The challenges of in silico contributions to drug metabolism in lead optimization.

IMPORTANCE OF THE FIELD: The site of metabolism (SOM) predictions by CYP 3A4 are extremely important during the drug discovery process especially during the lead discovery or library design phases. With the ability to rapidly characterize metabolites from these enzymes, the challenges facing in silico contribution change during the drug optimization phase. Some of the challenges are addressed in this article. Some aspects of the SOM prediction software and methodology are discussed in this opinion article and examples of software utility in overcoming metabolic instability in drug optimization are shown. AREAS COVERED IN THIS REVIEW: SOM prediction by various approaches is discussed. Two ways of overcoming metabolic instability, blocking the metabolic softspots and rational modification of the instable molecule to avoid interaction with the CYP pocket, are discussed. The contribution plot in MetaSite and its use are discussed. WHAT THE READER WILL GAIN: The reader will gain an understanding of possible approaches to either blocking the metabolic softspot or rationally modifying the molecule using MetaSite software or docking approaches. Blocking metabolism using fluorination has risks especially introducing multifluorinated benzene rings in the molecule. TAKE HOME MESSAGE: During the lead optimization phase of drug discovery, when metabolic instability is an issue in a series, in silico approaches can be used to modify the molecule in order to decrease clearance due to metabolism, even that due to CYP3A4.

Discovery of covalent inhibitors for MIF tautomerase via cocrystal structures with phantom hits from virtual screening.

Biochemical and X-ray crystallographic studies confirmed that hydroxyquinoline derivatives identified by virtual screening were actually covalent inhibitors of the MIF tautomerase. Adducts were formed by N-alkylation of the Pro-1 at the catalytic site with a loss of an amino group of the inhibitor.

Design of bivalent ligands using hydrogen bond linkers: synthesis and evaluation of inhibitors for human beta-tryptase.

We exploit the concept of using hydrogen bonds to link multiple ligands for maintaining simultaneous interactions with polyvalent binding sites. This approach is demonstrated by the syntheses and evaluation of pseudo-bivalent ligands as potent inhibitors of human beta-tryptase.

Characterization of HERG potassium channel inhibition using CoMSiA 3D QSAR and homology modeling approaches.

A data set consisting of twenty-two sertindole analogues and ten structurally diverse inhibitors, spanning a wide range in potency, was analyzed using CoMSiA. A homology model of HERG was constructed from the crystal structure of the open MthK potassium channel. A complementary relationship between our CoMSiA and homology models is apparent when the long inhibitor axis is oriented parallel to the longitudinal axis of the pore, with the tail region pointed toward the selectivity filter. The key elements of the pharmacophore, the CoMSiA and the homology model are: (1) The hydrophobic feature optimally consists of an aromatic group that is capable of engaging in pi-stacking with a Phe656 side chain. Optionally, a second aromatic or hydrophobic group present in some inhibitors may contact an additional Phe656 side chain. (2) The basic nitrogen appears to undergo a pi-cation interaction with Tyr652. (3) The pore diameter (12A+), and depth of the selectivity loop relative to the intracellular opening, act as constraints on the conformation-dependent inhibitor dimensions.