Dataset Information

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement.

ABSTRACT: With the emergence of drug-resistant strains and the cumulative toxicities associated with current therapies, demand remains for new inhibitors of HIV-1 replication. The inhibition of HIV-1 entry is an attractive, yet underexploited therapeutic approach with implications for salvage and preexposure prophylactic regimens, as well as topical microbicides. Using the combination of a field-derived bioactive conformation template to perform virtual screening and iterative bioisosteric replacements, coupled with in silico predictions of absorption, distribution, metabolism, and excretion, we have identified new leads for HIV-1 entry inhibitors.

SUBMITTER: Tuyishime M

PROVIDER: S-EPMC4355043 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement.

Tuyishime Marina M Danish Matt M Princiotto Amy A Mankowski Marie K MK Lawrence Rae R Lombart Henry-Georges HG Esikov Kirill K Berniac Joel J Liang Kuang K Ji Jingjing J Ptak Roger G RG Madani Navid N Cocklin Simon S

Bioorganic & medicinal chemistry letters 20141201 23

With the emergence of drug-resistant strains and the cumulative toxicities associated with current therapies, demand remains for new inhibitors of HIV-1 replication. The inhibition of HIV-1 entry is an attractive, yet underexploited therapeutic approach with implications for salvage and preexposure prophylactic regimens, as well as topical microbicides. Using the combination of a field-derived bioactive conformation template to perform virtual screening and iterative bioisosteric replacements, c ...[more]

PMID: 25454268

Similar Datasets

Project description:N6-Methyladenosine (m6A) is the most prevalent mRNA modification in mammalian cells that is mainly catalyzed by the methyltransferase complex of methyltransferase-like 3 and methyltransferase-like 14 (METTL3-METTL14). Many lines of evidence suggest that METTL3 plays important roles in several diseases such as cancers and viral infection. In the present study, 1,042 natural products from commercially available sources were chosen to establish a screening library, and docking-based high-throughput screening was performed to discover potential METTL3 inhibitors. The selected compounds were then further validated by an in vitro methyltransferase inhibition assay in which m6A content was determined by LC-MS/MS. A cellular assay of the inhibition of m6A methylation was performed to determine the METTL3 inhibitory activity of the selected compound. CCK-8 assay was applied to evaluate the effects of the selected compound on tumor cell viability. Additionally, binding mode analysis, molecular dynamics (MD) simulation, and binding free energy analysis were performed to study the process and characteristics of inhibitor binding. Finally, quercetin was identified as a METTL3 inhibitor with an IC50 value of 2.73 μM. The cellular assay of m6A methylation inhibition showed that quercetin decreased m6A level in a dose-dependent manner in MIA PaCa-2 pancreatic cancer cells. CCK-8 assay showed quercetin efficiently inhibited the proliferation of MIA PaCa-2 and Huh7 tumor cells, with IC50 values 73.51 ± 11.22 μM and 99.97 ± 7.03 μM, respectively. Molecular docking studies revealed that quercetin filled the pocket of the adenosine moiety of SAM but not the pocket of the SAM methionine in the METTL3 protein, and hydrogen bonds, hydrophobic interactions, and pi-stacking were formed. The values of the root mean square deviation (RMSD), the root mean square fluctuations (RMSF), and binding free energy suggested that quercetin can efficiently bind to the pocket of the METTL3 protein and form a stable protein-ligand complex. The present study is the first to identify METTL3 inhibitors from natural products, thus providing a basis for subsequent research and facilitating the development of METTL3-targeting drugs for diseases.

Dataset Information

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement.

Publications

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets