Depending on the usability, reliability, rapidity and throughput, these automated packages could find application at various stages of the drug discovery process across the wider pharmaceutical industry. In practise, however, the application of computational approaches is still dependent on the experience and knowledge of the practitioner. It remains a challenge for non-expert users to apply these existing tools to make robust predictions on a timescale that can substantially impact drug discovery programmes. For a given approach, the success of predictions also varies significantly across different protein targets with different sets of compounds. Studies have shown that the initial crystal structures and the existence of multiple conformations can have a significant effect on the quality of free energy predictions . Based on the experience, knowledge and intuition we have accumulated, we propose the following criteria to predict the quality of the calculations: 1) how well the binding site is defined and structured; 2) how well a compound fits into the binding pocket; and 3) how many rotamers and/or binding poses a compound may manifest.