Structural analysis of the coronavirus main protease for the design of pan-variant inhibitors

With the rapid rate of SARS-CoV-2 Main protease (M^pro) structures deposition, a computational method that can combine all the useful structural features becomes crucial. This research focuses on the frequently occurring atoms and residues to find a generalized strategy for inhibitor design given a large amount of protein complexes from SARS-CoV in contrast to SARS-CoV-2 M^pro. By superposing large numbers of the ligands onto the protein template and grid box, we can analyse which part of the structure is conserved from position-specific interaction for both data sets for the development of pan-M^pro antiviral design. The difference in conserved recognition sites from the crystal structures can be used to determine specificity determining residues for designing selective drugs. We can display pictures of the imaginary shape of the ligand by unionising all atoms from the ligand. We also pinpoint the most probable atom adjustments to imitate the frequently found densities from the ligand atoms statistics. With molecular docking, Molecular Dynamics simulation, and MM-PBSA methods, a carbonyl replacement at the nitrile warhead (N5) of Paxlovid's Nirmatrelvir (PF-07321332) was suggested. By gaining insights into the selectivity and promiscuity regions for proteins and ligands, crucial residues are highlighted, and the antiviral design strategies are proposed.

Exploring secondary interactions and the role of temperature in moisture-contaminated polymer networks through molecular simulations

Leveraging the state of absorbed moisture within a polymer network to identify physical and chemical features of the host material is predicated upon a clear understanding of the interaction between the polymer and a penetrant water molecule; an understanding that has remained elusive. Recent work has revealed that a novel damage detection method that exploits the very low baseline levels of water typically found in polymer matrix composites (PMC) may be a valuable tool in the composite NDE arsenal, provided that a clear understanding of polymer-water interaction can be obtained. Precise detection, location, and possible quantification of the extent of damage can be performed by characterizing the physical and chemical states of moisture present in an in-service PMC. Composite structures have a locally elevated dielectric constant near the damage sites due to a higher fraction of bulk ("free") water, which has a higher dielectric constant when compared to water molecules bound to the polymer network through secondary bonding interactions. In this study, we aim to get a clear atomistic scale picture of the interactions which drive the dielectric signature variations necessary for tracking damage. Molecular Dynamics (MD) simulations were used to explore the effect of temperature on the state of moisture in two epoxy matrices with identical chemical constituents but different morphologies. The motivation was to understand whether higher polarity binds a greater fraction of moisture even at higher temperatures, leading to suppressed dielectric activity. Consequently, the influence of secondary bonding interactions was investigated to understand the impact of temperature on the absorbed water molecules in a composite epoxy matrix.

Data mining the Cambridge Structural Database for hydrate–anhydrate pairs with SMILES strings

A search method based on SMILES string matching was developed to identify hydrate–anhydrate structure pairs in the Cambridge Structure Database.

A Million Crystal Structures: The Whole Is Greater than the Sum of Its Parts

The founding in 1965 of what is now called the Cambridge Structural Database (CSD) has reaped dividends in numerous and diverse areas of chemical research. Each of the million or so crystal structures in the database was solved for its own particular reason, but collected together, the structures can be reused to address a multitude of new problems. In this Review, which is focused mainly on the last 10 years, we chronicle the contribution of the CSD to research into molecular geometries, molecular interactions, and molecular assemblies and demonstrate its value in the design of biologically active molecules and the solid forms in which they are delivered. Its potential in other commercially relevant areas is described, including gas storage and delivery, thin films, and (opto)electronics. The CSD also aids the solution of new crystal structures. Because no scientific instrument is without shortcomings, the limitations of CSD research are assessed. We emphasize the importance of maintaining database quality: notwithstanding the arrival of big data and machine learning, it remains perilous to ignore the principle of garbage in, garbage out. Finally, we explain why the CSD must evolve with the world around it to ensure it remains fit for purpose in the years ahead.

Molecular interaction transfer among solvents and solutes modulates the formation of linezolid crystals

Molecular interaction transfer from solute–solvent to solute–solute pairs is the vital step for the nucleation of linezolid crystals.