Transcription factors (TFs) are a major class of protein signaling molecules that play key cellular roles in cancers such as the highly lethal brain cancer-glioblastoma (GBM). However, the development of specific TF inhibitors has proved difficult owing to expansive protein-protein interfaces and the absence of hydrophobic pockets. We uniquely defined the dimerization surface as an expansive parental pharmacophore comprised of several regional daughter pharmacophores. We targeted the OLIG2 TF which is essential for GBM survival and growth, we hypothesized that small molecules able to fit each subpharmacophore would inhibit OLIG2 activation. The most active compound was OLIG2 selective, it entered the brain, and it exhibited potent anti-GBM activity in cell-based assays and in pre-clinical mouse orthotopic models. These data suggest that (1) our multiple pharmacophore approach warrants further investigation, and (2) our most potent compounds merit detailed pharmacodynamic, biophysical, and mechanistic characterization for potential preclinical development as GBM therapeutics.

Cisplatin (cDDP) is known to bind to the CXXC motif of proteins containing a ferrodoxin-like fold but little is known about its ability to interact with other Cu-binding proteins. MEK1/2 has recently been identified as a Cu-dependent enzyme that does not contain a CXXC motif. We found that cDDP bound to and inhibited the activity of recombinant MEK1 with an IC50 of 0.28 μM and MEK1/2 in whole cells with an IC50 of 37.4 μM. The inhibition of MEK1/2 was relieved by both Cu+1 and Cu+2 in a concentration-dependent manner. cDDP did not inhibit the upstream pathways responsible for activating MEK1/2, and did not cause an acute depletion of cellular Cu that could account for the reduction in MEK1/2 activity. cDDP was found to bind MEK1/2 in whole cells and the extent of binding was augmented by supplementary Cu and reduced by Cu chelation. Molecular modeling predicts 3 Cu and cDDP binding sites and quantum chemistry calculations indicate that cDDP would be expected to displace Cu from each of these sites. We conclude that, at clinically relevant concentrations, cDDP binds to and inhibits MEK1/2 and that both the binding and inhibitory activity are related to its interaction with Cu bound to MEK1/2. This may provide the basis for useful interactions of cDDP with other drugs that inhibit MAPK pathway signaling.

We hypothesized that aberrations activating epidermal growth factor receptor (EGFR) via dimerization would be more sensitive to anti-dimerization agents (e.g., cetuximab). EGFR exon 19 abnormalities (L747_A750del; deletes amino acids LREA) respond to reversible EGFR kinase inhibitors (TKIs). Exon 20 in-frame insertions and/or duplications (codons 767 to 774) and T790M mutations are clinically resistant to reversible/some irreversible TKIs. Their impact on protein function/therapeutic actionability are not fully elucidated.In our study, the index patient with non-small cell lung cancer (NSCLC) harbored EGFR D770_P772del_insKG (exon 20). A twenty patient trial (NSCLC cohort) (cetuximab-based regimen) included two participants with EGFR TKI-resistant mutations ((i) exon 20 D770>GY; and (ii) exon 19 LREA plus exon 20 T790M mutations). Structural modeling predicted that EGFR exon 20 anomalies (D770_P772del_insKG and D770>GY), but not T790M mutations, stabilize the active dimer configuration by increasing the interaction between the kinase domains, hence sensitizing to an agent preventing dimerization. Consistent with predictions, the two patients harboring D770_P772del_insKG and D770>GY, respectively, responded to an EGFR antibody (cetuximab)-based regimen; the T790M-bearing patient showed no response to cetuximab combined with erlotinib. In silico modeling merits investigation of its ability to optimize therapeutic selection based on structural/functional implications of different aberrations within the same gene.

Anti-retrovirals have improved and extended the life expectancy of patients with HIV. However, as this population ages, the prevalence of cognitive changes is increasing. Aberrant activation of kinases, such as receptor tyrosine kinases (RTKs) and cyclin-dependent kinase 5 (CDK5), play a role in the mechanisms of HIV neurotoxicity. Inhibitors of CDK5, such as roscovitine, have neuroprotective effects; however, CNS penetration is low. Interestingly, tyrosine kinase inhibitors (TKIs) display some CDK inhibitory activity and ability to cross the blood-brain barrier.

Misfolding and pathological aggregation of neuronal proteins has been proposed to play a critical role in the pathogenesis of neurodegenerative disorders. Alzheimer's disease (AD) and Parkinson's disease (PD) are frequent neurodegenerative diseases of the aging population. While progressive accumulation of amyloid beta protein (Abeta) oligomers has been identified as one of the central toxic events in AD, accumulation of alpha-synuclein (alpha-syn) resulting in the formation of oligomers and protofibrils has been linked to PD and Lewy body Disease (LBD). We have recently shown that Abeta promotes alpha-syn aggregation and toxic conversion in vivo, suggesting that abnormal interactions between misfolded proteins might contribute to disease pathogenesis. However the molecular characteristics and consequences of these interactions are not completely clear.

