Introduction: Computational modeling has rapidly advanced over the last decades. Recently,
machine learning has emerged as a powerful and cost-effective strategy to learn from …

The serotonin transporter (SERT) removes synaptic serotonin and is the target of anti-
depressant drugs. SERT adopts three conformations: outward-open, occluded, and inward …

The quantification of chemical diversity has many applications in drug discovery, organic
chemistry, food, and natural product chemistry, to name a few. As the size of the chemical …

Molecular docking is a structure-based and computer-aided drug design approach that
plays a pivotal role in drug discovery and pharmaceutical research. AutoDock is the most …

The concept of chemical space is a cornerstone in chemoinformatics, and it has broad
conceptual and practical applicability in many areas of chemistry, including drug design and …

Since the number of drugs based on natural products (NPs) represents a large source of
novel pharmacological entities, NPs have acquired significance in drug discovery. Peru is …

Traditional Chinese Medicine (TCM) has long been viewed as a precious source of modern
drug discovery. AI-assisted drug discovery (AIDD) has been investigated extensively …

Structure-based drug discovery is a process for both hit finding and optimization that relies
on a validated three-dimensional model of a target biomolecule, used to rationalize the …

The emergence of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2)
posed a serious worldwide threat and emphasized the urgency to find efficient solutions to …

Hit finding, scaffold hopping, and structure–activity relationship studies are important tasks in
rational drug discovery. Implementation of these tasks strongly depends on the availability of …