Amyloid binding and beyond: a new approach for Alzheimer's disease drug discovery targeting Aßo-PrPC binding and downstream pathways.

Amyloid ß oligomers (Aßo) are the main toxic species in Alzheimer's disease, which have been targeted for single drug treatment with very little success. In this work we report a new approach for identifying functional Aßo binding compounds. A tailored library of 971 fluorine containing compounds was selected by a computational method, developed to generate molecular diversity. These compounds were screened for Aßo binding by a combined 19F and STD NMR technique. Six hits were evaluated in three parallel biochemical and functional assays. Two compounds disrupted Aßo binding to its receptor PrPC in HEK293 cells. They reduced the pFyn levels triggered by Aßo treatment in neuroprogenitor cells derived from human induced pluripotent stem cells (hiPSC). Inhibitory effects on pTau production in cortical neurons derived from hiPSC were also observed. These drug-like compounds connect three of the pillars in Alzheimer's disease pathology, i.e. prion, Aß and Tau, affecting three different pathways through specific binding to Aßo and are, indeed, promising candidates for further development.

Building Admiral, an Automated Molecular Dynamics and Analysis Platform.

We present Admiral (Automated Docking and Molecular dynamics InfoRmatics and AnaLysis), a platform which automates the process of running molecular docking and molecular dynamics on compound designs for medicinal chemistry project teams. In addition to running the simulations, Admiral analyzes the simulation and automatically generates a PowerPoint slide, with the goal of having all the information required to decide whether to synthesize the compound in one place. This information includes results and analyses from the MD simulation, predicted ADME and physical-chemical properties, information on similar compounds in the SAR, and an animated GIF of the simulation. This report is then emailed to the compound designer, generally within the same day. Within Eli Lilly and Co., we have developed and deployed Admiral on an internal discovery project where it has been heavily used by the project team. Several additional discovery projects have adopted the platfom in recent months.

Side chain virtual screening of matched molecular pairs: a PDB-wide and ChEMBL-wide analysis.

Optimization in medicinal chemistry often involves designing replacements for a section of a molecule which aim to retain potency while improving other properties of the compound. In this study, we perform a retrospective analysis using a number of computational methods to identify active side chains amongst a pool of random decoy side chains, mimicking a similar procedure that might be undertaken in a real medicinal chemistry project. We constructed a dataset derived from public ChEMBL and PDB data by identifying all ChEMBL assays where at least one of the compounds tested has also been co-crystallized in the PDB. Additionally, we required that there be at least ten active compounds tested in the same ChEMBL assay that are matched molecular pairs to the crystallized ligand. Using the compiled dataset consisting of sets of compounds from 402 assays, we have tested a number of methods for scoring side chains including Spark, a bioisostere replacement tool from Cresset, molecular docking using Glide from Schrodinger, docking with Smina, as well as other methods. In this work, we present a comparison of the performance of these methods in discriminating active side chains from decoys as well as recommendations for circumstances when different methods should be used.

Creating a Virtual Assistant for Medicinal Chemistry.

The virtual assistant concept is one that many technology companies have taken on despite having other well-developed and popular user interfaces. We wondered whether it would be possible to create an effective virtual assistant for a medicinal chemistry organization, the key being delivering the information the user would want to see, directly to them, at the right time. We introduce Kernel, an early prototype virtual assistant created at Lilly, and a number of examples of the scenarios that have been implemented to try to demonstrate the concept. A biochemical assay summary email is described that brings together new results and some basic analysis, delivered within an hour of new data appearing for that assay, and an email delivering new compound design ideas directly to the original submitter of a compound shortly after their compound was tested for the first time. We conclude with a high level description of the first example of a Design-Make-Test-Analyze cycle completed in the absence of any human intellectual input at Lilly. We believe that this concept has much potential in changing the way that computational results and analysis are delivered and consumed within a medicinal chemistry group, and we hope to inspire others to implement their own similar solutions.

Case series: Pyramidal cataracts, intact irides and nystagmus from three novel PAX6 mutations.