Immunotherapy with checkpoint inhibitors, such as antibodies blocking the programmed cell-death receptor-1 (PD-1), has resulted in remarkable responses in patients having traditionally refractory cancers. Although response to PD-1 inhibitors correlates with PD-1 ligand (PD-L1 or PD-L2) expression, PD-1 ligand positivity represents only a part of the predictive model necessary for selecting patients predisposed to respond to immunotherapy. We used all genomic, transcriptomic, proteomic and phenotypic data related to 8,475 pan-cancer samples available in The Cancer Genome Atlas (TCGA) and conducted a logistic regression analysis based on a large set of variables, such as microsatellite instability (MSI-H), mismatch repair (MMR) alterations, polymerase δ (POLD1) and polymerase ε (POLE) mutations, activation-induced/apolipoprotein-B editing cytidine deaminases (AID/APOBEC) alterations, lymphocyte markers and mutation burden estimates to determine independent factors that associate with PD-1 ligand overexpression. PD-1 ligand overexpression was independently and significantly correlated with overexpression of and mutations in APOBEC3 paralogs. Additionally, while high tumor mutation burden and overexpression of PD-L1 have been previously correlated with each other, we demonstrate that the specific mutation pattern caused by APOBEC enzymes and called kataegis-rather than overall mutation burden, MSI-H or MMR alterations-correlates independently with PD-L1/PD-L2 expression. These observations suggest that APOBEC3 alterations, APOBEC3 overexpression and kataegis play an important role in the regulation of PD-1 ligand overexpression, and thus, their relationship with immune checkpoint inhibitor response warrants exploration.

Several lines of evidence suggest that a characteristic of the neuropathology of Alzheimer's disease (AD) is the aggregation of the amyloid beta peptides (Aβ), fragments of the human amyloid precursor protein (hAPP). The dominating species are the Aβ40 and Aβ42 fragments with 40 and 42 amino acids, respectively. Aβ initially forms soluble oligomers that continue to expand to protofibrils, suggestively the neurotoxic intermediates, and thereafter turn into insoluble fibrils that are markers of the disease. Using the powerful tool of pharmacophore simulation, we selected small molecules not known to possess central nervous system (CNS) activity but that might interact with Aβ aggregation, from the NCI Chemotherapeutic Agents Repository, Bethesda, MD. We assessed the activity of these compounds on Aβ aggregation using the thioflavin T fluorescence correlation spectroscopy (ThT-FCS) assay. Förster resonance energy transfer-based fluorescence correlation spectroscopy (FRET-FCS) was used to characterize the dose-dependent activity of selected compounds at an early stage of Aβ aggregation. Transmission electron microscopy (TEM) confirmed that the interfering substances block fibril formation and identified the macrostructures of Aβ aggregates formed in their presence. We first found three compounds generating protofibrils with branching and budding never observed in the control. One compound generated a two-dimensional sheet structure and another generated a double-stranded filament. Importantly, these compounds generating protofibrils with altered macrostructure protected against Aβ-induced toxicity in a cell model while showing no toxicity in a model of cognition in normal mice. The data suggest that the active compounds act as decoys turning the aggregation into nontoxic trajectories and pointing toward novel approaches to therapy.

A cell-based high-throughput screen to identify small molecular weight stimulators of the innate immune system revealed substituted pyrimido[5,4-b]indoles as potent NFκB activators. The most potent hit compound selectively stimulated Toll-like receptor 4 (TLR4) in human and mouse cells. Synthetic modifications of the pyrimido[5,4-b]indole scaffold at the carboxamide, N-3, and N-5 positions revealed differential TLR4 dependent production of NFκB and type I interferon associated cytokines, IL-6 and interferon γ-induced protein 10 (IP-10) respectively. Specifically, a subset of compounds bearing phenyl and substituted phenyl carboxamides induced lower IL-6 release while maintaining higher IP-10 production, skewing toward the type I interferon pathway. Substitution at N-5 with short alkyl substituents reduced the cytotoxicity of the leading hit compound. Computational studies supported that active compounds appeared to bind primarily to MD-2 in the TLR4/MD-2 complex. These small molecules, which stimulate innate immune cells with minimal toxicity, could potentially be used as adjuvants or immune modulators.

