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Ononugbo CM, Shimura Y, Yamano-Adachi N, Omasa T, Koga Y. Rational design approach to improve the solubility of the β-sandwich domain 1 of a thermophilic protein. J Biosci Bioeng 2024; 138:271-282. [PMID: 39074993 DOI: 10.1016/j.jbiosc.2024.06.009] [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: 02/20/2024] [Revised: 05/28/2024] [Accepted: 06/20/2024] [Indexed: 07/31/2024]
Abstract
The β-sandwich domain 1 (SD1) of islandisin is a stable thermophilic protein with surface loops that can be redesigned for specific target binding, architecturally comparable to the variable domain of immunoglobulin (IgG). SD1's propensity to aggregate due to incorrect folding and subsequent accumulation in Escherichia coli inclusion bodies limits its use in biotechnological applications. We rationally designed SD1 for improved variants that were expressed in soluble forms in E. coli while maintaining the intrinsic thermal stability of the protein (melting temperature (Tm) = 73). We used FoldX's ΔΔG predictions to find beneficial mutations and aggregation-prone regions (APRs) using Tango. The S26K substitution within protein core residues did not affect protein stability. Among the soluble mutants studied, the S26K/Q91P combination significantly improved the expression and solubility of SD1. We also examined the effects of the surface residue, pH, and concentration on the solubility of SD1. We showed that the surface polarity of proteins had little or no effect on solubility, whereas surface charges played a substantial role. The storage stability of several SD1 variants was impaired at pH values near their isoelectric point, and pH levels resulting in highly charged groups. We observed that mutations that create an uneven distribution of charged groups on the SD1 surface could enhance protein solubility by eliminating favorable protein-protein surface charge interactions. Our findings suggest that SD1 is mutationally tolerant to new functionalities, thus providing a novel perspective for the application of rational design to improve the solubility of targeted proteins.
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Affiliation(s)
- Chukwuebuka M Ononugbo
- Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Yusaku Shimura
- Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Noriko Yamano-Adachi
- Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Takeshi Omasa
- Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Yuichi Koga
- Department of Applied Chemistry, Faculty of Engineering, Okayama University of Science, 1-1 Ridaicho, Kitaku, Okayama 700-0005, Japan.
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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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Gonzalez NA, Li BA, McCully ME. The stability and dynamics of computationally designed proteins. Protein Eng Des Sel 2022; 35:gzac001. [PMID: 35174855 PMCID: PMC9214642 DOI: 10.1093/protein/gzac001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 12/11/2022] Open
Abstract
Protein stability, dynamics and function are intricately linked. Accordingly, protein designers leverage dynamics in their designs and gain insight to their successes and failures by analyzing their proteins' dynamics. Molecular dynamics (MD) simulations are a powerful computational tool for quantifying both local and global protein dynamics. This review highlights studies where MD simulations were applied to characterize the stability and dynamics of designed proteins and where dynamics were incorporated into computational protein design. First, we discuss the structural basis underlying the extreme stability and thermostability frequently observed in computationally designed proteins. Next, we discuss examples of designed proteins, where dynamics were not explicitly accounted for in the design process, whose coordinated motions or active site dynamics, as observed by MD simulation, enhanced or detracted from their function. Many protein functions depend on sizeable or subtle conformational changes, so we finally discuss the computational design of proteins to perform a specific function that requires consideration of motion by multi-state design.
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Affiliation(s)
- Natali A Gonzalez
- Department of Biology, Santa Clara University, 500 El Camino Real, Santa Clara, CA 95053, USA
| | - Brigitte A Li
- Department of Biology, Santa Clara University, 500 El Camino Real, Santa Clara, CA 95053, USA
| | - Michelle E McCully
- Department of Biology, Santa Clara University, 500 El Camino Real, Santa Clara, CA 95053, USA
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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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