In Silico enzyme engineering – The importance of fast and accurate algorithms

Computer simulations are already widely used to rationally engineer new enzymes with improved properties. But if we can accurately screen millions of enzyme variants in a computer, then we can move into a new generation of in silico enzyme evolution. At ZYMVOL we are to be able to produce, model and rank protein-substrate interactions (including full protein dynamics) for over 50.000 enzyme variants per day. We have accelerated physics-based simulations, and combined experimental data with quantum approaches to develop a highly predictive computational platform. Our ZYMEVOLVER software can effectively reduce experimental validation to a few hundred variants and enzyme optimization campaigns to less than 6 months. We will illustrate how we are creating custom-made enzymes for industrial applications

Quantum chemistry and conformational sampling meet together : a powerful approach to study and design metalloprotein reactivity

Metalloprotein are proteins containing metal ion cofactors. Compared to chemical catalysts, metalloproteins have a well-defined configuration around the active site which ensures higher specificity, selectivity and reaction rates. Metalloproteins are soluble in water, their function can be optimized genetically by modifying an host (e.g. a bacteria) and are biodegradable. Therefore, they are ideal templates for the creation of novel green catalysts and therapeutics. Nonetheless, metalloproteins, as found in nature, are usually not ready for industrial scale-up and may need to be re-designed. Molecular simulations can guide the search for new metalloprotein functionality, cutting the costs of the experimental work. Modeling metalloproteins' function requires the sampling of both the electronic and nuclear degrees of freedom to exhaustively describe their chemical reactivity. The combination of conformational sampling and quantum chemical technique allows to model how they catalyze a reaction or covalently bind a ligand, without missing information about the dynamics of the whole protein. In this thesis, these computational techniques are systematically employed to study and guide present and future design efforts of laccases and hemoglobin. Laccases are copper-containing oxidoreductases that can oxidize a large variety of substrates at expenses of oxygen, which is reduced to water. Therefore, their interest in green chemistry applications: they work with air and produce water as sole by-product. So far, most efforts made to enlarge the chemical space of laccases have focused on increasing the redox potential of the first copper-based electron acceptor, a choice that yielded limited success. Here, it is proposed to focus on the desired substrate, modeling the active site of laccases to better fit and oxidize it. To do so, a computational protocol was developed, based on Monte Carlo sampling of the enzyme-substrate conformational space, followed by quick quantum chemical calculations to score oxidation. The protocol was first validated against experimental data, proving its capability to reproduce data and provide a rationale to laccases functioning. This new tool was then used to improve the oxidation of aniline by a laccase by simulating the effect of certain mutations (amino acid substitutions) which were tested in the lab by our collaborators. As a result, the design mutations significantly improved the oxidation of aniline (which leads to the formation of polyaniline, an organic semiconductor). Another design was carried out which lead to a significant improvement in activity of another laccase toward three different substrates. Therefore, the methodology developed proved to be capable of reproducing and rationalizing experimental results and rendering a la carte design of laccases toward a given (class of) substrates possible. A similar protocol, which uses an empirical computational method instead of quantum chemical techniques, was used to selectively attach a photosensitizer (a molecule that produces a chemical change in another molecule in a photochemical process) to the surface of a laccase. Hemoglobin, a heme-containing protein that carries oxygen from the lungs to the tissue in the body, is a candidate for blood substituent design. However, its design is rendered difficult by the limited knowledge of its functioning. Here, a mixed Monte Carlo-quantum chemical approach was used to support a theory about hemoglobin's allosteric mechanism and structurally characterize the tertiary end-states of the allosteric transition for the first time. These calculations, which were benchmarked against available experimental