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The recently discovered unspecific peroxygenases (UPOs) from the ascomycetes Chaetomium globosumand Humicola insolenswere capable of selectively hydroxylating isophorone to 4-hydroxyisophorone (4HIP) and 4-ketoisophorone (4KIP), which are substrates of interest for the pharmaceutical and flavor-and-fragrance sectors. The model UPO from the basidiomycete Agrocybe aegeritawas less regioselective, forming 7-hydroxyisophorone (and 7-formylisophorone) in addition to 4HIP. However, it was the most stereoselective UPO yielding the S-enantiomer of 4HIP with 88% ee. Moreover, using H. insolensUPO full kinetic resolution of racemic HIP was obtained within only 15 min, with >75% recovery of the R-enantiomer. Surprisingly, the UPOs from two other basidiomycetes, Marasmius rotulaand Coprinopsis cinerea, failed to transform isophorone. The different UPO selectivities were rationalized by computational simulations, in which isophorone and 4HIP were diffused into the enzymes using the adaptive PELE software, and the distances from heme-bound oxygen in H2O2-activated enzyme to different substrate atoms, and the corresponding binding energies were analyzed. Interestingly, for process upscaling, full conversion of 10 mM isophorone was achieved with H. insolensUPO within nine hours, with total turnover numbers up to 5500. These biocatalysts, which only require H2O2for activation, may represent a novel, simple and environmentally-friendly route for the production of isophorone derivatives.

Effects of altering the properties of an active site in an enzymatic homogeneous catalyst have been extensively reported. However, the possibility of increasing the number of such sites, as commonly done in heterogeneous catalytic materials, remains unexplored, particularly because those have to accommodate appropriate residues in specific configurations. This possibility was investigated by using a serine ester hydrolase as the target enzyme. By using the Protein Energy Landscape Exploration software, which maps ligand diffusion and binding, we found a potential binding pocket capable of holding an extra catalytic triad and oxyanion hole contacts. By introducing two mutations, this binding pocket became a catalytic site. Its substrate specificity, substrate preference, and catalytic activity were different from those of the native site of the wild type ester hydrolase and other hydrolases, due to the differences in the active site architecture. Converting the binding pocket into an extra catalytic active site was proven to be a successful approach to create a serine ester hydrolase with two functional reactive groups. Our results illustrate the accuracy and predictive nature of modern modeling techniques, opening novel catalytic opportunities coming from the presence of different catalytic environments in single enzymes.

Esterases receive special attention because of their wide distribution in biological systems and environments and their importance for physiology and chemical synthesis. The prediction of esterases’ substrate promiscuity level from sequence data and the molecular reasons why certain such enzymes are more promiscuous than others remain to be elucidated. This limits the surveillance of the sequence space for esterases potentially leading to new versatile biocatalysts and new insights into their role in cellular function. Here, we performed an extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters. We determined the primary factors shaping their substrate range by analyzing substrate range patterns in combination with structural analysis and protein–ligand simulations. We found a structural parameter that helps rank (classify) the promiscuity level of esterases from sequence data at 94% accuracy. This parameter, the active site effective volume, exemplifies the topology of the catalytic environment by measuring the active site cavity volume corrected by the relative solvent accessible surface area (SASA) of the catalytic triad. Sequences encoding esterases with active site effective volumes (cavity volume/SASA) above a threshold show greater substrate spectra, which can be further extended in combination with phylogenetic data. This measure provides also a valuable tool for interrogating substrates capable of being converted. This measure, found to be transferred to phosphatases of the haloalkanoic acid dehalogenase superfamily and possibly other enzymatic systems, represents a powerful tool for low-cost bioprospecting for esterases with broad substrate ranges, in large scale sequence data sets.

To meet the very specific requirements demanded by industry, proteins must be appropriately tailored. Engineering laccases, to improve the oxidation of small molecules, with applications in multiple fields, is, however, a difficult task. Most efforts have concentrated on increasing the redox potential of the enzyme, but in recent work, we have pursued an alternate strategy to engineering these biocatalysts. In particular, we have found that redesigning substrate binding at the T1 pocket, guided by in silicomethodologies, to be a more consistent option. In this work, we evaluate the robustness of our computational approach to estimate activity, emphasizing the importance of the binding event in laccase reactivity. Strengths and weaknesses of the protocol are discussed along with its potential for scoring large numbers of protein sequences and thus its significance in protein engineering.

