A mechanistic insight for the biosynthesis of N,N-dimethyltryptamine: An ONIOM theoretical approach.

Psychoactive natural products are potent serotonergic agonists capable of modulating brain functions such as memory and cognition. These substances have shown therapeutic potential for treating various mental disorders. The fact that N,N-dimethyltryptamine (DMT) is produced endogenously in several plants and animals, including humans, makes it particularly attractive. As an amino acid-derived alkaloid, the DMT biosynthetic pathway is part of the L-tryptophan biochemical cascade and can be divided into the decarboxylation by an aromatic L-amino acid decarboxylase (AADC) for tryptamine formation and the subsequent double-methylation by the indolethylamine-N-methyltransferase (INMT) through the cofactor S-adenosyl-L-methionine (SAM), a methyl donor. Unlike the decarboxylation mechanism of L-tryptophan, the molecular details of the double methylation of tryptamine have not been elucidated. Therefore, we propose an in silico model using molecular dynamics (MD), non-covalent interaction index (NCI) and density functional theory (DFT) calculations with the ONIOM QM:MM B3LYP/6-31+G(d,p):MM/UFF level of theory. Based on the obtained energetic data, the potential energy surface (PES) indicates an SN2 mechanism profile, with the second methylation energy barrier being the rate-limiting step with δG‡=60kJ∙mol-1 larger than the previous methylation, following the NCI analysis showing more repulsive interactions for the second transition state. In addition, the hybridization information of each reaction step provides geometric details about the double-methylation.

Structural insights and molecular dynamics into the inhibitory mechanism of a Kunitz-type trypsin inhibitor from Tamarindus indica L.

Trypsin inhibitors from tamarind seed have been studied in vitro and in preclinical studies for the treatment of obesity, its complications and associated comorbidities. It is still necessary to fully understand the structure and behaviour of these molecules. We purifed this inhibitor, sequenced de novo by MALDI-TOF/TOF, performed its homology modelling, and assessed the interaction with the trypsin enzyme through molecular dynamics (MD) simulation under physiological conditions. We identified additional 75 amino acid residues, reaching approximately 72% of total coverage. The four best conformations of the best homology modelling were submitted to the MD. The conformation n°287 was selected considering the RMSD analysis and interaction energy (-301.0128 kcal.mol-1). Residues Ile (54), Pro (57), Arg (59), Arg (63), and Glu (78) of pTTI presented the highest interactions with trypsin, and arginine residues were mainly involved in its binding mechanism. The results favour bioprospecting of this protein for pharmaceutical health applications.