A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.

The perceived and actual burden of false positives in high-throughput screening has received considerable attention; however, few studies exist on the contributions of distinct mechanisms of non-specific effects like chemical reactivity, assay signal interference, and colloidal aggregation. Here, we analyze the outcome of a screen of 197,861 diverse compounds in a concentration-response format against the cysteine protease cruzain, a target expected to be particularly sensitive to reactive compounds and using an assay format with light detection in the short-wavelength region where significant compound autofluorescence is typically encountered. Approximately 1.9% of all compounds screened were detergent-sensitive inhibitors. The contribution from autofluorescence and compounds bearing reactive functionalities was dramatically lower: of all hits, only 1.8% were autofluorescent and 1.48% contained reactive or undesired functional groups. The distribution of false positives was relatively constant across library sources. The simple step of including detergent in the assay buffer suppressed the nonspecific effect of approximately 93% of the original hits.

Virtual and high-throughput screens (HTS) should have complementary strengths and weaknesses, but studies that prospectively and comprehensively compare them are rare. We undertook a parallel docking and HTS screen of 197861 compounds against cruzain, a thiol protease target for Chagas disease, looking for reversible, competitive inhibitors. On workup, 99% of the hits were eliminated as false positives, yielding 146 well-behaved, competitive ligands. These fell into five chemotypes: two were prioritized by scoring among the top 0.1% of the docking-ranked library, two were prioritized by behavior in the HTS and by clustering, and one chemotype was prioritized by both approaches. Determination of an inhibitor/cruzain crystal structure and comparison of the high-scoring docking hits to experiment illuminated the origins of docking false-negatives and false-positives. Prioritizing molecules that are both predicted by docking and are HTS-active yields well-behaved molecules, relatively unobscured by the false-positives to which both techniques are individually prone.

This review will focus on two general approaches carried out at the Sandler Center, University of California, San Francisco, to address the challenge of developing new drugs for the treatment of Chagas disease. The first approach is target-based drug discovery, and two specific targets, cytochrome P450 CYP51 and cruzain (aka cruzipain), are discussed. A “proof of concept” molecule, the vinyl sulfone inhibitor K777, is now a clinical candidate. The preclinical assessment compliance for filing as an Investigational New Drug with the United States Food and Drug Administration (FDA) is presented, and an outline of potential clinical trials is given. The second approach to identifying new drug leads is parasite phenotypic screens in culture. The development of an assay allowing high throughput screening of Trypanosoma cruzi amastigotes in skeletal muscle cells is presented. This screen has the advantage of not requiring specific strains of parasites, so it could be used with field isolates, drug resistant strains or laboratory strains. It is optimized for robotic liquid handling and has been validated through a screen of a library of FDA-approved drugs identifying 65 hits.

Computer-based docking screens are now widely used to discover new ligands for targets of known structure; in the last two years alone, the discovery of ligands for over 20 proteins have been reported. Recently, investigators have also turned to predicting new substrates and for enzymes of unknown function, taking docking in a wholly new direction. Increasingly, the hit-rates, the true-and the falsepositives from the docking screens are being compared to those from empirical, high-throughput screens, revealing the strengths, weaknesses and complementarities of both techniques. The recent efflorescence of GPCR structures has made these quintessential drug targets available to structurebased approaches. Consistent with their "druggability", the docking screens have returned high hitrates and potent molecules. Finally, in the last several years, an approach almost exactly opposite to docking has also appeared; this pharmacological network approach begins not with the structure of the target but rather those of drug molecules and asks, given a pattern of chemistry in the ligands, what targets may a particular drug bind to? This method, which returns to an older, pharmacology logic, has been surprisingly successful in predicting new "off-targets" for established drugs.Since the work of Goodford in the mid-1970's [1], protein structures have held the promise of guiding the design of drugs. As is often true, the early potential of the field was largely unmet, and in the early 1990s there was a sense that "structure-based drug design" was not pragmatic. In the last decade, however, the use of structure-based computational design has made steady, if often unspectacular [2] technical progress, to the point where most pharmaceutical organizations have substantial groups devoted to its application. If one asks, "How many drugs have been discovered entirely by structure-based methods?", the answer will be "none", as these methods largely contribute only to the discovery and early optimization of leads for drug design. If one asks, conversely, "To the development of how many drugs have structure-based methods been critical?" then the answer will be close to ten. Whereas this number must seem small, it is put into perspective by the number of drugs that owe their origin to empirical high throughput screening (as of this writing, only two or three [3], though many more are now in trials or awaiting approval).Perhaps the area where structure-based methods have had the most quantifiable impact is in computational screens for of large compound libraries, looking for new chemical matter that will bind to and modulate a protein of known structure. These "virtual" or "structure-based" screens typically use molecular docking programs to fit small organic molecules into protein structures, evaluating them for structural and chemical complementarity. Several million

