thermal stability, and Michaelis-Menten constants (<i>k</i>_cat, K_M, and <i>k</i>_cat/K_M) for 129 designed mutants of a glycoside hydrolase. Statistical analyses reveal that functional T_m is independent of <i>k</i>_cat, K_M, and <i>k</i>_cat/K_M in this system, illustrating that an individual mutation can modulate these functional parameters independently. In addition, this data set is used to evaluate computational predictions of protein stability using the established Rosetta and FoldX algorithms. Predictions for both are found to correlate only weakly with experimental measurements, suggesting improvements are needed in the underlying algorithms.</p></div

Relative effects on enzyme functional parameters for 129 mutants of BglB.

<p>Each mutant gets a bar with six colored boxes, depicting 1) soluble protein expression, 2) T_m, 3) <i>k</i>_cat, 4) K_M, 5) <i>k</i>_cat/K_M, and 6) conservation within Pfam GH01. For expression (box 1), a black box indicates soluble expression > 0.10 mg/mL, and a white box indicates expression < 0.10 mg/mL in <i>E</i>. <i>coli</i> BLR (DE3). For T_m (box 2), a linear scale is used to depict change in T_m compared to wild type, with mutants with greater T_m in green, and those with lower T_m in purple. For <i>k</i>_cat, 1/K_M, and <i>k</i>_cat/K_M (boxes 3–5), blue indicates lower values, and orange indicates higher values relative to the wild type value, as indicated by the color legend (top). For conservation (box 6), the frequency of native BglB residue in an alignment of the BglB sequence to 1,554 sequences from Pfam GH01 is shown, on a linear scale from 0% to 100%. The quantitative measurements used to produce this illustration are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176255#pone.0176255.s001" target="_blank">S1 Table</a>.</p

Correlations between experimentally-determined T_m and structural features from molecular modeling algorithms.

<p>For each of the three computational protocols used for prediction of stability in this study, the two most-correlated (black) and two least-correlated (gray) features are plotted against experimentally-determined T_m. Pearson correlation between the two sets of values is provided above each plot. For descriptions of individual features for each of the three algorithms, see references for RosettaDesign [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176255#pone.0176255.ref011" target="_blank">11</a>], Rosetta ΔΔG [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176255#pone.0176255.ref012" target="_blank">12</a>], and FoldX [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176255#pone.0176255.ref009" target="_blank">9</a>].</p

Correlations between conservation within functional protein family and enzyme functional parameters protein melting temperature (T_m) and kinetic constants (<i>k</i>_cat, K_M, and <i>k</i>_cat/K_M) in the BglB system.

<p>Scatter plots showing conservation analysis from an alignment of 1,554 proteins in Pfam family 1 (glycoside hydrolases) versus measured values for T_m (linear scale, units of °C) and each of the kinetic constants <i>k</i>_cat, K_M, and <i>k</i>_cat/K_M (log scale) with units of min^–1, mM, and M^–1min^–1, respectively.</p

Structural analysis of Rosetta models of designed point mutants of BglB with effects on thermal stability.

<p>Four mutant panels are shown, sorted from left to right by increasing T_m. In the top panel, experimentally-determined change in T_m and k_cat/K_M are given. For reference, the T_m for the wild type sequence is 39.9°C, and the <i>k</i>_cat/K_M is 174,000 M^–1min^–1. In the next panel down, sequence logos depict the local area of sequence conservation based on an alignment of 1,544 sequences from Pfam GH01. At bottom, depictions of the local area of the mutation in the BglB WT protein (top) and RosettaDesign model of mutation (bottom).</p