data, disclosed the role of the amino acids next to the oxygen binding site. This information was used in a subsequent molecular dynamics study which showed how the four subunits of hemoglobin give rise the allosteric response, highlighting the signalling paths and their hierarchyLas metaloproteínas son proteínas que contienen iones metálicos como cofactores. En comparación con los catalizadores químicos, las metaloproteínas tienen una configuración bien definida alrededor del sitio activo que asegura mejor especificidad, selectividad y velocidad de reacción. Las metaloproteínas son solubles en agua, su función puede ser optimizada genéticamente mediante la modificación de un huésped y son biodegradables. Por lo tanto, son ideales para la creación de nuevos catalizadores verdes y terapéuticos. No obstante, las metaloproteínas, como se encuentran en la naturaleza, no suelen estar listas para la industria y pueden necesitar ser re-diseñadas. Las simulaciones moleculares pueden orientar el diseño de mejores metaloproteınas, reduciendo el trabajo experimental. Modelar la función de las metaloproteınas necesita el muestreo de los grados de libertad electrónicos y nucleares para describir exhaustivamente su reactividad química. La combinación de muestreo conformacional y técnicas de química cuántica permite modelar la catálisis de una reacción o como un ligando se une covalentemente a una metaloproteína, sin omitir información sobre la dinámica de la proteína. En esta tesis, estas técnicas computacionales se utilizan sistemáticamente para estudiar y orientar presentes y futuros esfuerzos de diseño de lacasas y hemoglobina. Las lacasas son oxidorreductasas que pueden oxidar una gran variedad de sustratos y reducir oxígeno a agua. Por lo tanto, tienen interés en las aplicaciones de la química verde: funcionan con aire y producen agua como subproducto. Hasta ahora, la mayoría de los esfuerzos realizados para ampliar el espacio químico de lacasas se han centrado en aumentar el potencial redox del primer aceptor de electrones a base de cobre, una elección que obtuvo un éxito limitado. En este trabajo, se propone centrarse en el sustrato deseado, diseñando el sitio activo de las lacasas para mejor enlace y oxidación. Para ello, un protocolo de cálculo fue desarrollado, basado en el muestreo del espacio conformacional de la enzima-sustrato con técnicas Monte Carlo, seguido de cálculos de química cuántica para cuantificar la oxidación. El protocolo fue validado por primera vez contra datos experimentales, lo que probó su capacidad para proporcionar una justificación de las lacasas de funcionar. A continuación se utilizó esta nueva herramienta para mejorar la oxidación de la anilina por una lacasa, simulando el efecto de ciertas mutaciones que se probaron en el laboratorio por nuestros colaboradores. Como resultado, las mutaciones mejoraron significativamente la oxidación de anilina. Otro diseño produjo una mejora significativa en la actividad de otro lacasa hacía tres sustratos diferentes. Por lo tanto, la metodología desarrollada demostró ser útil para diseñar las lacasas hacia un dado sustrato. Un protocolo similar, que utiliza un método de cálculo empírico en lugar de técnicas de química cuántica, se utilizó para unir selectivamente un fotosensibilizador a la superficie de una lacasa. La hemoglobina, una proteína que contiene cuatro grupos hemo para transportar el oxígeno de los pulmones a los tejidos en el cuerpo, es un candidato para el diseño sustituyente de la sangre. Sin embargo, su diseño se ve dificultado por el limitado conocimiento de su funcionamiento. Aquí, la combinación de técnicas Monte Carlo y química cuántica se utilizó para apoyar una teoría sobre el mecanismo alostérico de la hemoglobina y caracterizar estructuralmente los estados finales de la transición alostérica terciaria por primera vez. Estos cálculos, que fueron comparados con los datos experimentales disponibles, permitieron conocer el papel de los aminoácidos próximos al sitio de unión de oxígeno. Esta información se utilizó en un estudio posterior de la dinámica molecular que mostró cómo las cuatro subunidades de la hemoglobina dan lugar a la respuesta alostérica, destacando las rutas de señalización y su jerarquía

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Directed evolution (DE) creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding, and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of the art of molecular modeling, discussing their strengths, limitations, and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques and a synergic effort between simulations and experimental validation.Peer ReviewedPostprint (author's final draft

