Structural-based design of HD-TAC7 PROteolysis TArgeting chimeras (PROTACs) candidate transformations to abrogate SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for about 672 million infections and 6.85 million deaths worldwide. Upon SARS-CoV-2 infection, Histone deacetylases (HDACs) hyperactivate the pro-inflammatory response resulting in stimulation of Acetyl-Coenzyme A and cholesterol for viral entry. HDAC3 inhibition results in the anti-inflammatory activity and reduction of pro-inflammatory cytokines that may restrict COVID-19 progression. Here, we have designed 44 conformational ensembles of previously known HD-TAC7 by enumerating torsions of dihedral angles tested for their binding preferences against HDAC3. Through scrutinizing their placements at active site and binding affinities, three hits were isolated. Cereblon (CRBN) is a well-known E3 ligase that facilitates Proteolysis Targeting Chimeras (PROTACs) targeting. Three entities, including HDAC3-binding moiety (4-acetamido-N-(2-amino-4 fluorophenyl) benzamide), a 6-carbon linker, and CRBN binding ligand (pomalidomide) were assembled to design 4 PROTACs followed by energy minimization and docking against HDAC3 and CRBN, respectively. Subsequent molecular dynamics (MD) and free energy analyses corroborated similar binding trends and favorable energy values. Among all cases, Met88, GLu106, Pro352, Trp380 and Trp388 residues of CRBN, and Pro23, Arg28, Lys194, Phe199, Leu266, Thr299 and Ile346 residues of HDAC3 were engaged in PROTAC binding. Thus, conformational dynamics of both HDAC3 and CRBN moieties are essential for the placement of PROTAC, resulting in target degradation. Overall, the proposed bifunctional small molecules may effectively target HDAC3, stimulating innate immune response to restrict COVID-19 hyperinflammation. This study supports the basis for designing new PROTACs by limiting the conformational search space that may prove more efficient for targeting the protein of interest. Communicated by Ramaswamy H. Sarma</p

RMSD plot for 12 ns MD simulation.

<p>(a) RMSD plot for HDAC2-C8 complex (yellow) and HDAC2 without ligand (red). (b) RMSD plot for HDAC8-C8 complex (green) and HDAC8 without ligand (blue).</p

Structural basis of constitutive c-Src kinase activity due to R175L and W118A mutations

Cellular Src (c-Src) belongs to a non-receptor membrane-associated tyrosine kinase family that plays essential roles in cellular processes. Growing evidence suggests that R175L and W118A mutations in SH2/SH3 domains of c-Src functionally inactivate these domains leading to constitutive activation of kinase domain (KD). Here we modeled c-SrcR175L, c-SrcW118A and c-SrcW118A+R175L structures by inducing phosphorylation at Y416 or Y527, respectively to characterize the comparative dynamics in the active versus inactive states through molecular dynamics simulation assay. We observed more conformational readjustments in c-Srcopen than its close variants. In particular, C-terminal tail residues of c-SrcW118A-open and c-SrcW118A+R175L-open demonstrate significantly higher transitions. The cross-correlation analysis revealed an anticorrelation behavior in the motion of KD with respect to SH2, SH3 and the linker region of SrcW118A+R175L-open, while in c-SrcWT-open, SH2 and SH3 domains were anticorrelated, while KD and C-terminal tail motions were correlated. Due to these conformational differences, c-Src open forms exhibited lower interaction between pY527 and SH2 domain. Through detailed structural analysis, we observed a uniform myristate binding cavity in c-SrcWT-open, while the myristoyl pockets of mutant forms were deformed. We propose that constitutive activation of mutant Src forms may presumably be achieved by the prolonged membrane binding due to unusual conformations of C-terminal and myristoyl switch residues that may result in a higher dephosphorylation rate at pY527 in the myristoylated c-Src. Thus, our study establishes novel clues to decipher the constitutive activation status of c-Src in response to known mutations that may help in devising novel therapeutic strategies for cancer metastasis treatment. Communicated by Ramaswamy H. Sarma</p

Gene network clusters enriched in cancer and cell-cycle related nodes.

<p>Red nodes represent proteins involved in cancer and cell-cycle, yellow are known Plk1 substrates, while green nodes represent targets having no known contributions in cancer. The blue nodes are proteins selected for structural validation in this study. Green and red lines represent protein network edges.</p

Synthetic accessibility score and expected pIC₅₀ values.

<p>Synthetic accessibility score and expected pIC₅₀ values.</p

Radius of gyration (Rg) analysis for 12 ns MD simulation.

<p>(a) Rg/RMSD plot for HDAC2-C8 complex (yellow) and HDAC2 without ligand (red). (b) Rg/RMSD for HDAC8-C8 complex (green) and HDAC8 without ligand (blue).</p

Energy plot for 12 ns MD simulation.

<p>(a) Energy plot for HDAC2-C8 complex (yellow). (b) Energy plot for HDAC8-C8 complex (green).</p

Multiple sequence alignment (MSA), secondary and tertiary structures of four selected Plk1 specific substrates.

<p>(a) SMARCAD1, (b) GSG2, (c) NUP35, (d) NEK5, (e) KIF23 and (f) CEP170. MSA illustrates the conservation pattern of predicted PBD recognition and kinase phosphorylation motifs across close homologues of selected proteins (a–d). Secondary structure for each substrate was predicted by JPred as shown below the alignments Tertiary structures of (a–f) substrates are shown in cornflower blue ribbon-form, phosphorylation motifs are shown in yellow, PBD recognition motifs are shown in pink.</p

Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

<div><p>Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC₅₀ values and experimental energy scores with extensive validations. The QSAR model having an external R² value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.</p></div