Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule.

As with many other institutions, our company maintains many quantitative structure-activity relationship (QSAR) models of absorption, distribution, metabolism, excretion, and toxicity (ADMET) end points and updates the models regularly. We recently examined version-to-version predictivity for these models over a period of 10 years. In this approach we monitor the goodness of prediction of new molecules relative to the training set of model version V before they are incorporated in the updated model V+1. Using a cell-based permeability assay (Papp) as an example, we illustrate how the QSAR models made from this data are generally predictive and can be utilized to enrich chemical designs and synthesis. Despite the obvious utility of these models, we turned up unexpected behavior in Papp and other ADMET activities for which the explanation is not obvious. One such behavior is that the apparent predictivity of the models as measured by root-mean-square-error can vary greatly from version to version and is sometimes very poor. One intuitively appealing explanation is that the observed activities of the new molecules fall outside the bulk of activities in the training set. Alternatively, one may think that the new molecules are exploring different regions of chemical space than the training set. However, the real explanation has to do with activity cliffs. If the observed activities of the new molecules are different than expected based on similar molecules in the training set, the predictions will be less accurate. This is true for all our ADMET end points.

Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?

Given a particular descriptor/method combination, some quantitative structure-activity relationship (QSAR) datasets are very predictive by random-split cross-validation while others are not. Recent literature in modelability suggests that the limiting issue for predictivity is in the data, not the QSAR methodology, and the limits are due to activity cliffs. Here, we investigate, on in-house data, the relative usefulness of experimental error, distribution of the activities, and activity cliff metrics in determining how predictive a dataset is likely to be. We include unmodified in-house datasets, datasets that should be perfectly predictive based only on the chemical structure, datasets where the distribution of activities is manipulated, and datasets that include a known amount of added noise. We find that activity cliff metrics determine predictivity better than the other metrics we investigated, whatever the type of dataset, consistent with the modelability literature. However, such metrics cannot distinguish real activity cliffs due to large uncertainties in the activities. We also show that a number of modern QSAR methods, and some alternative descriptors, are equally bad at predicting the activities of compounds on activity cliffs, consistent with the assumptions behind "modelability." Finally, we relate time-split predictivity with random-split predictivity and show that different coverages of chemical space are at least as important as uncertainty in activity and/or activity cliffs in limiting predictivity.

Discovery of novel Cobactin-T based matrix metalloproteinase inhibitors via a ring closing metathesis strategy.

The discovery of potent N-hydroxyl caprolactam matrix metalloproteinase (MMP) inhibitors (6) based on the natural product Cobactin-T (2) is described. The synthetic method, which utilizes the ring closing metathesis reaction, is compatible to provide complementary (R) and (S) enantiomers. These compounds tested against MMP-2 and 9, show that the R stereochemistry (i.e., 16), which is opposite for that found in the natural product Cobactin-T is >1000-fold more active with IC(50) values of 0.2-0.6nM against both enzymes. The variation in the incorporation of the sulfonamide enzyme recognition element (Ar(2)XAr(1)SO(2)N(R(1)), 6), along with alterations in the RCM/double bond chemistry (R(2)) provided a series of sub nanomolar MMP inhibitors. For example, compounds 16 and 34 were found to be the most potent with IC(50) values against MMP-2 and MMP-9 found to be between 0.2 and 0.6nM with 34 being the most potent compound discovered (MMP-2 IC(50)=0.39nM and MMP-9 IC(50)=0.22nM). Compounds 16 and 34 showed acceptable drug-like properties in vivo with compound 34 showing oral bioavailability.

beta-N-Biaryl ether sulfonamide hydroxamates as potent gelatinase inhibitors: part 1. Design, synthesis, and lead identification.

A new series of beta-N-biaryl ether sulfonamide hydroxamates as novel gelatinase inhibitors is described. These compounds exhibit good potency for MMP-2 and MMP-9 without inhibiting MMP-1. The structure-activity relationships (SAR) reveal the biaryl ether type P1' moiety together with methanesulfonamide is the optimal combination that provides inhibitory activity of MMP-9 in the single-digit nanomolar range.

beta-N-Biaryl ether sulfonamide hydroxamates as potent gelatinase inhibitors: part 2. Optimization of alpha-amino substituents.

