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De Souza TPP, Cantão LXS, Rodrigues MQRB, Gonçalves DB, Nagem RAP, Rocha REO, Godoi RR, Lima WJN, Galdino AS, Minardi RCDM, Lima LHFD. Glycosylation and charge distribution orchestrates the conformational ensembles of a biotechnologically promissory phytase in different pHs - a computational study. J Biomol Struct Dyn 2024; 42:5030-5041. [PMID: 37325852 DOI: 10.1080/07391102.2023.2223685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/06/2023] [Indexed: 06/17/2023]
Abstract
Phytases [myo-inositol(1,2,3,4,5,6) hexakisphosphate phosphohydrolases] are phytate-specific phosphatases not present in monogastric animals. Nevertheless, they are an essential supplement to feeding such animals and for human special diets. It is crucial, hence, the biotechnological use of phytases with intrinsic stability and activity at the acid pHs from gastric environments. Here we use Metadynamics (METADY) simulations to probe the conformational space of the Aspergillus nidulans phytase and the differential effects of pH and glycosylation in this same space. The results suggest that strategic combinations of pH and glycosylation affect the stability of native-like conformations and alternate these structures from a metastable to a stable profile. Furthermore, the protein segments previously reported as more thermosensitive in phytases from this family present a pivotal role in the conformational changes at different conditions, especially H2, H5-7, L8, L10, L12, and L17. Also, the glycosylations and the pH-dependent charge balance modulate the mobility and interactions at these same regions, with consequences for the surface solvation and active site exposition. Finally, although the glycosylations have stabilized the native structure and improved the substrate docking at all the studied pHs, the data suggest a higher phytate receptivity at catalytic poses for the unglycosylated structure at pH 6.5 and the glycosylated one at pH 4.5. This behavior agrees with the exact change in optimum pH reported for this enzyme, expressed on low or high glycosylating systems. We hope the results and insights presented here will be helpful in future approaches for rational engineering of technologically promising phytases and intelligent planning of their heterologous expression systems and conditions for use.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Thaís P P De Souza
- Microbial Biotechnology Laboratory, Universidade Federal de São João Del-Rei, Divinópolis, Minas Gerais, Brazil
| | - Letícia Xavier Silva Cantão
- Laboratory of Bioinformatics and Systems (LBS), Department Of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Daniel Bonoto Gonçalves
- Department of Biosystems Engineering, Universidade Federal de São João Del-Rei, São João Del-Rei, Minas Gerais, Brazil
| | - Ronaldo Alves Pinto Nagem
- Institute of Biological Sciences Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Rafael Eduardo Oliveira Rocha
- Laboratory of Bioinformatics and Systems (LBS), Department Of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Laboratory Of Molecular Modeling and Bioinformatics, Department of Exacts and Biological Sciences (DECEB), Universidade Federal de São João Del-Rei, Sete Lagoas, Minas Gerais, Brazil
| | - Renato Ramos Godoi
- Institute of Biological Sciences Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - William James Nogueira Lima
- Institute of Agricultural Sciences, Universidade Federal de Minas Gerais, Campus Regional de Montes Claros, Montes Claros, Minas Gerais, Brazil
| | - Alexsandro Sobreira Galdino
- Microbial Biotechnology Laboratory, Universidade Federal de São João Del-Rei, Divinópolis, Minas Gerais, Brazil
| | - Raquel Cardoso de Melo Minardi
- Laboratory of Bioinformatics and Systems (LBS), Department Of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Leonardo Henrique França de Lima
- Laboratory Of Molecular Modeling and Bioinformatics, Department of Exacts and Biological Sciences (DECEB), Universidade Federal de São João Del-Rei, Sete Lagoas, Minas Gerais, Brazil
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2
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Dong CD, Patel AK, Madhavan A, Chen CW, Singhania RR. Significance of glycans in cellulolytic enzymes for lignocellulosic biorefinery - A review. BIORESOURCE TECHNOLOGY 2023; 379:128992. [PMID: 37011847 DOI: 10.1016/j.biortech.2023.128992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 05/03/2023]
Abstract
Lignocellulosic (LC) biomass is the most abundant renewable resource for mankind gravitating society towards sustainable solution for energy that can reduce the carbon footprint. The economic feasibility of 'biomass biorefinery' depends upon the efficiency cellulolytic enzymes which is the main crux. Its high production cost and low efficiencies are the major limitations, that need to be resolved. As the complexity of the genome increases, so does the complexity of the proteome, further facilitated by protein post-translational modifications (PTMs). Glycosylation is regarded the major PTMs and hardly any recent work is focused on importance of glycosylation in cellulase. By modifying protein side chains and glycans, superior cellulases with improved stability and efficiency can be obtained. Functional proteomics relies heavily on PTMs because they regulate activity, localization, and interactions with protein, lipid, nucleic acid, and cofactor molecules. O- and N- glycosylation in cellulases influences its characteristics adding positive attributes to the enzymes.
