Small molecules are frequently used both in nature and therapeutically to modulate the activity of the protein they bind to. This is attractive for altering protein activity in a time-resolved manner.
It might seem straightforward to identify such ligands, either by their complementarity to a binding pocket on a protein surface or by similarity to already known ligands. Yet, there are 1060 small molecules to choose from (the "chemical space").
We have identified novel ligands with chemotypes unprecedented for the respective targets by docking to G protein-coupled receptors, the pharmacologically most relevant protein family. Furthermore, we have attempted to open up new regions of chemical space for ligands of the β2-adrenergic receptor by expanding experimentally determined fragment ligands, which led to affinity improvements and non-obvious extensions. I will also describe strategies to make chemical space more accessible by harnessing databases of easily synthesizable molecules. By exploiting semi-automatic synthesis strategies of highly-designed libraries, we were able to obtain and optimize more than 100 novel ligands for the β2-adrenergic receptor within just 6 weeks.
Various computational tools and molecular modeling platforms are known to support medicinal chemists in understanding bioactivities, predicting binding events and rationally designing drug molecules. Among them, the pharmacophore approach is an accurate and minimal 3D-abstraction of chemical structures and intermolecular interactions.
Pharmacophore models are usually derived from a group of molecules in absence of structural information on their biological targets (ligand-based approach) or from a ligand-target complex (structure-based approach). However, only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In the presented work, T2F-Pharm, a fully automated tool for Truly Target-Focused Pharmacophore modeling will be introduced. Using a grid-based approach, this method samples the protein cavity, filters the grid points by energy level and clusters them into low energy hot spots. Subsequently, key features in the pocket required for optimal interaction in a 3D-pharmacophore model are derived.
T2F-Pharm represents a valuable instrument for drug discovery to investigate protein surfaces in absence of known binding partners, e.g. in cases of rather unexplored binding sites including allosteric pockets.
SeeSAR is a 21st century molecular modeling software for the medicinal chemist, which helps save time in a plethora of drug discovery applications: exploring proteins, finding binding sites, placing ligands in binding sites, ideation, optimizing ligands in binding sites, improving affinity and ADME/T properties, circumnavigating difficult cores and many more.
This webinar takes you on a tour of some of SeeSAR's many use cases, and will show you how you can apply it to save time, and, ultimately, valuable resources.
In a joint venture, Enamine and BioSolveIT built the world's largest chemical space and made it ultra-fast searchable. The new product, called REAL Space Navigator, comprising 650 million compounds, allows for efficient hit exploration, from finding previously unknown analogues to scaffold hopping. The chemical space encoded with more than 100 Enamine synthesis protocols and in-stock building blocks, provides an escape from availability bias of current stock screening collections towards IP free areas. Compounds selected from this space will be synthesized in 3-4 weeks with an exceptional success rate of 80% and above.
In this webinar we explain the genesis and composition of the space as well as the search technology to access this vast resource. We also demonstrate the user-friendly graphical interface. Afterwards you may simply download → install & execute to explore this huge resource for free within less than 5 minutes. Join us to learn more about this exciting endeavor. Over half a billion virtual molecules that become real on demand are a resource that is simply too valuable to miss...