Proteochemometrics is a machine learning based modeling approach relying on a
combination of ligand and protein descriptors. With ongoing developments in machine …

Identifying drug–target interactions (DTIs) is important for drug discovery. However,
searching all drug–target spaces poses a major bottleneck. Therefore, recently many deep …

Class I phosphoinositide 3-kinases (PI3Ks) are currently considered as significant targets for
the development of novel pharmaceuticals to treat cancers and inflammatory diseases …

Being widely accepted tools in computational drug search, the (Q) SAR methods have
limitations related to data incompleteness. The proteochemometrics (PCM) approach …

The high similarity between certain sub-pockets of serine proteases may lead to low
selectivity of protease inhibitors. Therefore the application of proteochemometrics (PCM) …

The phosphodiesterase (PDE) superfamily, including all PDE families and subfamilies, are
often implicated in diverse physiological disorders thereby making their selective inhibition …

Dihydrofolate reductase (DHFR) is an essential enzyme in the folate metabolism pathway
and an important target of antineoplastic, antimicrobial, antiprotozoal, and antiinflammatory …

Due to its physiological and clinical roles, carbonic anhydrase (CA) is one of the most
interesting case studies. There are different classes of CAinhibitors including sulfonamides …

Carbonic anhydrases (CAs) are essential enzymes in biological processes. Prediction of the
activity of compounds towards CA isoforms could be evaluated by computational techniques …

Due to its crucial role in DNA synthesis, thymidylate synthase (TS) has been considered as a
potential therapeutic target. Inhibition of the enzyme is a promising strategy for the treatment …