PURPOSE: To investigate the association between novel PAX6 mutations to bilateral anterior pyramidal congenital cataracts (APyC), complete and intact irides, and nystagmus. OBSERVATIONS: This is a retrospective observational case series in a multi-center setting with genetic testing. Three female patients were diagnosed with bilateral APyC, intact irides and nystagmus. Genetic testing identified the three patients had novel missense mutations in PAX6 - c.128C > T; p.Ser43Phe (S43F), c. 197T > A; p.Ile66Asn (I66N) and c.781C > G; p.Arg261Gly (R261G). CONCLUSIONS AND IMPORTANCE: This study demonstrates a novel phenotype of bilateral APyC, intact irides, and nystagmus in whom genetic testing for PAX6 identified novel missense mutations (S43F, I66N, R261G) in highly conserved DNA-binding domains. Implications of understanding why the iris is present in these cases is discussed.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2.

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge.

Induced fit or protein flexibility can make a given structure less useful for docking and/or scoring. The 2015 Drug Design Data Resource (D3R) Grand Challenge provided a unique opportunity to prospectively test optimal strategies for virtual screening in these type of targets: heat shock protein 90 (HSP90), a protein with multiple ligand-induced binding modes; and mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4), a kinase with a large flexible pocket. Using previously known co-crystal structures, we tested predictions from methods that keep the receptor structure fixed and used (a) multiple receptor/ligand co-crystals as binding templates for minimization or docking ("close"), (b) methods that align or dock to a single receptor ("cross"), and (c) a hybrid approach that chose from multiple bound ligands as initial templates for minimization to a single receptor ("min-cross"). Pose prediction using our "close" models resulted in average ligand RMSDs of 0.32 and 1.6 Å for HSP90 and MAP4K4, respectively, the most accurate models of the community-wide challenge. On the other hand, affinity ranking using our "cross" methods performed well overall despite the fact that a fixed receptor cannot model ligand-induced structural changes,. In addition, "close" methods that leverage the co-crystals of the different binding modes of HSP90 also predicted the best affinity ranking. Our studies suggest that analysis of changes on the receptor structure upon ligand binding can help select an optimal virtual screening strategy.

Peroxidase activation of cytoglobin by anionic phospholipids: Mechanisms and consequences.

Cytoglobin (Cygb) is a hexa-coordinated hemoprotein with yet to be defined physiological functions. The iron coordination and spin state of the Cygb heme group are sensitive to oxidation of two cysteine residues (Cys38/Cys83) and/or the binding of free fatty acids. However, the roles of redox vs lipid regulators of Cygb's structural rearrangements in the context of the protein peroxidase competence are not known. Searching for physiologically relevant lipid regulators of Cygb, here we report that anionic phospholipids, particularly phosphatidylinositolphosphates, affect structural organization of the protein and modulate its iron state and peroxidase activity both conjointly and/or independently of cysteine oxidation. Thus, different anionic lipids can operate in cysteine-dependent and cysteine-independent ways as inducers of the peroxidase activity. We establish that Cygb's peroxidase activity can be utilized for the catalysis of peroxidation of anionic phospholipids (including phosphatidylinositolphosphates) yielding mono-oxygenated molecular species. Combined with the computational simulations we propose a bipartite lipid binding model that rationalizes the modes of interactions with phospholipids, the effects on structural re-arrangements and the peroxidase activity of the hemoprotein.

Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment.

