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.

We have used molecular dynamics simulations to examine the surface adsorption of a model anti-agglomerant inhibitor (quaternary ammonium salt) binding to a hydrate surface in both aqueous and liquid hydrocarbon phases. From our molecular dynamics simulation data, we were able to identify the preferred binding sites on the (111) crystal face of a methane−propane sII hydrate as well as characterize the equilibrium binding configurations of the inhibitor and their associated binding energies. In the aqueous phase, we observed that the inhibitor proceeds through a two-step surface adsorption mechanism, whereas in the liquid hydrocarbon phase surface adsorption occurs through a single-step mechanism. To characterize the extent of surface adsorption in each liquid phase, we calculated the standard binding free energy using the free energy perturbation method following a double decoupling thermodynamic cycle. We found that the surface adsorption in the liquid hydrocarbon phase is an exergonic process, whereas the surface adsorption in the aqueous phase is an endergonic process. Our results demonstrate that the extent of surface adsorption is much larger in the liquid hydrocarbon phase relative to the aqueous phase and suggest that the inhibitor is less effective in the aqueous phase because the surface adsorption is less favorable. Finally, we examine the effect of the inhibitor on the water structure in the liquid phase and in the hydrate phase, with the results highlighting the difference between the nature of anti-agglomerant/hydrate interactions as compared to kinetic inhibitor/hydrate interactions.

The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the “hotspot” residues at protein–protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis and also provide useful information for the design of antiviral drugs.

We used molecular dynamics simulations to examine the surface adsorption of a model antiagglomerant (AA) molecule binding to an sII methane–propane hydrate in environments of different salinities. From our simulation data, we identified the preferred binding sites on the hydrate surface and characterized the equilibrium binding configurations. In addition, for a subset of these binding configurations, we calculated the standard binding free energy in different concentrations of brine using potential of mean force free-energy calculations. We demonstrate that in higher salinity environments, the surface adsorption of the AAs is enhanced through two distinct mechanisms. First, the salt decreases the solubility of the AA in the solution, which increases the thermodynamic driving force for surface adsorption. Second, the salt ions create a negatively charged interfacial layer close to the hydrate surface that effectively solvates the cationic head of the AA molecule. Quantitatively, we found that the presence of 3.5 and 10 wt % NaCl decreases the standard binding free energy of the long hydrocarbon tail binding configuration by 0.8 and 1.4 kcal/mol, decreases the standard binding free energy of the cationic head binding by 1.5 and 3.3 kcal/mol, and decreases the standard binding free energy of simultaneous head and tail binding by 1.9 and 4.3 kcal/mol, respectively.

Simulating nucleation of molecular crystals is extremely challenging for all but the simplest cases. The challenge lies in formulating effective order parameters that are capable of driving the transition process. In recent years, order parameters based on molecular pair-functions have been successfully used in combination with enhanced sampling techniques to simulate nucleation of simple molecular crystals. However, despite the success of these approaches, we demonstrate that they can fail when applied to more complex cases. In fact, we show that order parameters based on molecular pair-functions, while successful at nucleating benzene, fail for paracetamol. Hence, we introduce a novel approach to formulate order parameters. In our approach, we construct reduced dimensional distributions of relevant quantities on the fly and then quantify the difference between these distributions and selected reference distributions. By computing the distribution of different quantities and by choosing different reference distributions, it is possible to systematically construct an effective set of order parameters. We then show that our new order parameters are capable of driving the nucleation of ordered states and, in particular, the form I crystal of paracetamol.

The ultrafast enol-keto photoisomerization in the lowest singlet excited state of 3-hydroxyflavone is investigated using classical molecular dynamics in conjunction with empirical valence bond (EVB) potentials for the description of intramolecular interactions, and a molecular mechanics and variable partial charge model, dependent on transferring proton position, for the description of solute-solvent interactions. A parallel multi-level genetic program was used to accurately fit the EVB potential energy surfaces to high level ab initio data. We have studied the excited state intramolecular proton transfer (ESIPT) reaction in three different solvent environments: methylcyclohexane, acetonitrile, and methanol. The effects of the environment on the proton transfer time and the underlying mechanisms responsible for the varied time scales of the ESIPT reaction rates are analyzed. We find that simulations with our EVB potential energy surfaces accurately reproduce experimentally determined reaction rates, fluorescence spectra, and vibrational frequency spectra in all three solvents. Furthermore, we find that the ultrafast ESIPT process results from a combination of ballistic transfer, and intramolecular vibrational redistribution, which leads to the excitation of a set of low frequency promoting vibrational modes. From this set of promoting modes, we find that an O-O in plane bend and a C-H out of plane bend are present in all three solvents, indicating that they are fundamental to the ultrafast proton transfer. Analysis of the slow proton transfer trajectories reveals a solvent mediated proton transfer mechanism, which is diffusion limited.

Drug design with patient centricity for ease of administration and pill burden requires robust understanding of the impact of chemical modifications on relevant physicochemical properties early in lead optimization. To this end, we have developed a physics-based ensemble approach to predict aqueous thermodynamic crystalline solubility, with a 2D chemical structure as the input. Predictions for the bromodomain and extraterminal domain (BET) inhibitor series show very close match (0.5 log unit) with measured thermodynamic solubility for cases with low crystal anisotropy and good match (1 log unit) for high anisotropy structures. The importance of thermodynamic solubility is clearly demonstrated by up to a 4 log unit drop in solubility compared to kinetic (amorphous) solubility in some cases and implications thereof, for instance on human dose. We have also demonstrated that incorporating predicted crystal structures in thermodynamic solubility prediction is necessary to differentiate (up to 4 log unit) between solubility of molecules within the series. Finally, our physics-based ensemble approach provides valuable structural insights into the origins of 3-D conformational landscapes, crystal polymorphism, and anisotropy that can be leveraged for both drug design and development.

Nucleation kinetics of small-molecule organics can be directed by heterogeneous surfaces imprinted with angular nanopatterns. In this work, we utilized biocompatible polymer thin films to enhance the nucleation rates of paracetamol (APAP). We found that flat polymer films without nanoimprinting enabled crystallization of APAP two times faster than bulk crystallization. Nanoimprinting of polymer films led to further enhancement of the nucleation rates. Polymer films imprinted with a nanopattern containing 40°angles were the most effective and enabled crystallization of APAP four times faster than bulk crystallization and two times faster than crystallization with flat polymer films. The films imprinted with the nanopatterns containing 60, 65, 80, or 90°angles were more effective in enhancing crystallization of APAP than the flat films but less effective compared to the 40°nanopattern. We also performed molecular dynamics simulations and an analysis of the hydrogen bonding between crystal faces and the polymer surface. The results suggest that the 40°pattern, the smallest angle nanopattern, targets the ( 001) and ( 011) faces (intrinsic angle of 34°) due to the strong interaction of these crystal faces with the polymer. The computational results are supported by crystallographic studies and atomic force microscopy images of a nanocrystal growing in the corners of the nanopatterns. Our findings indicate ways to rationally design the geometry of heterogeneous surfaces to enhance the nucleation of small-molecule organics. Moreover, considering that the only required input for this design is the chemical structure of the polymer and the chemical and crystal structure of the crystallizing solute, we expect that our method is applicable to a wide range of crystallization processes.