Rational Guidelines for the Two-Step Scalability of Enzymatic Polycondensation: Experimental and Computational Optimization of the Enzymatic Synthesis of Poly(glycerolazelate).

The lipase-catalyzed polycondensation of azelaic acid and glycerol is investigated according to a Design-of-Experiment approach that helps to elucidate the effect of experimental variables on monomer conversion, Mn and regioselectivity of acylation of glycerol. Chemometric analysis shows that after 24 h the reaction proceeds regardless of the presence of the enzyme. Accordingly, the biocatalyst was removed after a first step of synthesis and the chain elongation continued at 80 °C. That allowed the removal of the biocatalyst and the preservation of its activity: pre-requites for efficient applicability at industrial scale. The experimental study, combined with docking-based computational analysis, provides rational guidelines for the optimization of the regioselective acylation of glycerol. The process is scaled up to 73.5 g of monomer. The novelty of the present study is the rigorous control of the reaction conditions and of the integrity of the immobilized biocatalyst, which serve to avoiding any interference of free enzyme or fines released in the reaction mixture. The quantitative analysis of the effect of experimental conditions and the overcoming of some major technical bottlenecks for the scalability of enzymatic polycondensation opens new scenarios for industrial exploitation.

Evolving biocatalysis to meet bioeconomy challenges and opportunities.

The unique selectivity of enzymes, along with their remarkable catalytic activity, constitute powerful tools for transforming renewable feedstock and also for adding value to an array of building blocks and monomers produced by the emerging bio-based chemistry sector. Although some relevant biotransformations run at the ton scale demonstrate the success of biocatalysis in industry, there is still a huge untapped potential of catalytic activities available for targeted valorization of new raw materials, such as waste streams and CO2. For decades, the needs of the pharmaceutical and fine chemistry sectors have driven scientific research in the field of biocatalysis. Nowadays, such consolidated advances have the potential to translate into effective innovation for the benefit of bio-based chemistry. However, the new scenario of bioeconomy requires a stringent integration between scientific advances and economics, and environmental as well as technological constraints. Computational methods and tools for effective big-data analysis are expected to boost the use of enzymes for the transformation of a new array of renewable feedstock and, ultimately, to enlarge the scope of biocatalysis.

Investigating the Role of Conformational Effects on Laccase Stability and Hyperactivation under Stress Conditions.

Fungal laccase from Steccherinum ochraceum 1833 displays remarkable stability under different harsh conditions: organic/buffer mixtures, thermal treatment, and microwave radiation. The behavior is particularly significant in the light of the sharp inactivation observed for two different fungal laccases. Laccase from S. ochraceum 1833 also displays hyperactivation under mild thermal treatment (60 °C). Molecular dynamics simulations at 80 °C explained how this laccase retains the geometry of the electron transfer pathway, thereby assuring electron transfer through the copper ions and thus maintaining its catalytic activity at high temperature. Spectroscopic studies revealed that the thermal activation corresponds to specific conformational changes in the protein. The results indicate that this laccase is potentially applicable under denaturing conditions that might be beneficial for the biotransformation of recalcitrant substrates.

BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space). The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".

Efficient immobilisation of industrial biocatalysts: criteria and constraints for the selection of organic polymeric carriers and immobilisation methods.

Efficient immobilisation protocols are the result of perfect matching of factors depending on the enzyme, the process and the support for immobilisation. Physical-chemical phenomena, such as partition, solvation and diffusion, strongly affect the efficiency of the biocatalyst in each specific reaction system. Therefore, tailored solutions must be developed for each specific process of interest. Indeed, direct investigation of what occurs at the molecular level in a reaction catalysed by an immobilised enzyme is a quite formidable task and observed differences in the performance of immobilised biocatalysts must be interpreted very carefully. In any study dealing with enzyme immobilisation the prerequisite is the rigorous planning and reporting of experiments, being aware of the complexity of these multi-phase systems.

Lipases immobilization for effective synthesis of biodiesel starting from coffee waste oils.