Using the crystal structure of SARS-CoV-2 papain-like protease (PLpro) as a template, we developed a pharmacophore model of functional centers of the PLpro inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search identified 147 compounds that can be potential inhibitors of SARS-CoV-2 PLpro. The conformations of these compounds underwent 3D fingerprint similarity clusterization, followed by docking of possible conformers to the binding pocket of PLpro. Docking of random compounds to the binding pocket of protease was also done for comparison. Free energies of the docking interaction for the selected compounds were lower than for random compounds. The drug list obtained includes inhibitors of HIV, hepatitis C, and cytomegalovirus (CMV), as well as a set of drugs that have demonstrated some activity in MERS, SARS-CoV, and SARS-CoV-2 therapy. We recommend testing of the selected compounds for treatment of COVID-19.

Because imaging has a high sensitivity to diagnose hepatocellular carcinoma (HCC) and tissue biopsies carry risks such as bleeding, the latter are often not performed in HCC. Blood-derived circulating tumor DNA (ctDNA) analysis can identify somatic alterations, but its utility has not been characterized in HCC.

Tumor-associated neo-antigens are mutated peptides that allow the immune system to recognize the affected cell as foreign. Cells carrying excessive mutation load often develop mechanisms of tolerance. PD-L1/PD-1 checkpoint immunotherapy is a highly promising approach to overcome these protective signals and induce tumor shrinkage. Yet, the nature of the neo-antigens driving those beneficial responses remains unclear. Here, we show that APOBEC-related mutagenesis - a mechanism at the crossroads between anti-viral immunity and endogenous nucleic acid editing - increases neo-peptide hydrophobicity (a feature of immunogenicity), as demonstrated by in silico computation and in the TCGA pan-cancer cohort, where APOBEC-related mutagenesis was also strongly associated with immune marker expression. Moreover, APOBEC-related mutagenesis correlated with immunotherapy response in a cohort of 99 patients with diverse cancers, and this correlation was independent of the tumor mutation burden (TMB). Combining APOBEC-related mutagenesis estimate and TMB resulted in greater predictive ability than either parameter alone. Based on these results, further investigation of APOBEC-related mutagenesis as a marker of response to anti-cancer checkpoint blockade is warranted.

A significant percentage of Duchenne muscular dystrophy (DMD) cases are caused by premature termination codon (PTC) mutations in the dystrophin gene, leading to the production of a truncated, non-functional dystrophin polypeptide. PTC-suppressing compounds (PTCSC) have been developed in order to restore protein translation by allowing the incorporation of an amino acid in place of a stop codon. However, limitations exist in terms of efficacy and toxicity. To identify new compounds that have PTC-suppressing ability, we selected and clustered existing PTCSC, allowing for the construction of a common pharmacophore model. Machine learning (ML) and deep learning (DL) models were developed for prediction of new PTCSC based on known compounds. We conducted a search of the NCI compounds database using the pharmacophore-based model and a search of the DrugBank database using pharmacophore-based, ML and DL models. Sixteen drug compounds were selected as a consensus of pharmacophore-based, ML, and DL searches. Our results suggest notable correspondence of the pharmacophore-based, ML, and DL models in prediction of new PTC-suppressing compounds.

The objective of this research is, with the analysis of existing data of thyroid cancer (TC) metabolites, to develop a machine-learning model that can diagnose TC using metabolite biomarkers. Through data mining, pathway analysis, and machine learning (ML), the model was developed. We identified seven metabolic pathways related to TC: Pyrimidine metabolism, Tyrosine metabolism, Glycine, serine, and threonine metabolism, Pantothenate and CoA biosynthesis, Arginine biosynthesis, Phenylalanine metabolism, and Phenylalanine, tyrosine, and tryptophan biosynthesis. The ML classifications' accuracies were confirmed through 10-fold cross validation, and the most accurate classification was 87.30%. The metabolic pathways identified in relation to TC and the changes within such pathways can contribute to more pattern recognition for diagnostics of TC patients and assistance with TC screening. With independent testing, the model's accuracy for other unique TC metabolites was 92.31%. The results also point to a possibility for the development of using ML methods for TC diagnostics and further applications of ML in general cancer-related metabolite analysis.

Oligodendrocyte lineage transcription factor 2 (OLIG2) plays a pivotal role in glioma development. Here we conducted a comprehensive study of the critical gene regulatory networks involving OLIG2. These include the networks responsible for OLIG2 expression, its translocation to nucleus, cell cycle, epigenetic regulation, and Rho-pathway interactions. We described positive feedback loops including OLIG2: loops of epigenetic regulation and loops involving receptor tyrosine kinases. These loops may be responsible for the prolonged oncogenic activity of OLIG2. The proposed schemes for epigenetic regulation of the gene networks involving OLIG2 are confirmed by patient survival (Kaplan-Meier) curves based on the cancer genome atlas (TCGA) datasets. Finally, we elucidate the Coherent-Gene Modules (CGMs) networks-framework of OLIG2 involvement in cancer. We showed that genes interacting with OLIG2 formed eight CGMs having a set of intermodular connections. We showed also that among the genes involved in these modules the most connected hub is EGFR, then, on lower level, HSP90 and CALM1, followed by three lower levels including epigenetic genes KDM1A and NCOR1. The genes on the six upper levels of the hierarchy are involved in interconnections of all eight CGMs and organize functionally defined gene-signaling subnetworks having specific functions. For example, CGM1 is involved in epigenetic control. CGM2 is significantly related to cell proliferation and differentiation. CGM3 includes a number of interconnected helix-loop-helix transcription factors (bHLH) including OLIG2. Many of these TFs are partially controlled by OLIG2. The CGM4 is involved in PDGF-related: angiogenesis, tumor cell proliferation and differentiation. These analyses provide testable hypotheses and approaches to inhibit OLIG2 pathway and relevant feed-forward and feedback loops to be interrogated. This broad approach can be applied to other TFs.