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Affiliation(s)
- Cheng-Di Dong
- Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan; Sustainable Environment Research Center, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan
| | - Anil Kumar Patel
- Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan; Centre for Energy and Environmental Sustainability, Lucknow 226 029, India
| | - Aravind Madhavan
- School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, Kerala 690 525, India
| | - Chiu-Wen Chen
- Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan; Sustainable Environment Research Center, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan
| | - Reeta Rani Singhania
- Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan; Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan; Centre for Energy and Environmental Sustainability, Lucknow 226 029, India.
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3
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Rocha REO, Mariano DCB, Almeida TS, CorrêaCosta LS, Fischer PHC, Santos LH, Caffarena ER, da Silveira CH, Lamp LM, Fernandez-Quintero ML, Liedl KR, de Melo-Minardi RC, de Lima LHF. Thermostabilizing mechanisms of canonical single amino acid substitutions at a GH1 β-glucosidase probed by multiple MD and computational approaches. Proteins 2023; 91:218-236. [PMID: 36114781 DOI: 10.1002/prot.26424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 01/07/2023]
Abstract
β-glucosidases play a pivotal role in second-generation biofuel (2G-biofuel) production. For this application, thermostable enzymes are essential due to the denaturing conditions on the bioreactors. Random amino acid substitutions have originated new thermostable β-glucosidases, but without a clear understanding of their molecular mechanisms. Here, we probe by different molecular dynamics simulation approaches with distinct force fields and submitting the results to various computational analyses, the molecular bases of the thermostabilization of the Paenibacillus polymyxa GH1 β-glucosidase by two-point mutations E96K (TR1) and M416I (TR2). Equilibrium molecular dynamic simulations (eMD) at different temperatures, principal component analysis (PCA), virtual docking, metadynamics (MetaDy), accelerated molecular dynamics (aMD), Poisson-Boltzmann surface analysis, grid inhomogeneous solvation theory and colony method estimation of conformational entropy allow to converge to the idea that the stabilization carried by both substitutions depend on different contributions of three classic mechanisms: (i) electrostatic surface stabilization; (ii) efficient isolation of the hydrophobic core from the solvent, with energetic advantages at the solvation cap; (iii) higher distribution of the protein dynamics at the mobile active site loops than at the protein core, with functional and entropic advantages. Mechanisms i and ii predominate for TR1, while in TR2, mechanism iii is dominant. Loop A integrity and loops A, C, D, and E dynamics play critical roles in such mechanisms. Comparison of the dynamic and topological changes observed between the thermostable mutants and the wildtype protein with amino acid co-evolutive networks and thermostabilizing hotspots from the literature allow inferring that the mechanisms here recovered can be related to the thermostability obtained by different substitutions along the whole family GH1. We hope the results and insights discussed here can be helpful for future rational approaches to the engineering of optimized β-glucosidases for 2G-biofuel production for industry, biotechnology, and science.
