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de Abreu AP, Carvalho FC, Mariano D, Bastos LL, Silva JRP, de Oliveira LM, de Melo-Minardi RC, Sabino ADP. An Approach for Engineering Peptides for Competitive Inhibition of the SARS-COV-2 Spike Protein. Molecules 2024; 29:1577. [PMID: 38611856 PMCID: PMC11013848 DOI: 10.3390/molecules29071577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 02/29/2024] [Accepted: 03/22/2024] [Indexed: 04/14/2024] Open
Abstract
SARS-CoV-2 is the virus responsible for a respiratory disease called COVID-19 that devastated global public health. Since 2020, there has been an intense effort by the scientific community to develop safe and effective prophylactic and therapeutic agents against this disease. In this context, peptides have emerged as an alternative for inhibiting the causative agent. However, designing peptides that bind efficiently is still an open challenge. Here, we show an algorithm for peptide engineering. Our strategy consists of starting with a peptide whose structure is similar to the interaction region of the human ACE2 protein with the SPIKE protein, which is important for SARS-COV-2 infection. Our methodology is based on a genetic algorithm performing systematic steps of random mutation, protein-peptide docking (using the PyRosetta library) and selecting the best-optimized peptides based on the contacts made at the peptide-protein interface. We performed three case studies to evaluate the tool parameters and compared our results with proposals presented in the literature. Additionally, we performed molecular dynamics (MD) simulations (three systems, 200 ns each) to probe whether our suggested peptides could interact with the spike protein. Our results suggest that our methodology could be a good strategy for designing peptides.
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Affiliation(s)
- Ana Paula de Abreu
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Frederico Chaves Carvalho
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Diego Mariano
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Luana Luiza Bastos
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Juliana Rodrigues Pereira Silva
- Department of Biochemistry and Immunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil
| | - Leandro Morais de Oliveira
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Raquel C. de Melo-Minardi
- Laboratory of Bioinformatics and Systems, Department of Computer Science, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil; (A.P.d.A.); (F.C.C.); (L.L.B.); (L.M.d.O.)
| | - Adriano de Paula Sabino
- Laboratory of Clinical and Experimental Hematology, Clinical and Toxicological Analysis Department, Faculty of Pharmacy, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil
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Abstract
We report an analysis of Homo sapiens DNA through the formalism of κ statistics, which encompasses power-law correlations and provides an optimization principle that permits us to model distinct physical systems; i.e., the power-law distribution of the length of DNA bases is calculated from a general model which follows arguments similar to those proposed in Maxwell's deduction of statistical distributions. The viability of the model is tested using a data set from a catalog of proteins collected from the Ensembl Project. The results indicate that the short-range correlations, always present in coding DNA sequences, are appropriately captured through the Kaniadakis power-law distribution, adequately describing the cumulative length distribution of DNA bases, in contrast with the case of the traditional exponential statistical model.
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Affiliation(s)
- M O Costa
- Departamento de Física, Universidade do Estado do Rio Grande do Norte, Mossoró, 59610-210, Brazil
| | - R Silva
- Departamento de Física, Universidade do Estado do Rio Grande do Norte, Mossoró, 59610-210, Brazil.,Universidade Federal do Rio Grande do Norte, Departamento de Física, Natal-RN, 59072-970, Brazil
| | - D H A L Anselmo
- Universidade Federal do Rio Grande do Norte, Departamento de Física, Natal-RN, 59072-970, Brazil
| | - J R P Silva
- Departamento de Física, Universidade do Estado do Rio Grande do Norte, Mossoró, 59610-210, Brazil
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