Accurate prediction of dynamic protein-ligand binding using P-score ranking.

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions.

Synthetically accessible de novo design using reaction vectors: Application to PARP1 inhibitors.

De novo design has been a hotly pursued topic for many years. Most recent developments have involved the use of deep learning methods for generative molecular design. Despite increasing levels of algorithmic sophistication, the design of molecules that are synthetically accessible remains a major challenge.

Design of the Global Health chemical diversity library v2 for screening against infectious diseases.

There is a need for novel chemical matter for phenotypic and target-based screens to find starting points for drug discovery programmes in neglected infectious diseases and non-hormonal contraceptives that disproportionately affect Low- and Middle-Income Countries (LMICs). In some disease areas multiple screens of corporate and other libraries have been carried out, giving rise to some valuable starting points and leading to preclinical candidates. Whilst in other disease areas, little screening has been carried out.

High-Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques.

Structure-based drug design (SBDD) is rapidly evolving to be a fundamental tool for faster and more cost-effective methods of lead drug discovery. SBDD aims to offer a computational replacement to traditional high-throughput screening (HTS) methods of drug discovery. This "virtual screening" technique utilizes the structural data of a target protein in conjunction with large databases of potential drug candidates and then applies a range of different computational techniques to determine which potential candidates are likely to bind with high affinity and efficacy.

Neighborhood disadvantage and immune-related illnesses among residents living in the US Gulf States.

Purpose: Neighborhood disadvantage has been associated with increased risk for pneumonia and influenza-associated hospitalizations. Few studies, however, have investigated how neighborhood disadvantage may influence immune-related illnesses. The aim of this study was to examine the association between neighborhooddisadvantage and immune-related illnesses.