Prolyl oligopeptidase (POP) is a large 80 kDa protease, which cleaves oligopeptides at the C-terminal side of proline residues and constitutes an important pharmaceutical target. Despite the existence of several crystallographic structures, there is an open debate about migration (entrance and exit) pathways for ligands, and their coupling with protein dynamics. Recent studies have shown the capabilities of molecular dynamics and classical force fields in describing spontaneous binding events and nonbiased ligand migration pathways. Due to POP’s size and to the buried nature of its active site, an exhaustive sampling by means of conventional long enough molecular dynamics trajectories is still a nearly impossible task. Such a level of sampling, however, is possible with the breakthrough protein energy landscape exploration technique. Here, we present an exhaustive sampling of POP with a known inhibitor, Z-pro-prolinal. In >3000 trajectories Z-pro-prolinal explores all the accessible surface area, showing multiple entrance events into the large internal cavity through the pore in the β-propeller domain. Moreover, we modeled a natural substrate binding and product release by predicting the entrance of an undecapeptide substrate, followed by manual active site cleavage and nonbiased exit of one of the products (a dipeptide). The product exit shows preference from a flexible 18-amino acid residues loop, pointing to an overall mechanism where entrance and exit occur in different sites.

Cluster analysis is becoming a relevant tool in structural bioinformatics. It allows analyzing large conformational ensembles in order to extract features or diminish redundancy, or just as a first step for other methods. Unfortunately, the successfulness of this analysis strongly depends on the data set traits, the chosen algorithm, and its parameters, which can lead to poor or even erroneous results not easily detected. In order to overcome this problem, we have developed pyProCT, a Python open source cluster analysis toolkit specially designed to be used with ensembles of biomolecule conformations. pyProCT implements an automated protocol to choose the clustering algorithm and parameters that produce the best results for a particular data set. It offers different levels of customization according to users’ expertise. Moreover, pyProCT has been designed as a collection of interchangeable libraries, making it easier to reuse it as part of other programs.

Computer simulations have been demonstrated to be important for unraveling atomic mechanisms in biological systems. In this study, we show how combining unbiased molecular dynamic simulations with appropriate analysis tools can successfully describe metal-based drug interactions with DNA. To elucidate the noncovalent affinity of cisplatin’s family to DNA, we performed extensive all-atom molecular dynamics simulations (3.7 μs total simulation length). The results show that the parent drug, cisplatin, has less affinity to form noncovalent adducts in the major groove than its aquo complexes. Furthermore, the relative position in which the drugs enter the major groove is dependent on the compound’s net charge. Based on the simulations, we estimated noncovalent binding free energies through the use of Markov state models. In addition, and to overcome the lack of experimental information, we employed two additional methods: Molecular Mechanics Poisson-Boltzmann Surface Area (MMPB-SA) and steered molecular dynamics with the Jarzynski estimator, with an overall good agreement between the three methods. All complexes show interaction energies below 3 kcal/mol with DNA but the charged hydrolysis products have slightly more favorable binding free energies than the parent drug. Moreover, this study sets the precedent for future unbiased DNA-ligand simulations of more complex binders.

A significant amount of work has been devoted to obtaining a detailed atomistic knowledge of the human hemoglobin mechanism. Despite this impressive research, to date, the ligand diffusion processes remain unclear and controversial. Using recently developed computational techniques, PELE, we are capable of addressing the ligand migration processes. First, the methodology was tested on myoglobin's CO migration, and the results were compared with the wealth of theoretical and experimental studies. Then, we explored both hemoglobin tense and relaxed states and identified the differences between the α-and β-subunits. Our results indicate that the proximal site, equivalent to the Xe1 cavity in myoglobin, is never visited. Furthermore, strategically positioned residues alter the diffusion processes within hemoglobin's subunits and suggest that multiple pathways exist, especially diversified in the α-globins. A significant dependency of the ligand dynamics on the tertiary structure is also observed.

Flavin-dependent carbohydrate oxidases are valuable tools in biotechnological applications due to their high selectivity in the oxidation of carbohydrates. In this study, we report the biochemical and structural characterization of a recently discovered carbohydrate oxidase from the bacterium Ralstonia solanacearum, which is a member of the vanillyl alcohol oxidase flavoprotein family. Due to its exceptionally high activity toward N-acetyl-d-galactosamine and N-acetyl-d-glucosamine, the enzyme was named N-acetyl-glucosamine oxidase (NagOx). In contrast to most known (fungal) carbohydrate oxidases, NagOx could be overexpressed in a bacterial host, which facilitated detailed biochemical and enzyme engineering studies. Steady state kinetic analyses revealed that non-acetylated hexoses were also accepted as substrates albeit with lower efficiency. Upon determination of the crystal structure, structural insights into NagOx were obtained. A large cavity containing a bicovalently bound FAD, tethered via histidyl and cysteinyl linkages, was observed. Substrate docking highlighted how a single residue (Leu251) plays a key role in the accommodation of N-acetylated sugars in the active site. Upon replacement of Leu251 (L251R mutant), an enzyme variant was generated with a drastically modified substrate acceptance profile, tuned toward non-N-acetylated monosaccharides and disaccharides. Furthermore, the activity toward bulkier substrates such as the trisaccharide maltotriose was introduced by this mutation. Due to its advantage of being overexpressed in a bacterial host, NagOx can be considered a promising alternative engineerable biocatalyst for selective oxidation of monosaccharides and oligosaccharides.