Immobilized lipases were applied to the enzymatic conversion of oils from spent coffee ground into biodiesel. Two lipases were selected for the study because of their conformational behavior analysed by Molecular Dynamics (MD) simulations taking into account that immobilization conditions affect conformational behavior of the lipases and ultimately, their efficiency upon immobilization. The enzymatic synthesis of biodiesel was initially carried out on a model substrate (triolein) in order to select the most promising immobilized biocatalysts. The results indicate that oils can be converted quantitatively within hours. The role of the nature of the immobilization support emerged as a key factor affecting reaction rate, most probably because of partition and mass transfer barriers occurring with hydrophilic solid supports. Finally, oil from spent coffee ground was transformed into biodiesel with yields ranging from 55% to 72%. The synthesis is of particular interest in the perspective of developing sustainable processes for the production of bio-fuels from food wastes and renewable materials. The enzymatic synthesis of biodiesel is carried out under mild conditions, with stoichiometric amounts of substrates (oil and methanol) and the removal of free fatty acids is not required.

Endo- and exo-inulinases: enzyme-substrate interaction and rational immobilization.

Three-dimensional models of exoinulinase from Bacillus stearothermophilus and endoinulinase from Aspergillus niger were built up by means of homology modeling. The crystal structure of exoinulinase from Aspergillus awamori was used as a template, which is the sole structure of inulinase resolved so far. Docking and molecular dynamics simulations were performed to investigate the differences between the two inulinases in terms of substrate selectivity. The analysis of the structural differences between the two inulinases provided the basis for the explanation of their different regio-selectivity and for the understanding of enzyme-substrate interactions. Surface analysis was performed to point out structural features that can affect the efficiency of enzymes also after immobilization. The computational analysis of the three-dimensional models proved to be an effective tool for acquiring information and allowed to formulate an optimal immobilized biocatalyst even more active that the native one, thus enabling the full exploitation of the catalytic potential of these enzymes.

Synbeads porous-rigid methacrylic support: application to solid phase peptide synthesis and characterization of the polymeric matrix by FTIR microspectroscopy and high resolution magic angle spinning NMR.

Porous and rigid methacrylic Synbeads were optimized and applied efficiently to the solid phase peptide synthesis with the objective of improving significantly volumetric yields (0.33 mol/L calculated on the basis of maximum chemical accessibility, i.e. the maximum number of functional groups that can be acylated by FmocCl) as compared to swelling commercial polymers (from 0.06 to 0.12 mol/L). The effects of the density of functional groups and spacer length were investigated obtaining a chemical accessibility of the functional groups up to 1 mmol/g(dry). High resolution magic angle spinning (HR-MAS) was exploited to evidence the presence of "solution-like" flexible linkers anchored on the rigid methacrylic backbone of Synbeads and to study the degree of functionalization by the Wang linker. To demonstrate the efficiency of the optimized Synbeads, the peptides Somatostatin and Terlipressin were synthesized. In the case of Somatostatin, final synthetic yields of 45 and 60% were achieved by following the HCTU/DIPEA and DIC/HOBt routes respectively, with the HPLC purity always higher than 83%. In the case of Terlipressin, the synthesis was carried out in parallel on Synbeads and also on TentaGel, ChemMatrix, and PS-DVB for comparison (DIC/HOBt route). The profiles describing the synthetic efficiency demonstrated that Synbeads leads to synthetic efficiency (86%) comparable to PS-DVB (96%) or ChemMatrix (84%). In order to gain a more precise picture of chemical and morphological features of Synbeads, their matrix was also characterized by exploiting innovative approaches based on FTIR microspectroscopy with a conventional source and with synchrotron radiation. A uniform distribution of the functional groups was evidenced through a detailed chemical mapping.

Volsurf computational method applied to the prediction of stability of thermostable enzymes.

A computational model for the quantitative prediction of protein thermostability has been developed by means of the Volsurf method. A data set of 22 enzymes of reported thermostability in water systems, for the most part coming from thermophilic and hyperthermophilic organisms, has been built up. Molecular descriptors of the protein surface have been calculated and their role in the stabilization of the macromolecule has been analyzed by a multivariate statistical approach. The resulting regression model has shown a good predictivity and it has been able to quantitatively identify some structural requirements correlated with protein stability. The method can be the basis for a new computational support tool in rational protein design, which is complementary to the existing methods based on the sequence analysis.

Computational methods to rationalize experimental strategies in biocatalysis.

Computational methods are more and more widely applied in biocatalysis to gain rational guidelines, to orient experimental planning and, ultimately, to avoid expensive and time-consuming experiments. In this respect, molecular modelling, multivariate statistical analysis and chemometrics in general are useful computational tools, although they follow completely different investigative approaches.

