Aminonitriles are heterocyclic compounds commonly used as intermediates in the synthesis of various compounds, but which have versatility in physiological processes, with peculiar characteristics and high biological value that still needs to be investigated with greater avidity. Given this perspective, the present study aimed to determine the probability of substituted aminonitriles interacting with classes of pharmacological targets in the human body. For this, 8 unpublished aminonitriles (HAN-1 to HAN-8) were synthesized and used in the in silico prediction of the compounds, using the Molinspiration software, where the potentiality of the substances to act as a G Protein Coupled Receptor (GPCR) ligand was evaluated. , ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor and enzyme inhibitor. Thus, it was observed that the molecules showed considerable bioactivity in 100% for GPCR ligand (-0.27 to -0.5), 87.5% as enzyme inhibitor (-0.33 to -0.49), 75 % as a kinase inhibitor (-0.39 to -0.5), 62.5% as an ion channel modulator (-0.3 to -0.47) and as a protease inhibitor (-0.45 to -0 .49) and 37.5% as nuclear receptor ligand (-0.43 to -0.46). The computational analysis carried out in this study indicated that the HAN-4 and HAN-6 molecules were the only ones that reached a considerable activity score for all classes of proposed pharmacological targets, thus being the most promising to be possible therapeutic tools, being necessary , yet, advances in studies, such as the performance of pre-clinical and clinical tests to verify its real bioactivity.
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                    In Silico Pharmacological Prediction of Substituted Aminonitriles
                
                                    
                
                
                    Published:
15 November 2023
by MDPI
in The 27th International Electronic Conference on Synthetic Organic Chemistry
session Computational Chemistry
                
                                    
                
                
                    Abstract: 
                                    
                        Keywords: in silico; aminonitriles; pharmacological targets; computer simulation;
                    
                
                
                
                 
         
            
 
        
    
    
         
    
    
         
    
    
         
    
    
         
    
