Benchmarking virtual screening methods poses a challenge, because no single measure, or even combination of measures, can be used to unambiguously quantify the success of virtual screens, let alone determine which among many binders is the "best". Although binding affinity will be the main benchmarking criterion, it is relevant to incorporate other properties important for drug discovery, including the calculated lipophilicity and novelty of the predicted structures, and also the experimentally-determined selectivity against one or more homologous "off-targets" (if this is called for in a challenge). Solubility of the compounds will be predicted, but also will be determined experimentally. Insoluble compounds will be flagged because precipitation is a confounder in nearly all binding assays. CACHE will publish in advance the success criteria (activity, selectivity, aqueous solubility, lipophilicity, novelty, etc.) for each challenge, and how they will be combined into an overall multi-objective score , such as oralPhysChemScore (oPCS) . CACHE will provide the workflows and scripts that were used to calculate the different descriptors. In one possible scheme (TABLE ), active compounds will not be ranked per se, but rather will be classified into 3 buckets (green, yellow, red) by summing up the traffic light values for each property (column). The scoring scheme used to assess a compound's physical and molecular properties will be similar across the challenges, but the values for potency and selectivity may change depending on the challenge. For example, compounds with weaker affinity might be acceptable for hard targets with no precedent, but higher affinities might be the aim if the challenge is to identify novel chemotypes for precedented targets. As stated above, to facilitate comparison among methods, all predictions from all participants for a given target will be combined into a single small virtual library, and all participants will also be asked to rank these compounds.