The recently introduced TrixX Conformer Generator (TCG)  was developed paying close attention to the trade-off between accuracy and conformational ensemble size. The tool utilizes a rule-based strategy and identifies low-energy conformers in a best-first-search build-up algorithm. The amount of explored search space in this heuristic is determined according to an exponential function, which employs a user-specified quality level as base and an exponent which depends on the molecule's flexibility.
A comparison of TCG to frequently used conformer generators shows that it performs well with respect to the trade-off between accuracy and ensemble size, while achieving comparable accuracy. Furthermore we show that for lead-like molecules on average 20 conformers per ensemble suffice to achieve an average accuracy below 1Å...
 Griewel, A., et al.; J. Chem. Inf. Model. In press.
Virtual screening is widely established as part of the drug discovery process. So far, the primary domain of application are screening collections based on in-house repositories and vendor catalogs, while pharma companies have access to large numbers of validated chemistries. It would be of great interest to perform virtual screens based on all compounds that are synthetically accessible by any such combinatorial library protocol. However, the number of possible compounds easily exceeds – by many orders of magnitude – the number of compounds that can be stored and searched by conventional methods.
We overcame these limitations by converting large numbers of combinatorial libraries into a "virtual chemistry space". FTrees is capable of searching such spaces for similar molecules and FlexNovo can retrieve virtual products on the basis of their fit to a protein active site. In each case compounds are suggested which are synthetically accessible via one or more of the existing synthetic routes. Such output provides library design ideas for hit follow-up from high-throughput screening or lead hopping into novel series. The design of a free publicly available chemistry space and a number of successful applications will be presented.
Chemists are well trained in perceiving 2D molecular sketches. On the side of computer assistance, the automated generation of such sketches becomes very difficult when it comes to multi-molecular arrangements such as protein-ligand complexes in a drug design context.
During the last few years we have developed PoseView, a tool which displays molecular complexes incorporating a simple, easy-to-perceive arrangement of the ligand and the amino acids to which it forms interactions. Resulting in atomic resolution diagrams, PoseView operates on a fast tree re-arrangement algorithm to minimize crossing lines in the sketches. Due to a de-coupling of interaction perception and the drawing engine, PoseView can draw any interactions, such as hydrogen bonds, metal interactions, pi interactions and undirected hydrophobic contacts, determined by either distance-based rules or the FlexX interaction model. Owing to the small-molecule drawing engine 2Ddraw, molecules are drawn in a textbook-like manner following the IUPAC regulations.
Besides the novel underlying interaction models, we will present new algorithmic approaches, assess usability issues and a large-scale validation study on the PDB.
Fragment spaces have proven to be a valuable source of molecules that are biologically active and synthetically feasible. A fragment space consists of a set of molecular fragments with defined linking positions and a set of rules to combine fragments to new molecules.
We have developed an expert system for medicinal chemists to allow to search fragment spaces for molecules that can fulfill a chosen three dimensional pharmacophore. The fragment space is searched with an evolutionary approach, where partial solutions evolve to fit the posed query by adding, deleting of replacing fragments. The fitness of a partial solution is calculated by its ability to obey to the constraints of the pharmacophore.
We tested the program by searching several focused fragment spaces with pharmacophores for common drug targets. The resulting molecules obey to the input pharmacophore and look chemically sound.
Lead discovery often starts from small fragment binders for which experimental evidence has been found in an active site. Development into a lead structure can involve three possible scenarios: a) to grow from these 'needles' into the depth of the pocket; b) linkage of two or more fragments into one compound with optimized potency; or c) merging two or more fragments in regions of mutual overlap.
These tasks can now be accomplished with a novel software tool, which comprises the interactive fragment based software ReCore and the well established docking engine FlexX. With ReCore, synthetically accessible compounds can be generated in seconds by using an indexed 3D fragment library on fragments or compounds that should be altered. The results can then be validated by docking without leaving the software environment.
We will elucidate the basic principles and give examples which map onto experimental data and evolve into novel lead ideas.
An often encountered scenario in FBLD is experimental evidence of one or multiple fragment binders in a protein binding site. Typically, depending on quality and amount of information, subsequent steps can be divided into three classes: a) growing from these 'seeds', b) linking of two or more fragment binders, or c) merging multiple overlapping binders into a single potent lead.