The 2013/2014 Community Structure-Activity Resource (CSAR) challenge was designed to prospectively validate advancement in the field of docking and scoring receptor-small molecule interactions. Purely computational methods have been found to be quite limiting. Thus, the challenges assessed methods that combined both experimental data and computational approaches. Here, we describe our contribution to solve three important challenges in rational drug discovery: rank-ordering protein primary sequences based on affinity to a compound, determining close-to-native bound conformations out of a set of decoy poses, and rank-ordering sets of congeneric compounds based on affinity to a given protein. We showed that the most significant contribution to a meaningful enrichment of native-like models was the identification of the best receptor structure for docking and scoring. Depending on the target, the optimal receptor for cross-docking and scoring was identified by a self-consistent docking approach that used the Vina scoring function, by aligning compounds to the closest cocrystal or by selecting the cocrystal receptor with the largest pocket. For tRNA (m1G37) methyltransferase (TRMD), ranking a set of 31 congeneric binding compounds cross-docked to the optimal receptor resulted in a R(2) = 0.67; whereas, using any other of the 13 receptor structures led to almost no enrichment of native-like complex structures. Furthermore, although redocking predicted lower RMSDs relative to the bound structures, the ranking based on multiple receptor structures did not improve the correlation coefficient. Our predictions highlight the role of rational structure-based modeling in maximizing the outcome of virtual screening, as well as limitations scoring multiple receptors.

A Discovery Strategy for Selective Inhibitors of c-Src in Complex with the Focal Adhesion Kinase SH3/SH2-binding Region.

The c-Src tyrosine kinase co-operates with the focal adhesion kinase to regulate cell adhesion and motility. Focal adhesion kinase engages the regulatory SH3 and SH2 domains of c-Src, resulting in localized kinase activation that contributes to tumor cell metastasis. Using assay conditions where c-Src kinase activity required binding to a tyrosine phosphopeptide based on the focal adhesion kinase SH3-SH2 docking sequence, we screened a kinase-biased library for selective inhibitors of the Src/focal adhesion kinase peptide complex versus c-Src alone. This approach identified an aminopyrimidinyl carbamate compound, WH-4-124-2, with nanomolar inhibitory potency and fivefold selectivity for c-Src when bound to the phospho-focal adhesion kinase peptide. Molecular docking studies indicate that WH-4-124-2 may preferentially inhibit the 'DFG-out' conformation of the kinase active site. These findings suggest that interaction of c-Src with focal adhesion kinase induces a unique kinase domain conformation amenable to selective inhibition.

Discovery of a novel activator of 5-lipoxygenase from an anacardic acid derived compound collection.

Lipoxygenases (LOXs) and cyclooxygenases (COXs) metabolize poly-unsaturated fatty acids into inflammatory signaling molecules. Modulation of the activity of these enzymes may provide new approaches for therapy of inflammatory diseases. In this study, we screened novel anacardic acid derivatives as modulators of human 5-LOX and COX-2 activity. Interestingly, a novel salicylate derivative 23a was identified as a surprisingly potent activator of human 5-LOX. This compound showed both non-competitive activation towards the human 5-LOX activator adenosine triphosphate (ATP) and non-essential mixed type activation against the substrate linoleic acid, while having no effect on the conversion of the substrate arachidonic acid. The kinetic analysis demonstrated a non-essential activation of the linoleic acid conversion with a KA of 8.65 µM, αKA of 0.38µM and a ß value of 1.76. It is also of interest that a comparable derivative 23d showed a mixed type inhibition for linoleic acid conversion. These observations indicate the presence of an allosteric binding site in human 5-LOX distinct from the ATP binding site. The activatory and inhibitory behavior of 23a and 23d on the conversion of linoleic compared to arachidonic acid are rationalized by docking studies, which suggest that the activator 23a stabilizes linoleic acid binding, whereas the larger inhibitor 23d blocks the enzyme active site.

Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise.

We describe a general methodology for designing an empirical scoring function and provide smina, a version of AutoDock Vina specially optimized to support high-throughput scoring and user-specified custom scoring functions. Using our general method, the unique capabilities of smina, a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure-Activity Resource) 2010 data set, we created a custom scoring function and evaluated it in the context of the CSAR 2011 benchmarking exercise. We find that our custom scoring function does a better job sampling low RMSD poses when crossdocking compared to the default AutoDock Vina scoring function. The design and application of our method and scoring function reveal several insights into possible improvements and the remaining challenges when scoring and ranking putative ligands.