Can computed crystal energy landscapes help understand pharmaceutical solids?

被引：152

作者：

Price, Sarah L. ^{[1
]}

Braun, Doris E. ^{[2
]}

Reutzel-Edens, Susan M. ^{[3
]}

机构：

[1] UCL, Dept Chem, 20 Gordon St, London WC1H 0AJ, England

[2] Univ Innsbruck, Inst Pharm, Innrain 52c, A-6020 Innsbruck, Austria

[3] Eli Lilly & Co, Lilly Corp Ctr, Small Mol Design & Dev, Indianapolis, IN 46285 USA

来源：

CHEMICAL COMMUNICATIONS | 2016年 / 52卷 / 44期

基金：

奥地利科学基金会; 英国工程与自然科学研究理事会;

关键词：

DENSITY-FUNCTIONAL THEORY; LASER-INDUCED NUCLEATION; STRUCTURE PREDICTION; ORGANIC-COMPOUNDS; BLIND TEST; POLYMORPH; FORM; CRYSTALLIZATION; ACID; RITONAVIR;

D O I：

10.1039/c6cc00721j

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape.

引用

页码：7065 / 7077

页数：13

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