Drug Discovery


believed would be a more comprehensive chemical library to fit all of the biologies being studied at the centre, and with four simple rules: 1) The build has to be over time; 2) The overall size should not exceed 500,000 molecules; 3) Loose exclusion cri- teria/rules for molecules; and 4) Enrichment in non-Lipinski compliant compounds, ie natural products, is a must. Ten years later, my chemical library is beautiful, approaching 400,000 chemi- cals and with a good track record in identifying actives in screening campaigns7-18.


Surprisingly though, when Fox and colleagues sought opinions on the success of HTS from inter- viewing HTS lab heads back in 2001, only 12.5% felt chemical libraries were the problem and better ones were needed to be used for screening4, hard- ly a majority that one would have expected. However, Scannell and colleagues would argue that the chemical library content is a huge prob- lem considering the reality of the chemical space coverage of today’s libraries being infinitesimally small5. They further add that Pharma and biotech merger activities in the past few years have revealed substantial overlaps between their respec- tive chemical libraries5; not surprising considering that similar brains think alike, only a handful of commercial vendors to go to, and similar chemistries were applied. It also means that we are all screening similar compounds whether we are aware of it or not. If that is truly reflective of the dire state of the composition of chemical libraries and content, then how do we explain the source/origin of these 13,000 novel and unique compounds alluded to by Berggren6? How do you begin to judge whether a chemical library is good or bad? In my opinion, you cannot really judge a library; you can only describe its con- tent in terms of unique chemotypes, how big a clus- ter they represent, presence of nuisance chemistries or reactive groups, and if you are really desperate for a validation statement then by all means apply the Lipinski’s rules of five; segregating the library into categories of ‘compliance’. As an example, a recent publication by Baell addressing the coverage of lead-likes in commercial libraries using their in- house developed PAINS filters, reported that only 6,000 lead-like molecules in a vendor library of 400,000 chemicals19; that is a very high attrition rate of only 1 in 67 molecules is lead-like and per- haps worth screening. I would take a completely different approach and claim that each molecule in your library presents an opportunity, I do not know what it is yet and it does not really matter; the dis- covery is dependent on the biological question being asked, and the assay used for the screen is


Drug Discovery World Spring 2013


highly critical. Nowadays, there are fewer and fewer reports addressing or questioning assay suit- ability/validity for HTS. This is unfortunate consid- ering the overwhelming investment in screening from both the public and private sectors. We have also been led to believe that a single measure, known as the Z-factor20, is all you need to deter- mine whether the assay is good for HTS or not. With a Z-factor value of >0.5, your assay must be robust and ready for screening. This magic factor has industrialised the screening world and unfortu- nately, is the sole culprit of misguidance in assay development for HTS. The Z-factor is defined as a measure of ‘statistical effect size’, meaning that to be statistically relevant you need a larger data set to assess the separation of your assay signal to its noise or background. What the Z-factor does not tell us is: 1) The relevance of your assay signal to the question you are trying to study since we are fully vested in sensitivities, miniaturisations and ultra-HTS; 2) Assay dynamics and sensitivity to specific and non-specific modulators; and 3) Heterogeneity of the biology being studied. In essence, it is an abused measure and sometimes irrelevant such is the case for high content cell- based assays18; but we must have it to get approvals to carry out our screens, to get our man- uscripts published as reviewers will more than often ask for it, and to get our grant proposals funded as it is part of the funding requirement. Many of us do forget that screening these libraries represent the largest live casino you will ever play in, whether you are a blackjack, poker, roulette or slot-machine player, the odds are always in favour of the house; unless of course you cheat or get lucky. So, today’s chemical libraries are indeed one size fits all and as far as I am concerned nothing is wrong with them; they are also the only available and accessible tools to use and should be used across a multitude of biologies and screens with the hope of getting lucky one day. Baell’s com- ment on the sheer level of artifacts being generated by screening these libraries is duly noted19, but biology without noise is not worth studying. I would also argue that these reported pan-active hit(s) from screening these libraries are the best metrics of suitability/validity of your assay in the first place.


Chemical space exploration


Curiosity is one of the many traits of human beings leading us to always wanting to explore and better understand our world. In very ancient times, our ancestors used to observe objects in the skies lead- ing them to make predictions of their motions only


References 1 Lahana, R. How many leads from HTS? Drug Discov Today 4, 447-448 (1999). 2 Ramesha, CS. How many leads from HTS? – Comment. Drug Discov Today 5, 43-44 (2000). 3 Fox, S et al. High throughput screening: early successes indicate a promising future. J Biomol Screen 6, 137-140 (2001). 4 Fox, S et al. High throughput screening 2002: moving toward increased success rates. J Biomol Screen 7, 313-316 (2002). 5 Scannell, JW et al. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov 11, 191-200 (2012). 6 Berggren, R et al. Nat Rev Drug Discov 11, 435-436 (2012). 7 Antczak, C et al. High- throughput Identification of Inhibitors of the Cancer Target Human Mitochondrial Peptide Deformylase. J Biomol Screen 12, 521-535 (2007). 8 Deng, L et al. Identification of novel antipoxviral agents: Mitoxanthrone inhibits Vaccinia virus replication by blocking virion assembly. J Virol 81, 13392-402 (2007). 9 Desbordes, SC et al. High- Throughput Screening Assay for The Identification of


Compounds Regulating Human Embryonic Stem Cells Self- Renewal and Differentiation. Cell Stem Cell 2, 602-12 (2008). 10 Antczak, C et al. Revisiting Old Drugs as Novel Agents for Retinoblastoma: In vitro and In vivo Antitumor Activity of Cardenolides. Invest Ophthalm Visual Science 50, 3065-3073 (2009). 11 Somwar, R et al. Identification and preliminary characterization of novel small molecules that inhibit growth of human lung adenocarcinoma cells. J Biomol Screen 14, 1176-1184 (2009). 12 Shelton, CC et al. Modulation of -secretase specificity using small molecule allosteric inhibitors. PNAS (USA) 106, 20228-33 (2009).


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