Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa.

Factor Xa inhibitors are innovative anticoagulant agents that provide a better safety/efficacy profile compared to other anticoagulative drugs. A chemical feature-based modeling approach was applied to identify crucial pharmacophore patterns from 3D crystal structures of inhibitors bound to human factor Xa (Pdb entries 1fjs, 1kns, 1eqz) using the software LIGANDSCOUT and CATALYST. The complex structures were selected regarding the criteria of high inhibitory potency (i.e. all ligands show K(i) values against factor Xa in the subnanomolar range) and good resolution (i.e. at least 2.2 A) in order to generate selective and high quality pharmacophore models. The resulting chemical-feature based hypotheses were used for virtual screening of commercial molecular databases such as the WDI database. Furthermore, a ligand-based molecular modeling approach was performed to obtain common-feature hypotheses that represent the relevant chemical interactions between 10 bioactive factor Xa inhibitors and the protein, respectively. In a next step a virtual combinatorial library was designed in order to generate new compounds with similar chemical and spatial properties as known inhibitors. The software tool ILIB DIVERSE was used for this procedure in order to provide new scaffolds of this group of anticoagulants. Finally we present the combination of these two techniques, hence virtual screening was performed with selective pharmacophore models in a focused virtual combinatorial database. De novo derived molecular scaffolds that were able to adequately satisfy the pharmacophore criteria are revealed and are promising templates for candidates for further development.

Impact of scoring functions on enrichment in docking-based virtual screening: an application study on renin inhibitors.

The docking program LigandFit/Cerius(2) has been used to perform shape-based virtual screening of databases against the aspartic protease renin, a target of determined three-dimensional structure. The protein structure was used in the induced fit binding conformation that occurs when renin is bound to the highly active renin inhibitor 1 (IC(50) = 2 nM). The scoring was calculated using several different scoring functions in order to get insight into the predictability of the magnitude of binding interactions. A database of 1000 diverse and druglike compounds, comprised of 990 members of a virtual database generated by using the iLib diverse software and 10 known active renin inhibitors, was docked flexibly and scored to determine appropriate scoring functions. All seven scoring functions used (LigScore1, LigScore2, PLP1, PLP2, JAIN, PMF, LUDI) were able to retrieve at least 50% of the active compounds within the first 20% (200 molecules) of the entire test database. A hit rate of 90% in the top 1.4% resulted using the quadruple consensus scoring of LigScore2, PLP1, PLP2, and JAIN. Additionally, a focused database was created with the iLib diverse software and used for the same procedure as the test database. Docking and scoring of the 990 focused compounds and the 10 known actives were performed. A hit rate of 100% in the top 8.4% resulted with use of the triple consensus scoring of PLP1, PLP2, and PMF. As expected, a ranking of the known active compounds within the focused database compared to the test database was observed. Adequate virtual screening conditions were derived empirically. They can be used for proximate docking and scoring application of compounds with putative renin inhibiting potency.

Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification.

Chemical feature based pharmacophore models were elaborated for angiotensin II receptor subtype 1 (AT(1)) antagonists using both a quantitative and a qualitative approach (Catalyst HypoGen and HipHop algorithms, respectively). The training sets for quantitative model generation consisted of 25 selective AT(1) antagonists exhibiting IC(50) values ranging from 1.3 nM to 150 microM. Additionally, a qualitative pharmacophore hypothesis was derived from multiconformational structure models of the two highly active AT(1) antagonists 4u (IC(50) = 0.2 nM) and 3k (IC(50) = 0.7 nM). In the case of the quantitative model, the best pharmacophore hypothesis consisted of a five-features model (Hypo1: seven points, one hydrophobic aromatic, one hydrophobic aliphatic, a hydrogen bond acceptor, a negative ionizable function, and an aromatic plane function). The best qualitative model consisted of seven features (Hypo2: 11 points, two aromatic rings, two hydrogen bond acceptors, a negative ionizable function, and two hydrophobic functions). The obtained pharmacophore models were validated on a wide set of test molecules. They were shown to be able to identify a range of highly potent AT(1) antagonists, among those a number of recently launched drugs and some candidates presently undergoing clinical tests and/or development phases. The results of our study provide confidence for the utility of the selected chemical feature based pharmacophore models to retrieve structurally diverse compounds with desired biological activity by virtual screening.

Synthesis and molecular modeling of new 1-aryl-3-[4-arylpiperazin-1-yl]-1-propane derivatives with high affinity at the serotonin transporter and at 5-HT(1A) receptors.

It has been proposed that 5-HT(1A) receptor antagonists augment the antidepressant efficacy of selective serotonin (5-HT) reuptake inhibitors. In a search toward new and efficient antidepressants, 1-(aryl)-3-[4-arylpiperazin-1-yl]-1-propane molecular hybrids were designed, synthesized, and evaluated for 5-HT reuptake inhibition and 5-HT(1A) receptor affinity. The design was based in coupling structural moieties related to inhibition of serotonin reuptake, such as benzo[b]thiophene derivatives to arylpiperazines, typical 5-HT(1A) receptor ligands. In binding studies, several compounds showed affinity at the 5-HT transporter and at 5-HT(1A) receptors. Molecular modeling studies predicted the pharmacophore elements required for high affinity binding and the features that enable to discriminate between agonist, partial agonist, or antagonist action at 5-HT(1A) receptors and 5-HT transporter inhibition. Solvent interactions in desolvation prior to the binding step along with enthalpy and enthropy compensations might be responsible to explain agonist, partial agonist, and antagonist character. Hydrogen-bonding capability seems to be important to break hydrogen interhelical hydrogen bonds or alternatively to form other bonds upon ligand binding. Partial agonists and antagonists are unable to do this as the full agonist, which interacts closely by long-range forces or directly. The compounds showing the higher affinity at both the 5-HT transporter (K(i) < 50 nM) and the 5-HT(1A) receptors (K(i) < 20 nM) were further explored for their ability to stimulate [(35)S]GTPgammaS binding or to antagonize 8-hydroxy-2-di-n-propylamino-tetralin (8-OH-DPAT)-stimulated [(35)]GTPgammaS binding to rat hippocampal membranes, an index of agonist/antagonist action at 5-HT(1A) receptors, respectively. Compound 8g exhibited agonist activity (EC(50) = 30 nM) in this assay, whereas compounds 7g and 8h,i behaved as weak partial agonists and 7h-j and 8j,l antagonized the R(+)-8-OH-DPAT-stimulated GTPgammaS binding. Functional characterization was performed by measuring the antagonism to 8-OH-DPAT-induced hypothermia in mice.