Design and synthesis of novel and potent allosteric HIV-1 integrase inhibitors with a spirocyclic moiety.

We report herein the design and discovery of novel allosteric HIV-1 integrase inhibitors. Our design concept utilized the spirocyclic moiety to restrain the flexibility of the conformation of the lipophilic part of the inhibitor. Compound 5 showed antiviral activity by binding to the nuclear lens epithelium-derived growth factor (LEDGF/p75) binding site of HIV-1 integrase (IN). The introduction of a lipophilic amide substituent into the central benzene ring resulted in a significant increase in antiviral activity against HIV-1 WT X-ray crystallography of compound 15 in complex with the integrase revealed the presence of a hydrogen bond between the oxygen atom of the amide of compound 15 and the hydroxyl group of the T125 side chain. Chiral compound 17 showed high antiviral activity, good bioavailability, and low clearance in rats.

AQDnet: Deep Neural Network for Protein-Ligand Docking Simulation.

We have developed an innovative system, AI QM Docking Net (AQDnet), which utilizes the three-dimensional structure of protein-ligand complexes to predict binding affinity. This system is novel in two respects: first, it significantly expands the training dataset by generating thousands of diverse ligand configurations for each protein-ligand complex and subsequently determining the binding energy of each configuration through quantum computation. Second, we have devised a method that incorporates the atom-centered symmetry function (ACSF), highly effective in describing molecular energies, for the prediction of protein-ligand interactions. These advancements have enabled us to effectively train a neural network to learn the protein-ligand quantum energy landscape (P-L QEL). Consequently, we have achieved a 92.6% top 1 success rate in the CASF-2016 docking power, placing first among all models assessed in the CASF-2016, thus demonstrating the exceptional docking performance of our model.

Discovery of (1S,2R,3R)-2,3-dimethyl-2-phenyl-1-sulfamidocyclopropanecarboxylates: novel and highly selective aggrecanase inhibitors.

Aggrecanases, particularly aggrecanase-1 (ADAMTS-4) and aggrecanase-2 (ADAMTS-5), are believed to be key enzymes involved in the articular cartilage breakdown that leads to osteoarthritis. Thus, aggrecanases are considered to be viable drug targets for the treatment of this debilitating disease. A series of (1S,2R,3R)-2,3-dimethyl-2-phenyl-1-sulfamidocyclopropanecarboxylates was discovered to be potent, highly selective, and orally bioavailable aggrecanase inhibitors. These compounds have unique P1' groups comprising novel piperidine- or piperazine-based heterocycles that are connected to a cyclopropane amino acid scaffold via a sulfamido linkage. These P1' groups are quite effective in imparting selectivity over other MMPs, and this selectivity was further increased by incorporation of a methyl substituent in the 2-position of the cyclopropane ring. In contrast to classical hydroxamate-based inhibitors that tend to lack metabolic stability, our aggrecanase inhibitors bear a carboxylate zinc-binding group and have good oral bioavailability. Lead compound 13b, characterized by the novel P1' portion of 1,2,3,4-tetrahydropyrido[3',4':4,5]imidazo[1,2-a]pyridine ring, is a potent and selective aggrecanse inhibitor with excellent pharmacokinetic profiles.

Synthesis and SAR of 2-phenyl-1-sulfonylaminocyclopropane carboxylates as ADAMTS-5 (Aggrecanase-2) inhibitors.

A series of 1-sulfonylaminocyclopropanecarboxylates was synthesized as ADAMTS-5 (Aggrecanase-2) inhibitors. After an intensive investigation of the central cyclopropane core including its absolute stereochemistry and substituents, we found compound 22 with an Agg-2 IC50=7.4 nM, the most potent ADAMTS-5 inhibitor reported so far.