Drug molecules consist of a few tens of atoms connected by covalent bonds. How many such molecules are possible in total and what is their structure? This question is of pressing interest in medicinal chemistry to help solve the problems of drug potency, selectivity, and toxicity and reduce attrition rates by pointing to new molecular series. To better define the unknown chemical space, we have enumerated 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens forming the chemical universe database GDB-17, covering a size range containing many drugs and typical for lead compounds. GDB-17 contains millions of isomers of known drugs, including analogs with high shape similarity to the parent drug. Compared to known molecules in PubChem, GDB-17 molecules are much richer in nonaromatic heterocycles, quaternary centers, and stereoisomers, densely populate the third dimension in shape space, and represent many more scaffold types.

We have developed a new primer design method based on the QuickChange site-directed mutagenesis protocol, which significantly improves the PCR amplification efficiency. This design method minimizes primer dimerization and ensures the priority of primer-template annealing over primer self-pairing during the PCR. Several different multiple mutations (up to 7 bases) were successfully performed with this partial overlapping primer design in a variety of vectors ranging from 4 to 12 kb in length. In comparison, all attempts failed when using complete-overlapping primer pairs as recommended in the standard QuickChange protocol. Our protocol was further extended to site-saturation mutagenesis by introducing randomized codons. Our data indicated no specific sequence selection during library construction, with the randomized positions resulting in average occurrence of each base in each position. This method should be useful to facilitate the preparation of high-quality site saturation libraries.

One of the simplest questions that can be asked about molecular diversity is how many organic molecules are possible in total? To answer this question, my research group has computationally enumerated all possible organic molecules up to a certain size to gain an unbiased insight into the entire chemical space. Our latest database, GDB-17, contains 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens, by far the largest small molecule database reported to date. Molecules allowed by valency rules but unstable or nonsynthesizable due to strained topologies or reactive functional groups were not considered, which reduced the enumeration by at least 10 orders of magnitude and was essential to arrive at a manageable database size. Despite these restrictions, GDB-17 is highly relevant with respect to known molecules. Beyond enumeration, understanding and exploiting GDBs (generated databases) led us to develop methods for virtual screening and visualization of very large databases in the form of a “periodic system of molecules” comprising six different fingerprint spaces, with web-browsers for nearest neighbor searches, and the MQN- and SMIfp-Mapplet application for exploring color-coded principal component maps of GDB and other large databases. Proof-of-concept applications of GDB for drug discovery were realized by combining virtual screening with chemical synthesis and activity testing for neurotransmitter receptor and transporter ligands. One surprising lesson from using GDB for drug analog searches is the incredible depth of chemical space, that is, the fact that millions of very close analogs of any molecule can be readily identified by nearest-neighbor searches in the MQN-space of the various GDBs. The chemical space project has opened an unprecedented door on chemical diversity. Ongoing and yet unmet challenges concern enumerating molecules beyond 17 atoms and synthesizing GDB molecules with innovative scaffolds and pharmacophores.

Multivalency plays a major role in biological processes and particularly in the relationship between pathogenic microorganisms and their host that involves protein–glycan recognition. These interactions occur during the first steps of infection, for specific recognition between host and bacteria, but also at different stages of the immune response. The search for high-affinity ligands for studying such interactions involves the combination of carbohydrate head groups with different scaffolds and linkers generating multivalent glycocompounds with controlled spatial and topology parameters. By interfering with pathogen adhesion, such glycocompounds including glycopolymers, glycoclusters, glycodendrimers and glyconanoparticles have the potential to improve or replace antibiotic treatments that are now subverted by resistance. Multivalent glycoconjugates have also been used for stimulating the innate and adaptive immune systems, for example with carbohydrate-based vaccines. Bacteria present on their surfaces natural multivalent glycoconjugates such as lipopolysaccharides and S-layers that can also be exploited or targeted in anti-infectious strategies.

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 s and perform a complete search in less than 1 min. Moreover, the development of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software with high maintainability. Finally, the software is well documented to make it suitable for beginners. The software is available at http://www.github.com/MolecularAI/aizynthfinder.