Docking covalent fragments

Most drugs interact non-covalently with their target. The conventional wisdom was that covalent drugs – especially irreversible ones – would have dangerous side effects. Although this is still a concern, the success of drugs such as ibrutinib and dimethyl fumarate has caused a resurgence of interest. In a new paper in Nature Chemical Biology, Brian Shoichet, Jack Taunton, and colleagues at the University of California San Francisco describe how computational chemistry can be used to find new covalent inhibitors.

The researchers created a modified version of the program DOCK called – wait for it – DOCKovalent. Happily, they have made this available for free to anyone. To start, you upload your crystal structure and choose which amino acid residue you are interested in targeting. You can then pick from 9 different libraries of various electrophiles, each covering a different class of covalent “warhead”: epoxides, aldehydes, etc. There are about 650,000 molecules in total, roughly half of which easily qualify as fragments, with the rest being lead-like (still < 350 Da). Each molecule is either commercially available or readily synthesized in one or two steps.

The program then virtually links each molecule with the selected protein residue (typically cysteine or serine) and calculates scores based on predicted van der Waals and electrostatic interactions as well as desolvation. Multiple conformations of each ligand are sampled (with fragments there are not that many) as are different rotamers of the nucleophile. Users then manually inspect and test the top hits.

The researchers first benchmarked the program against four proteins with known covalent inhibitors, where it performed well. In the case of the bacterial protein AmpC β-lactamase (which we previously discussed here), the program retrospectively predicted the correct structure of 15 out of 23 known boronic acid ligands. In one case where the prediction differed from the reported co-crystal structure, the researchers re-determined the co-crystal structure at high resolution and found that DOCKovalent was actually correct.

Thus confident, the researchers docked 23,000 commercial boronic acids against AmpC and selected 6 on the basis of score and structural novelty. Of these, 5 had inhibition constants of 3.55 µM or better, with the best being 40 nM. A crystal structure of this compound bound to the protein led them to purchase 7 additional compounds, one of which had K_i = 10 nM and a ligand efficiency of 0.73 kcal/mol/atom. Most of the molecules were also selective against 4 other proteases and were able to reverse antibiotic resistance in AmpC-expressing bacteria.

Of course, by design all of these molecules have a boronic acid warhead; will any such molecule inhibit this enzyme? To find out, the researchers tested 5 low-scoring molecules and found that 4 of them showed, as hoped, less than 10% inhibition at 10 µM. However, a fifth molecule showed reasonable inhibition, with Ki = 3.2 µM. To understand this false-negative, the team solved the crystal structure of the molecule bound to AmpC. Interestingly, the molecule bound in a conformation different than had been predicted – one that also required conformational changes in the protein, which are not allowed in DOCKovalent.

The researchers took a similar approach to seek novel inhibitors of the kinases RSK2 and MSK1 using reversible cyanoacrylamide-containing molecules (previously highlighted here). Here too the researchers were able to identify selective nanomolar cell-active inhibitors.

This looks like a very nice approach. Of course, it does require a crystal structure (or at least a good model). Also, as mentioned above, the fact that the protein is kept rigid means the program will be unable to detect ligands that bind to cryptic pockets, so there is still plenty of opportunity for empirical surprises. Still, the fact that DOCKovalent is freely available will hopefully encourage people to give it a try on their favorite protein.