4-Pregnen-21-ol-3,20-dione-21-(4-bromobenzenesulfonate) (NSC 88915) and related novel steroid derivatives as tyrosyl-DNA phosphodiesterase (Tdp1) inhibitors

Tyrosyl-DNA phosphodiesterase 1 (Tdp1) is an enzyme that catalyzes the hydrolysis of 3'-phosphotyrosyl bonds. Such linkages form in vivo when topoisomerase I (Top1) processes DNA. For this reason, Tdp1 has been implicated in the repair of irreversible Top1-DNA covalent complexes. Tdp1 inhibitors have been regarded as potential therapeutics in combination with Top1 inhibitors, such as the camptothecin derivatives, topotecan and irinotecan, which are used to treat human cancers. Using a novel high-throughput screening assay, we have identified the C21-substituted progesterone derivative, NSC 88915 (1), as a potential Tdp1 inhibitor. Secondary screening and cross-reactivity studies with related DNA processing enzymes confirmed that compound 1 possesses specific Tdp1 inhibitory activity. Deconstruction of compound 1 into discrete functional groups reveals that both components are required for inhibition of Tdp1 activity. Moreover, the synthesis of analogues of compound 1 has provided insight into the structural requirements for the inhibition of Tdp1. Surface plasmon resonance shows that compound 1 binds to Tdp1, whereas an inactive analogue fails to interact with the enzyme. Based on molecular docking and mechanistic studies, we propose that these compounds are competitive inhibitors, which mimics the oligonucleotide-peptide Tdp1 substrate. These steroid derivatives represent a novel chemotype and provide a new scaffold for developing small molecule inhibitors of Tdp1

Virtual screening of ultra-large chemical libraries identifies cell-permeable small-molecule inhibitors of a “non-druggable” target, STAT3 N-terminal domain

STAT3 N-terminal domain is a promising molecular target for cancer treatment and modulation of immune responses. However, STAT3 is localized in the cytoplasm, mitochondria, and nuclei, and thus, is inaccessible to therapeutic antibodies. Its N-terminal domain lacks deep pockets on the surface and represents a typical “non-druggable” protein. In order to successfully identify potent and selective inhibitors of the domain, we have used virtual screening of billion structure-sized virtual libraries of make-on-demand screening samples. The results suggest that the expansion of accessible chemical space by cutting-edge ultra-large virtual compound databases can lead to successful development of small molecule drugs for hard-to-target intracellular proteins

Antiangiogenic Activity and in Silico Cereblon Binding Analysis of Novel Thalidomide Analogs

Funding: This research was supported in part by the Intramural Research Program of the Center for Cancer Research, National Cancer Institute (ZIA SC006538); in part with Federal funds from the Frederick National Laboratory for Cancer Research, National Institutes of Health, under contract HHSN261200800001E; the Intramural Research Program of the National Institute on Aging, National Institutes of Health; and a Wellcome Trust-NIH PhD Studentship to SB, WDF, and NV (Grant number 098252/Z/12/Z). Acknowledgments: The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government.Peer reviewedPublisher PD

Tautomerism in large databases

We have used the Chemical Structure DataBase (CSDB) of the NCI CADD Group, an aggregated collection of over 150 small-molecule databases totaling 103.5 million structure records, to conduct tautomerism analyses on one of the largest currently existing sets of real (i.e. not computer-generated) compounds. This analysis was carried out using calculable chemical structure identifiers developed by the NCI CADD Group, based on hash codes available in the chemoinformatics toolkit CACTVS and a newly developed scoring scheme to define a canonical tautomer for any encountered structure. CACTVS’s tautomerism definition, a set of 21 transform rules expressed in SMIRKS line notation, was used, which takes a comprehensive stance as to the possible types of tautomeric interconversion included. Tautomerism was found to be possible for more than 2/3 of the unique structures in the CSDB. A total of 680 million tautomers were calculated from, and including, the original structure records. Tautomerism overlap within the same individual database (i.e. at least one other entry was present that was really only a different tautomeric representation of the same compound) was found at an average rate of 0.3% of the original structure records, with values as high as nearly 2% for some of the databases in CSDB. Projected onto the set of unique structures (by FICuS identifier), this still occurred in about 1.5% of the cases. Tautomeric overlap across all constituent databases in CSDB was found for nearly 10% of the records in the collection

Structural and functional analyses of minimal phosphopeptides targeting the polo-box domain of polo-like kinase 1

Polo-like kinase-1 (Plk1) has a pivotal role in cell proliferation and is considered a potential target for anticancer therapy. The noncatalytic polo-box domain (PBD) of Plk1 forms a phosphoepitope binding module for protein-protein interaction. Here, we report the identification of minimal phosphopeptides that specifically interact with the PBD of human PLK1, but not those of the closely related PLK2 and PLK3. Comparative binding studies and analyses of crystal structures of the PLK1 PBD in complex with the minimal phosphopeptides revealed that the C-terminal SpT dipeptide functions as a high-affinity anchor, whereas the N-terminal residues are crucial for providing specificity and affinity to the interaction. Inhibition of the PLK1 PBD by phosphothreonine mimetic peptides was sufficient to induce mitotic arrest and apoptotic cell death. The mode of interaction between the minimal peptide and PBD may provide a template for designing therapeutic agents that target PLK1.National Institutes of Health (U.S.) (Grant R01 GM60594)National Cancer Institute (U.S.)National Institutes of Health (U.S.) (Contract N01-CO-12400)National Institutes of Health (U.S.) (HHSN261200800001E

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop.

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.The workshop was supported by funding to RCSB PDB by the National Science Foundation (DBI 1338415); PDBe by the Wellcome Trust (104948); PDBj by JST-NBDC; BMRB by the National Institute of General Medical Sciences (GM109046); D3R by the National Institute of General Medical Sciences (GM111528); registration fees from industrial participants; and tax-deductible donations to the wwPDB Foundation by the Genentech Foundation and the Bristol-Myers Squibb Foundation.This is the final version of the article. It first appeared from Cell Press via https://doi.org//10.1016/j.str.2016.02.01

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30–31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.This is the publisher’s final pdf. The published article is copyrighted by Elsevier (Cell Press) and can be found at: http://www.cell.com/structure/hom

Therapeutic Antibodies to Ganglioside GD2 Evolved from Highly Selective Germline Antibodies

Antibodies play a crucial role in host defense and are indispensable research tools, diagnostics, and therapeutics. Antibody generation involves binding of genomically encoded germline antibodies followed by somatic hypermutation and in vivo selection to obtain antibodies with high affinity and selectivity. Understanding this process is critical for developing monoclonal antibodies, designing effective vaccines, and understanding autoantibody formation. Prior studies have found that antibodies to haptens, peptides, and proteins evolve from polyspecific germline antibodies. The immunological evolution of antibodies to mammalian glycans has not been studied. Using glycan microarrays, protein microarrays, cell binding studies, and molecular modeling, we demonstrate that therapeutic antibodies to the tumor-associated ganglioside GD2 evolved from highly specific germline precursors. The results have important implications for developing vaccines and monoclonal antibodies that target carbohydrate antigens. In addition, they demonstrate an alternative pathway for antibody evolution within the immune system that is distinct from the polyspecific germline pathway