Pharmacophore Modeling in Drug Discovery: Methodology and Current Status

Abstract

A pharmacophore describes the framework of molecular features that are vital for the biologicalactivity of a compound. Pharmacophore models are built by using the structural information about theactive ligands or targets. The pharmacophore models developed are used to identify novel compounds thatsatisfy the pharmacophore requirements and thus expected to be biologically active. Drug discoveryprocess is a challenging task that requires the contribution of multidisciplinary approaches. Pharmacophoremodeling has been used in various stages of the drug discovery process. The major application areas arevirtual screening, docking, drug target fishing, ligand profiling, and ADMET prediction. There are severalpharmacophore modeling programs in use. The user must select the right program for the right purposecarefully. There are new developments in pharmacophore modeling with the involvement of the othercomputational methods. It has been integrated with molecular dynamics simulations. The latestcomputational approaches like machine learning have also played an important role in the advancesachieved. Moreover, with the rapid advance in computing capacity, data storage, software and algorithms,more advances are anticipated. Pharmacophore modeling has contributed to a faster, cheaper, and moreeffective drug discovery process. With the integration of pharmacophore modeling with the othercomputational methods and advances in the latest algorithms, programs that have better perfomance areemerging. Thus, improvements in the quality of the phamacophore models generated have been achievedwith this new developments.