Computational chemistry articles from across Nature Portfolio

Identifying molecular properties of compounds that best correlate with outer membrane permeation and growth inhibition could guide the discovery of new antibiotics. Here, the authors evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa to derive a statistical protocol to identify mechanistic predictors of outer membrane permeation.

Understanding the stability and activity of freeze-dried bio-macromolecules at low degrees of hydration is crucial for pharmaceutical and food industries, however, the building of in silico models for dynamical studies at a molecular level needs careful consideration. Here, the authors propose a modelling protocol that mimics experimental protein lyophilization, and proteins in weakly hydrated amorphous states, and validate it against experimental neutron scattering data.

Reduced molecular graphs can integrate higher-level chemical information and leverage advantages from atom-level graph neural networks. Here, the authors introduce the Multiple Molecular Graph eXplainable model, investigating the effects of multiple molecular graphs, including Atom, Pharmacophore, JunctionTree, and FunctionalGroup, on model learning and interpretation from various perspectives

A method is developed for the directional optimization of multiple properties without prior knowledge on their nature. Using a large ligand dataset, diverse metal complexes are found along the Pareto front of vast chemical spaces.

Norcoclaurine synthase from Thalictrum flavum (TfNCS) has been demonstrated to display high stereospecificity and yield in catalyzing the Pictet-Spengler reaction of dopamine with chiral aldehydes, however, the mechanism and factors related to this high stereospecificity remain unclear. Here, the authors conduct quantum chemical calculations and reveal the rate-limiting step and differential energy barriers for the reactions of two enantiomers of α-methylphenylacetaldehyde, as well as key residues related to stereospecificity.

We highlight the challenges and opportunities in organic redox flow battery research, underscoring the need for collaborative research efforts. The synergy between computation and experimentation holds the potential to expedite progress in this field and can have far-reaching impacts beyond energy storage applications.

The ab initio atomistic thermodynamics approach, coined by Reuter and Scheffler formally in 2001, remains pivotal for understanding and predicting the stable surfaces of thermal catalysts under technical conditions.

The K⁺ ion channel KCNQ2 modulates neuronal excitability and is targeted by retigabine, an anti-epileptic drug that enhances the probability of channel opening. New activators have now been discovered to increase unitary conductance through an unprecedented mechanism.

Communications Chemistry is delighted to introduce a Collection of research works focused on the modelling and advanced characterization of framework materials. Here, the Guest Editors outline the themes within and look towards the future of the field.

The electrocatalytic nitrogen reduction reaction is a promising alternative to the Haber–Bosch process. However, the reproducibility and reliability of this process suffer from the persistence of false positives. Computational tools have the potential to alleviate this issue but several challenges must be addressed.