{'fraction_non_alphanumeric': 0.021252796420581657, 'fraction_numerical': 0.010067114093959731, 'mean_word_length': 5.047297297297297, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A structure-based approach to retinoid X receptor-alpha inhibition.

In this paper we describe a structure-based approach designed to identify novel ligands for retinoid X receptor-alpha (RXRalpha). By using a virtual approach based on a modified scoring function, we have selected 200 potential candidates on the basis of their predicted ability of docking into the ligand-binding site of the target. Subsequent experimental verification of the compounds in in vitro and cell-based assays led to the identification of a number of novel high affinity ligands for RXRalpha. The compounds are capable of displacing 9-cis-retinoic acid with IC(50) values in the 10 nm and 5 mum range and exhibit marked antagonistic activity in cellular assays. The inhibitory scaffolds discovered with this method form the basis for the development of novel RXRalpha ligands with potential therapeutic properties.