Jenipher Stephanie Pereira das Neves; Arthur Araújo de Lacerda; Edson Luiz Folador.
In late 2019, new pneumonia quickly emerged in Wuhan, China. Experts identified the causative agent as a new coronavirus, called SARS-CoV-2, which belongs to the Betacoronavirus genus and the Sarbecovirus subgenus. covid-19 has spread globally and on March 12, 2020, the World Health Organization officially declared a global pandemic. Despite vaccines, the continued emergence of new variants of the virus may compromise the effectiveness of immunization, generating a more contagious and less sensitive to vaccines variant of SARS-CoV-2, possibly leading to immune evasion and reduced vaccine effectiveness. In this scenario, finding effective antiviral treatments becomes crucial, complementing our approaches to combating the disease. These therapies can reduce the severity of symptoms and control the disease, playing a fundamental role in protecting the population. New drug discovery involves computational methods that evaluate multiple drug candidates, identifying promising molecules for future biological testing. These techniques enable efficient and cost-effective screening, significantly accelerating the drug development process. Nitazoxanide or Annita®, is among some of the drugs used to treat covid-19, being a broad-spectrum antiparasitic drug, with efficacy described against a wide range of parasites, it has shown promise in the treatment of covid-19, reducing the time of hospitalization and reducing immunological and T lymphocyte activation markers. Furthermore, it can cause depletion of ATP-sensitive Ca 2+ storage, phosphorylation of protein kinase, inhibition of cellular translation and impairment of viral replication capacity. Reuse of existing medicines is encouraged due to the advantage of taking advantage of prior knowledge about safety, dosage and complications. Furthermore, this approach is more accessible in terms of cost, facilitating its use on a large scale. Thus, computational methods are promising for identifying nitazoxanide analogues with potential antiviral action against SARS-CoV-2, contributing to new treatments for covid-19. This work aims to identify possible molecules analogous to Nitazoxanide, which present antiviral activity against SARS-CoV-2, based on protein-ligand interaction, through the search for similar pharmacophoric groups and evaluation of pharmacokinetic and toxicity properties. The work consists of 6 steps: LBVS, SBVS, selection of the best protein-analogue complexes, search for pharmacophoric groups, energy minimization and analysis of pharmacokinetic properties. In the LBVS stage, nitazoxanide analogues were downloaded from the ZINC and PUBCHEM databases. At SBVS, SARS-CoV-2 target proteins were downloaded, filtered and prepared, 7KR1, 7KNB and 7DK5, then pockets with druggability score >= 0.5 were predicted and selected, followed by docking of the analogues in these pockets. The complexed analogues were used to search for similar pharmacophoric groups using Pharmit. The molecules that presented more negative affinity scores than nitazoxanide (-9.00 kcal/mol), in the energy minimization stage, passed to the ADMET analysis stage (Absorption, distribution, metabolism, excretion and toxicity) in AdmetLab 2.0. Molecules analogous to nitazoxanide with the best affinity scores showed high toxicity, therefore, a search was carried out for similar pharmacophoric groups in order to find analogues of these candidates with promising affinity scores, in addition to good pharmacokinetic properties and lower toxicity. The result of this search produced 2,553 compounds with affinity values more negative than -9.0 kcal/mol, from different sources, including 204 from ZINC, 2,019 from PubChem and 330 from CHEMBL32. In total, 1,519 molecules had their ADMET properties analyzed and 83 showed satisfactory results in absorption, metabolism, distribution, excretion and lower toxicity compared to nitazoxanide, being subjected to a more detailed analysis to select the best ones. Finally, 11 molecules achieved the best performances, and 4 of them did not show toxicity in silico tests. Nitazoxanide itself exhibits trace toxicity, demonstrating unfavorable results in assessments of drug-induced liver injury (DILI), AMES toxicity, carcinogenic potential, and respiratory toxicity. Notably, a probability slightly above 0.8 appears, indicating the possibility of it being a compound with carcinogenic potential and influencing the p53 protein (SR-p53), associated with tumor suppression, as well as having two groups in its structure that raise warnings about the rule of genotoxic carcinogenicity. Furthermore, nitazoxanide has a value classified as unfavorable with regard to the respiratory toxicity parameter. This aspect must be carefully considered as a negative point for drugs intended to combat covid-19, so all molecules that showed this toxicity were immediately discarded. As a result, all molecules presented as the best results obtained fewer toxicity points compared to the model drug. Based on the available literature, Nitazoxanide was identified as a possible model with potential pharmacological action against covid-19. Studies were conducted and provided evidence that pointed to its effectiveness against the virus. These discoveries motivated this study, consisting of the creation of a library of analogous compounds, which presented chemical similarity to Nitazoxanide, and subsequently, the analogues of the model drug went through the stages of virtual screening, energy minimization and analysis of pharmacokinetic properties. In the ADMET property analyses, 11 molecules (A8, A9, D2, E4, E5, E6, E7, E8, E10, E11 and E12) were identified with promising results. Among them, 4 molecules proved to be non-toxic in all parameters related to toxicity. The molecules received an alphanumeric nomenclature to preserve their identities due to the possibility of carrying out future work. All met the SAscore parameter, which evaluates ease of synthesis, except E7. However, E7 is a monoterpenoid diglucoside, derived from "madressilva de caixa" (Lonicera nitida E. H. Wilson, family Caprifoliaceae), which makes it a valuable candidate due to the possibility of natural extraction of this molecule. The identified molecules not only possess favorable pharmacological profiles, but also demonstrated significant interactions with the active sites of NSP3 and SPIKE. This highlights the effectiveness of the pharmacophoric group search strategy in obtaining compounds with higher affinity and lower in silico toxicity compared to Nitazoxanide. The combination of these interactions with low toxicity makes these molecules promising candidates for future in vitro testing.
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Comissão Organizadora
Francisco Mendonça Junior
Pascal Marchand
Teresinha Gonçalves da Silva
Isabelle Orliac-Garnier
Gerd Bruno da Rocha
Comissão Científica
Ricardo Olimpio de Moura
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