No abstract

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

Manganese (Mn) is both an essential biological cofactor and neurotoxicant. Disruption of Mn biology in the basal ganglia has been implicated in the pathogenesis of neurodegenerative disorders, such as parkinsonism and Huntington's disease. Handling of other essential metals (e.g. iron and zinc) occurs via complex intracellular signaling networks that link metal detection and transport systems. However, beyond several non-selective transporters, little is known about the intracellular processes regulating neuronal Mn homeostasis. We hypothesized that small molecules that modulate intracellular Mn could provide insight into cell-level Mn regulatory mechanisms. We performed a high throughput screen of 40,167 small molecules for modifiers of cellular Mn content in a mouse striatal neuron cell line. Following stringent validation assays and chemical informatics, we obtained a chemical ‘toolbox' of 41 small molecules with diverse structure-activity relationships that can alter intracellular Mn levels under biologically relevant Mn exposures. We utilized this toolbox to test for differential regulation of Mn handling in human floor-plate lineage dopaminergic neurons, a lineage especially vulnerable to environmental Mn exposure. We report differential Mn accumulation between developmental stages and stage-specific differences in the Mn-altering activity of individual small molecules. This work demonstrates cell-level regulation of Mn content across neuronal differentiation.

Discoidin domain receptor (DDR) 1 and 2 are transmembrane receptors that belong to the family of receptor tyrosine kinases (RTK). Upon collagen binding, DDRs transduce cellular signaling involved in various cell functions, including cell adhesion, proliferation, differentiation, migration, and matrix homeostasis. Altered DDR function resulting from either mutations or overexpression has been implicated in several types of disease, including atherosclerosis, inflammation, cancer, and tissue fibrosis. Several established inhibitors, such as imatinib, dasatinib, and nilotinib, originally developed as Abelson murine leukemia (Abl) kinase inhibitors, have been found to inhibit DDR kinase activity. As we review here, recent discoveries of novel inhibitors and their co-crystal structure with the DDR1 kinase domain have made structure-based drug discovery for DDR1 amenable.

Small angle X-ray scattering (SAXS) is used for low resolution structural characterization of proteins often in combination with other experimental techniques. After briefly reviewing the theory of SAXS we discuss computational methods based on 1) the Debye equation and 2) Spherical Harmonics to compute intensity profiles from a particular macromolecular structure. Further, we review how these formulas are parameterized for solvent density and hydration shell adjustment. Finally we introduce our solution to compute SAXS profiles utilizing GPU acceleration.