Accurate and rapid crystal structure predictions have the potential to transform the development of new materials, particularly in fields with highly complex molecular structures (such as in drug development). In this work we present a novel cloud-computing crystal structure prediction (CSP) platform with the capability of scheduling hundreds of thousands CPU cores and integrating cutting-edge computational chemistry algorithms. This new cloud-computing based CSP platform has been applied to three crystalline drug substances of increasing complexity. The lattice energies of the experimental crystal structures are all within 4.0 kJ/mol of the lowest energy predicted structures. On the basis of the results of this work, the algorithm improvement and the mass computational power of cloud computing can reduce the whole CSP process to just 1–3 weeks for Z′ = 1 systems and less than 5 weeks for significantly more complex systems. Furthermore, it is possible to simultaneously perform calculations for multiple molecules if desired. As a result of these improvements, CSP calculations can potentially be applied in conjunction with state-of-the-art experimental screening techniques to reduce the risk of finding new solid forms after product launch provided that a sufficient number of stoichiometries and space groups are explored.

Crystal structure prediction (CSP) calculations can reduce risk and improve efficiency during drug development. Traditionally, CSP calculations use lattice energies computed through density functional theory. While this approach is often successful in predicting the low energy structures, it neglects the crucial role of thermal effects on polymorph stabilities. In the present study, we develop a robust and efficient protocol for predicting the relative stability of polymorphs at different temperatures. The protocol is executed on a highly parallel cloud computing infrastructure to produce results at time scales useful for drug development timelines. We demonstrate this protocol on molecule XXIII from the sixth crystal structure prediction blind test. Our results predict that Form D is the most stable experimentally observed polymorph at ambient temperature and Form C is the most stable at low temperature consistent with experiments also conducted in the present study.

Human soluble calcium-activated nucleotidase 1 (hSCAN-1) is the human homologue of soluble apyrases found in blood-sucking insects. This family of nucleotidases is unrelated in sequence to more well-studied nucleotidases, and very little is known about the enzymatic mechanism. By multiple sequence alignment, eight regions that are highly conserved in the hSCAN-1 family were identified and named. To identify amino acids important for catalytic activity and enzyme specificity, seven point mutations were constructed, expressed in bacteria, refolded, purified, and characterized. Substitution of glutamic acid 130 with tyrosine resulted in dramatically increased nucleotidase activities, while mutagenesis of aspartic acid 151 to alanine and aspartic acid 84 to alanine completely abolished activity. Mutagenesis of arginine 133 and arginine 271 resulted in enzymes with very little nucleotidase activity. Mutagenesis of aspartic acid 175 to alanine and glycine 122 to glutamic acid had smaller negative effects on enzyme activities. Previously, our laboratory showed that calcium triggers a conformational change in hSCAN-1 necessary for nucleotidase activity. Here we show that several mutants (D84A, R133A, and D151A) that lost most of their activity were unable to undergo the conformational change induced by Ca(2+), as shown by Cibacron blue binding, limited proteolysis, and tryptophan fluorescence. We conclude that aspartic acid residues 84 and 151, as well as arginine residue 133, are essential for the Ca(2+)-induced conformational change that is necessary for enzyme activity. Aspartic acid 175 and glutamic acid 130 are important for determining substrate specificity. In addition, we show that Sr(2+), unlike Mg(2+) and other divalent cations, can substitute for Ca(2+) to induce the conformational change necessary for enzyme activity. However, Sr(2+) cannot substitute for Ca(2+) to support nucleotide hydrolysis, presumably because Sr(2+) cannot substitute for Ca(2+) in its second role as a nucleotide cosubstrate. The ramifications of our results on the interpretation of a recently published crystal structure are discussed. This information will facilitate future engineering of this enzyme designed to enhance its ability to hydrolyze ADP and thus increase its potential for therapeutic use in the treatment of pathological ischemic events triggered via activation of platelets by ADP.

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