MedChemica Limited, Ebenezer House, Ryecroft, Newcastle-Under-Lyme, Staffordshire ST5 2BE, UK.
Drug Discov Today. 2013 Aug;18(15-16):724-31. doi: 10.1016/j.drudis.2013.03.003. Epub 2013 Apr 2.
Multiple parameter optimisation in drug discovery is difficult, but Matched Molecular Pair Analysis (MMPA) can help. Computer algorithms can process data in an unbiased way to yield design rules and suggest better molecules, cutting the number of design cycles. The approach often makes more suggestions than can be processed manually and methods to deal with this are proposed. However, there is a paucity of contextually specific design rules, which would truly make the technique powerful. By combining extracted information from multiple sources there is an opportunity to solve this problem and advance medicinal chemistry in a matter of months rather than years.
药物发现中的多参数优化很困难,但匹配分子对分析(MMPA)可以提供帮助。计算机算法可以以无偏的方式处理数据,得出设计规则并提出更好的分子,从而减少设计周期的数量。该方法通常会提出比手动处理更多的建议,因此需要提出一些方法来应对。然而,目前缺乏上下文特定的设计规则,这将真正使该技术具有强大的功能。通过从多个来源提取信息进行组合,就有机会解决这个问题,并在数月而不是数年的时间内推动药物化学的发展。