P-glycoprotein substrate prediction

P-glycoprotein (P-gp), a key member of the ATP-binding cassette (ABC) transporter family, plays a critical role in drug absorption, distribution, and multidrug resistance by actively effluxing a broad range of substrates across cellular membranes. Predicting whether a compound is a P-gp substrate is essential in early-stage drug development, as it directly influences pharmacokinetics, bioavailability, and the potential for drug-drug interactions. In silico models using machine learning algorithms, molecular descriptors, and structural alerts have emerged as powerful tools to predict P-gp substrate specificity with increasing accuracy. These models are often trained on large, curated datasets of known substrates and non-substrates and can guide medicinal chemists in optimizing drug candidates to either evade P-gp-mediated efflux or exploit it in targeted delivery strategies. Incorporating P-gp substrate prediction into ADME profiling enhances the efficiency of lead optimization and supports regulatory expectations for safety and efficacy.