The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein-ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the wellcharacterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.

ω-Transaminases (ω-TAs) catalyze the conversion of ketones to chiral amines, often with high enantioselectivity and specificity, which makes them attractive for industrial production of chiral amines. Tailoring ω-TAs to accept non-natural substrates is necessary because of their limited substrate range. We present a computational protocol for predicting the enantioselectivity and catalytic selectivity of an ω-TA from Vibrio fluvialis with different substrates and benchmark it against 62 compounds gathered from the literature. Rosetta-generated complexes containing an external aldimine intermediate of the transamination reaction are used as starting conformations for multiple short independent molecular dynamics (MD) simulations. The combination of molecular docking and MD simulations ensures sufficient and accurate sampling of the relevant conformational space. Based on the frequency of near-attack conformations observed during the MD trajectories, enantioselectivities can be quantitatively predicted. The predicted enantioselectivities are in agreement with a benchmark dataset of experimentally determined ee% values. The substrate-range predictions can be based on the docking score of the external aldimine intermediate. The low computational cost required to run the presented framework makes it feasible for use in enzyme design to screen thousands of enzyme variants.

ω-Transaminases (ω-TA) are attractive biocatalysts for the production of chiral amines from prochiral ketones via asymmetric synthesis. However, the substrate scope of ω-TAs is usually limited due to steric hindrance at the active site pockets. We explored a protein engineering strategy using computational design to expand the substrate scope of an ( S )-selective ω-TA from Pseudomonas jessenii ( Pj TA-R6) toward the production of bulky amines. Pj TA-R6 is attractive for use in applied biocatalysis due to its thermostability, tolerance to organic solvents, and acceptance of high concentrations of isopropylamine as amino donor. Pj TA-R6 showed no detectable activity for the synthesis of six bicyclic or bulky amines targeted in this study. Six small libraries composed of 7–18 variants each were separately designed via computational methods and tested in the laboratory for ketone to amine conversion. In each library, the vast majority of the variants displayed the desired activity, and of the 40 different designs, 38 produced the target amine in good yield with >99% enantiomeric excess. This shows that the substrate scope and enantioselectivity of Pj TA mutants could be predicted in silico with high accuracy. The single mutant W58G showed the best performance in the synthesis of five structurally similar bulky amines containing the indan and tetralin moieties. The best variant for the other bulky amine, 1-phenylbutylamine, was the triple mutant W58M + F86L + R417L, indicating that Trp58 is a key residue in the large binding pocket for Pj TA-R6 redesign. Crystal structures of the two best variants confirmed the computationally predicted structures. The results show that computational design can be an efficient approach to rapidly expand the substrate scope of ω-TAs to produce enantiopure bulky amines.

The production of chiral amines by transaminase-catalyzed amination of ketones is an important application of biocatalysis in synthetic chemistry. It requires transaminases that show high enantioselectivity in asymmetric conversion of the ketone precursors. A robust derivative of ω-transaminase from Pseudomonasjessenii (PjTA-R6) that naturally acts on aliphatic substrates was constructed previously by our group. Here, we explore the catalytic potential of this thermostable enzyme for the synthesis of optically pure aliphatic amines and compare it to the well-studied transaminases from Vibrio fluvialis (VfTA) and Chromobacterium violaceum (CvTA). The product yields indicated improved performance of PjTA-R6 over the other transaminases, and in most cases, the optical purity of the produced amine was above 99% enantiomeric excess (e.e.). Structural analysis revealed that the substrate binding poses were influenced and restricted by the switching arginine and that this accounted for differences in substrate specificities. Rosetta docking calculations with external aldimine structures showed a correlation between docking scores and synthetic yields. The results show that PjTA-R6 is a promising biocatalyst for the asymmetric synthesis of aliphatic amines with a product spectrum that can be explained by its structural features.

Processivity is an important feature of enzyme families such as DNA polymerases, polysaccharide synthases, and protein kinases, to ensure high fidelity in biopolymer synthesis and modification. Here, we reveal processive character in the family of cytoplasmic protein N-glycosyltransferases (NGTs). Through various activity assays, intact protein mass spectrometry, and proteomics analysis, we established that NGTs from nontypeable Haemophilus influenzae and Actinobacillus pleuropneumoniae modify an adhesin protein fragment in a semiprocessive manner. Molecular modeling studies suggest that the processivity arises from the shallow substrate binding groove in NGT, which promotes the sliding of the adhesin over the surface to allow further glycosylations without temporary dissociation. We hypothesize that the processive character of these bacterial protein glycosyltransferases is the mechanism to ensure multisite glycosylation of adhesins in vivo, thereby creating the densely glycosylated proteins necessary for bacterial self-aggregation and adherence to human cells, as a first step toward infection.