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提出了一种利用SMILES码构建虚拟组合化学库的新方法。该方法用SMILES码代表骨架和侧链,通过对其进行排列组合生成虚拟组合化学库。用户可设定ADME筛选条件对生成的库进行初筛,以舍弃在理论上药代动力学行为不好的分子。该法通过构建一个抗2型糖尿病药物虚拟组合化学库(A2DDVCL)而得到了验证。A2DDVCL建立在过氧化物酶增殖体活化受体(PPAR)配体的基础上,拟从其中发现治疗慢性代谢疾病特别是2型糖尿病的药物。
A new method for constructing virtual combinatorial chemical library by using SMILES code is proposed. The method uses the SMILES code to represent the skeleton and side chains, and arranges them to generate a virtual combinatorial chemical library. The user can set the ADME screening criteria to pre-screen the resulting library to discard molecules that theoretically do not behave as pharmacokinetically. The method was validated by constructing an anti-type 2 diabetes virtual combinatorial chemistry library (A2DDVCL). A2DDVCL is based on peroxisome proliferator activated receptor (PPAR) ligands and is intended to find agents for the treatment of chronic metabolic diseases, especially type 2 diabetes.