Putative bioactive conformers of small molecules: A concerted approach using NMR spectroscopy and computational chemistry (original) (raw)
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Conformational Sampling of Bioactive Molecules: A Comparative Study
Journal of Chemical Information and Modeling, 2007
The necessity to generate conformations that sample the entire conformational space accessible to a given molecule is ubiquitous in the field of computer-aided drug design. Protein-ligand docking, 3D database searching, and 3D QSAR are three commonly used techniques that depend critically upon the quality and diversity of the generated conformers. Although there are a wide range of conformational search algorithms available, the extent to which they sample conformational space is often unclear. To address this question, we conducted a robust comparison of the search algorithms implemented in several widely used molecular modeling packages, including Catalyst, Macromodel, Omega, MOE, and Rubicon as well as our own method, stochastic proximity embedding (SPE). We found that SPE used in conjunction with conformational boosting, a heuristic for biasing conformational search toward more extended or compact geometries, along with Catalyst, are significantly more effective in sampling the full range of conformational space compared to the other methods, which show distinct preferences for either more extended or more compact geometries.
The conformational musings of a medicinal chemist
Drug Discovery Today, 2014
Structure-based drug design strategies based on X-ray crystallographic data of ligands bound to biological targets or computationally derived pharmacophore models have been introduced over the past 25 years or so. These have now matured and are deeply embedded in the drug discovery process in most pharmaceutical and biotechnology companies where they continue to play a major part in the discovery of new medicines and drug candidates. Newly developed NMR methods can now provide a full description of the conformations in which ligands exist in free solution, crucially allowing those that are dominant to be identified. Integrating experimentally determined conformational information on active and inactive molecules in drug discovery programmes, alongside the existing techniques, should have a major impact on the success of drug discovery.
The Journal of Physical Chemistry A, 2003
This work presents the determination of a semiclassical conformational partition function for bioactive compounds. The proposed partition function includes the effect of the rotovibrational coupling and the conformational kinetic energy, through the rotovibrational G matrix. In addition, the model considers a relaxed potential that includes the effect of the nonconformational, internal, coordinates. Comparison of results from harmonic and anharmonic vibrational models shows that the present partition function is a good approximation to the quantum one. The effect of the rotovibrational coupling and conformational kinetic energy, i.e. the G matrix, on the partition function is analyzed considering the biologically active, protonated, forms of nicotine and the nicotinic analgesic ABT-594. All energetic and structural data are derived from ab initio results at the MP2/cc-pVDZ level. Only two conformers are found to be significantly populated at physiological temperature in the nicotine case. The relative population of both conformers is clearly affected by the value of the G matrix. For ABT-594, several minima on the conformational potential energy hypersurface are found. However, only one conformer collects the population. Here, the distribution of population is only slightly affected by the G matrix. Performing simulations with a double minima potential, we show that for conformers separated by energy differences about or higher than 2 kcal mol-1 , the effect of the G matrix can be neglected.
1990
An understanding of the structural factors that control interaction between ligands and their receptors in solution is now possible through two-and threedimensional nuclear magnetic resonance (2D-and 3D-NMR) spectroscopy. Of particular value is the ability to examine these interactions in solution and follow the kinetics of reactions that involve equilibria amongst isoforms of ligand or protein. The conference reported in this volume was convened to examine the latest developments in this technique and their application to the design of new therapeutic agents.
Journal of Chemical Information and Computer Sciences, 1998
Software has been developed for potential energy surface analysis and the local minima method of pharmacophore determination. 1 LMM is rigorous and systematic and employs multiple conformations which are the local minima from the potential energy surface of each compound in the data set. It produces a series of possible pharmacophores from a postulated set of pharmacophore elements. The best pharmacophore is then determined by performing a comparative molecular field analysis (CoMFA) on each one. The pharmacophore which produces the most self-consistent model is deemed the best. Local minima on the gas-phase potential energy surface are shown to be a reasonably close approximation to protein bound conformations, and these conformations can be found through systematic conformational searches followed by minimization of the local minima. LMM was used to develop a 3D-QSAR model for dopamine-hydroxylase (DBH) inhibitors which was highly predictive (predictive R 2) 0.71 and standard error of predictions) 0.41). The model predicted that the phenyl and thienyl series of inhibitors were acting as bioisosteres. Examination of compounds overlayed in the model indicated a possible hydrogen bond acceptor in the DBH active site. Three tyrosine residues previously labeled by mechanism based inhibitors may be acting as the acceptor and therefore represent excellent candidates for site-directed mutagenesis studies.
BMC bioinformatics, 2006
The increasing number of known protein structures provides valuable information about pharmaceutical targets. Drug binding sites are identifiable and suitable lead compounds can be proposed. The flexibility of ligands is a critical point for the selection of potential drugs. Since computed 3D structures of millions of compounds are available, the knowledge of their binding conformations would be a great benefit for the development of efficient screening methods. Integration of two public databases allowed superposition of conformers for 193 approved drugs with 5507 crystallised target-bound counterparts. The generation of 9600 drug conformers using an atomic force field was carried out to obtain an optimal coverage of the conformational space. Bioactive conformations are best described by a conformational ensemble: half of all drugs exhibit multiple active states, distributed over the entire range of the reachable energy and conformational space.A number of up to 100 conformers per ...
CHIMIA, 2006
Nuclear magnetic resonance (NMR) methods at the Institute of Molecular Pharmacy (IMP) provide crucial information in several fundamental themes in drug discovery. Assignments of complex carbohydrates are obtained to a high degree of completion and accuracy, thereby accelerating their identity. Conformational analysis of ligands in their unbound state reveals to what extent the steric considerations, essential for minimizing entropy losses upon binding, are optimized. Small libraries of compounds are screened for their binding to receptors. Promising ligands are analyzed in the presence of their receptor to determine the geometric arrangements in the bound state, as well as the functional groups responsible for the observed binding.
Journal of Chemical Information and Modeling, 2012
Identification of the global energy minimum conformation of a small molecule can be approached with a range of computational strategies. Smaller sets of compounds can be studied by molecular dynamics methods in explicit water or by ab initio methods. For large compound libraries, conformational search methods can be used. One such method is Monte Carlo sampling, where thousands of random starting conformations for each compound are generated and subsequently minimized using force field methods. To increase the computational efficiency, this type of calculation is performed in vacuo or using a continuum solvent model. The quality of implicit solvent models is currently such that the behavior of most molecules is well modeled. In the case of polar or charged compounds, some issues still linger. There is a tendency to overestimate the electrostatic interaction between charged groups when these are located close to each other in a given conformation. 1,2 For some molecules, the opportunity for such interactions during a conformational search leads to a reported global energy minimum conformation, where these groups form an internal hydrogen bond. Such folded conformations may well exist in solution, in equilibrium with their extended counterparts. This is observed in the case of β-alanine, where NMR data and ab initio calculations demonstrate that the two types of conformations, extended and folded, are both represented in water. 2 It is not a problem that a given method reports the folded conformation, but in the case of β-alanine, the energy difference between the two conformers, as calculated by force field methods, has been reported as high as 20 kcal/mol. 2,3 This indicates that the force field methods may overestimate the stability of the folded conformation. This is most likely caused by the incomplete description of solvation effects by the continuum models, in combination with force field specific effects. Moreover, entropic penalties from introducing an internal hydrogen bond are also not included in the energy minimization methods and are difficult to estimate, even with computationally expensive methods due to sampling issues.