Rapid and efficient delivery of radioactive metal complexes to the cell interior would enable novel applications in medical imaging and radiotherapy. Membrane permeant peptide conjugates incorporating HIV-1 Tat transactivation protein sequences (GRKKRRQRRR) and an appropriate peptide-based motif (epsilon-KGC) that provides an N(3)S donor core for chelating technetium and rhenium were synthesized. Oxotechnetium(V) and oxorhenium(V) Tat-peptide complexes were prepared by facile transchelation reactions with permetalates, tin(II) chloride and sodium glucoheptonate. RP-HPLC showed two major [(99m)Tc]Tat-peptide species (4) that differed in retention time by approximately 2 min corresponding to two [Re]Tat-peptide species (7) shown to have identical mass, consistent with formation of two isomers, likely the oxo-metal diastereomers. [(99m)Tc]Tat-peptides were stable to transchelation in vitro. In human Jurkat cells, [(99m)Tc]Tat-peptide 4 showed concentrative cell accumulation (30-fold greater than extracellular concentration) and rapid uptake kinetics (t(1/2) < 2 min) in a diastereomeric-comparable manner. Paradoxically, uptake was enhanced in 4 degrees C buffer compared to 37 degrees C, while depolarization of membrane potential as well as inhibition of microtubule function and vesicular trafficking showed no inhibitory effect. Cells preloaded with 4 showed rapid washout kinetics into peptide-free solution. Modification of [(99m)Tc]Tat-peptide by deletion of the N-terminus Gly with or without biotinylation minimally impacted net cell uptake. In addition, the C-terminus thiol of the prototypic Tat-peptide was labeled with fluorescein-5-maleimide to yield conjugate 8. Fluorescence microscopy directly localized conjugate 8 to the cytosol and nuclei (possibly nucleolus) of human Jurkat, KB 3-1 and KB 8-5 tumor cells. Preliminary imaging studies in mice following intravenous administration of prototypic [(99m)Tc]Tat-peptide 4 showed an initial whole body distribution and rapid clearance by both renal and hepatobiliary excretion. Analysis of murine blood in vivo and human serum ex vivo revealed >95% intact complex, while murine urine in vivo showed 65% parent complex. Thus, these novel Tat-peptide chelate conjugates, capable of forming stable [Tc/Re(V)]complexes, rapidly translocate across cell membranes into intracellular compartments and can be readily derivatized for further targeted applications in molecular imaging and radiotherapy.

While conventional random forest regression (RFR) virtual screening models appear to have excellent accuracy on random held-out test sets, they prove lacking in actual practice. Analysis of 18 historical virtual screens showed that random test sets are far more similar to their training sets than are the compounds project teams actually order. A new, cluster-based "realistic" training/test set split, which mirrors the chemical novelty of real-life virtual screens, recapitulates the poor predictive power of RFR models in real projects. The original Profile-QSAR (pQSAR) method greatly broadened the domain of applicability over conventional models by using as independent variables a profile of activity predictions from all historical assays in a large protein family. However, the accuracy still fell short of experiment on realistic test sets. The improved "pQSAR 2.0" method replaces probabilities of activity from naïve Bayes categorical models at several thresholds with predicted ICs from RFR models. Unexpectedly, the high accuracy also requires removing the RFR model for the actual assay of interest from the independent variable profile. With these improvements, pQSAR 2.0 activity predictions are now statistically comparable to medium-throughput four-concentration IC measurements even on the realistic test set. Beyond the yes/no activity predictions from a typical high-throughput screen (HTS) or conventional virtual screen, these semiquantitative IC predictions allow for predicted potency, ligand efficiency, lipophilic efficiency, and selectivity against antitargets, greatly facilitating hitlist triaging and enabling virtual screening panels such as toxicity panels and overall promiscuity predictions.

Profile-QSAR (pQSAR) is a massively multi-task, 2-step machine learning method with unprecedented scope, accuracy and applicability domain. In step one, a "profile" of conventional single-assay random forest regression (RFR) models are trained on a very large number of biochemical and cellular pIC50 assays using Morgan 2 sub-structural fingerprints as compound descriptors. In step two, a panel of PLS models are built using the profile of pIC50 predictions from those RFR models as compound descriptors. Hence the name. Previously described for a panel of 728 biochemical and cellular kinase assays, we have now built an enormous pQSAR from 11,805 diverse Novartis IC50 and EC50 assays. This large number of assays, and hence of compound descriptors for PLS, dictated reducing the profile by only including RFR models whose predictions correlate with the assay being modeled. The RFR and pQSAR models were evaluated with our "realistically novel" held-out test set whose median average similarity to the nearest training set member across the 11,805 assays was only 0.34, thus testing a realistically large applicability domain. For the 11,805 single-assay RFR models, the median correlation of prediction with experiment was only R 2 ext=0.05, virtually random, and only 8% of the models achieved our standard success threshold of R 2 ext=0.30. For pQSAR, the median correlation was R 2 ext=0.53, comparable to 4-concentration experimental IC50s, and 72% of the models met our R 2 ext>0.30 standard, totaling 8558 successful models. The successful models included assays from all of the 51 annotated target sub-classes, as well as 4196 phenotypic assays, indicating that pQSAR can be applied to virtually any disease area. Every month, all models are updated to include new measurements, and predictions are made for 5.5 million Novartis compounds, totaling 50 billion predictions. Common uses have included virtual screening, selectivity design, toxicity and promiscuity prediction, mechanism-of-action prediction, and others.