The introduction and the optimization of an alpha-amino substituent based on a series of alpha-hydroxy-beta-N-biaryl ether sulfonamide hydroxamates is described. The modification leads to a new series of MMP-2/MMP-9 inhibitors with enhanced inhibitory activities and improved ADME properties. An efficacy study on reducing the ischemia-induced brain edema in the rat transient middle cerebral artery occlusion (tMCAo) model is also demonstrated.

7-[1H-Indol-2-yl]-2,3-dihydro-isoindol-1-ones as dual Aurora-A/VEGF-R2 kinase inhibitors: design, synthesis, and biological activity.

A novel series of 7-[1H-indol-2-yl]-2,3-dihydro-isoindol-1-ones designed to be inhibitors of VEGF-R2 kinase was synthesized and found to potently inhibit VEGF-R2 and Aurora-A kinases. The structure-based design, synthesis, and initial SAR of the series are discussed.

1-Hydroxy-2-pyridinone-based MMP inhibitors: synthesis and biological evaluation for the treatment of ischemic stroke.

Matrix metalloproteinase-9 (MMP-9) has been implicated in the breakdown of the blood-brain barrier during cerebral ischemia. As a result, inhibition of MMP-9 may have utility as a therapeutic intervention in stroke. Towards this end, we have synthesized a series of 1-hydroxy-2-pyridinones that have excellent in vitro potency in inhibiting MMP-9 in addition to MMP-2. Representative compounds also demonstrate good efficacy in the mouse transient mid-cerebral artery occlusion (tMCAO) model of cerebral ischemia.

A novel 5-[1,3,4-oxadiazol-2-yl]-N-aryl-4,6-pyrimidine diamine having dual EGFR/HER2 kinase activity: design, synthesis, and biological activity.

A novel 5-[1,3,4-oxadiazol-2-yl]-N-aryl-4,6-pyrimidine diamine was synthesized and found to have potent dual EGFR/HER2 kinase inhibitory activity. The structure-based drug design of this molecule as well as the kinase and cellular inhibition of HER2 kinase dependent cell lines will be discussed.

Practical approaches to efficient screening: information-rich screening protocol.

The past approach of high-throughput screening of everything in the corporate collection has been shown to be very expensive in terms of reagents cost, disposal cost, and compound collection depletion. It is well known that screening campaigns produce several hits, of which only 50% confirm on average. More efficient ways of screening can provide an informative structure-activity relationship (SAR), which in turn can be used to build mathematical models for further probing the activity space and directing chemical synthesis. The authors report new methods and insights to extract the maximum possible information from a screening experiment and find most of the possible hits in the corporate collection while screening as few compounds as possible.

Discovery of Potent and Orally Active p53-MDM2 Inhibitors RO5353 and RO2468 for Potential Clinical Development.

The development of small-molecule MDM2 inhibitors to restore dysfunctional p53 activities represents a novel approach for cancer treatment. In a previous communication, the efforts leading to the identification of a non-imidazoline MDM2 inhibitor, RG7388, was disclosed and revealed the desirable in vitro and in vivo pharmacological properties that this class of pyrrolidine-based inhibitors possesses. Given this richness and the critical need for a wide variety of chemical structures to ensure success in the clinic, research was expanded to evaluate additional derivatives. Here we report two new potent, selective, and orally active p53-MDM2 antagonists, RO5353 and RO2468, as follow-ups with promising potential for clinical development.

4-Aryl-5-cyano-2-aminopyrimidines as VEGF-R2 inhibitors: synthesis and biological evaluation.

A novel series of 4-aryl-5-cyano-2-aminopyrimidines were synthesized and found to have potent VEGF-R2 kinase inhibitory activity. Structure-activity relationships were investigated and compound 14a was shown to be efficacious in a mouse model of corneal neovascularization.

Synthesis and SAR of alpha-sulfonylcarboxylic acids as potent matrix metalloproteinase inhibitors.

A series of novel carboxylic acid-based alpha-sulfone MMP inhibitors have been synthesized and the in vitro enzyme SAR is discussed. A potential binding mode in the active site of the MMP-9 homology model was highlighted. These compounds are potent MMP-9 inhibitors and are selective over MMP-1.