Optimized polymer-enzyme electrostatic interactions significantly improve penicillin G amidase efficiency in charged PEGA polymers.

Hydrolytic yields as high as 80% were obtained by using penicillin G amidase (PGA) on substrates anchored on optimized positively charged PEGA polymers. By increasing the amount of permanent charges inside the polymer, electrostatic interactions between the positively charged PEGA(+) and the negatively charged PGA (pI = 5.2-5.4) were strengthened, thus favouring the accessibility of the bulky enzyme (MW = 88 kDa) inside the pores. The effect of different amounts of charges on polymer swelling and protein retention inside the polymer was investigated and correlated to the enzyme efficiency demonstrating that electrostatic interactions predominate over swelling properties in determining enzyme accessibility.

An innovative application of the "flexible" GRID/PCA computational method: study of differences in selectivity between PGAs from Escherichia coli and a Providentia rettgeri mutant.

The original GRID/PCA technique was adapted for the development of a tool potentially useful for the plan of a research strategy in rational enzyme design. The use of the MOVE directive of GRID made it possible to partially take into account protein flexibility, and the multivariate analysis was used as an instrument for focusing only on relevant information related to the differences in enzyme substrate selectivities. The comparison of two different penicillin G acylases, from Escherichia coli and from Providentia rettgeri, was used as a case study; these enzymes are very similar and their reported selectivities differ only for a couple of mutations around the active site. The "flexible" GRID/PCA method was able to correctly predict the observed selectivity differences caused not only by mutations of residues of the active site but also by long range effects on substrate selectivity due to sequence mutations on residues not directly involved in substrate recognition.

Nonswelling macroporous synbeads for improved efficiency of solid-phase biotransformations.

An application of novel, highly porous nonswelling resins (Synbeads) for enzymatic catalysis on solid supports is reported. These new resins combine easy handling of the beads, chemical stability, improved accessibility of proteins and higher productivity relative to swelling polymers. The present study demonstrates that the resin porosity greatly affects the efficiency in solid-phase biotransformations and that Synbead resins are valuable alternatives to swelling polymers for solid-phase chemistry and biocatalysis. The present study investigates the influence of key parameters, such as porosity and reactive functional-group density, on the reaction efficiency.

A homology model of penicillin acylase from Alcaligenes faecalis and in silico evaluation of its selectivity.

A three-dimensional model of the relatively unknown penicillin acylase from Alcaligenes faecalis (PA-AF) was built up by means of homology modeling based on three different crystal structures of penicillin acylase from various sources. An in silico selectivity study was performed to compare this homology model to the structure of the Escherichia coli enzyme (PA-EC) in order to find any selectivity differences between the two enzymes. The program GRID was applied in combination with the principal component analysis technique to identify the regions of the active sites where the PAs potentially engage different interactions with ligands. These differences were further analyzed and confirmed by molecular docking simulations. The PA-AF homology model provided the structural basis for the explanation of the different enantioselectivities of the enzymes previously demonstrated experimentally and reported in the literature. Different substrate selectivities were also predicted for PA-AF compared to PA-EC. Since no crystallographic data are available for PA-AF to date, the three-dimensional homology model represents a useful and efficient tool for fully exploiting this attractive and efficient biocatalyst, particularly in enantioselective acylations of amines.

GRID/tetrahedral intermediate computational approach to the study of selectivity of penicillin G acylase in amide bond synthesis.

Molecular modelling was used to investigate the catalytic site of penicillin G acylase (PGA) by building up a simple enzyme-ligand model able to describe and predict the enzyme selectivity. The investigation was based on a double computational approach: first, the GRID computational procedure was applied to gain a qualitative description of the chemical features of the PGA active site; second, a classical "transition state approach" was used to simulate the tetrahedral intermediates and to evaluate their energies. GRID calculations employed different probes which gave a complete description of the chemical interactions occurring upon binding of different ligands, thus indicating those structures having good affinity with the active site of the enzyme. Tetrahedral intermediates were constructed on the basis of GRID results and provided both geometrical features and energies of enzyme-substrate interaction. Such energies were compared to experimental kinetic data obtained in the enzymatic acylation of L-phenylglycine methyl ester using various methyl phenylacetate derivatives. The good agreement of computational results with experimental evidence demonstrates the validity of the model as a rapid and flexible tool to describe and predict the enzyme selectivity.