Structural Diversity and Stability of Hexamorphic Mavacamten: Experimental and Computational Insights

被引:1
|
作者
Braun, Doris E. [1 ,2 ]
Stefinovic, Marijan [3 ]
Griesser, Ulrich J. [1 ]
机构
[1] Univ Innsbruck, Inst Pharm Pharmaceut Technol, A-6020 Innsbruck, Austria
[2] Univ Innsbruck, Inst Pharm, Christian Doppler Lab Adv Crystal Engn Strategies, A-6020 Innsbruck, Austria
[3] Sandoz GmbH, A-6250 Kundl, Austria
关键词
CRYSTAL-STRUCTURE PREDICTION; PACKING POLYMORPHISM; MOLECULAR-CRYSTALS; ENERGY LANDSCAPES; FORM; DIFFRACTION; PHARMACEUTICALS; TEMPERATURE; REFINEMENT; PRINCIPLES;
D O I
10.1021/acs.cgd.4c00889
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Mavacamten (MAV), an innovative therapeutic agent targeting hypertrophic cardiomyopathy, was found to crystallize in six polymorphs, three solvates, and also to form an amorphous phase. The compound crystallizes easily, but often concomitantly, with five out of the six structures of the polymorphs solved, allowing for unambiguous identification of the phases. Experimental and computational methods consistently indicate that the stability order at 0 K for three of the five structurally characterized polymorphs is <bold>I</bold> (most stable) > <bold>II</bold> > <bold>IV</bold>. For forms <bold>III</bold> and <bold>V</bold>, they disagree on which of the two is the least stable. The metastable forms, with the exception of <bold>V</bold>, show very high kinetic stability under ambient conditions. This contrasts with the unstable solvates (chloroform, pyridine, and N-methylpyrrolidone) and the amorphous phase, which readily transform into the anhydrates. Numerous feasible crystal structures were identified among the lowest-energy structures on the computationally generated lattice energy landscape. The calculations reveal that uniquely distinct MAV conformations can form the same type of strong H-bonded chain motif, which is a characteristic feature of the structures, rationalizing the stability of the metastable forms and their tendency to crystallize concomitantly. These findings emphasize the significance of computational tools in understanding and predicting the polymorphic behavior of complex pharmaceutical compounds. Furthermore, this study highlights the need for continued improvements of modeling tools to enhance their predictive accuracy and practical application.
引用
收藏
页码:8381 / 8396
页数:16
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