A computational model of the inhibition of Mycobacterium tuberculosis ATPase by a new drug candidate R207910.

Diarylquinolines (DARQs) are a new class of potent inhibitors of the ATPase of Mycobacterium tuberculosis. We have created a homology model of a binding site for this class of compounds located on the contact area of the a-subunit (gene atpB) and c-subunits (gene atpE) of Mycobacterium tuberculosis ATPase. The binding pocket that was identified from the analysis of the homology model is formed by 4 helices of three c-subunits and 2 helices of the a-subunit. The lead compound of the DARQ series, R207910, was docked into the pocket using a simulated annealing, multiple conformer, docking algorithm. Different stereoisomers were treated separately. The best docking pose for each stereoisomer was optimized by molecular dynamics simulation on the 5300 atoms of the binding region and ligand. The interaction energies in the computed complexes enable us to rank the different stereoisomers in order of interaction strength with the ATPase binding pockets. We propose that the activity of R207910 against Mycobacterium tuberculosis is based on interference of the compound with the escapement geometry of the proton transfer chain. Upon binding the compound mimics the conserved Arg-186 residue of the a-subunit and interacts in its place with the conserved acidic residue Glu-61 of the c-subunit. This mode of action is corroborated by the good agreement between the computed interaction energies and the observed pattern of stereo-specificity in the model of the binding region.

An ant algorithm for the conformational analysis of flexible molecules.

Originally, the ant system was developed for optimization in discrete search spaces such as the traveling salesman problem. We detail our adaptation of the algorithm to optimization in the continuous search space of conformational analysis. The parameters of the algorithm were tuned using a simple test molecule, undecane, and a drug molecule, imatinib. The algorithm is further tested on four more drug or drug-like molecules, on vitamin A and on alanine tetrapeptide.

In search of a novel anti-HIV drug: multidisciplinary coordination in the discovery of 4-[[4-[[4-[(1E)-2-cyanoethenyl]-2,6-dimethylphenyl]amino]-2- pyrimidinyl]amino]benzonitrile (R278474, rilpivirine).

Ideally, an anti-HIV drug should (1) be highly active against wild-type and mutant HIV without allowing breakthrough; (2) have high oral bioavailability and long elimination half-life, allowing once-daily oral treatment at low doses; (3) have minimal adverse effects; and (4) be easy to synthesize and formulate. R278474, a new diarylpyrimidine (DAPY) non-nucleoside reverse transcriptase inhibitor (NNRTI), appears to meet these criteria and to be suitable for high compliance oral treatment of HIV-1 infection. The discovery of R278474 was the result of a coordinated multidisciplinary effort involving medicinal chemists, virologists, crystallographers, molecular modelers, toxicologists, analytical chemists, pharmacists, and many others.

Design, synthesis, and SAR of a novel pyrazinone series with non-nucleoside HIV-1 reverse transcriptase inhibitory activity.

A series of novel pyrazinones designed as non-nucleoside reverse transcriptase inhibitors (NNRTIs) was synthesized and their anti-HIV structure-activity relationship (SAR) was studied.

Synthesis of novel diarylpyrimidine analogues and their antiviral activity against human immunodeficiency virus type 1.

This paper reports the synthesis and the antiviral properties of new diarylpyrimidine (DAPY) compounds as nonnucleoside reverse transcriptase inhibitors (NNRTIs). The synthesis program around this new DAPY series was further optimized to produce compounds displaying improved activity against a panel of eight clinically relevant single and double mutant strains of human immunodeficiency virus type 1 (HIV-1).

Genotype dependent QSAR for HIV-1 protease inhibition.

The development of drug-resistant viruses limits the therapeutic success of anti-HIV therapies. Some of these genetic HIV-variants display complex mutational patterns in their pol gene that codes for protease and reverse transcriptase, the most investigated molecular targets for antiretroviral therapy. In this paper, we present a computational structure-based approach to predict the resistance of a HIV-1 protease strain to amprenavir by calculating the interaction energy of the drug with HIV-1 protease. By considering the interaction energy per residue, we can identify what residue mutations contribute to drug-resistance. This approach is presented here as a structure-based tool for the prediction of resistance of HIV-1 protease toward amprenavir, with a view to use the drug-protein interaction-energy pattern in a lead-optimization procedure for the discovery of new anti-HIV drugs.

Structure based activity prediction of HIV-1 reverse transcriptase inhibitors.

We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications.

Correlations between factors determining the pharmacokinetics and antiviral activity of HIV-1 non-nucleoside reverse transcriptase inhibitors of the diaryltriazine and diarylpyrimidine classes of compounds.