Repurposing designed mutants: a valuable strategy for computer-aided laccase engineering – the case of POXA1b

The broad specificity of laccases, a direct consequence of their shallow binding site, makes this class of enzymes a suitable template to build specificity toward putative substrates. In this work, a computational methodology that accumulates beneficial interactions between the enzyme and the substrate in productive conformations is applied to oxidize 2,4-diamino-benzenesulfonic acid with POXA1b laccase. Although the experimental validation of two designed variants yielded negative results, most likely due to the hard oxidizability of the target substrate, molecular simulations suggest that a novel polar binding scaffold was designed to anchor negatively charged groups. Consequently, the oxidation of three such molecules, selected as representative of different classes of substances with different industrial applications, significantly improved. According to molecular simulations, the reason behind such an improvement lies in the more productive enzyme–substrate binding achieved thanks to the designed polar scaffold. In the future, mutant repurposing toward other substrates could be first carried out computationally, as done here, testing molecules that share some similarity with the initial target. In this way, repurposing would not be a mere safety net (as it is in the laboratory and as it was here) but rather a powerful approach to transform laccases into more efficient multitasking enzymes.This work was funded by INDOX (KBBE-2013-7-613549) European project and CTQ2013-48287-R Spanish National Project. V. G. and E. M. acknowledge Università degli Studi di Napoli and Generalitat de Catalunya for their respective predoctoral fellowships.Peer ReviewedPostprint (author's final draft

Re-designing the substrate binding pocket of laccase for enhanced oxidation of sinapic acid

Iterative saturation mutagenesis was performed over six residues delimiting the substrate binding pocket of a high-redox potential chimeric laccase with the aim of enhancing its activity over sinapic acid, a lignin-related phenol of industrial interest. In total, more than 15000 clones were screened and two selected variants, together with the parent-type laccase, were purified and characterized. The new variants presented shifted pH activity profiles and enhanced turnover rates on sinapic acid and its methyl ester, whereas the oxidation of related phenols was not significantly enhanced. Neither the enzyme's redox potential nor the mechanism of the reaction were affected. Thus, quantum mechanics and molecular dynamics calculations were done to rationalize the effect of the selected mutations, revealing the critical role of the residues of the enzyme pocket to provide the precise binding of the substrate that enables an efficient electron transfer to the T1 copper. The results presented highlight the power of combining directed evolution and computational approaches to give novel solutions in enzyme engineering and to understand the mechanistic reasons behind them, offering new insights for further rational design towards specific targets

Rational Enzyme Engineering Through Biophysical and Biochemical Modeling

Due to its importance in the pharmaceutical industry, ligand dynamic simulations have experienced a great expansion. Using all-atom models and cutting edge hardware, one can perform non-biased ligand migration, active site search and binding studies. In this letter we demonstrate (and validate by PCR mutagenesis) how these techniques, when combined with quantum mechanics, open new possibilities in enzyme engineering. We provide a complete analysis where: 1) biophysical simulations produce ligand diffusion and, 2) biochemical modeling samples the chemical event. Using such broad analysis we engineer a highly stable peroxidase activating the enzyme for new substrate oxidation after rational mutation of two non-conserved surface residues. In particular, we create a new surface-binding site, quantitatively predicting the in vitro change in oxidation rate obtained by mutagenic PCR and achieving a comparable specificity constant to active peroxidases.This work was supported by the INDOX (KBBE-2013-7-613549 to ATM) European project, and the CTQ2013-48287 (to VG) and BIO2014-56388-R (to FJR-D) projects of the Spanish Ministry of Economy and Competitiveness (MINECO). FJR-D acknowledges a MINECO Ramón&Cajal contract.Peer ReviewedPostprint (author's final draft

Probing the Surface of a Laccase for Clues towards the Design of Chemo-Enzymatic Catalysts

