Triagem virtual de proteínas com interação com TNF-α na saliva de Ixodes scapularis

Abstract

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine produced mainly by lymphocytes and macrophages in response to different stimuli. Although inflammation is a mechanism to protect the body, an inappropriate or exacerbated inflammatory reaction can result in tissue damage and in severe cases can cause organ failure and death. Currently anti-TNF-α drugs such as Infliximab and Adalimumab are used in the treatment of inflammatory diseases, including ankylosing spondylitis and Crohn's disease, however, in addition to the important side effects, these immunobiologicals are extremely expensive and difficult for the population to access. Hematophagous arthropods, especially ticks, produce bioactive substances capable of modulating the activity of immune molecules, including cytokines. Konik et al., for example, described anti-TNF-α activity in the saliva and salivary gland extract of Ixodes ricinus ticks. Subsequently, Rezková and Kopecký compared the presence of anti-TNF-α activity in 11 tick species of the Ixodidae family, finding activity in Haemaphysalis concinna, Ixodes hexagonus, Ixodes persulcatus and Ixodes scapularis. Thus, the identification and isolation of a protein with anti-TNF-α activity in tick saliva opens possibilities for use in the treatment of inflammatory and autoimmune diseases. However, one of the challenges of identifying and isolating proteins and other immunomodulatory molecules in tick saliva by common methodologies, such as separation by immune reactions, microHPLC and identification by mass spectrometry, is a large number of compounds in very small amounts, making the in silico prospecting is required. The aim of the present work was to perform a virtual screening of proteins that interact with TNF-α in the saliva of Ixodes scapularis using molecular modeling and docking. Molecular modeling of 548 proteins was performed, of which 150 are housekeeping proteins and 398 secreted proteins classified using the Robetta tool and verified using VERIFY 3D. The structures were anchored to TNF-α initially with rigid docking without site crossing using ClusPro, Hdock and Zdock tools. The best evaluated proteins for the three tools were submitted to the flexible SwarmDock docking tool, then binding energies, number of interaction residues in common with the TNF-R2 receptor and buried surface area were evaluated. Protein AAM93640.1 was identified, a possible histamine-binding lipocalin that binds to TNF-α A and C chains. This protein makes 137 atomic contacts of which 4 are repulsive, 10 attractive contacts and 30 atomic hydrogen bonds, in addition to 90 hydrophobic atomic contacts obtaining a binding energy of 144 Å. Furthermore, lipocalin interacts with 8 of the 13 residues that are part of the TNF-R2 receptor binding site. Taking into account the characteristics, considering the use of lipocalins as biopharmaceuticals, it is suggested that the AAM93640.1 protein is a good candidate for a protein with TNF-α inhibitory activity