De novo molecule generation for drug design has seen a resurgence in recent years, mostly
due to the rapid advances in machine learning (ML) algorithms that utilise deep neural …

Drug discovery using traditional methods is expensive on resources. Advances in algorithms
for computational methods toward solving problems in chemical biology and affordable …

O desenvolvimento de anticorpos miméticos (AM), capazes de combinar a elevada
afinidade e seletividade dos anticorpos com o pequeno tamanho dos peptídeos, tem um …

Current strategies centred on either merging or linking initial hits from fragment-based drug
design (FBDD) crystallographic screens ignore 3D structural information. We show that an …

Deep generative models can virtually generate chemical structures with desired properties.
These models are widely used in de-novo molecular design projects, and are becoming an …

Abstract Analysis of protein structures shows that most of them have potential binding sites
that may be considered as applicable for new ligand design. The lack of known ligands …

Traditionally, the exogenous allosteric modulators of G protein-coupled receptors (GPCRs)
have been extensively investigated due to their pharmacological signi cance. However, to …

Le métabolisme glycolytique joue un rôle essentiel dans les processus physiologiques
normaux et dans la croissance des cellules cancéreuses. Les isoformes 1 et 2 de la …

Our current treatments for bacterial infections are under threat by the growth of antibiotic
resistance in many different pathogens. Of these pathogens, Salmonella is a particularly …

Seit einigen Jahrzehnten werden bei der Entwicklung und Repositionierung von
Arzneimitteln rechenintensive computergestützte Methoden eingesetzt, insbesondere da …