Systems featuring a multi-copper oxidase associated with transition-metal complexes can be used to perform oxidation reactions in mild conditions. Here, a strategy is presented for achieving a controlled orientation of a ruthenium–polypyridyl graft at the surface of a fungal laccase. Laccase variants are engineered with unique surface-accessible lysine residues. Distinct ruthenium–polypyridyl-modified laccases are obtained by the reductive alkylation of lysine residues precisely located relative to the T1 copper centre of the enzyme. In none of these hybrids does the presence of the graft compromise the catalytic efficiency of the enzyme on the substrate 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid). Furthermore, the efficiency of the hybrids in olefin oxidation coupled to the light-driven reduction of O2 is highly dependent on the location of the graft at the enzyme surface. Simulated RuII–CuII electron coupling values and distances fit well the observed reactivity and could be used to guide future hybrid designs.L.S. was the recipient of a MinistHre de l’Education Nationale fellowship. This study was supported by grants from the Agence Nationale de la Recherche (ANR-09-BLANC-0176 and ANR-15-CE07-0021-01) and from the Ministerio de EconomÍa, Industria y Competitividad (CTQ2016-79138-R). We thank Elise Courvoisier-Dezord from the Plateforme AVB (AMU): Analyse et Valorisation de la Biodiversit8 and Yolande Charmasson for help in the production of the recombinant enzymes, as well as Pascal Mansuelle and R8gine Lebrun from the Plateforme Prot8omique (CNRSAMU) for help in acquiring mass spectrometry data.Peer ReviewedPostprint (published version

Re-designing the substrate binding pocket of laccase for enhanced oxidation of sinapic acid

Iterative saturation mutagenesis was performed over six residues delimiting the substrate binding pocket of a high redox potential chimeric laccase with the aim of enhancing its activity over sinapic acid, a ligninrelated phenol of industrial interest. In total, more than 15000 clones were screened and two selected variants, together with the parent-type laccase, were purified and characterized. The new variants presented shifted pH activity profiles and enhanced turnover rates on sinapic acid and its methyl ester, whereas the oxidation of related phenols was not significantly enhanced. Neither the enzyme's redox potential nor the mechanism of the reaction was affected. Quantum mechanics and molecular dynamics calculations were done to rationalize the effect of the selected mutations, revealing the critical role of the residues of the enzyme pocket to provide the precise binding of the substrate that enables an efficient electron transfer to the T1 copper. The results presented highlight the power of combining directed evolution and computational approaches to give novel solutions in enzyme engineering and to understand the mechanistic reasons behind them, offering new insights for further rational design towards specific targets.This work was funded by INDOX (KBBE-2013-7-613549) European project and NOESIS (BIO2014-56388-R) and CTQ2013- 48287-R Spanish National Projects. I. P. and G. S. acknowledge the Spanish Research Council (CSIC) and MINECO for their respective predoctoral fellowships.Peer ReviewedPostprint (published version

The Role of Attitudes Toward Medication and Treatment Adherence in the Clinical Response to LAIs: Findings From the STAR Network Depot Study

Background: Long-acting injectable (LAI) antipsychotics are efficacious in managing psychotic symptoms in people affected by severe mental disorders, such as schizophrenia and bipolar disorder. The present study aimed to investigate whether attitude toward treatment and treatment adherence represent predictors of symptoms changes over time. Methods: The STAR Network \u201cDepot Study\u201d was a naturalistic, multicenter, observational, prospective study that enrolled people initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centers were assessed at three time points: baseline, 6-month, and 12-month follow-up. Psychopathological symptoms, attitude toward medication and treatment adherence were measured using the Brief Psychiatric Rating Scale (BPRS), the Drug Attitude Inventory (DAI-10) and the Kemp's 7-point scale, respectively. Linear mixed-effects models were used to evaluate whether attitude toward medication and treatment adherence independently predicted symptoms changes over time. Analyses were conducted on the overall sample and then stratified according to the baseline severity (BPRS < 41 or BPRS 65 41). Results: We included 461 participants of which 276 were males. The majority of participants had received a primary diagnosis of a schizophrenia spectrum disorder (71.80%) and initiated a treatment with a second-generation LAI (69.63%). BPRS, DAI-10, and Kemp's scale scores improved over time. Six linear regressions\u2014conducted considering the outcome and predictors at baseline, 6-month, and 12-month follow-up independently\u2014showed that both DAI-10 and Kemp's scale negatively associated with BPRS scores at the three considered time points. Linear mixed-effects models conducted on the overall sample did not show any significant association between attitude toward medication or treatment adherence and changes in psychiatric symptoms over time. However, after stratification according to baseline severity, we found that both DAI-10 and Kemp's scale negatively predicted changes in BPRS scores at 12-month follow-up regardless of baseline severity. The association at 6-month follow-up was confirmed only in the group with moderate or severe symptoms at baseline. Conclusion: Our findings corroborate the importance of improving the quality of relationship between clinicians and patients. Shared decision making and thorough discussions about benefits and side effects may improve the outcome in patients with severe mental disorders

