Current Topics in Medicinal Chemistry - Volume 5, Issue 8, 2005

Ligand flexibility is an important problem in molecular docking and virtual screening. To address this challenge, we investigate a hierarchical pre-organization of multiple conformations of small molecules. Such organization of pre-calculated conformations removes the exploration of ligand conformational space from the docking calculation and allows for concise representation of what can be thousands of conformations. The hierarchy also recognizes and prunes incompatible conformations early in the calculation, eliminating redundant calculations of fit. We investigate the method by docking the MDL Drug Data Report (MDDR), an annotated database of 100,000 molecules, into apo and holo forms of seven unrelated targets. This annotated database allows us to track the ranking of tens to hundreds of annotated ligands in each of the docking systems. The binding sites and database are prepared in an automated fashion in an attempt to remove some human bias from the calculations. Many thousands of explicit and implicit ligand conformations may be docked in calculations not much longer than required for single conformer docking. As long as internal energies are not considered, recombination with the hierarchy is additive as the number of degrees of freedom is increased. Molecules with even millions of conformations can be docked in a few minutes on a single desktop computer..

According to Hann's model of molecular complexity an increased probability of detection binding to a target protein can be expected when small, low complex molecular fragments are screened with high sensitivity instead of fullsized ligands with lower sensitivity. Analysis of the HTS summary data of Novartis and comparison with NMR screening results obtained on generic fragment libraries indicate this expectation to be true with hitrates of 0.001% - 0.151% observed in the identification of ligands with an IC50 threshold in the micromolar range in an HTS setup and hitrates above or equal to 3% observed in NMR screening of fragments with an affinity threshold in the millimolar range. It is however necessary to keep in mind that the sets of target studied were not identical for both method and the experience in NMR screening is too limited for a final conclusion. The term hitrate as used here reflects only the success rate in the observation of ligand binding event. It must not be confused with the overall success rate of fragment and high throughput screening in the lead finding process, which can be entirely different, since the steps required to follow-up a ligand binding event to a lead are different for both methods. A survey of fragment-based lead discovery case studies given in the literature shows that in approximately half of the cases the initial hit fragment was discovered by screening a generic library, whereas in the other cases some knowledge about an initial ligands or the protein binding site has been used, whereas systematic virtual screening of fragment databases has been only rarely reported. As comparatively high hitrates were obtained, further consideration to optimize the generic fragment screening library were directed to the chemical tractability of the fragment. As several functional groups preferred by chemists for modification and linking of the fragments are also preferentially involved in interactions between the fragments and the target protein, a set of screening fragments was derived from chemical building blocks by masking its linker group by a chemical transformation which can be later on used in the chemical follow-up of the fragment hit. For example primary amines can be masked as acetamides. If the screening fragment is active the related building block can then be used for synthesis of a follow-up library.

Nuclear receptors form a family of ligand-activated transcription factors that regulate a wide variety of biological processes and are thus generally considered relevant targets in drug discovery. We have constructed an annotated compound library directed to nuclear receptors (NRacl) as a means for integrating the chemical and biological data being generated within this family. Special care has been put in the appropriate storage of annotations by using hierarchical classification schemes for both molecules and nuclear receptors, which takes the ability to extract knowledge from annotated compound libraries to another level. Analysis of NRacl has ultimately led to the identification of scaffolds with highly promiscuous nuclear receptor profiles and to the classification of nuclear receptor groups with similar scaffold promiscuity patterns. This information can be exploited in the design of probing libraries for deorphanization activities as well as for devising screening batteries to address selectivity issues.

Motivated by the need to augment Merck's in-house small molecule collection, web-based tools for designing, enumerating, optimizing and tracking compound libraries have been developed. The path leading to the current version of this Virtual Library Tool Kit (VLTK) is discussed in context of the (then) available commercial offerings and the constraints and requirements imposed by the end users. Though the effort was initiated to simplify the tasks of designing novel, drug-like and diverse compound libraries containing between 2K-10K unique entities, it has also evolved into a powerful tool for outsourcing syntheses as well as lead identification and optimization. The web tool includes components that select reagents, analyze synthons, identify backup reagents, enumerate libraries, calculate properties, optimize libraries and finally track the synthesized compounds through biological assays. In addition to accommodating project specific designs and virtual 3D library scanning, the application includes tools for parallel synthesis, laboratory automation and compound registration.

Information extraction approaches have been successfully applied to mine the scientific literature in biology and medicine. So far, the main focus of research and development in this domain was on the recognition and extraction of gene and protein names in the context of molecular biology and genome research and on disease names and other medical terms in the context of clinical research. Similar to biology and medical sciences, medicinal chemistry, pharmacology and toxicology are descriptive sciences. However, information extraction approaches in these disciplines encounter a number of problems that are specific to the fact that these scientific areas are essentially centred at chemical compounds and their structures. In this review, we will give a short overview on general information extraction strategies in the life sciences and we will introduce new approaches to apply information extraction to the domain of pharmacology, medicinal chemistry and toxicology. Finally, we will emphasize on how information extraction approaches will support public and commercial research in medicinal chemistry, pharmacology and toxicology by linking information on chemical structures to biological information.

Partitioning algorithms are described that operate in chemical reference spaces formed by combinations of binary-transformed molecular descriptors and aim at the identification of potent hits in ligand-based virtual screening. One of these approaches depends on mapping of consensus positions of compound activity sets in descriptor spaces followed by step-wise extension of the dimensionality of these spaces and re-mapping of activity-dependent consensus positions. Dimension extension is carried out to increase the discriminatory power of descriptor combinations and distinguish database compounds from potential hits. This method was originally named Dynamic Mapping of Consensus positions (DMC) and subsequently extended in order to take different potency levels of known active molecules into account and increase the probability of recognizing potent database hits. The extension was accomplished by adding potency scaling to DMC calculations, and the resulting approach was termed POT-DMC. Results of comparisons of DMC and POT-DMC calculations on different classes of active compounds with substantially varying potency levels support the validity of the POT-DMC approach.

The original publication of Mortlock, A.; Keen, N. J.; Jung, F. H.; Heron, N. M.; Foote, K. M.; Wilkinson, R.; Green, R. Progress in the Development of Selective Inhibitors of Aurora Kinases, 2005, 5, 199-214 contained numerous errors, and the properly corrected version is reprinted here in it's entirety.

Errors in the mitotic process are thought to be one of the principal sources of the genetic instability that hallmarks cancer. Unsurprisingly, many of the proteins that regulate mitosis are aberrantly expressed in tumour cells when compared to their normal counterparts. These may represent a good source of targets for the development of novel anticancer agents. The Aurora kinases represent one such family of mitotic regulators. In recent years there has been intense interest in both understanding the role of the Aurora kinases in cell cycle regulation and also in developing small molecule inhibitors as potential novel anti-cancer drugs. With several companies now starting to take Aurora kinase inhibitors into clinical development, the time is right to review the medicinal chemistry contribution to developing the field, in particular to review the increasingly broad range of small molecule inhibitors with activity against this kinase family.