Fragment screens for new ligands have had wide success, notwithstanding their constraint to libraries of 1,000 -10,000 molecules. Larger libraries would be addressable were molecular docking reliable for fragment screens, but this has not been widely accepted. To investigate docking's ability to prioritize fragments, a library of >137,000 such molecules were docked against the structure of ␤-lactamase. Forty-eight fragments highly ranked by docking were acquired and tested; 23 had Ki values ranging from 0.7 to 9.2 mM. X-ray crystal structures of the enzyme-bound complexes were determined for 8 of the fragments. For 4, the correspondence between the predicted and experimental structures was high (RMSD between 1.2 and 1.4 Å), whereas for another 2, the fidelity was lower but retained most key interactions (RMSD 2.4 -2.6 Å). Two of the 8 fragments adopted very different poses in the active site owing to enzyme conformational changes. The 48% hit rate of the fragment docking compares very favorably with ''lead-like'' docking and high-throughput screening against the same enzyme. To understand this, we investigated the occurrence of the fragment scaffolds among larger, lead-like molecules. Approximately 1% of commercially available fragments contain these inhibitors whereas only 10 ؊7 % of lead-like molecules do. This suggests that many more chemotypes and combinations of chemotypes are present among fragments than are available among lead-like molecules, contributing to the higher hit rates. The ability of docking to prioritize these fragments suggests that the technique can be used to exploit the better chemotype coverage that exists at the fragment level.crystallography ͉ drug design ͉ hit rates ͉ chemical space

Trypanosoma cruzi and Trypanosoma brucei are parasites that cause Chagas' disease and African sleeping sickness, respectively. Both parasites rely on essential cysteine proteases for survival, cruzain for T. cruzi and TbCatB/rhodesain for T. brucei. A recent quantitative high-throughput screen of cruzain identified triazine nitriles, which are known inhibitors of other cysteine proteases, as reversible inhibitors of the enzyme. Structural modifications detailed herein, including core scaffold modification from triazine to purine, improved the in vitro potency against both cruzain and rhodesain by 350-fold, while also gaining activity against T. brucei parasites. Selected compounds were screened against a panel of human cysteine and serine proteases to determine selectivity, and a cocrystal was obtained of our most potent analog bound to Cruzain.

The development of cruzain inhibitors has been driven by the urgent need to develop novel and more effective drugs for the treatment of Chagas' disease. Herein, we report the lead optimization of a class of noncovalent cruzain inhibitors, starting from an inhibitor previously cocrystallized with the enzyme (K i = 0.8 μM). With the goal of achieving a better understanding of the structure−activity relationships, we have synthesized and evaluated a series of over 40 analogues, leading to the development of a very promising competitive inhibitor (8r, IC 50 = 200 nM, K i = 82 nM). Investigation of the in vitro trypanocidal activity and preliminary cytotoxicity revealed the potential of the most potent cruzain inhibitors in guiding further medicinal chemistry efforts to develop drug candidates for Chagas' disease.