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“Just take the ball and throw it where you want to. Throw strikes. Home plate don’t move.”
Satchel Paige (1906-1982)
The COVID Moonshot and OSC19 are examples of what are sometimes called crowdsourced or open source approaches to drug discovery. While I’m not particularly keen on the use of the term ‘open source’ in this context, I have absolutely no quibble with the goal of seeking cures and treatments for diseases that are ignored by commercial drug discovery organizations. Open source drug discovery originated with OSDD in India and it should be noted that the approach has also been pioneered for malaria by OSM. I see crowdsourcing primarily as a different way to organize and resource drug discovery rather than as a radically different way to do drug discovery.
One point that’s not always appreciated by cheminformaticians, computational chemists and drug discovery scientists in academia is that there’s a bit more to drug discovery than making predictions. In particular, I advise those seeking to transform drug discovery to ensure that they actually know what a drug needs to do and understand the constraints under which drug discovery scientists work. Currently, it does not appear to be possible to predict the effects of compounds in live humans from molecular structure with the accuracy needed for prediction-driven design and this is the primary reason that drug discovery is incremental in nature. A big part of drug discovery is generation of the information needed in order to maintain progress and there are gains to be had by doing this as efficiently as possible. Efficient generation of information, in turn, requires a degree of coordination that may prove difficult to achieve in a crowdsourced project.
The SARS-CoV-2 main protease (Mpro) is one of a number of potential targets of interest in the search for COVID-19 therapies. Like the cathepsins that are (or, at least, have been) of interest to the pharma/biotech industry as potential targets for therapeutic intervention, Mpro is a cysteine protease. If I’d been charged with quickly delivering an inhibitor of Mpro as a candidate drug then I’d be taking a very close look at how the pharma/biotech industry has pursued cysteine protease targets. Balacatib, odanacatib (cathepsin K inhibitors) and petesicatib (cathepsin S inhibitor) can each be described as a peptidomimetic with a warhead (nitrile) that forms a covalent bond reversibly with the catalytic cysteine.
A number of peptidomimetic Mpro inhibitors have been described in the literature and this blog post by Chris Southan may be of interest. I’ve been looking at the published inhibitors shown below in Chart 1 (which exhibit antiviral activity and have been subjected to pharmacokinetic and toxicological evaluation) and have written some notes on mapping the structure-activity relationship for compounds like these. I should stress that compounds discussed in these notes are not expected to be dramatically more potent than the two shown in Chart 1 (in fact, I expect at least one to be significantly less potent). Nevertheless, I would argue that assay results for these proposed synthetic targets would inform design.
My assessment of these compounds is that there is significant room for improvement and I think that it would be relatively easy to achieve a pIC50 of 8 (corresponding to an IC50 of 10 nM) using the aldehyde warhead. I’d consider taking an aldehyde forward (there are options for dosing as a prodrug) although it really would be much better if there was also the option to exchange this warhead for the nitrile (a warhead that is much-loved by industrial medicinal chemists since it’s rugged, polar and contributes minimally to molecular size). While I’d anticipate that replacement of aldehyde with nitrile will lead to a reduction in potency, it’s necessary to quantify the potency loss to enable the potential of nitriles to be properly assessed. The binding mode observed for 1 is shown below in Figure 1 and it’s likely that the groove region will need to be more fully exploited (this article will give you an idea of the sort of thing I have in mind) in order to achieve acceptable potency if the aldehyde warhead is replaced by nitrile.
The COVID Moonshot project currently appears to be in what many industrial drug discovery scientists would call the hit-to-lead phase. In my view the principal objective of hit-to-lead work is to create options since having options will give the lead optimization team room to manoeuvre (you can think of hit-to-lead work as being a bit like playing in midfield). The COVID Moonshot project is currently focused on exploitation of hits from a fragment screen against MPro and, while I’d question whether this approach is likely to get to a candidate drug more quickly than the conventional structure-based design used in industry to pursue cathepsins, it’s certainly an interesting project that I’m happy to contribute to. It’s also worth mentioning that fragment screens have been run against SARS-CoV-2 Nsp3 macrodomain at UCSF and Diamond since there are no known inhibitors for this target.
Here’s a blog post by Pat Walters in which he examines the structure-activity relationships emerging for the fragment-derived inhibitors. Specifically, he uses a metric known as the Structure-Activity Landscape Index (SALI) to quantify the sensitivity of activity to structural changes. Medicinal chemists apply the term ‘activity cliff’ to situations where a small change in structure results in a large change in activity and I’ve argued that the idea of quantifying the sensitivity of a physicochemical effect to structural modifications goes all the way back to Hammett. One point that comes out of Pat’s post is that it’s difficult to establish structure-activity relationships for low affinity ligands with a conventional biochemical assay. When applying fragment-based approaches in lead discovery, there are distinct advantages to being able to measure low binding affinity (~ 1 mM) since this allows fragment-based structure-activity relationships to be explored prior to synthetic elaboration of fragment hits. As Pat notes, inadequate solubility in assay buffer clearly places limits on the affinity that can be reliably measured in any assay although interference with the readout of a biochemical assay can also lead to misleading results. This is one reason that biophysical detection of binding using methods such as surface plasmon resonance (SPR) are favored in fragment-based lead discovery. Here’s an article by some of my former colleagues which shows how you can assess the impact of interference with the readout of a biochemical assay (and even correct for it if the effect isn’t too great).
My first contribution to the COVID Moonshot project is illustrated in Chart 2 and the fragment-derived inhibitor 3 from which I started is also featured in Pat’s post. From inspection of the crystal structure, I noticed that the catalytic cysteine might be targeted by linking a ‘reversible’ warhead from the amide nitrogen (4 and 5). Although this might look fine on paper, the experimental data in this article suggest that linking any saturated carbon to the amide nitrogen will bias the preferred amide geometry away from trans to cis. Provided that the intrinsic gain in affinity resulting from linking the warhead is greater than the cost of adopting the bound conformation, the structural modification will lead to a net increase in affinity and the structures could be locked (here's an article that shows how this can work) into the bound conformation (e.g. by forming a ring).
In addition to being accessible to a warhead linked from the amide nitrogen of 3, the catalytic cysteine is also within striking distance of the carbonyl carbon and it would be prudent to consider the possibility that 3 and its analogs can function as substrates for Mpro. There is precedent for this type of behavior and I’ll point you toward an article that notes that a series of esters identified as cruzain inhibitors can function as substrates and more recent article that presents cruzain inhibitors that I’d consider to be potential substrates. A crystal structure of the protein-ligand complex is potentially misleading in this context since the enzyme might not be catalytically active. I believe that 6 could be used to explore this possibility since the carbonyl carbon would be expected to be more electrophilic and 3-hydroxy, 4-methylpyridine would be expected to be a better leaving group than its 3-amino analog.
This is a good point to wrap things up. I think that Satchel Paige gave us some pretty good advice on how to approach drug discovery and that's yet another reason that Black Lives Matter.