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Affiliation(s)
- Rafael Eduardo Oliveira Rocha
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Campus Sete Lagoas, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil.,Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.,Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Diego César Batista Mariano
- Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Tiago Silva Almeida
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Campus Sete Lagoas, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
| | - Leon Sulfierry CorrêaCosta
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Campus Sete Lagoas, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil.,Computational Modeling Coordination (COMOD), Laboratório Nacional de Computação Científica (LNCC), Petrópolis, Brazil
| | - Pedro Henrique Camargo Fischer
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Campus Sete Lagoas, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
| | - Lucianna Helene Santos
- Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.,Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | - Leonida M Lamp
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Chemistry and Biomedicine Innsbruck (CCB), University of Innsbruck, Innsbruck, Austria
| | - Monica Lisa Fernandez-Quintero
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Chemistry and Biomedicine Innsbruck (CCB), University of Innsbruck, Innsbruck, Austria
| | - Klaus Roman Liedl
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Chemistry and Biomedicine Innsbruck (CCB), University of Innsbruck, Innsbruck, Austria
| | - Raquel Cardoso de Melo-Minardi
- Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Leonardo Henrique França de Lima
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Campus Sete Lagoas, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil.,Institute of General, Inorganic and Theoretical Chemistry, and Center for Chemistry and Biomedicine Innsbruck (CCB), University of Innsbruck, Innsbruck, Austria
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4
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Dos Santos VP, Rodrigues A, Dutra G, Bastos L, Mariano D, Mendonça JG, Lobo YJG, Mendes E, Maia G, Machado KDS, Werhli AV, Rocha G, de Lima LHF, de Melo-Minardi R. E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces. PeerJ 2022; 10:e13099. [PMID: 35341044 PMCID: PMC8953562 DOI: 10.7717/peerj.13099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 02/21/2022] [Indexed: 01/12/2023] Open
Abstract
Background The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein. Methods Hence, for real-time measuring of the impacts caused by variant strains in such complexes, we implemented E-Volve, a tool designed to model a structure with a list of mutations requested by users and return analyses of the variant protein. As a proof of concept, we scrutinized the spike-antibody and spike-ACE2 complexes formed in the variants of concern, B.1.1.7 (Alpha), B.1.351 (Beta), and P.1 (Gamma), by using contact maps depicting the interactions made amid them, along with heat maps to quantify these major interactions. Results The results found in this study depict the highly frequent interface changes made by the entire set of mutations, mainly conducted by N501Y and E484K. In the spike-Antibody complex, we have noticed alterations concerning electrostatic surface complementarity, breaching essential sites in the P17 and BD-368-2 antibodies. Alongside, the spike-ACE2 complex has presented new hydrophobic bonds. Discussion Molecular dynamics simulations followed by Poisson-Boltzmann calculations corroborate the higher complementarity to the receptor and lower to the antibodies for the K417T/E484K/N501Y (Gamma) mutant compared to the wild-type strain, as pointed by E-Volve, as well as an intensification of this effect by changes at the protein conformational equilibrium in solution. A local disorder of the loop α1'/β1', as well its possible effects on the affinity to the BD-368-2 antibody were also incorporated to the final conclusions after this analysis. Moreover, E-Volve can depict the main alterations in important biological structures, as shown in the SARS-CoV-2 complexes, marking a major step in the real-time tracking of the virus mutant lineages. E-Volve is available at http://bioinfo.dcc.ufmg.br/evolve.
