Mignani, SergeRodrigues, JoãoTomás, HelenaJalal, RachidSingh, Parvinder PalMajoral, Jean-PierreVishwakarma, Ram A.2019-06-272019-06-272018Mignani, S., Rodrigues, J., Tomas, H., Jalal, R., Singh, P. P., Majoral, J. P., & Vishwakarma, R. A. (2018). Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?. Drug discovery today, 23(3), 605-615.1359-6446http://hdl.handle.net/10400.13/2436During the past decade, decreasing the attrition rate of drug development candidates reaching the market has become one of the major challenges in pharmaceutical research and drug development (R&D). To facilitate the decision-making process, and to increase the probability of rapidly finding and developing high-quality compounds, a variety of multiparametric guidelines, also known as rules and ligand efficiency (LE) metrics, have been developed. However, what are the 'best' descriptors and how far can we simplify these drug-likeness prediction tools in terms of the numerous, complex properties that they relate to?engDrug designDrug discoveryPharmaceutical preparationsFilters in medicinal chemistry.Faculdade de Ciências Exatas e da EngenhariaCentro de Química da Madeirajournal article10.1016/j.drudis.2018.01.010