Bovine leukemia virus (BLV) is a virus that infects cattle around the world and is very similar to the human T-cell leukemia virus (HTLV), which causes adult T-cell leukemia/lymphoma (ATL). Recently, presence of BLV DNA and protein was demonstrated in commercial bovine products and in humans. BLV DNA is generally found at higher rates in humans who have or will develop breast cancer, according to research done with subjects from several countries. These findings have led to a hypothesis that BLV transmission plays a role in breast cancer oncogenesis in humans. Here we summarize the current knowledge in the field.

Transcription factors (TFs) are fundamental in the regulation of gene expression in the development and differentiation of cells. They may act as oncogenes and when overexpressed in tumors become plausible targets for the design of antitumor agents. Homodimerization or heterodimerization of TFs are required for DNA binding and the association interface between subunits, for the design of allosteric modulators, appears as a privileged structure for the pharmacophore-based computational strategy. Based on this strategy, a set of compounds were earlier identified as potential suppressors of OLIG2 dimerization and found to inhibit tumor growth in a mouse glioblastoma cell line and in a whole-animal study. To investigate whether the antitumor activity is due to the predicted mechanism of action, we undertook a study of OLIG2 dimerization using fluorescence cross-correlation spectroscopy (FCCS) of live HEK cells transfected with 2 spectrally different OLIG2 clones. The selected compounds showed an effect with potency, which correlated with the earlier observed antitumor activity. The OLIG2 proteins showed change in diffusion time under compound treatment in line with dissociation from DNA. The data suggest a general approach of drug discovery based on the design of allosteric modulators of protein-protein interaction.

The endogenous catecholamine release-inhibitory peptide catestatin (CST) regulates events leading to hypertension and cardiovascular disease. Earlier we studied the structure of CST by NMR, molecular modeling, and amino acid scanning mutagenesis. That structure has now been exploited for elucidation of interface pharmacophores that mediate binding of CST to its target, with consequent secretory inhibition. Designed pharmacophore models allowed screening of 3D structural domains. Selected compounds were tested on both cultured catecholaminergic cells and an in vivo model of hypertension; in each case, the candidates showed substantial mimicry of native CST actions, with preserved or enhanced potency and specificity. The approach and compounds have thus enabled rational design of novel drug candidates for treatment of hypertension or autonomic dysfunction.

Successful control of the COVID-19 pandemic depends on vaccines that prevent transmission. The full-length Spike protein is highly immunogenic but the majority of antibodies do not target the virus: ACE2 interface. In an effort to affect the quality of the antibody response focusing it to the receptor-binding motif (RBM) we generated a series of conformationally-constrained immunogens by inserting solvent-exposed RBM amino acid residues into hypervariable loops of an immunoglobulin molecule. Priming C57BL/6 mice with plasmid (p)DNA encoding these constructs yielded a rapid memory response to booster immunization with recombinant Spike protein. Immune sera antibodies bound strongly to the purified receptor-binding domain (RBD) and Spike proteins. pDNA primed for a consistent response with antibodies efficient at neutralizing authentic WA1 virus and three variants of concern (VOC), B.1.351, B.1.617.2, and BA.1. We demonstrate that immunogens built on structure selection can be used to influence the quality of the antibody response by focusing it to a conserved site of vulnerability shared between wildtype virus and VOCs, resulting in neutralizing antibodies across variants.

We developed a machine-learning system for the selective diagnostics of adenocarcinoma (AD), squamous cell carcinoma (SQ), and small-cell carcinoma lung (SC) cancers based on their metabolomic profiles. The system is organized as two-stage binary classifiers. The best accuracy for classification is 92%. We used the biomarkers sets that contain mostly metabolites related to cancer development. Compared to traditional methods, which exclude hierarchical classification, our method splits a challenging multiclass task into smaller tasks. This allows a two-stage classifier, which is more accurate in the scenario of lung cancer classification. Compared to traditional methods, such a "divide and conquer strategy" gives much more accurate and explainable results. Such methods, including our algorithm, allow for the systematic tracking of each computational step.