To accomplish these tasks with ultimate efficiency, the software tool ReCore has been developed. Based on a vast 3D fragment library, ReCore finds fragments which provide an optimal fit with the 'dangling bonds' and comply with optional filters and pharmacophore features. Based on a novel indexing technology, ReCore, in contrast to other tools targeting a similar challenge, provides its results within seconds, thus allowing interactive usage.
Synthetic access of results (which was a major weakness in the early days of de novo design) is taken care of in ReCore at three levels: during fragment creation, within query definition, and when creating the results. We will elucidate the basic principles and give examples which map onto experimental data and evolve into novel lead ideas.
It is highly desirable to have a scoring function that provides guidance for the design of compounds with optimized bioactivity. Hyde  is such a scoring function. Its basic principle is a balanced assessment of the energetics of desolvation. Only three major factors are taken into consideration: (a) local hydrophobicity, (b) solvent accessible surface, and (c) contact surface area. Based on these, energetically favorable and unfavorable contributions to the binding affinity can be assessed on an atomic level.
It has been demonstrated previously that Hyde is able to distinguish between strong binders, weak binders, and non-binders . However, systematically missing are terms regarding repulsion and strain which rendered Hyde not entirely applicable to conformationally strained or clashing poses. We have therefore further improved the scoring function and now consider the respective terms in an optimization phase prior to the actual score assessment. Further, we coupled it to a graphical interface. Hyde has never been calibrated for an improved correlation with measured binding affinities.
Atomic contributions can now be visualized, which turns out to be particularly helpful in a lead-optimization setup. One may immediately identify energetically unfavorable arrangements, like an H-bonding group without a counter-part in an otherwise hydrophobic pocket. Medicinal chemists will immediately have ideas how to alter a given structure in order to gain activity. The interface allows these changes to be tried out in an interactive manner like on a virtual workbench. We will demonstrate the performance of Hyde based on benchmark datasets as well as on published data of congeneric compound series.
 Reulecke et al., ChemMedChem 2007
 Lange, G. et al., ICCS 2008
Lead discovery often starts from small fragment binders for which experimental evidence has been found in an active site. Development into a lead structure can involve three possible scenarios: a) to grow from these 'needles' into the depths of the pocket; b) merging multiple overlapping binders into a single potent lead; or c) the more difficult prospect of linking two or more fragments into one compound with optimized potency.
These tasks can now be accomplished computationally with a novel software tool, LeadIT, which was primarily designed for mixed medicinal and computational chemistry teams. Synthetically accessible compounds can be generated in seconds using fragment based design by using an indexed 3D fragment library of fragments. We will elucidate the basic principles of the approach and give examples which map onto experimental data and evolve into novel lead ideas. Workshop participants may then proceed to working on individual hands-on exercises and application of the methods to their case study problems.
Descriptor-based similarity searches are known to be extremely fast and sutable for high throughput virtual screening. Whereas shape-based methods are consitered to be more accurate but significantly slower. We have combined these two approaches to gain the better of both worlds, the speed of the descriptor-based search and the accuracy of the shape matching. Application examples and results of benchmark studies will be presented.
It has frequently been shown in the course of the last years that using fragments as a starting point for buildup is a very sensible approach to finding promising new lead structures. Fragment Growing, linking and merging have been employed to successfully improve binding affinity of new chemical entities. Moreover, searching fragment spaces for novel entities that meet a certain pharmacophore or synthetic criteria is a very powerful means of quickly ascertain new lead compounds with different scaffolds and improved binding motifs. In this contribution we bring an overview of 2D and 3D methods capable of using fragments to find, change or improve new chemical entities, scaffold hop across compound classes, and the sensible design of the underlying fragment spaces. We show some improvements we recently introduced to excel these apporaches. Some recent applications in the industry that verify these methods will be shown.
As a methods developer it is highly desirable to have high-quality benchmark data available for testing. Unfortunately the number and quality of such data sets that are pblished and freely available is quite limited. Also if such data is available, methods developers may use the data for training and testing. It was therefore quite valuable for the community to have a data-set that was not only well prepared and standardized such as to be applicable for various computer programs, but also to be able to preform blind studies which prevented the developers from overfitting their methods in an effort to improve performance. We will share our experience from application studies based on such data and explain in which way this guided the further development of our docking technology.