One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening.

Traditional best practices for quantitative structure activity relationship (QSAR) modeling recommend dataset balancing and balanced accuracy (BA) as the key desired objective of model development. This study explores the value of the conventional norms in the context of using QSAR models for virtual screening of modern large and ultra-large chemical libraries. For this increasingly common task, we now recommend the use of models with the highest positive predictive value (PPV) built on imbalanced training sets as preferred virtual screening tools.

Applications of Machine Learning Approaches for the Discovery of SARS-CoV-2 PLpro Inhibitors.

The global impact of SARS-CoV-2 highlights the need for treatments beyond vaccination, given the limited availability of effective medications. While Pfizer introduced , an FDA-approved antiviral targeting the SARS-CoV-2 main protease (Mpro), this study focuses on designing new antivirals against another protease, papain-like protease (PLpro), which is crucial for viral replication and immune suppression. NCATS/NIH performed a high-throughput screen of ∼15,000 molecules from an internal molecular library, identifying initial hits with a 0.

A High-Throughput Screening Pipeline to Identify Methyltransferase and Exonuclease Inhibitors of SARS-CoV-2 NSP14.

SARS-CoV-2 infections led to a worldwide pandemic in 2020. As of 2024, therapeutics against SARS-CoV-2 have continued to be desirable. NSP14 is a dual-function methyltransferase (MTase) and exonuclease (ExoN) with key roles in SARS-CoV-2 genome propagation and host immune system evasion.

Paired correlations of dipolar liquid crystals: A mean-force-potentials approach.

Pair correlations for a polar liquid-crystal (LC) system have been theoretically investigated by means of integral equation approach. Using the dipolar Gay-Berne (GB) interactions between the molecules that composed the LC system, calculations of the nearest-neighbor (NN) and next-NN (NNN) correlators as well as the order parameters and the static dielectric coefficients were performed. It is shown that for a simple cubic packing, NN dipoles tend to be mutually antiparallel with respect to the central dipole, while the opposite trend was observed for NNN dipoles.

Nanoscale imaging and control of altermagnetism in MnTe.

Nanoscale detection and control of the magnetic order underpins a spectrum of condensed-matter research and device functionalities involving magnetism. The key principle involved is the breaking of time-reversal symmetry, which in ferromagnets is generated by an internal magnetization. However, the presence of a net magnetization limits device scalability and compatibility with phases, such as superconductors and topological insulators.