Marked difference in saxitoxin and tetrodotoxin affinity for the human nociceptive voltage-gated sodium channel (Nav1.7) [corrected].

Human nociceptive voltage-gated sodium channel (Na(v)1.7), a target of significant interest for the development of antinociceptive agents, is blocked by low nanomolar concentrations of (-)-tetrodotoxin(TTX) but not (+)-saxitoxin (STX) and (+)-gonyautoxin-III (GTX-III). These findings question the long-accepted view that the 1.7 isoform is both tetrodotoxin- and saxitoxin-sensitive and identify the outer pore region of the channel as a possible target for the design of Na(v)1.7-selective inhibitors. Single- and double-point amino acid mutagenesis studies along with whole-cell electrophysiology recordings establish two domain III residues (T1398 and I1399), which occur as methionine and aspartate in other Na(v) isoforms, as critical determinants of STX and gonyautoxin-III binding affinity. An advanced homology model of the Na(v) pore region is used to provide a structural rationalization for these surprising results.

Bayesian analysis of isothermal titration calorimetry for binding thermodynamics.

Isothermal titration calorimetry (ITC) is the only technique able to determine both the enthalpy and entropy of noncovalent association in a single experiment. The standard data analysis method based on nonlinear regression, however, provides unrealistically small uncertainty estimates due to its neglect of dominant sources of error. Here, we present a Bayesian framework for sampling from the posterior distribution of all thermodynamic parameters and other quantities of interest from one or more ITC experiments, allowing uncertainties and correlations to be quantitatively assessed. For a series of ITC measurements on metal:chelator and protein:ligand systems, the Bayesian approach yields uncertainties which represent the variability from experiment to experiment more accurately than the standard data analysis. In some datasets, the median enthalpy of binding is shifted by as much as 1.5 kcal/mol. A Python implementation suitable for analysis of data generated by MicroCal instruments (and adaptable to other calorimeters) is freely available online.

SWEETLEAD: an in silico database of approved drugs, regulated chemicals, and herbal isolates for computer-aided drug discovery.

In the face of drastically rising drug discovery costs, strategies promising to reduce development timelines and expenditures are being pursued. Computer-aided virtual screening and repurposing approved drugs are two such strategies that have shown recent success. Herein, we report the creation of a highly-curated in silico database of chemical structures representing approved drugs, chemical isolates from traditional medicinal herbs, and regulated chemicals, termed the SWEETLEAD database. The motivation for SWEETLEAD stems from the observance of conflicting information in publicly available chemical databases and the lack of a highly curated database of chemical structures for the globally approved drugs. A consensus building scheme surveying information from several publicly accessible databases was employed to identify the correct structure for each chemical. Resulting structures are filtered for the active pharmaceutical ingredient, standardized, and differing formulations of the same drug were combined in the final database. The publically available release of SWEETLEAD (https://simtk.org/home/sweetlead) provides an important tool to enable the successful completion of computer-aided repurposing and drug discovery campaigns.

Design of ß-amyloid aggregation inhibitors from a predicted structural motif.

Drug design studies targeting one of the primary toxic agents in Alzheimer's disease, soluble oligomers of amyloid ß-protein (Aß), have been complicated by the rapid, heterogeneous aggregation of Aß and the resulting difficulty to structurally characterize the peptide. To address this, we have developed [Nle(35), D-Pro(37)]Aß(42), a substituted peptide inspired from molecular dynamics simulations which forms structures stable enough to be analyzed by NMR. We report herein that [Nle(35), D-Pro(37)]Aß(42) stabilizes the trimer and prevents mature fibril and ß-sheet formation. Further, [Nle(35), D-Pro(37)]Aß(42) interacts with WT Aß(42) and reduces aggregation levels and fibril formation in mixtures. Using ligand-based drug design based on [Nle(35), D-Pro(37)]Aß(42), a lead compound was identified with effects on inhibition similar to the peptide. The ability of [Nle(35), D-Pro(37)]Aß(42) and the compound to inhibit the aggregation of Aß(42) provides a novel tool to study the structure of Aß oligomers. More broadly, our data demonstrate how molecular dynamics simulation can guide experiment for further research into AD.