A series of N-(2-amino-6-trifluoromethyl-pyridin-3-ylmethyl) 2-(3-fluoro-4-methylsulfonylaminophenyl) propanamides were designed combining previously identified pharmacophoric elements and evaluated as hTRPV1 antagonists. The SAR analysis indicated that specific hydrophobic interactions of the 2-amino substituents in the C-region of the ligand were critical for high hTRPV1binding potency. In particular, compound 49S was an excellent TRPV1 antagonist (Ki(CAP) = 0.2 nM; IC50(pH) = 6.3 nM) and was thus ca. 100- and 20-fold more potent, respectively, than the parent compounds 2 and 3 for capsaicin antagonism. Furthermore, it demonstrated strong analgesic activity in the rat neuropathic model superior to 2 with almost no side effects. Compound 49S antagonized capsaicin induced hypothermia in mice, but showed TRPV1-related hyperthermia. The basis for the high potency of 49S compared to 2 is suggested by docking analysis with our hTRPV1 homology model in which the 4-methylpiperidinyl group in the C-region of 49S made additional hydrophobic interactions with the hydrophobic region.

In order to enhance performance of robot systems in the manufacturing industry, it is essential to develop motion and task planning algorithms. Especially, it is important for the motion plan to be generated automatically in order to deal with various working environments. Although PRM (Probabilistic Roadmap) provides feasible paths when the starting and goal positions of a robot manipulator are given, the path might not be smooth enough, which can lead to inefficient performance of the robot system. This paper proposes a motion planning algorithm for robot manipulators using a twin delayed deep deterministic policy gradient (TD3) which is a reinforcement learning algorithm tailored to MDP with continuous action. Besides, hindsight experience replay (HER) is employed in the TD3 to enhance sample efficiency. Since path planning for a robot manipulator is an MDP (Markov Decision Process) with sparse reward and HER can deal with such a problem, this paper proposes a motion planning algorithm using TD3 with HER. The proposed algorithm is applied to 2-DOF and 3-DOF manipulators and it is shown that the designed paths are smoother and shorter than those designed by PRM.

Structure activity relationships for the A-region in a series of N-4-t-butylbenzyl 2-(4-methylsulfonylaminophenyl) propanamides as TRPV1 antagonists have been investigated. Among them, the 3-fluoro analogue 54 showed high binding affinity and potent antagonism for both rTRPV1 and hTRPV1 in CHO cells. Its stereospecific activity was demonstrated with marked selectivity for the (S)-configuration (54S versus 54R). A docking study of 54S with our hTRPV1 homology model highlighted crucial hydrogen bonds between the ligand and the receptor contributing to its potency.

The chiral isomers of the two potent simplified RTX-based vanilloids, compounds 2 and 3, were synthesized employing highly enantioselective PTC alkylation and evaluated as hTRPV1 ligands. The analysis indicated that the R-isomer was the eutomer in binding affinity and functional activity. The agonism of compound 2R was comparable to that of RTX. Docking analysis of the chiral isomers of 3 suggested the basis for its stereospecific activity and the binding mode of 3R.

A series of TRPV1 agonists with amide, reverse amide, and thiourea groups in the B-region and their corresponding α-methylated analogues were investigated. Whereas the α–methylation of the amide B-region enhanced the binding affinities and potencies as agonists, that of the reverse amide and thiourea led to a reduction in receptor affinity. The analysis indicated that proper hydrogen bonding as well as steric effects in the B-region are critical for receptor binding.