Furthermore, despite the vastness of chemical space, estimated at 10 60 molecules, there is an argument suggesting that an ideal, all-powerful search algorithm could pinpoint small druglike molecules within a few hundred fitness function evaluations. Considering the efficiency demonstrated by GB-BI and keeping this idealized benchmark in mind, it becomes evident that the long-term efficacy of restricting the maximum allowed fitness calls to enhance the discriminative power of fingerprint rediscovery tasks for small molecules is at risk. To prevent future benchmarking issues and to further challenge and engage the research field, this paper introduces two novel classes of benchmarks. These benchmarks involve encoding a randomly selected conformer of a target molecule into either a USRCAT or Zernike descriptor, along with tailored similarity metrics. Although both these benchmarks closely resemble fingerprint rediscovery tasks, they present significantly increased optimisation challenges while simultaneously remaining computationally affordable in comparison to docking-based tasks.