OBJECTIVE: To investigate the important factors that determine the bioavailability and the antiviral activity of the diaryltriazine (DATA) and diarylpyrimidine (DAPY) non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1 in animal species and humans using cell-based assays, physicochemical and computed parameters. METHODS: This naturalistic study included 15 parameters ranging from molecular mechanics calculations to phase I clinical trials. The calculated parameters were solvent-accessible surface area (SASA), polar surface area and Gibbs free energy of solvation. Physicochemical parameters comprised lipophilicity (octanol/water partition coefficient [cLogP]), ionisation constant (pKa), solubility and aggregate radius. Cell-based assays included human colonic adenocarcinoma cell (Caco-2) permeability (transepithelial transport), drug metabolism and antiviral activity (negative logarithm of the molar effective concentration inhibiting viral replication by 50% [pEC50]). Exposure was tested in rats, dogs and human volunteers. RESULTS: Of the 15 parameters, eight correlated consistently among one another. Exposure (area under the plasma concentration-time curve [AUC]) in humans correlated positively with that in rats (r = 1.00), with transepithelial transport (r = 0.83), lipophilicity (r = 0.60), ionisability (r = 0.89), hydrodynamic radius of aggregates (r = 0.66) and with antiviral activity (r = 0.61). Exposure in humans was also seen to correlate negatively with SASA (r = -0.89). No consistent correlation was found between exposure in dogs and the eight parameters. Of the 14 DATA/DAPY molecules, 11 form aggregates with radii between 34 and 100 nm. CONCLUSIONS: We observed correlations between exposure in humans with exposure in rats, transepithelial transport (Caco-2 cells), ionisability, lipophilicity, aggregate radius and SASA in the class of DATA/DAPY NNRTI compounds. The lipophilic DATA/DAPY compounds form aggregates. It can be assumed that absorption in the intestinal tract and endocytosis in infected cells of these lipophilic compounds are governed by the common phenomenon of aggregate formation. As the lymphatic system offers a pathway for intestinal uptake of aggregates, this may offer a therapeutic advantage in the treatment of HIV-1 infection. Although it was not the objective of the study, we found that the rat was a better in vivo model than the dog for the prediction of systemic exposure in this particular set of compounds.

Roles of conformational and positional adaptability in structure-based design of TMC125-R165335 (etravirine) and related non-nucleoside reverse transcriptase inhibitors that are highly potent and effective against wild-type and drug-resistant HIV-1 variants.

Anti-AIDS drug candidate and non-nucleoside reverse transcriptase inhibitor (NNRTI) TMC125-R165335 (etravirine) caused an initial drop in viral load similar to that observed with a five-drug combination in naïve patients and retains potency in patients infected with NNRTI-resistant HIV-1 variants. TMC125-R165335 and related anti-AIDS drug candidates can bind the enzyme RT in multiple conformations and thereby escape the effects of drug-resistance mutations. Structural studies showed that this inhibitor and other diarylpyrimidine (DAPY) analogues can adapt to changes in the NNRTI-binding pocket in several ways: (1). DAPY analogues can bind in at least two conformationally distinct modes; (2). within a given binding mode, torsional flexibility ("wiggling") of DAPY analogues permits access to numerous conformational variants; and (3). the compact design of the DAPY analogues permits significant repositioning and reorientation (translation and rotation) within the pocket ("jiggling"). Such adaptations appear to be critical for potency against wild-type and a wide range of drug-resistant mutant HIV-1 RTs. Exploitation of favorable components of inhibitor conformational flexibility (such as torsional flexibility about strategically located chemical bonds) can be a powerful drug design concept, especially for designing drugs that will be effective against rapidly mutating targets.

A pharmacophore docking algorithm and its application to the cross-docking of 18 HIV-NNRTI's in their binding pockets.

The docking of small molecules into the binding site of a target protein is an important but difficult step in structure-based drug design. The performance of a docking algorithm is usually evaluated by re-docking ligands into their native binding sites. We have explored the cross-docking of 18 HIV-NNRTIs (non-nucleoside inhibitors of HIV reverse transcriptase) of which the ligand-protein structure has been determined: each of the 18 ligands was docked into each of the 18 binding sites. The docking algorithms studied are an energy-based simulated annealing algorithm and a novel pharmacophore docking algorithm. It turns out that the energy-based docking of the ligands into non-native pockets is far less successful than the docking into their native pockets. The results can be improved by using explicit pharmacophore information, and by docking a ligand into a panel of protein structures and selecting the ligand-protein combination with the lowest interaction energy as the final result.

On the detection of multiple-binding modes of ligands to proteins, from biological, structural, and modeling data.

There are several indications that a given compound or a set of related compounds can bind in different modes to a specific binding site of a protein. This is especially evident from X-ray crystallographic structures of ligand-protein complexes. The availability of multiple binding modes of a ligand in a binding site may present an advantage in drug design when simultaneously optimizing several criteria. In the case of the design of anti-HIV compounds we observed that the more active compounds that are also resilient against mutation of the non-nucleoside binding site of HIV1-reverse transcriptase make use of more binding modes than the less active and resilient compounds.

SYNOPSIS: SYNthesize and OPtimize System in Silico.

We present a de novo design program called SYNOPSIS, that includes a synthesis route for each generated molecule. SYNOPSIS designs novel molecules by starting from a database of available molecules and simulating organic synthesis steps. This way of generating molecules imposes synthetic accessibility on the molecules. In addition to a starting database, a fitness function is needed that calculates the value of a desired property for an arbitrary molecule. The values obtained from this function guide the design process in optimizing the molecules toward an optimal value of the calculated property. Two applications are described. The first uses an electric dipole moment calculation to generate molecules possessing a strong dipole moment. The second makes use of the three-dimensional structure of a viral enzyme in order to generate high affinity ligands. Twenty eight compounds designed with the program resulted in 18 synthesized and tested compounds, 10 of which showed HIV inhibitory activity in vitro.