Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
Chem Biol Drug Des. 2013 Jan;81(1):33-40. doi: 10.1111/cbdd.12054.
We provide a future perspective of the virtual screening field. A number of challenges will be highlighted that virtual screening will likely face when compound data will further grow at or beyond current rates and when much more target information will become available. These challenges go beyond computational efficiency issues (that will of course also play a critical role). For example, for structure-based approaches, the accuracy of scoring functions and energy calculations will need to be improved. For ligand-based approaches, the compound class-dependence of similarity methods needs to be further explored and relationships between molecular similarity and activity similarity need to be established. We also comment on the current and future value of virtual screening. Opportunities for further development in a postgenome era are also discussed. It is hoped that some of the views and hypotheses we articulate might stimulate further discussion about the virtual screening field going forward.
我们提供了虚拟筛选领域的未来展望。当化合物数据以当前或更高的速度增长，并且更多的靶标信息变得可用时，虚拟筛选可能会面临许多挑战。这些挑战不仅限于计算效率问题（当然这也将起到至关重要的作用）。例如，对于基于结构的方法，需要提高评分函数和能量计算的准确性。对于基于配体的方法，需要进一步探索相似性方法的化合物类别依赖性，并建立分子相似性和活性相似性之间的关系。我们还评论了虚拟筛选的当前和未来价值。还讨论了在后基因组时代进一步发展的机会。希望我们阐明的一些观点和假设能够激发对虚拟筛选领域未来的进一步讨论。