CLK2 inhibition has been proposed as a potential mechanism to improve autism and neuronal functions in Phelan-McDermid syndrome (PMDS). Herein, the discovery of a very potent indazole CLK inhibitor series and the CLK2 X-ray structure of the most potent analogue are reported. This new indazole series was identified through a biochemical CLK2 Caliper assay screen with 30k compounds selected by an in silico approach. Novel high-resolution X-ray structures of all CLKs, including the first CLK4 X-ray structure, bound to known CLK2 inhibitor tool compounds (e.g., TG003, CX-4945), are also shown and yield insight into inhibitor selectivity in the CLK family. The efficacy of the new CLK2 inhibitors from the indazole series was demonstrated in the mouse brain slice assay, and potential safety concerns were investigated. Genotoxicity findings in the human lymphocyte micronucleus test (MNT) assay are shown by using two structurally different CLK inhibitors to reveal a major concern for pan-CLK inhibition in PMDS.

The discovery and development of new antibiotics capable of curing infections due to multidrug-resistant and pandrug-resistant Gram-negative bacteria are a major challenge with fundamental importance to our global healthcare system. Part of our broad program at Novartis to address this urgent, unmet need includes the search for new agents that inhibit novel bacterial targets. Here we report the discovery and hit-to-lead optimization of new inhibitors of phosphopantetheine adenylyltransferase (PPAT) from Gram-negative bacteria. Utilizing a fragment-based screening approach, we discovered a number of unique scaffolds capable of interacting with the pantetheine site of E. coli PPAT and inhibiting enzymatic activity, including triazolopyrimidinone 6. Structure-based optimization resulted in the identification of two lead compounds as selective, small molecule inhibitors of bacterial PPAT: triazolopyrimidinone 53 and azabenzimidazole 54 efficiently inhibited E. coli and P. aeruginosa PPAT and displayed modest cellular potency against the efflux-deficient E. coli Δ tolC mutant strain.

RAS oncogenes have been implicated in >30% of human cancers, all representing high unmet medical need. The exquisite dependency on CRAF kinase in KRAS mutant tumors has been established in genetically engineered mouse models and human tumor cells. To date, many small molecule approaches are under investigation to target CRAF, yet kinase-selective and cellular potent inhibitors remain challenging to identify. Herein, we describe 14 (RAF709) [ Aversa , Biaryl amide compounds as kinase inhibitors and their preparation . WO 2014151616, 2014 ], a selective B/C RAF inhibitor, which was developed through a hypothesis-driven approach focusing on drug-like properties. A key challenge encountered in the medicinal chemistry campaign was maintaining a balance between good solubility and potent cellular activity (suppression of pMEK and proliferation) in KRAS mutant tumor cell lines. We investigated the small molecule crystal structure of lead molecule 7 and hypothesized that disruption of the crystal packing would improve solubility, which led to a change from N-methylpyridone to a tetrahydropyranyl oxy-pyridine derivative. 14 proved to be soluble, kinase selective, and efficacious in a KRAS mutant xenograft model.

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Communication of data and ideas within a medicinal chemistry project on a global as well as local level is a crucial aspect in the drug design cycle. Over a time frame of eight years, we built and optimized FOCUS, a platform to produce, visualize, and share information on various aspects of a drug discovery project such as cheminformatics, data analysis, structural information, and design. FOCUS is tightly integrated with internal services that involve-among others-data retrieval systems and in-silico models and provides easy access to automated modeling procedures such as pharmacophore searches, R-group analysis, and similarity searches. In addition, an interactive 3D editor was developed to assist users in the generation and docking of close analogues of a known lead. In this paper, we will specifically concentrate on issues we faced during development, deployment, and maintenance of the software and how we continually adapted the software in order to improve usability. We will provide usage examples to highlight the functionality as well as limitations of FOCUS at the various stages of the development process. We aim to make the discussion as independent of the software platform as possible, so that our experiences can be of more general value to the drug discovery community.