Defining Kawasaki disease and pediatric inflammatory multisystem syndrome-temporally associated to SARS-CoV-2 infection during SARS-CoV-2 epidemic in Italy: results from a national, multicenter survey

Background: There is mounting evidence on the existence of a Pediatric Inflammatory Multisystem Syndrome-temporally associated to SARS-CoV-2 infection (PIMS-TS), sharing similarities with Kawasaki Disease (KD). The main outcome of the study were to better characterize the clinical features and the treatment response of PIMS-TS and to explore its relationship with KD determining whether KD and PIMS are two distinct entities. Methods: The Rheumatology Study Group of the Italian Pediatric Society launched a survey to enroll patients diagnosed with KD (Kawasaki Disease Group - KDG) or KD-like (Kawacovid Group - KCG) disease between February 1st 2020, and May 31st 2020. Demographic, clinical, laboratory data, treatment information, and patients' outcome were collected in an online anonymized database (RedCAP®). Relationship between clinical presentation and SARS-CoV-2 infection was also taken into account. Moreover, clinical characteristics of KDG during SARS-CoV-2 epidemic (KDG-CoV2) were compared to Kawasaki Disease patients (KDG-Historical) seen in three different Italian tertiary pediatric hospitals (Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste; AOU Meyer, Florence; IRCCS Istituto Giannina Gaslini, Genoa) from January 1st 2000 to December 31st 2019. Chi square test or exact Fisher test and non-parametric Wilcoxon Mann-Whitney test were used to study differences between two groups. Results: One-hundred-forty-nine cases were enrolled, (96 KDG and 53 KCG). KCG children were significantly older and presented more frequently from gastrointestinal and respiratory involvement. Cardiac involvement was more common in KCG, with 60,4% of patients with myocarditis. 37,8% of patients among KCG presented hypotension/non-cardiogenic shock. Coronary artery abnormalities (CAA) were more common in the KDG. The risk of ICU admission were higher in KCG. Lymphopenia, higher CRP levels, elevated ferritin and troponin-T characterized KCG. KDG received more frequently immunoglobulins (IVIG) and acetylsalicylic acid (ASA) (81,3% vs 66%; p = 0.04 and 71,9% vs 43,4%; p = 0.001 respectively) as KCG more often received glucocorticoids (56,6% vs 14,6%; p < 0.0001). SARS-CoV-2 assay more often resulted positive in KCG than in KDG (75,5% vs 20%; p < 0.0001). Short-term follow data showed minor complications. Comparing KDG with a KD-Historical Italian cohort (598 patients), no statistical difference was found in terms of clinical manifestations and laboratory data. Conclusion: Our study suggests that SARS-CoV-2 infection might determine two distinct inflammatory diseases in children: KD and PIMS-TS. Older age at onset and clinical peculiarities like the occurrence of myocarditis characterize this multi-inflammatory syndrome. Our patients had an optimal response to treatments and a good outcome, with few complications and no deaths