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.