Trends in covalent drug discovery: a 2020-23 patent landscape analysis focused on select covalent reacting groups (CRGs) found in FDA-approved drugs.

Introduction: Covalent drugs contain electrophilic groups that can react with nucleophilic amino acids located in the active sites of proteins, particularly enzymes. Recently, there has been considerable interest in using covalent drugs to target non-catalytic amino acids in proteins to modulate difficult targets (i.e.

Mixed-methods examination of attitudes and behaviors related to COVID-19 vaccines among parents of children with autism and autistic adults.

Increased risks associated with Coronavirus disease 2019 (COVID-19) among individuals with autism spectrum disorder (ASD) combined with previous reports of heightened vaccine hesitancy among parents of children with ASD indicate the need for a better understanding of attitudes and behaviors related to COVID-19 vaccines among the ASD community. This study is the first to our knowledge to use a mixed-methods approach to understand attitudes toward COVID-19 vaccines among parents of children with ASD and autistic adults. Participants were 135 members of the ASD community residing in the state of Arizona (99 parents of children with ASD and 36 autistic adults) who responded to the third (Spring 2021) and fourth (Summer 2021) time points of a larger longitudinal online survey.

Planning anesthesia of a child with a rare disease: useful tools.

Up to 8,000 rare diseases are currently described in the scientific literature. The presence of a rare disease constitutes an additional challenge for the practitioner given its implications on the management of anesthesia. Moreover, it is not possible for an anesthesiologist to know them all especially as the sources of information are scattered.

Relation extraction from DailyMed structured product labels by optimally combining crowd, experts and machines.

The effectiveness of machine learning models to provide accurate and consistent results in drug discovery and clinical decision support is strongly dependent on the quality of the data used. However, substantive amounts of open data that drive drug discovery suffer from a number of issues including inconsistent representation, inaccurate reporting, and incomplete context. For example, databases of FDA-approved drug indications used in computational drug repositioning studies do not distinguish between treatments that simply offer symptomatic relief from those that target the underlying pathology.

Design and synthesis of a stereodynamic catalyst with reversal of selectivity by enantioselective self-inhibition.

Chirality plays a pivotal role in an uncountable number of biological processes, and nature has developed intriguing mechanisms to maintain this state of enantiopurity. The strive for a deeper understanding of the different elements that constitute such self-sustaining systems on a molecular level has sparked great interest in the studies of autoinductive and amplifying enantioselective reactions. The design of these reactions remains highly challenging; however, the development of generally applicable principles promises to have a considerable impact on research of catalyst design and other adjacent fields in the future.