Representation of target-bound drugs by computed conformers: implications for conformational libraries

BACKGROUND: 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. RESULTS: 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 drug enabled us to reproduce the bound states within a similarity threshold of 1.0 Å in 70% of all cases. This fraction rises to about 90% for smaller or average sized drugs. CONCLUSION: Single drugs adopt multiple bioactive conformations if they interact with different target proteins. Due to the structural diversity of binding sites they adopt conformations that are distributed over a broad conformational space and wide energy range. Since the majority of drugs is well represented by a predefined low number of conformers (up to 100) this procedure is a valuable method to compare compounds by three-dimensional features or for fast similarity searches starting with pharmacophores. The underlying 9600 generated drug conformers are downloadable from the Super Drug Web site [1]. All superpositions are visualised at the same source. Additional conformers (110,000) of 2400 classified WHO-drugs are also available

Genome-wide DNA methylation levels and altered cortisol stress reactivity following childhood trauma in humans

DNA methylation likely plays a role in the regulation of human stress reactivity. Here we show that in a genome-wide analysis of blood DNA methylation in 85 healthy individuals, a locus in the Kit ligand gene (KITLG; cg27512205) showed the strongest association with cortisol stress reactivity (P=5.8 � 10?6). Replication was obtained in two independent samples using either blood (N=45, P=0.001) or buccal cells (N=255, P=0.004). KITLG methylation strongly mediates the relationship between childhood trauma and cortisol stress reactivity in the discovery sample (32% mediation). Its genomic location, a CpG island shore within an H3K27ac enhancer mark, and the correlation between methylation in the blood and prefrontal cortex provide further evidence that KITLG methylation is functionally relevant for the programming of stress reactivity in the human brain. Our results extend preclinical evidence for epigenetic regulation of stress reactivity to humans and provide leads to enhance our understanding of the neurobiological pathways underlying stress vulnerability

DOGS: Reaction-Driven de novo Design of Bioactive Compounds

We present a computational method for the reaction-based de novo design of drug-like molecules. The software DOGS (Design of Genuine Structures) features a ligand-based strategy for automated ‘in silico’ assembly of potentially novel bioactive compounds. The quality of the designed compounds is assessed by a graph kernel method measuring their similarity to known bioactive reference ligands in terms of structural and pharmacophoric features. We implemented a deterministic compound construction procedure that explicitly considers compound synthesizability, based on a compilation of 25'144 readily available synthetic building blocks and 58 established reaction principles. This enables the software to suggest a synthesis route for each designed compound. Two prospective case studies are presented together with details on the algorithm and its implementation. De novo designed ligand candidates for the human histamine H4 receptor and γ-secretase were synthesized as suggested by the software. The computational approach proved to be suitable for scaffold-hopping from known ligands to novel chemotypes, and for generating bioactive molecules with drug-like properties

Ab Initio potential grid based docking: From High Performance Computing to In Silico Screening

We present a new method for the generation of potential grids for protein-ligand docking. The potential of the docking target structure is obtained directly from the electron density derived through an ab initio computation. A large subregion was selected to allow the full ab initio treatment of a the Isocitrate Lyase enzyme. The electrostatic potential is tested by docking a small charged molecule (succinate) into the binding site. The ab initio grid yields a superior result by producing the best binding orientation and position, and by recognizing it as the best. In contrast the same docking procedure, but using a classical point-charge based potential, produces a number of additional incorrect binding poses, and does not recognize the correct pose as the best solution

The GAMESS-UK electronic structure package: algorithms, developments and applications.

NoA description of the ab initio quantum chemistry package GAMESS-UK is presented. The package offers a wide range of quantum mechanical wavefunctions, capable of treating systems ranging from closed-shell molecules through to the species involved in complex reaction mechanisms. The availability of a wide variety of correlation methods provides the necessary functionality to tackle a number of chemically important tasks, ranging from geometry optimization and transition-state location to the treatment of solvation effects and the prediction of excited state spectra. With the availability of relativistic ECPs and the development of ZORA, such calculations may be performed on the entire Periodic Table, including the lanthanides. Emphasis is given to the DFT module, which has been extensively developed in recent years, and a number of other, novel features of the program. The parallelization strategy used in the program is outlined, and detailed speedup results are given. Applications of the code in the areas of enzyme and zeolite catalysis and in spectroscopy are described