Rationalization of a Streptavidin Based Enantioselective Artificial Suzukiase : An Integrative Computational Approach

Altres ajuts: acords transformatius de la UABAn Artificial Metalloenzyme (ArM) built employing the streptavidin-biotin technology has been used for the enantioselective synthesis of binaphthyls by means of asymmetric Suzuki-Miyaura cross-coupling reactions. Despite its success, it remains a challenge to understand how the length of the biotin cofactors or the introduction of mutations to streptavidin leads the preferential synthesis of one atropisomer over the other. In this study, we apply an integrated computational modeling approach, including DFT calculations, protein-ligand dockings and molecular dynamics to rationalize the impact of mutations and length of the biotion cofactor on the enantioselectivities of the biaryl product. The results unravel that the enantiomeric differences found experimentally can be rationalized by the disposition of the first intermediate, coming from the oxidative addition step, and the entrance of the second substrate. The work also showcases the difficulties facing to control the enantioselection when engineering ArM to catalyze enantioselective Suzuki-Miyaura couplings and how the combination of DFT calculations, molecular dockings and MD simulations can be used to rationalize artificial metalloenzymes

Getting Deeper into the Molecular Events of Heme Binding Mechanisms : A Comparative Multi-level Computational Study of HasAsm and HasAyp Hemophores

Altres ajuts: acord transformatiu CRUE-CSICMany biological systems obtain their activity by the inclusion of metalloporphyrins into one or several binding pockets. However, decoding the molecular mechanism under which these compounds bind to their receptors is something that has not been widely explored and is a field with open questions. In the present work, we apply computational techniques to unravel and compare the mechanisms of two heme-binding systems, concretely the HasA hemophores from Gram negative bacteria Serratia marcescens (HasAsm) and Yersinia pestis (HasAyp). Despite the high sequence identity between both systems, the comparison between the X-ray structures of their apo and holo forms suggests different heme-binding mechanisms. HasAyp has extremely similar structures for heme-free and heme-bound forms, while HasAsm presents a very large displacement of a loop that ultimately leads to an additional coordination to the metal with respect to HasAyp. We combined Gaussian accelerated molecular dynamics simulations (GaMDs) in explicit solvent and protein-ligand docking optimized for metalloligands. GaMDs were first carried out on heme-free forms of both hemophores. Then, protein-ligand dockings of the heme were performed on cluster representatives of these simulations and the best poses were then subjected to a new series of GaMDs. A series of analyses reveal the following: (1) HasAyp has a conformational landscape extremely similar between heme-bound and unbound states with no to limited impact on the binding of the cofactor, (2) HasAsm presents as a slightly broader conformational landscape in its apo state but can only visit conformations similar to the X-ray of the holo form when the heme has been bound. Such behavior results from a complex cascade of changes in interactions that spread from the heme-binding pocket to the flexible loop previously mentioned. This study sheds light on the diversity of molecular mechanisms of heme-binding and discusses the weight between the pre-organization of the receptor as well as the induced motions resulting in association. Heme-containing enzymes and proteins are important for many biological and biotechnological processes. However, very little is known about heme-binding mechanisms. To shed light on this, we report a multi-level approach combining Gaussian accelerated molecular dynamics and protein−ligand dockings optimized for metallic moieties. The protocol unveils the difference in heme recruitment between HasAsm and HasAyp hemophores and shows its possible applicability to other heme-binding proteins

Direct Benzene Hydroxylation with Dioxygen Induced by Copper Complexes : Uncovering the Active Species by DFT Calculations

Acord transformatiu CRUE-CSICThe direct oxidation of benzene into phenol using molecular oxygen at very mild temperatures can be promoted in the presence of the copper complex TpCu(NCMe) in the homogeneous phase in the presence of ascorbic acid as the source of protons and electrons. The stoichiometric nature, relative to copper, of this transformation prompted a thorough DFT study in order to understand the reaction pathway. As a result, the dinuclear species TpCu(μ-O)(μ-OH)CuTpis proposed as the relevant structure which is responsible for activating the arene C-H bond leading to phenol formation

Investigating potential inhibitory effect of Uncaria tomentosa (Cat's Claw) against the main protease 3CL pro of SARS-CoV-2 by molecular modeling

COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2. Presently, there is no effective treatment for COVID-19. As part of the worldwide efforts to find efficient therapies and preventions, it has been reported the crystalline structure of the SARS-CoV-2 main protease M pro (also called 3CL pro) bound to a synthetic inhibitor, which represents a major druggable target. The druggability of M pro could be used for discovering drugs to treat COVID-19. A multilevel computational study was carried out to evaluate the potential antiviral properties of the components of the medicinal herb Uncaria tomentosa (Cat's claw), focusing on the inhibition of M pro. The in silico approach starts with protein-ligand docking of 26 Cat's claw key components, followed by ligand pathway calculations, molecular dynamics simulations, and MM-GBSA calculation of the free energy of binding for the best docked candidates. The structural bioinformatics approaches led to identification of three bioactive compounds of Uncaria tomentosa (speciophylline, cadambine, and proanthocyanidin B2) with potential therapeutic effects by strong interaction with 3CL pro. Additionally, in silico drug-likeness indices for these components were calculated and showed good predicted therapeutic profiles of these phytochemicals. Our findings suggest the potential effectiveness of Cat's claw as complementary and/or alternative medicine for COVID-19 treatment

Advanced computational strategies for metalloenzyme design

A la natura abunden les proteïnes que contenen metalls, des de metal·loenzims que catalitzen reaccions crucials fins a proteïnes que emmagatzemen i transporten metalls. L'estudi molecular de les metal·loproteïnes permet trobar solucions a una àmplia gamma de problemes químics i estudiar-ne els processos de reconeixement. La investigació ha aprofitat l'oportunitat de copiar aquesta naturalesa creant nous catalitzadors, els metal·loenzims artificials (ArM). Aquests ArMs es dissenyen a partir de la combinació de proteïnes naturals amb metalls, cosa que els permet dur a terme reaccions noves a la natura. En els darrers anys, la modelització molecular s'ha convertit en una eina essencial en aquest camp, malgrat que encara queden per resoldre alguns reptes. Aquesta tesi doctoral pretén aplicar la modelització molecular per comprendre el comportament de proteïnes que contenen metalls, centrant-se en certes proteïnes metàl·liques naturals i els ArMs. La primera part d'aquesta tesi es centra en l'estudi de proteïnes que contenen un cofactor metàl·lic prototípic, el grup hemo. S'aplica un protocol computacional basat en tècniques de dinàmica molecular accelerades per estudiar diferents mecanismes d'unió del grup hemo amb l'hemòfor HasA. A més, també es desenvolupa un programari per detectar llocs d'unió de l'hemo que es basa únicament en informació estructural de les proteïnes. En la segona part d'aquesta tesi el focus està en el disseny computacional d'ArMs. S'aplica una estratègia integradora que combina diverses tècniques, com mecànica quàntica, dockings i simulacions de dinàmica molecular per estudiar en detall dos ArM: un basat en la hidroaminació amb or i l'altra en una reacció Suzuki-Miyaura en què intervé pal·ladi.En la naturaleza abundan las proteínas que contienen metales, desde metaloenzimas que catalizan reacciones cruciales hasta proteínas que almacenan y transportan metales. El estudio molecular de las metaloproteínas permite encontrar soluciones a una amplia gama de problemas químicos y estudiar sus procesos de reconocimiento. La investigación ha aprovechado la oportunidad de copiar esta naturaleza creando nuevos catalizadores, las metaloenzimas artificiales (ArM). Estas ArM se diseñan a partir de la combinación de proteínas naturales con metales, lo que les permite llevar a cabo reacciones nuevas en la naturaleza. En los últimos años, la modelización molecular se ha convertido en una herramienta esencial en este campo, aunque todavía quedan por resolver algunos retos. Esta tesis doctoral pretende aplicar la modelización molecular para comprender el comportamiento de proteínas que contienen metales, centrándose en ciertas proteínas metálicas naturales y las ArM. La primera parte de esta tesis abarca el estudio de proteínas que contienen un cofactor metálico prototípico, el grupo hemo. En ella, se aplica un protocolo computacional basado en técnicas de dinámica molecular aceleradas para estudiar diferentes mecanismos de unión del grupo hemo con la proteína hemóforo HasA. Además, se desarrolla un software para detectar los sitios de unión del hemo que se basa únicamente en información estructural de las proteínas. La segunda parte de esta tesis se centra en el diseño computacional de ArM. Se aplican enfoques integradores que combinan varias técnicas, como mecánica cuántica, dockings y simulaciones de dinámica molecular para obtener un conocimiento más profundo de dos ArM: uno basado en la hidroaminación con oro y la otra en una reacción Suzuki-Miyaura en la que interviene paladio.Nature is abundant with proteins that contain metals, ranging from metalloenzymes serving crucial catalytic reactions to proteins that storage and transport metals. The molecular study of metalloproteins allows to find solutions to a wide range of chemical problems and provides insights into their recognition processes. Researchers have seized the opportunity to copy nature by create new catalysts, Artificial metalloenzymes (ArM). These ArMs are designed by combining natural protein scaffolds with metallic moieties, enabling them to carry out new reactions in nature. In the recent years, molecular modeling has become an essential tool in these fields, though certain challenges still need to be addressed. This PhD thesis aims to apply molecular modeling to understand the behavior of metal containing proteins, focusing on natural metallic proteins and ArMs. The first part of this thesis encompasses the study of proteins containing the prototypical metallic cofactor heme. A molecular modeling protocol based on enhanced molecular dynamics techniques is applied to unravel different binding mechanism of heme on protein hemophore HasA. Furthermore, a software is developed for detecting heme binding sites based only on structural information. The second part of this thesis focuses on the computational-aided design of ArM. Integrative approaches combining various techniques, such as quantum mechanics, molecular docking, and classical molecular dynamics simulations are applied to obtain a deeper understanding of two different ArMs: one based on single or dual gold hydroamination and the other a Suzuki-Miyaura reaction involving palladium

