Effects of amantadine on circulating neurotransmitters in healthy subjects

Considering that glutamatergic axons innervate the C1(Ad) medullary nuclei, which are responsible for the excitation of the peripheral adrenal glands, we decided to investigate catecholamines (noradrenaline, adrenaline and dopamine) plus indolamines (plasma serotonin and platelet serotonin) at the blood level, before and after a small oral dose of amantadine, a selective NMDA antagonist. We found that the drug provoked a selective enhancement of noradrenaline plus a minimization of adrenaline, dopamine, plasma serotonin and platelet serotonin circulating levels. Significant enhancement of diastolic blood pressure plus reduction of systolic blood pressure and heart rate paralleled the circulating parameter changes. The above findings allow us to postulate that the drug was able to enhance the peripheral neural sympathetic activity. Minimization of both adrenal sympathetic and parasympathetic activities was also registered after the amantadine challenge. The above findings supported the postulation that this drug should be a powerful therapeutic tool for treating diseases affected by adrenal sympathetic hyperactivity

On Simplified Global Nonlinear Function for Fitness Landscape: A Case Study of Inverse Protein Folding

The construction of fitness landscape has broad implication in understanding molecular evolution, cellular epigenetic state, and protein structures. We studied the problem of constructing fitness landscape of inverse protein folding or protein design, with the aim to generate amino acid sequences that would fold into an a priori determined structural fold which would enable engineering novel or enhanced biochemistry. For this task, an effective fitness function should allow identification of correct sequences that would fold into the desired structure. In this study, we showed that nonlinear fitness function for protein design can be constructed using a rectangular kernel with a basis set of proteins and decoys chosen a priori. The full landscape for a large number of protein folds can be captured using only 480 native proteins and 3,200 non-protein decoys via a finite Newton method. A blind test of a simplified version of fitness function for sequence design was carried out to discriminate simultaneously 428 native sequences not homologous to any training proteins from 11 million challenging protein-like decoys. This simplified function correctly classified 408 native sequences (20 misclassifications, 95% correct rate), which outperforms several other statistical linear scoring function and optimized linear function. Our results further suggested that for the task of global sequence design of 428 selected proteins, the search space of protein shape and sequence can be effectively parametrized with just about 3,680 carefully chosen basis set of proteins and decoys, and we showed in addition that the overall landscape is not overly sensitive to the specific choice of this set. Our results can be generalized to construct other types of fitness landscape