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Affiliation(s)
- Vitor Pimentel Dos Santos
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - André Rodrigues
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Gabriel Dutra
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Luana Bastos
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Diego Mariano
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - José Gutembergue Mendonça
- Laboratory of Quantum and Computational Chemistry, Center of Exact and Natural Sciences, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, PB, Brazil
| | - Yan Jerônimo Gomes Lobo
- Laboratory of Molecular Modeling and Bioinformatics, Campus Sete Lagoas, Department of Exact and Biological Sciences, Universidade Federal de São João del-Rei, Sete Lagoas, MG, Brazil
| | - Eduardo Mendes
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Giovana Maia
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Karina dos Santos Machado
- Computational Biology Laboratory (ComBi-Lab), Center for Computational Sciences-C3, Universidade Federal do Rio Grande, Rio Grande, RS, Brazil
| | - Adriano Velasque Werhli
- Computational Biology Laboratory (ComBi-Lab), Center for Computational Sciences-C3, Universidade Federal do Rio Grande, Rio Grande, RS, Brazil
| | - Gerd Rocha
- Laboratory of Quantum and Computational Chemistry, Center of Exact and Natural Sciences, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, PB, Brazil
| | - Leonardo Henrique França de Lima
- Laboratory of Molecular Modeling and Bioinformatics, Campus Sete Lagoas, Department of Exact and Biological Sciences, Universidade Federal de São João del-Rei, Sete Lagoas, MG, Brazil
| | - Raquel de Melo-Minardi
- Laboratory of Bioinformatics and Systems, Institute of Exact Sciences, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
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5
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Fungal cellulases: protein engineering and post-translational modifications. Appl Microbiol Biotechnol 2021; 106:1-24. [PMID: 34889986 DOI: 10.1007/s00253-021-11723-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 11/28/2021] [Accepted: 11/30/2021] [Indexed: 12/18/2022]
Abstract
Enzymatic degradation of lignocelluloses into fermentable sugars to produce biofuels and other biomaterials is critical for environmentally sustainable development and energy resource supply. However, there are problems in enzymatic cellulose hydrolysis, such as the complex cellulase composition, low degradation efficiency, high production cost, and post-translational modifications (PTMs), all of which are closely related to specific characteristics of cellulases that remain unclear. These problems hinder the practical application of cellulases. Due to the rapid development of computer technology in recent years, computer-aided protein engineering is being widely used, which also brings new opportunities for the development of cellulases. Especially in recent years, a large number of studies have reported on the application of computer-aided protein engineering in the development of cellulases; however, these articles have not been systematically reviewed. This article focused on the aspect of protein engineering and PTMs of fungal cellulases. In this manuscript, the latest literatures and the distribution of potential sites of cellulases for engineering have been systematically summarized, which provide reference for further improvement of cellulase properties. KEY POINTS: •Rational design based on virtual mutagenesis can improve cellulase properties. •Modifying protein side chains and glycans helps obtain superior cellulases. •N-terminal glutamine-pyroglutamate conversion stabilizes fungal cellulases.
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Pimentel V, Mariano D, Cantão LXS, Bastos LL, Fischer P, de Lima LHF, Fassio AV, de Melo-Minardi RC. VTR: A Web Tool for Identifying Analogous Contacts on Protein Structures and Their Complexes. FRONTIERS IN BIOINFORMATICS 2021; 1:730350. [PMID: 36303745 PMCID: PMC9581016 DOI: 10.3389/fbinf.2021.730350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 07/27/2021] [Indexed: 11/19/2022] Open
Abstract
Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of the inter-residues contacts for the protein structure has been the target of many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular structures such as proteins. Here we show VTR, a new method for the detection of analogous contacts in protein pairs. The VTR web tool performs structural alignment between proteins and detects interactions that occur in similar regions. To evaluate our tool, we proposed three case studies: we 1) compared vertebrate myoglobin and truncated invertebrate hemoglobin; 2) analyzed interactions between the spike protein RBD of SARS-CoV-2 and the cell receptor ACE2; and 3) compared a glucose-tolerant and a non-tolerant β-glucosidase enzyme used for biofuel production. The case studies demonstrate the potential of VTR for the understanding of functional similarities between distantly sequence-related proteins, as well as the exploration of important drug targets and rational design of enzymes for industrial applications. We envision VTR as a promising tool for understanding differences and similarities between homologous proteins with similar 3D structures but different sequences. VTR is available at http://bioinfo.dcc.ufmg.br/vtr.
