Dunn W J, Hopfinger A J, Catana C, Duraiswami C
Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago 60612, USA.
J Med Chem. 1996 Nov 22;39(24):4825-32. doi: 10.1021/jm960491r.
Molecular recognition is the basis of rational drug design, and for this reason it has been extensively studied. However, the process by which a ligand recognizes and binds to its receptor is complex and not well understood. For the case in which the geometries (conformation and alignment) of the ligand and receptor are known from X-ray crystal structure data, the problem is simplified. The receptor-bound conformation and alignment of the ligand is assumed, and those of additional ligands are inferred. For the general case in which the geometries of the ligand(s) and receptor are unknown, no general treatment or solution is available and receptor-ligand geometries must be obtained indirectly from structure-activity studies or synthesis and evaluation of rigid analogs. A general treatment for solving for the receptor-bound geometry of a series of ligands is presented here. Using molecular shape analysis, for ligand description, tensor analysis of N-way arrays by partial least-squares (PLS) regression, and 3-way factor analysis, the receptor-bound geometries of trimethoprim and a series of trimethoprim-like dihydrofolate reductase inhibitors are correctly predicted.
分子识别是合理药物设计的基础,因此它已得到广泛研究。然而,配体识别并结合其受体的过程很复杂,尚未得到很好的理解。对于从X射线晶体结构数据已知配体和受体几何结构(构象和排列)的情况,问题得到了简化。假定配体与受体结合的构象和排列,并推断其他配体的构象和排列。对于配体和受体几何结构未知的一般情况,没有通用的处理方法或解决方案,必须从构效关系研究或刚性类似物的合成与评估中间接获得受体-配体几何结构。本文提出了一种求解一系列配体与受体结合几何结构的通用方法。通过分子形状分析、使用偏最小二乘法(PLS)回归对N维数组进行张量分析以及三元因子分析,正确预测了甲氧苄啶和一系列甲氧苄啶样二氢叶酸还原酶抑制剂与受体结合的几何结构。