Anik Peeters

Which Compound to Select in Lead Optimization? Prospectively Validated Proteochemometric Models Guide Preclinical Development

In quite a few diseases, drug resistance due to target variability poses a serious problem in pharmacotherapy. This is certainly true for HIV, and hence, it is often unknown which drug is best to use or to develop against an individual HIV strain. In this work we applied ‘proteochemometric’ modeling of HIV Non-Nucleoside Reverse Transcriptase (NNRTI) inhibitors to support preclinical development by predicting compound performance on multiple mutants in the lead selection stage. Proteochemometric models are based on both small molecule and target properties and can thus capture multi-target activity relationships simultaneously, the targets in this case being a set of 14 HIV Reverse Transcriptase (RT) mutants. We validated our model by experimentally confirming model predictions for 317 untested compound – mutant pairs, with a prediction error comparable with assay variability (RMSE 0.62). Furthermore, dependent on the similarity of a new mutant to the training set, we could predict with high accuracy which compound will be most effective on a sequence with a previously unknown genotype. Hence, our models allow the evaluation of compound performance on untested sequences and the selection of the most promising leads for further preclinical research. The modeling concept is likely to be applicable also to other target families with genetic variability like other viruses or bacteria, or with similar orthologs like GPCRs.

Crystal Structure of Lysine Sulfonamide Inhibitor Reveals the Displacement of the Conserved Flap Water Molecule in Human Immunodeficiency Virus Type 1 Protease

ABSTRACT Human immunodeficiency virus type 1 (HIV-1) protease has been continuously evolving and developing resistance to all of the protease inhibitors. This requires the development of new inhibitors that bind to the protease in a novel fashion. Most of the inhibitors that are on the market are peptidomimetics, where a conserved water molecule mediates hydrogen bonding interactions between the inhibitors and the flaps of the protease. Recently a new class of inhibitors, lysine sulfonamides, was developed to combat the resistant variants of HIV protease. Here we report the crystal structure of a lysine sulfonamide. This inhibitor binds to the active site of HIV-1 protease in a novel manner, displacing the conserved water and making extensive hydrogen bonds with every region of the active site.

Ab initio conformational analysis of N-formyl l-alanine amide including electron correlation

Abstract The conformational properties of N -formyl l -alanine amide (ALA) were investigated using RMP2/6-311G ∗∗ ab initio gradient geometry optimization. One hundred forty four structures of ALA were optimized at 30° grid points in its φ (N–C(α)), ψ (C(α)–C′) conformational space. Using cubic spline functions, the grid structures were then used to construct analytical representations of complete surfaces, in φ , ψ -space, of bond lengths, bond angles, torsional sensitivity and electrostatic atomic charges. Analyses show that, in agreement with previous studies, the right-handed helical conformation, α R , is not a local energy minimum of the potential energy surface of ALA. Comparisons with protein crystallographic data show that the characteristic differences between geometrical trends in dipeptides and proteins, previously found for ab initio dipeptide structures obtained without electron correlation, are also found in the electron-correlated geometries. In contrast to generally accepted features of force fields used in empirical molecular modeling, partial atomic charges obtained by the CHELPG method are found to be not constant, but to vary significantly throughout the φ , ψ -space. By comparing RHF and MP2 structures, the effects of dispersion forces on ALA were studied, revealing molecular contractions for those conformations, in which small adjustments of torsional angles entail large changes in non-bonded distances.

Conformational analysis of TMC114, a novel HIV-1 protease inhibitor.

TMC114, a potent novel HIV-1 protease inhibitor, remains active against a broad spectrum of mutant viruses. In order to bind to a variety of mutants, the compound needs to make strong, preferably backbone, interactions and have enough conformational flexibility to adapt to the changing geometry of the active site. The conformational analysis of TMC114 in the gas phase yielded 43 conformers in which five types of intramolecular H-bond interactions could be observed. All 43 conformers were subject to both rigid and flexible ligand docking in the wild-type and a triple mutant (L63P/V82T/I84V) of HIV-1 protease. The largest binding energy was calculated for the conformations that are close to the conformation observed in the X-ray complexes of TMC114 and HIV-1 protease.

On the use of the supermolecule model for the calculation of the Young's modulus of crystalline polymers

The use of the supermolecule model for the calculation of the Youngs modulus of crystalline polymers has been tested for a series of small and large n-alkanes. The molecules were divided into a head, body, and tail part, with the body being representative for a polyethylene chain. Calculations were performed with and without including periodicity in the body, and the results have been compared. Guidelines have been formulated to describe the applicability of the approach for other polymers.

Using BRABO/CHARMM: application to 2-(2-methyl-3-chloroanilino) nicotinic acid

Molecular crystals have been studied using two new forms of the cluster approach: an extended point charge (PCX) and an extended supermolecule (SMX) model. These models extend, using a hybrid quantum mechanical/ molecularmechanical (QM/MM) approach, that part of the molecular environment that was previously described by point charges in, respectively, the point charge (PC) and supermolecule (SM) models. After interfacing the ab initio program BRABO with the molecular mechanics program CHARMM, the PCX and SMX models have been tested on formamide oxime, α-glycine, and the yellow form of dimethyl 3,6-dichloro-2,5-dihydroxyterephthalate. PCX results are in notably better agreement with experimental results than PC results and are shown to be a viable alternative to SM calculations. For α-glycine, the SMX model improves results over the SM model. For dimethyl 3,6-dichloro-2,5-dihydroxyterephthalate, it was shown that the SMX model can give SM-quality results when fewer neighbors are included in the wave function, thereby reducing the computation time significantly. As a second part of this study, the PCX model was applied to the geometry optimization of the four polymorphs of 2-(2-methyl-3-chloroanilino) nicotinic acid. In contrast to a previous study using the PC model, the newly developed PCX model introduced in this study allowed full geometry optimization of all polymorphs.