Publications

Background: Bivalent regions of chromatin (BvCR) are characterized by trimethylated lysine 4 (H3K4me3) and lysine 27 on histone H3 (H3K27me3) deposition which aid gene expression control during cell differentiation. The role of BvCR in post-transcriptional DNA damage response remains unidentified. Oncoprotein survivin binds chromatin and mediates IFNγ effects in CD4+ cells. In this study, we explored the role of BvCR in DNA damage response of autoimmune CD4+ cells in rheumatoid arthritis (RA). Methods: We performed deep sequencing of the chromatin bound to survivin, H3K4me3, H3K27me3, and H3K27ac, in human CD4+ cells and identified BvCR, which possessed all three histone H3 modifications. Protein partners of survivin on chromatin were predicted by integration of motif enrichment analysis, computational machine-learning, and structural modeling, and validated experimentally by mass spectrometry and peptide binding array. Survivin-dependent change in BvCR and transcription of genes controlled by the BvCR was studied in CD4+ cells treated with survivin inhibitor, which revealed survivin-dependent biological processes. Finally, the survivin-dependent processes were mapped to the transcriptome of CD4+ cells in blood and in synovial tissue of RA patients and the effect of modern immunomodulating drugs on these processes was explored. Results: We identified that BvCR dominated by H3K4me3 (H3K4me3-BvCR) accommodated survivin within cis-regulatory elements of the genes controlling DNA damage. Inhibition of survivin or JAK-STAT signaling enhanced H3K4me3-BvCR dominance, which improved DNA damage recognition and arrested cell cycle progression in cultured CD4+ cells. Specifically, BvCR accommodating survivin aided sequence-specific anchoring of the BRG1/SWI chromatin-remodeling complex coordinating DNA damage response. Mapping survivin interactome to BRG1/SWI complex demonstrated interaction of survivin with the subunits anchoring the complex to chromatin. Co-expression of BRG1, survivin and IFNγ in CD4+ cells rendered complete deregulation of DNA damage response in RA. Such cells possessed strong ability of homing to RA joints. Immunomodulating drugs inhibited the anchoring subunits of BRG1/SWI complex, which affected arthritogenic profile of CD4+ cells. Conclusions: BvCR execute DNA damage control to maintain genome fidelity in IFN-activated CD4+ cells. Survivin anchors the BRG1/SWI complex to BvCR to repress DNA damage response. These results offer a platform for therapeutic interventions targeting survivin and BRG1/SWI complex in autoimmunity.

Abstract Sustained drug delivery strategies have many potential benefits for treating a range of diseases, particularly chronic diseases that require treatment for years. For many chronic ocular diseases, patient adherence to eye drop dosing regimens and the need for frequent intraocular injections are significant barriers to effective disease management. Here, we utilize peptide engineering to impart melanin binding properties to peptide-drug conjugates to act as a sustained-release depot in the eye. We develop a super learning-based methodology to engineer multifunctional peptides that efficiently enter cells, bind to melanin, and have low cytotoxicity. When the lead multifunctional peptide (HR97) is conjugated to brimonidine, an intraocular pressure lowering drug that is prescribed for three times per day topical dosing, intraocular pressure reduction is observed for up to 18 days after a single intracameral injection in rabbits. Further, the cumulative intraocular pressure lowering effect increases ~17-fold compared to free brimonidine injection. Engineered multifunctional peptide-drug conjugates are a promising approach for providing sustained therapeutic delivery in the eye and beyond.

Design of peptide binders is an attractive strategy for targeting “undruggable” protein-protein interfaces. Current design protocols rely on the extraction of an initial sequence from one known protein interactor of the target protein, followed by in-silico or in-vitro mutagenesis-based optimization of its binding affinity. Wet lab protocols can explore only a minor portion of the vast sequence space and cannot efficiently screen for other desirable properties such as high specificity and low toxicity, while in-silico design requires intensive computational resources and often relies on simplified binding models. Yet, for a multivalent protein target, dozens to hundreds of natural protein partners already exist in the cellular environment. Here, we describe a peptide design protocol that harnesses this diversity via a machine learning generative model. After identifying putative natural binding fragments by literature and homology search, a compositional Restricted Boltzmann Machine is trained and sampled to yield hundreds of diverse candidate peptides. The latter are further filtered via flexible molecular docking and an in-vitro microchip-based binding assay. We validate and test our protocol on calcineurin, a calcium-dependent protein phosphatase involved in various cellular pathways in health and disease. In a single screening round, we identified multiple 16-length peptides with up to six mutations from their closest natural sequence that successfully interfere with the binding of calcineurin to its substrates. In summary, integrating protein interaction and sequence databases, generative modeling, molecular docking and interaction assays enables the discovery of novel protein-protein interaction modulators.

An array of 4000 defined and addressable tripeptides on a polymer-coated glass slide is used to synthesize molecularly imprinted polymer (MIP) nanoparticles. This work is undertaken to systematically probe the impact of the peptide sequence on the ability to generate affinity MIPs. The polymer affinity is assessed by measuring the fluorescence of bound MIP nanoparticles at each peptide spot on the surface after washing the array to remove any low-affinity polymer. The generic composition commonly used in the preparation of MIPs against proteins seems to be equally suitable for imprinting hydrophobic and hydrophilic tripeptides. The amino acids frequently contributing to the formation of high-affinity MIPs include T, F, D, N, Y, W, and P. The amino acids that rarely contribute to the formation of high-affinity interactions with MIPs are G, V, A, L, I, and M. These observations are confirmed by computational modeling. The basic technique proposed here may be applicable in optimizing polymer compositions for the production of high-affinity MIPs or, more specifically, for the selection of appropriate amino acid sequences when peptide epitopes are used instead of whole protein imprinting.