A common structural basis for c.n.s. drug action

Antiamyloidogenic Activity of Aβ42-Binding Peptoid in Modulating Amyloid Oligomerization

The oligomerization and aggregation of amyloid β (Aβ) play central role in the pathogenesis of Alzheimer's disease (AD). Molecular binding agents for modulating the formation of Aβ oligomers and fibrils have promising application potential in AD therapies. By screening a peptoid library using surface plasmon resonance imaging, amyloid inhibitory peptoid 1 (AIP1) that has high affinity to Aβ42 is identified. AIP1 is demonstrated to inhibit Aβ42 oligomerization and fibrillation and to rescue Aβ42-induced cytotoxicity through decreasing the content of Aβ42 oligomers that is related to cell membrane permeability. Molecular docking suggests that the binding sites of AIP1 may be at the N-terminus of Aβ42. The blood-brain barrier (BBB) permeability of AIP1 using an in vitro BBB model is also revealed. This work provides a strategy for the design and development of peptoid-based antiamyloidogenic agents. The obtained amyloid inhibitory peptoid shows prospects in the therapeutic application in AD.

A k-nearest neighbor classification of hERG K(+) channel blockers

A series of 172 molecular structures that block the hERG K⁺ channel were used to develop a classification model where, initially, eight types of PaDEL fingerprints were used for k-nearest neighbor model development. A consensus model constructed using Extended-CDK, PubChem and Substructure count fingerprint-based models was found to be a robust predictor of hERG activity. This consensus model demonstrated sensitivity and specificity values of 0.78 and 0.61 for the internal dataset compounds and 0.63 and 0.54 for the external (PubChem) dataset compounds, respectively. This model has identified the highest number of true positives (i.e. 140) from the PubChem dataset so far, as compared to other published models, and can potentially serve as a basis for the prediction of hERG active compounds. Validating this model against FDA-withdrawn substances indicated that it may even be useful for differentiating between mechanisms underlying QT prolongation.

Aβ42-binding peptoids as amyloid aggregation inhibitors and detection ligands

Alzheimer's disease (AD) is the most common form of dementia and currently affects 5.4 million Americans. A number of anti-Aβ (beta amyloid) therapeutic agents have been developed for AD, but so far all of them failed in clinic. Here we used peptoid chemistry to develop ligands selective for Aβ42. Peptoids are N-substituted glycine oligomers, a class of peptidomimics. We synthesized an on-bead peptoid library consisting of 38,416 unique peptoids. The generated peptoid library was screened and arrays of Aβ42-selective peptoid ligands were identified. One of those peptoid ligands, IAM1 (inhibitor of amyloid), and the dimeric form (IAM1)2 were synthesized and evaluated in a variety of biochemical assays. We discovered that IAM1 selectively binds to Aβ42, while the dimeric derivative (IAM1)2 has a higher affinity for Aβ42. Furthermore, we demonstrated that IAM1 and (IAM1)2 were able to inhibit the aggregation of Aβ42 in a concentration-dependent manner, and that (IAM1)2 protected primary hippocampal neurons from the Aβ-induced toxicity in vitro. These results suggest that IAM1 and (IAM1)2 are specific Aβ42 ligands with antiaggregation and neuroprotective properties. IAM1, (IAM1)2, and their derivatives hold promise as Aβ42 detection agents and as lead compounds for the development of AD therapeutic agents.

Morpheus: a conformation-activity relationships and receptor modeling package

Our molecular modeling software package, MORPHEUS, allows the study of the interactions between biologically active molecules and their receptors. The package is capable of exploring the multidimensional conformational space accessible to each molecule of the data set under study. By specifying distance constraints or hypothetical receptor binding points, the package is able to filter the biologically accessible conformations of each active compound and deduce a three-dimensional model of the binding sites consistent with the properties of the agonists (or antagonists) under scrutiny. The electrostatic potentials in the environment of a putative binding site can also be investigated using the MORPHEUS package. The molecular modeling module CRYS-X, which is written in FORTRAN 77 for IBM PC machines, is capable of building, displaying and manipulating molecules.

Conformation-activity relationships of opiate analgesics

Extensive conformational calculations were performed on the potent opiate analgesics etorphine, PET, R30490 and etonitazene to determine all of their many low-energy conformations. The results were used to characterize four possible models for binding of a simple pharmacophore, comprising two phenyl rings plus a protonated nitrogen, to opiate analgesic receptors. These four models may define the necessary three-dimensional features leading to particular opiate actions. The model favoured for mu receptor activity can accommodate a protonated nitrogen, an aromatic ring (which may be substituted with an electronegative group) and a second lipophilic group. These structural features must be presented in a precise three-dimensional arrangement. It appears likely that a hydrophilic substituent in a certain region of the analgesic pharmacophore may also interact with the receptor as a secondary binding group.