Publisher Correction: Novel selective, potent naphthyl TRPM8 antagonists identified through a combined ligand- and structure-based virtual screening approach.

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Novel selective, potent naphthyl TRPM8 antagonists identified through a combined ligand- and structure-based virtual screening approach.

Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predominant mammalian cold temperature thermosensor and it is activated by cold temperatures and cooling compounds, such as menthol and icilin. Because of its role in cold allodynia, cold hyperalgesia and painful syndromes TRPM8 antagonists are currently being pursued as potential therapeutic agents for the treatment of pain hypersensitivity. Recently TRPM8 has been found in subsets of bladder sensory nerve fibres, providing an opportunity to understand and treat chronic hypersensitivity. However, most of the known TRPM8 inhibitors lack selectivity, and only three selective compounds have reached clinical trials to date. Here, we applied two virtual screening strategies to find new, clinics suitable, TRPM8 inhibitors. This strategy enabled us to identify naphthyl derivatives as a novel class of potent and selective TRPM8 inhibitors. Further characterization of the pharmacologic properties of the most potent compound identified, compound 1, confirmed that it is a selective, competitive antagonist inhibitor of TRPM8. Compound 1 also proved itself active in a overreactive bladder model in vivo. Thus, the novel naphthyl derivative compound identified here could be optimized for clinical treatment of pain hypersensitivity in bladder disorders but also in different other pathologies.

Targeting the minor pocket of C5aR for the rational design of an oral allosteric inhibitor for inflammatory and neuropathic pain relief.

Chronic pain resulting from inflammatory and neuropathic disorders causes considerable economic and social burden. Pharmacological therapies currently available for certain types of pain are only partially effective and may cause severe adverse side effects. The C5a anaphylatoxin acting on its cognate G protein-coupled receptor (GPCR), C5aR, is a potent pronociceptive mediator in several models of inflammatory and neuropathic pain. Although there has long been interest in the identification of C5aR inhibitors, their development has been complicated, as for many peptidomimetic drugs, mostly by poor drug-like properties. Herein, we report the de novo design of a potent and selective C5aR noncompetitive allosteric inhibitor, DF2593A, guided by the hypothesis that an allosteric site, the "minor pocket," previously characterized in CXC chemokine receptors-1 and -2, is functionally conserved in the GPCR class. In vitro, DF2593A potently inhibited C5a-induced migration of human and rodent neutrophils. In vivo, oral administration of DF2593A effectively reduced mechanical hyperalgesia in several models of acute and chronic inflammatory and neuropathic pain, without any apparent side effects. Mechanical hyperalgesia after spared nerve injury was also reduced in C5aR(-/-) mice compared with WT mice. Furthermore, treatment of C5aR(-/-) mice with DF2593A did not produce any further antinociceptive effect compared with C5aR(-/-) mice treated with vehicle. The successful medicinal chemistry strategy confirms that a conserved minor pocket is amenable for the rational design of selective inhibitors and the pharmacological results support that the allosteric blockade of the C5aR represents a highly promising therapeutic approach to control chronic inflammatory and neuropathic pain.

Molecular docking methodologies.

Molecular docking represents an important technology for structure-based drug design. Docking is a computational technique aimed at the prediction of the most favorable ligand-target spatial configuration and an estimate of the corresponding complex free energy, although as stated at the beginning accurate scoring methods remain still elusive. In this chapter, the state of art of molecular docking methodologies and their applications in drug discovery is summarized.

Swimming into peptidomimetic chemical space using pepMMsMIMIC.

pepMMsMIMIC is a novel web-oriented peptidomimetic compound virtual screening tool based on a multi-conformers three-dimensional (3D)-similarity search strategy. Key to the development of pepMMsMIMIC has been the creation of a library of 17 million conformers calculated from 3.9 million commercially available chemicals collected in the MMsINC® database. Using as input the 3D structure of a peptide bound to a protein, pepMMsMIMIC suggests which chemical structures are able to mimic the protein-protein recognition of this natural peptide using both pharmacophore and shape similarity techniques. We hope that the accessibility of pepMMsMIMIC (freely available at http://mms.dsfarm.unipd.it/pepMMsMIMIC) will encourage medicinal chemists to de-peptidize protein-protein recognition processes of biological interest, thus increasing the potential of in silico peptidomimetic compound screening of known small molecules to expedite drug development.

A Novel Generalized 3D-QSAR Model of Camptothecin Analogs.

In the present paper, we are interested to explore if the application of docking-driven conformational analysis could increase the goodness of 3D-QSAR statistical models, as alternative approach to a conventional ligand-based conformer generation. In particular, we have selected as peculiar key-study an ensemble of Camptothecin (CPT) analogs classified as human DNA Topoisomerase I (Top1) selective inhibitors. The CPT analogs dataset has been recently analyzed by Hansch and Verma using a classical 2D-QSAR study.

MMsINC: a large-scale chemoinformatics database.

MMsINC (http://mms.dsfarm.unipd.it/MMsINC/search) is a database of non-redundant, richly annotated and biomedically relevant chemical structures. A primary goal of MMsINC is to guarantee the highest quality and the uniqueness of each entry. MMsINC then adds value to these entries by including the analysis of crucial chemical properties, such as ionization and tautomerization processes, and the in silico prediction of 24 important molecular properties in the biochemical profile of each structure. MMsINC is consequently a natural input for different chemoinformatics and virtual screening applications. In addition, MMsINC supports various types of queries, including substructure queries and the novel 'molecular scissoring' query. MMsINC is interfaced with other primary data collectors, such as PubChem, Protein Data Bank (PDB), the Food and Drug Administration database of approved drugs and ZINC.