Advanced computational strategies for metalloenzyme design

A la natura abunden les proteïnes que contenen metalls, des de metal·loenzims que catalitzen reaccions crucials fins a proteïnes que emmagatzemen i transporten metalls. L'estudi molecular de les metal·loproteïnes permet trobar solucions a una àmplia gamma de problemes químics i estudiar-ne els processos de reconeixement. La investigació ha aprofitat l'oportunitat de copiar aquesta naturalesa creant nous catalitzadors, els metal·loenzims artificials (ArM). Aquests ArMs es dissenyen a partir de la combinació de proteïnes naturals amb metalls, cosa que els permet dur a terme reaccions noves a la natura. En els darrers anys, la modelització molecular s'ha convertit en una eina essencial en aquest camp, malgrat que encara queden per resoldre alguns reptes. Aquesta tesi doctoral pretén aplicar la modelització molecular per comprendre el comportament de proteïnes que contenen metalls, centrant-se en certes proteïnes metàl·liques naturals i els ArMs. La primera part d'aquesta tesi es centra en l'estudi de proteïnes que contenen un cofactor metàl·lic prototípic, el grup hemo. S'aplica un protocol computacional basat en tècniques de dinàmica molecular accelerades per estudiar diferents mecanismes d'unió del grup hemo amb l'hemòfor HasA. A més, també es desenvolupa un programari per detectar llocs d'unió de l'hemo que es basa únicament en informació estructural de les proteïnes. En la segona part d'aquesta tesi el focus està en el disseny computacional d'ArMs. S'aplica una estratègia integradora que combina diverses tècniques, com mecànica quàntica, dockings i simulacions de dinàmica molecular per estudiar en detall dos ArM: un basat en la hidroaminació amb or i l'altra en una reacció Suzuki-Miyaura en què intervé pal·ladi.En la naturaleza abundan las proteínas que contienen metales, desde metaloenzimas que catalizan reacciones cruciales hasta proteínas que almacenan y transportan metales. El estudio molecular de las metaloproteínas permite encontrar soluciones a una amplia gama de problemas químicos y estudiar sus procesos de reconocimiento. La investigación ha aprovechado la oportunidad de copiar esta naturaleza creando nuevos catalizadores, las metaloenzimas artificiales (ArM). Estas ArM se diseñan a partir de la combinación de proteínas naturales con metales, lo que les permite llevar a cabo reacciones nuevas en la naturaleza. En los últimos años, la modelización molecular se ha convertido en una herramienta esencial en este campo, aunque todavía quedan por resolver algunos retos. Esta tesis doctoral pretende aplicar la modelización molecular para comprender el comportamiento de proteínas que contienen metales, centrándose en ciertas proteínas metálicas naturales y las ArM. La primera parte de esta tesis abarca el estudio de proteínas que contienen un cofactor metálico prototípico, el grupo hemo. En ella, se aplica un protocolo computacional basado en técnicas de dinámica molecular aceleradas para estudiar diferentes mecanismos de unión del grupo hemo con la proteína hemóforo HasA. Además, se desarrolla un software para detectar los sitios de unión del hemo que se basa únicamente en información estructural de las proteínas. La segunda parte de esta tesis se centra en el diseño computacional de ArM. Se aplican enfoques integradores que combinan varias técnicas, como mecánica cuántica, dockings y simulaciones de dinámica molecular para obtener un conocimiento más profundo de dos ArM: uno basado en la hidroaminación con oro y la otra en una reacción Suzuki-Miyaura en la que interviene paladio.Nature is abundant with proteins that contain metals, ranging from metalloenzymes serving crucial catalytic reactions to proteins that storage and transport metals. The molecular study of metalloproteins allows to find solutions to a wide range of chemical problems and provides insights into their recognition processes. Researchers have seized the opportunity to copy nature by create new catalysts, Artificial metalloenzymes (ArM). These ArMs are designed by combining natural protein scaffolds with metallic moieties, enabling them to carry out new reactions in nature. In the recent years, molecular modeling has become an essential tool in these fields, though certain challenges still need to be addressed. This PhD thesis aims to apply molecular modeling to understand the behavior of metal containing proteins, focusing on natural metallic proteins and ArMs. The first part of this thesis encompasses the study of proteins containing the prototypical metallic cofactor heme. A molecular modeling protocol based on enhanced molecular dynamics techniques is applied to unravel different binding mechanism of heme on protein hemophore HasA. Furthermore, a software is developed for detecting heme binding sites based only on structural information. The second part of this thesis focuses on the computational-aided design of ArM. Integrative approaches combining various techniques, such as quantum mechanics, molecular docking, and classical molecular dynamics simulations are applied to obtain a deeper understanding of two different ArMs: one based on single or dual gold hydroamination and the other a Suzuki-Miyaura reaction involving palladium.Universitat Autònoma de Barcelona. Programa de Doctorat en Bioinformàtic

