Intrinsically disordered proteins play vital roles in biology， and their dysfunction contributes to many major disease states. These proteins remain challenging targets for rational ligand discovery or drug design because they are highly dynamic and fluctuate through a diverse set of conformations， frustrating structure-based approaches. To meet this challenge， we have developed protocols to efficiently identify active small molecule ligands of disordered proteins. Our approach utilizes enhanced sampling molecular dynamics and conformational analysis approaches optimized for disordered targets， coupled with computational docking and machine learning-based screens of compound libraries. By applying this protocol to an amyloid-forming segment of microtubule-associated protein tau， we successfully identified novel， chemically diverse tau ligands， including an inhibitor that delays the aggregation reaction in vitro without affecting the amount of aggregate formed at the steady state. Our results indicate that we have expanded the toolkit of protein aggregation inhibitors into new areas of chemical space and demonstrate the feasibility of our ligand discovery strategy.