One of the most popular strategies of the optimization of drug properties in the pharmaceutical industry appears to be a solid form changing into a cocrystalline form. A number of virtual screening approaches have been previously developed to allow a selection of the most promising cocrystal formers (coformers) for an experimental follow-up. A significant drawback of those methods is related to the lack of accounting for the crystallinity contribution to cocrystal formation. To address this issue, we propose in this study two virtual coformer screening approaches based on a modern cloud-computing crystal structure prediction (CSP) technology at a dispersion-corrected density functional theory (DFT-D) level. The CSP-based methods were for the first time validated on challenging cases of indomethacin and paracetamol cocrystallization, for which the previously developed approaches provided poor predictions. The calculations demonstrated a dramatic improvement of the virtual coformer screening performance relative to the other methods. It is demonstrated that the crystallinity contribution to the formation of paracetamol and indomethacin cocrystals is a dominant one and, therefore, should not be ignored in the virtual screening calculations. Our results encourage a broad utilization of the proposed CSP-based technology in the pharmaceutical industry as the only virtual coformer screening method that directly accounts for the crystallinity contribution.

We report the results of a systematic atomistic modeling study of small helium cluster behavior near tungsten symmetric tilt grain boundaries. This behavior was studied qualitatively by molecular dynamics simulations and quantitatively by molecular statics simulations combined with elastic inclusion theory. The sink strength is used to describe the magnitude of the clusters' attraction to the grain boundary. We find that small helium clusters show impeded transport behavior relative to the bulk around all types of grain boundaries, including low-angle, high-angle, low-Sigma-value, and high-Sigma-value grain boundaries. Helium clusters tend to become trapped near, but typically not directly on, the grain boundary plane. Both the distance between the helium cluster and the grain boundary when the cluster first becomes immobilized and the sink strength are correlated with helium cluster size, grain boundary formation energy, grain boundary tilt angle, excess volume, and other aspects of grain boundary structure. We expect similar impeded transport behavior for other types of grain boundaries and in other metals, because helium is effectively insoluble in most materials and has a similar interstitial-based diffusion mechanism in most metals.

Combining microcrystal electron diffraction (MicroED) and a cloud-based and artificial intelligence implemented crystal structure prediction (CSP) platform to support selection of a stable solid form of remdesivir in quick time.

We present the results of an atomistic modeling study of small helium cluster migration in the plane of symmetric tilt grain boundaries. The relevant migration pathways and energies were determined by way of temperature accelerated dynamics and the nudged elastic band method. We find that small helium clusters show much higher migration energies when bound to the grain boundary than in the bulk for all types of grain boundaries, indicating strongly-impeded helium transport behavior. Larger helium clusters (up to three helium atoms) tend to have higher migration energies compared with smaller clusters. Longer-distance migrations also tend to have higher migration energies, but helium cluster migration is highly affected by the structure of the grain boundary. The binding energy of the grain boundaries studied is high enough that helium clusters would be unlikely to leave the grain boundary plane. However, vacancy migration energies are relatively low compared to the bulk, and are also much lower than helium cluster migration energies on the grain boundary plane. This suggests that helium cluster migration on the grain boundary is actually governed by the rate of vacancy migration: in the bulk, helium clusters are mobile, but they become bound to and immobilized by grain boundaries, forming bubbles. Bubbles, however, are likely more mobile on the grain boundary than they are in the bulk due to the increased rate of vacancy migration on the grain boundary. We expect similar migration behavior for other types of grain boundaries because of the increased excess volume found near all grain boundaries.

Crystal structure prediction (CSP) is an invaluable tool in the pharmaceutical industry because it allows to predict all the possible crystalline solid forms of small-molecule active pharmaceutical ingredients. We have used a CSP-based cocrystal prediction method to rank ten potential cocrystal coformers by the energy of the cocrystallization reaction with an antiviral drug candidate, MK-8876, and a triol process intermediate, 2ethynylglyclerol. For MK-8876, the CSP-based cocrystal prediction was performed retrospectively and successfully predicted the maleic acid cocrystal as the most likely cocrystal to be observed. The triol is known to form two different cocrystals with 1,4diazabicyclo[2.2.2]octane (DABCO), but a larger solid form landscape was desired. CSP-based cocrystal screening predicted the triol-DABCO cocrystal as rank one, while a triol-L-proline cocrystal was predicted as rank two. Computational finite-temperature corrections enabled determination of relative crystallization propensities of the triol-DABCO cocrystals with different stoichiometries and prediction of the triol-L-proline polymorphs in the free-energy landscape. The triol-L-proline cocrystal was obtained during subsequent targeted cocrystallization experiments and was found to exhibit an improved melting point and deliquescence behavior over the triol-free acid, which could be considered as an alternative solid form in the synthesis of islatravir.