Dataset for discovering new hypertension small molecules using machine learning-aided computational fragment-based design.

This dataset demonstrates the use of computational fragmentation-based and machine learning-aided drug discovery to generate new lead molecules for the treatment of hypertension. Specifically, the focus is on agents targeting the renin-angiotensin-aldosterone system (RAAS), commonly classified as Angiotensin-Converting Enzyme Inhibitors (ACEIs) and Angiotensin II Receptor Blockers (ARBs). The preliminary dataset was a target-specific, user-generated fragment library of 63 molecular fragments of the 26 approved ACEI and ARB molecules obtained from the ChEMBL and DrugBank molecular databases.

Burden of depressive disorders in Vietnam from 1990 to 2019: A secondary analysis of the Global Burden of Disease Study 2019.

Depressive disorders are among the leading causes of disability globally. However, information on the burden of depressive disorders in Vietnam is limited. We aimed to analyse the burden of depressive disorders in Vietnam from 1990 to 2019.