High-throughput screening (HTS) is one of the most powerful approaches available for identifying new lead compounds for the growing catalogue of validated drug targets. However, just as virtual and experimental HTS have accelerated lead identification and changed drug discovery, they have also introduced a large number of peculiar molecules. Some of these have turned out to be interesting for further optimization, others to be dead ends when attempts are made to optimize their activity, typically after a great deal of time and resources have been devoted. Such false positive hits are still one of the key problems in the field of HTS and in the early stages of drug discovery in general. Many studies have been devoted to understanding the origins of false-positives, and the findings have been incorporated in filters and methods that can predict and eliminate problematic molecules from further consideration. This paper will focus on the structural classes and known mechanisms of nonleadlike false positives, together with experimental and computational methods for identifying such compounds.