An Approach for Engineering Peptides for Competitive Inhibition of the SARS-COV-2 Spike Protein
Ana Paula de Abreu,
Frederico Chaves Carvalho,
Diego Mariano,
Luana Luiza Bastos,
Juliana Rodrigues Pereira Silva,
Leandro Morais de Oliveira,
Raquel C. de Melo-Minardi,
Adriano de Paula Sabino
Affiliations
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
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
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
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
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
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
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
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.