Consensus Pharmacophore Strategy For Identifying Novel SARS-Cov-2 Mpro Inhibitors from Large Chemical Libraries.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome and is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development, and multiple Mpro crystals complexed with competitive inhibitors have been reported. In this study, we aimed to develop an Mpro consensus pharmacophore as a tool to expand the search for inhibitors. We generated a consensus model by aligning and summarizing pharmacophoric points from 152 bioactive conformers of SARS-CoV-2 Mpro inhibitors. Validation against a library of conformers from a subset of ligands showed that our model retrieved poses that reproduced the crystal-binding mode in 77% of the cases. Using models derived from a consensus pharmacophore, we screened >340 million compounds. Pharmacophore-matching and chemoinformatics analyses identified new potential Mpro inhibitors. The candidate compounds were chemically dissimilar to the reference set, and among them, demonstrating the relevance of our model. We evaluated the effect of 16 candidates on Mpro enzymatic activity finding that seven have inhibitory activity. Three compounds (1, 4, and 5) had IC50 values in the midmicromolar range. The Mpro consensus pharmacophore reported herein can be used to identify compounds with improved activity and novel chemical scaffolds against Mpro. The method developed for its generation is provided as an open-access code (https://github.com/AngelRuizMoreno/ConcensusPharmacophore) and can be applied to other pharmacological targets.

In Silico Design and Selection of New Tetrahydroisoquinoline-Based CD44 Antagonist Candidates.

CD44 promotes metastasis, chemoresistance, and stemness in different types of cancer and is a target for the development of new anti-cancer therapies. All CD44 isoforms share a common N-terminal domain that binds to hyaluronic acid (HA). Herein, we used a computational approach to design new potential CD44 antagonists and evaluate their target-binding ability. By analyzing 30 crystal structures of the HA-binding domain (CD44HAbd), we characterized a subdomain that binds to 1,2,3,4-tetrahydroisoquinoline (THQ)-containing compounds and is adjacent to residues essential for HA interaction. By computational combinatorial chemistry (CCC), we designed 168,190 molecules and compared their conformers to a pharmacophore containing the key features of the crystallographic THQ binding mode. Approximately 0.01% of the compounds matched the pharmacophore and were analyzed by computational docking and molecular dynamics (MD). We identified two compounds, Can125 and Can159, that bound to human CD44HAbd (hCD44HAbd) in explicit-solvent MD simulations and therefore may elicit CD44 blockage. These compounds can be easily synthesized by multicomponent reactions for activity testing and their binding mode, reported here, could be helpful in the design of more potent CD44 antagonists.

Repositioning of Etravirine as a Potential CK1ε Inhibitor by Virtual Screening.

CK1ε is a key regulator of WNT/ß-catenin and other pathways that are linked to tumor progression; thus, CK1ε is considered a target for the development of antineoplastic therapies. In this study, we performed a virtual screening to search for potential CK1ε inhibitors. First, we characterized the dynamic noncovalent interactions profiles for a set of reported CK1ε inhibitors to generate a pharmacophore model, which was used to identify new potential inhibitors among FDA-approved drugs. We found that etravirine and abacavir, two drugs that are approved for HIV infections, can be repurposed as CK1ε inhibitors. The interaction of these drugs with CK1ε was further examined by molecular docking and molecular dynamics. Etravirine and abacavir formed stable complexes with the target, emulating the binding behavior of known inhibitors. However, only etravirine showed high theoretical binding affinity to CK1ε. Our findings provide a new pharmacophore for targeting CK1ε and implicate etravirine as a CK1ε inhibitor and antineoplastic agent.

Pranlukast Antagonizes CD49f and Reduces Stemness in Triple-Negative Breast Cancer Cells.

INTRODUCTION: Cancer stem cells (CSCs) drive the initiation, maintenance, and therapy response of breast tumors. CD49f is expressed in breast CSCs and functions in the maintenance of stemness. Thus, blockade of CD49f is a potential therapeutic approach for targeting breast CSCs. In the present study, we aimed to repurpose drugs as CD49f antagonists. MATERIALS AND METHODS: We performed consensus molecular docking using a subdomain of CD49f that is critical for heterodimerization and a collection of pharmochemicals clinically tested. Molecular dynamics simulations were employed to further characterize drug-target binding. Using MDA-MB-231 cells, we evaluated the effects of potential CD49f antagonists on 1) cell adhesion to laminin; 2) mammosphere formation; and 3) cell viability. We analyzed the effects of the drug with better CSC-selectivity on the activation of CD49f-downstream signaling by Western blot (WB) and co-immunoprecipitation. Expressions of the stem cell markers CD44 and SOX2 were analyzed by flow cytometry and WB, respectively. Transactivation of SOX2 promoter was evaluated by luciferase reporter assays. Changes in the number of CSCs were assessed by limiting-dilution xenotransplantation. RESULTS: Pranlukast, a drug used to treat asthma, bound to CD49f in silico and inhibited the adhesion of CD49f+ MDA-MB-231 cells to laminin, indicating that it antagonizes CD49f-containing integrins. Molecular dynamics analysis showed that pranlukast binding induces conformational changes in CD49f that affect its interaction with ß1-integrin subunit and constrained the conformational dynamics of the heterodimer. Pranlukast decreased the clonogenicity of breast cancer cells on mammosphere formation assay but had no impact on the viability of bulk tumor cells. Brief exposure of MDA-MB-231 cells to pranlukast altered CD49f-dependent signaling, reducing focal adhesion kinase (FAK) and phosphatidylinositol 3-kinase (PI3K) activation. Further, pranlukast-treated cells showed decreased CD44 and SOX2 expression, SOX2 promoter transactivation, and in vivo tumorigenicity, supporting that this drug reduces the frequency of CSC. CONCLUSION: Our results support the function of pranlukast as a CD49f antagonist that reduces the CSC population in triple-negative breast cancer cells. The pharmacokinetics and toxicology of this drug have already been established, rendering a potential adjuvant therapy for breast cancer patients.

Guide for Selection of Relevant Cell Lines During the Evaluation of new Anti-Cancer Compounds.

BACKGROUND: Human cancer cell lines are valuable models for anti-cancer drug development. Although all cancer cells share common biological features, each cancer cell line has unique genotypic/ phenotypic characteristics that affect drug response. Thus, the information obtained with a specific cancer cell line cannot be easily extrapolated to other cancer cells. Consequently, cell line selection during experimental design is critical for providing proper and clinically relevant structure-activity analysis. METHODS: Herein, we critically review the use of cancer cell lines as tools for activity analysis by comparing two different scenarios: i) the use of multiple cancer cell lines, with the NCI-60 Program as the most representative example; and, ii) the selection of a single cell line with specific biological characteristics that match the rationale of compound design. RESULTS: Considering that most laboratories evaluate the activity of new compounds using few cell lines, we provide a systematic strategy for selection based on the expression levels and genetic status of the target and the effectiveness of target inhibition or silencing. We exemplify the use of public databases for data retrieval and analysis as well as the critical comparison of such information with published results. CONCLUSION: This approach refines cell line selection, avoiding the perpetuation of published poor selection and enhancing the relevance of the results.