Selecting a stable solid form of remdesivir using microcrystal electron diffraction and crystal structure prediction

Selecting a stable solid form of remdesivir using microcrystal electron diffraction and crystal structure prediction

Therapeutic options in response to the coronavirus disease 2019 (COVID-19) outbreak are urgently needed. In this communication, we demonstrate how to support selection of a stable solid form of an antiviral drug remdesivir in quick time using the microcrystal electron diffraction (MicroED) technique and a cloud-based and artificial intelligence implemented crystal structure prediction platform. We present the MicroED structures of remdesivir forms II and IV and conclude that form II is more stable than form IV at ambient temperature in agreement with experimental observations. The combined experimental and theoretical study can serve as a template for formulation scientists in the pharmaceutical industry.

Novel Physics-Based Ensemble Modeling Approach That Utilizes 3D Molecular Conformation and Packing to Access Aqueous Thermodynamic Solubility: A Case Study of Orally Available Bromodomain and Extraterminal Domain Inhibitor Lead Optimization Series

J. Chem. Inf. Model. 2021, 61, 3, 1412–1426

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.

Computational Modeling of the Disulfide Cross-Linking Reaction

J. Phys. Chem. B 2020, 124, 44, 9840–9851

Disulfide cross-linking is one of the fundamental covalent bonds that exist prevalently in many biological molecules that is involved in versatile functional activities such as antibody stability, viral assembly, and protein folding. Additionally, it is a crucial factor in various industrial applications. Therefore, a fundamental understanding of its reaction mechanism would help gain insight into its different functional activities. Computational simulation of the disulfide cross-linking reaction with hydrogen peroxide (H₂O₂) was performed at the integrated quantum mechanical/molecular mechanical (QM/MM) level of theory in a water box under periodic boundary conditions. A benchmarking study for the barrier height of the disulfide formation step was performed on a model system between methanethiol and methane sulfenic acid to determine, for the QM system, the best-fit density functional theory (DFT) functional/basis set combination that produces comparable results to a higher-level theory of the coupled-cluster method. Computational results show that the disulfide cross-linking reaction with H₂O₂ reagent can proceed through a one-step or a two-step pathway for the high pK_a cysteines or two different pathways for the low pK_a cysteines to ultimately produce the sulfenic acid/sulfenate intermediate complex. Subsequently, those intermediates react with another neutral/anionic cysteine residue to form the cysteine product. In addition, the solvent-assisted proton-exchange/proton-transfer effects were examined on the energetic barriers for the different transition states, and the molecular contributions of the chemically involved water molecules were studied in detail.

A fluorophore's electron-deficiency does matter in designing high-performance near-infrared fluorescent probes

Chem. Sci., 2020,11, 11205-11213

Prediction of the Relative Free Energies of Drug Polymorphs above Zero Kelvin

Cryst. Growth Des. 2020, 20, 8, 5211–5224

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.

Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations

J. Chem. Inf. Model. 2020, XXXX, XXX, XXX-XXX

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.