Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Bacterial infections caused by 'superbugs' are increasing globally, and conventional
antibiotics are becoming less effective against these bacteria, such that we risk entering a …

In this work, we developed a QSAR model using the K-Nearest Neighbor (KNN) algorithm to
predict the corrosion inhibition performance of the inhibitor compound. To overcome the …

Generative chemical language models (CLMs) can be used for de novo molecular structure
generation by learning from a textual representation of molecules. Here, we show that hybrid …

Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two
decades to become a successful key technology in the pharmaceutical industry for early …

Many lead compounds fail to reach clinical trials despite being potent because of low
bioavailability attributed to their insufficient solubility making solubility a primary and crucial …

The application of computational approaches in drug discovery has been consolidated in
the last decades. These families of techniques are usually grouped under the common …

Molecular docking predicts whether and how small molecules bind to a macromolecular
target using a suitable 3D structure. Scoring functions for structure‐based virtual screening …

Application of machine and deep learning methods in drug discovery and cancer research
has gained a considerable amount of attention in the past years. As the field grows, it …

Drug discovery and repositioning are important processes for the pharmaceutical industry.
These processes demand a high investment in resources and are time-consuming. Several …