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Affiliation(s)
- Vitor Pimentel
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Diego Mariano
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Letícia Xavier Silva Cantão
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luana Luiza Bastos
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Pedro Fischer
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Universidade Federal de São João Del-Rei, Sete Lagoas, Brazil
| | - Leonardo Henrique Franca de Lima
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Universidade Federal de São João Del-Rei, Sete Lagoas, Brazil
| | - Alexandre Victor Fassio
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Raquel Cardoso de Melo-Minardi
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- *Correspondence: Raquel Cardoso de Melo-Minardi,
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7
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Rocha REO, Chaves EJF, Fischer PHC, Costa LSC, Grillo IB, da Cruz LEG, Guedes FC, da Silveira CH, Scotti MT, Camargo AD, Machado KS, Werhli AV, Ferreira RS, Rocha GB, de Lima LHF. A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers. J Biomol Struct Dyn 2021; 40:9214-9234. [PMID: 33970798 PMCID: PMC8127201 DOI: 10.1080/07391102.2021.1924271] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022]
Abstract
The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rafael E. O. Rocha
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Laboratory of Structural Biology, Department of Molecular Biology, Universität Salzburg, Salzburg, Austria
| | - Elton J. F. Chaves
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Pedro H. C. Fischer
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
| | - Leon S. C. Costa
- Comp. Modeling Coordination, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Igor Barden Grillo
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Luiz E. G. da Cruz
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Fabiana C. Guedes
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Carlos H. da Silveira
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Marcus T. Scotti
- Graduate Program in Natural and Synthetic Bioactive Products; Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Alex D. Camargo
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Karina S. Machado
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Adriano V. Werhli
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Rafaela S. Ferreira
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Gerd B. Rocha
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Leonardo H. F. de Lima
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
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8
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Mariano D, Pantuza N, Santos LH, Rocha REO, de Lima LHF, Bleicher L, de Melo-Minardi RC. Glutantβase: a database for improving the rational design of glucose-tolerant β-glucosidases. BMC Mol Cell Biol 2020; 21:50. [PMID: 32611314 PMCID: PMC7329481 DOI: 10.1186/s12860-020-00293-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/22/2020] [Indexed: 11/22/2022] Open
Abstract
Β-glucosidases are key enzymes used in second-generation biofuel production. They act in the last step of the lignocellulose saccharification, converting cellobiose in glucose. However, most of the β-glucosidases are inhibited by high glucose concentrations, which turns it a limiting step for industrial production. Thus, β-glucosidases have been targeted by several studies aiming to understand the mechanism of glucose tolerance, pH and thermal resistance for constructing more efficient enzymes. In this paper, we present a database of β-glucosidase structures, called Glutantβase. Our database includes 3842 GH1 β-glucosidase sequences collected from UniProt. We modeled the sequences by comparison and predicted important features in the 3D-structure of each enzyme. Glutantβase provides information about catalytic and conserved amino acids, residues of the coevolution network, protein secondary structure, and residues located in the channel that guides to the active site. We also analyzed the impact of beneficial mutations reported in the literature, predicted in analogous positions, for similar enzymes. We suggested these mutations based on six previously described mutants that showed high catalytic activity, glucose tolerance, or thermostability (A404V, E96K, H184F, H228T, L441F, and V174C). Then, we used molecular docking to verify the impact of the suggested mutations in the affinity of protein and ligands (substrate and product). Our results suggest that only mutations based on the H228T mutant can reduce the affinity for glucose (product) and increase affinity for cellobiose (substrate), which indicates an increment in the resistance to product inhibition and agrees with computational and experimental results previously reported in the literature. More resistant β-glucosidases are essential to saccharification in industrial applications. However, thermostable and glucose-tolerant β-glucosidases are rare, and their glucose tolerance mechanisms appear to be related to multiple and complex factors. We gather here, a set of information, and made predictions aiming to provide a tool for supporting the rational design of more efficient β-glucosidases. We hope that Glutantβase can help improve second-generation biofuel production. Glutantβase is available at http://bioinfo.dcc.ufmg.br/glutantbase .
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Affiliation(s)
- Diego Mariano
- Laboratory of Bioinformatics and Systems. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil.
| | - Naiara Pantuza
- Laboratory of Bioinformatics and Systems. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Lucianna H Santos
- Laboratory of Bioinformatics and Systems. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Rafael E O Rocha
- Laboratory of Bioinformatics and Systems. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Leonardo H F de Lima
- Laboratory of Molecular Modelling and Bioinformatics (LAMMB), Department of Physical and Biological Sciences, Universidade Federal de São João Del-Rei, Campus Sete Lagoas, Sete Lagoas, 35701-970, Brazil
| | - Lucas Bleicher
- Protein Computational Biology Laboratory, Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Raquel Cardoso de Melo-Minardi
- Laboratory of Bioinformatics and Systems. Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil.
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