Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using "Backrub" motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.

Major efforts in bioenergy research have focused on producing fuels that can directly replace petroleum-derived gasoline and diesel fuel through metabolic engineering of microbial fatty acid biosynthetic pathways. Typically, growth and pathway induction are conducted under aerobic conditions, but for operational efficiency in an industrial context, anaerobic culture conditions would be preferred to obviate the need to maintain specific dissolved oxygen concentrations and to maximize the proportion of reducing equivalents directed to biofuel biosynthesis rather than ATP production. A major concern with fermentative growth conditions is elevated NADH levels, which can adversely affect cell physiology. The purpose of this study was to identify homologs of Escherichia coli FabG, an essential reductase involved in fatty acid biosynthesis, that display a higher preference for NADH than for NADPH as a cofactor. Four potential NADH-dependent FabG variants were identified through bioinformatic analyses supported by crystallographic structure determination (1.3- to 2.0-Å resolution). In vitro assays of cofactor (NADH/NADPH) preference in the four variants showed up to ≈ 35-fold preference for NADH, which was observed with the Cupriavidus taiwanensis FabG variant. In addition, FabG homologs were overexpressed in fatty acid- and methyl ketone-overproducing E. coli host strains under anaerobic conditions, and the C. taiwanensis variant led to a 60% higher free fatty acid titer and 75% higher methyl ketone titer relative to the titers of the control strains. With further engineering, this work could serve as a starting point for establishing a microbial host strain for production of fatty acid-derived biofuels (e.g., methyl ketones) under anaerobic conditions.

Harnessing the biotechnological potential of the large number of proteins available in sequence databases requires scalable methods for functional characterization. Here we propose a workflow to address this challenge by combining phylogenomic guided DNA synthesis with high-throughput mass spectrometry and apply it to the systematic characterization of GH1 β-glucosidases, a family of enzymes necessary for biomass hydrolysis, an important step in the conversion of lignocellulosic feedstocks to fuels and chemicals. We synthesized and expressed 175 GH1s, selected from over 2000 candidate sequences to cover maximum sequence diversity. These enzymes were functionally characterized over a range of temperatures and pHs using nanostructure-initiator mass spectrometry (NIMS), generating over 10,000 data points. When combined with HPLC-based sugar profiling, we observed GH1 enzymes active over a broad temperature range and toward many different β-linked disaccharides. For some GH1s we also observed activity toward laminarin, a more complex oligosaccharide present as a major component of macroalgae. An area of particular interest was the identification of GH1 enzymes compatible with the ionic liquid 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]), a next-generation biomass pretreatment technology. We thus searched for GH1 enzymes active at 70 °C and 20% (v/v) [C2mim][OAc] over the course of a 24-h saccharification reaction. Using our unbiased approach, we identified multiple enzymes of different phylogentic origin with such activities. Our approach of characterizing sequence diversity through targeted gene synthesis coupled to high-throughput screening technologies is a broadly applicable paradigm for a wide range of biological problems.