BioMetAll: Identifying Metal-Binding Sites in Proteins from Backbone Preorganization

With a large amount of research dedicated to decoding how metallic species bind to proteins, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal-binding templates. These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parameterization from a statistical analysis. Then, the successful benchmark of BioMetAll on a set of more than 90 metal-binding X-ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems whose structures (either experimental or theoretical) are not optimal for metal-binding sites. We report here its application on three different challenging cases: (i) the modulation of metal-binding sites during conformational transition in human serum albumin, (ii) the identification of possible routes of metal migration in hemocyanins, and (iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding. BioMetAll is an open-source application available at https://github.com/insilichem/biometall.J.E.-S.A., L.T.-S., L.R.-M., G.S., and J.-D.M. thank Spanish MINECO (grant CTQ2017-87889-P) and Generalitat de Catalunya (2017SGR1323) for the financial support. L.T.-S. thanks Spanish Ministerio de Ciencia, Innovación y Universidades (grant FPU18/05895), for the financial support. L.V.-C. thanks the University of the Basque Country (predoctoral grant PIF17/22) for the financial support. L.R.-M. thanks Generalitat de Catalunya (grant 2020FI_B2_01000) for the financial support.Peer reviewe

BioMetAll: Identifying Metal-Binding Sites in Proteins from Backbone Preorganization

With a large amount of research dedicated to decoding how metallic species bind to protein, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal binding templates. These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parametrization from a statistical analysis. Then, the successful benchmark of BioMetAll on a set of more than 50 metal-binding X-Ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems which structures (either experimental or theoretical) are not optimal for metal binding sites. We report here its application on three different challenging cases i) the modulation of metal-binding sites during conformational transition in human serum albumin, ii) the identification of possible routes of metal migration in hemocyanins, and iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology, and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding.</div

Photocatalytic Hydrogen Production and Carbon Dioxide Reduction Catalyzed by an Artificial Cobalt Hemoprotein

The covalent insertion of a cobalt heme into the cavity of an artificial protein named alpha Rep (&alpha;Rep) leads to an artificial cobalt hemoprotein that is active as a catalyst not only for the photo-induced production of H2, but also for the reduction of CO2 in a neutral aqueous solution. This new artificial metalloenzyme has been purified and characterized by Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS), circular dichroism, and UltraViolet&ndash;Visible spectroscopy. Using theoretical experiments, the structure of this biohybrid and the positioning of the residues near the metal complex were examined, which made it possible to complete the coordination of the cobalt ion by an axial glutamine Gln283 ligand. While the Co(III)&ndash;porphyrin catalyst alone showed weak catalytic activity for both reactions, 10 times more H2 and four times more CO2 were produced when the Co(III)&ndash;porphyrin complex was buried in the hydrophobic cavity of the protein. This study thus provides a solid basis for further improvement of these biohybrids using well-designed modifications of the second and outer coordination sphere by site-directed mutagenesis of the host protein

Design and evolution of chimeric streptavidin for protein-enabled dual gold catalysis

Artificial metalloenzymes result from anchoring an organometallic catalyst within an evolvable protein scaffold. Thanks to its dimer of dimers quaternary structure, streptavidin allows the precise positioning of two metal cofactors to activate a single substrate, thus expanding the reaction scope accessible to artificial metalloenzymes. To validate this concept, we report herein on our efforts to engineer and evolve an artificial hydroaminase based on dual gold activation of alkynes. Guided by modelling, we designed a chimeric streptavidin equipped with a hydrophobic lid shielding its active site, which enforces the advantageous positioning of two synergistic biotinylated gold cofactors. Three rounds of directed evolution using Escherichia coli cell-free extracts led to the identification of mutants favouring either the anti-Markovnikov product (an indole carboxamide with 96% regioselectivity, 51 turnover numbers), resulting from a dual gold σ,π-activation of an ethynylphenylurea substrate, or the Markovnikov product (a phenyl-dihydroquinazolinone with 99% regioselectivity, 333 turnover numbers), resulting from the π-activation of the alkyne by gold