Terpenoid synthases create diverse carbon skeletons by catalyzing complex carbocation rearrangements, making them particularly challenging for enzyme function prediction. To begin to address this challenge, we have developed a computational approach for the systematic enumeration of terpenoid carbocations. Application of this approach allows us to systematically define a nearly complete chemical space for the potential carbon skeletons of products from monoterpenoid synthases. Specifically, 18758 carbocations were generated, which we cluster into 74 cyclic skeletons. Five of the 74 skeletons are found in known natural products; some of the others are plausible for new functions, either in nature or engineered. This work systematizes the description of function for this class of enzymes, and provides a basis for predicting functions of uncharacterized enzymes. To our knowledge, this is the first computational study to explore the complete product chemical space of this important class of enzymes.

The biosynthetic pathways to isoprenoid compounds involve transfer of the prenyl moiety in allylic diphosphates to electron-rich (nucleophilic) acceptors. The acceptors can be many types of nucleophiles, while the allylic diphosphates only differ in the number of isoprene units and stereochemistry of the double bonds in the hydrocarbon moieties. Because of the wide range of nucleophilicities of naturally occurring acceptors, the mechanism for prenyltransfer reactions may be dissociative or associative with early to late transition states. We have measured δ-secondary kinetic isotope effects operating through four bonds for substitution reactions with dimethylallyl derivatives bearing deuterated methyl groups at the distal (C3) carbon atom in the double bond under dissociative and associative conditions. Computational studies with density functional theory indicate that the magnitudes of the isotope effects correlate with the extent of bond formation between the allylic moiety and the electron-rich acceptor in the transition state for alkylation and provide insights into the structures of the transition states for associative and dissociative alkylation reactions.

Terpenoids are a large structurally diverse group of natural products with an array of functions in their hosts. The large amount of genomic information from recent sequencing efforts provides opportunities and challenges for the functional assignment of terpene synthases that construct the carbon skeletons of these compounds. Inferring function from the sequence and/or structure of these enzymes is not trivial because of the large number of possible reaction channels and products. We tackle this problem by developing an algorithm to enumerate possible carbocations derived from the farnesyl cation, the first reactive intermediate of the substrate, and evaluating their steric and electrostatic compatibility with the active site. The homology model of a putative pentalenene synthase (Uniprot: B5GLM7) from Streptomyces clavuligerus was used in an automated computational workflow for product prediction. Surprisingly, the workflow predicted a linear triquinane scaffold as the top product skeleton for B5GLM7. Biochemical characterization of B5GLM7 reveals the major product as (5S,7S,10R,11S)-cucumene, a sesquiterpene with a linear triquinane scaffold. To our knowledge, this is the first documentation of a terpene synthase involved in the synthesis of a linear triquinane. The success of our prediction for B5GLM7 suggests that this approach can be used to facilitate the functional assignment of novel terpene synthases.

The number of available protein sequences has increased exponentially with the advent of high-throughput genomic sequencing, creating a significant challenge for functional annotation. Here, we describe a large-scale study on assigning function to unknown members of the trans-polyprenyl transferase (E-PTS) subgroup in the isoprenoid synthase superfamily, which provides substrates for the biosynthesis of the more than 55,000 isoprenoid metabolites. Although the mechanism for determining the product chain length for these enzymes is known, there is no simple relationship between function and primary sequence, so that assigning function is challenging. We addressed this challenge through large-scale bioinformatics analysis of >5,000 putative polyprenyl transferases; experimental characterization of the chain-length specificity of 79 diverse members of this group; determination of 27 structures of 19 of these enzymes, including seven cocrystallized with substrate analogs or products; and the development and successful application of a computational approach to predict function that leverages available structural data through homology modeling and docking of possible products into the active site. The crystallographic structures and computational structural models of the enzyme-ligand complexes elucidate the structural basis of specificity. As a result of this study, the percentage of E-PTS sequences similar to functionally annotated ones (BLAST e-value ≤ 1e(-70)) increased from 40.6 to 68.8%, and the percentage of sequences similar to available crystal structures increased from 28.9 to 47.4%. The high accuracy of our blind prediction of newly characterized enzymes indicates the potential to predict function to the complete polyprenyl transferase subgroup of the isoprenoid synthase superfamily computationally.