Rational peptide design for targeting cancer cell invasion.

Cell invasion is an important process in cancer progression and recurrence. Invasion and implantation of cancer cells from their original place to other tissues, by disabling vital organs, challenges the treatment of cancer patients. Given the importance of the matter, many molecular treatments have been developed to inhibit cancer cell invasion. Because of their low production cost and ease of production, peptides are valuable therapeutic molecules for inhibiting cancer cell invasion. In recent years, advances in the field of computational biology have facilitated the design of anti-cancer peptides. In our investigation, using computational biology approaches such as evolutionary analysis, residue scanning, protein-peptide interaction analysis, molecular dynamics, and free energy analysis, our team designed a peptide library with about 100 000 candidates based on A6 (acetyl-KPSSPPEE-amino) sequence which is an anti-invasion peptide. During computational studies, two of the designed peptides that give the highest scores and showed the greatest sequence similarity to A6 were entered into the experimental analysis workflow for further analysis. In experimental analysis steps, the anti-metastatic potency and other therapeutic effects of designed peptides were evaluated using MTT assay, RT-qPCR, zymography analysis, and invasion assay. Our study disclosed that the IK1 (acetyl-RPSFPPEE-amino) peptide, like A6, has great potency to inhibit the invasion of cancer cells.

REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation.

REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a major update of the underlying estimation method with penalized beta regression, which demonstrates great reliability and accuracy in dose estimation and uncertainty quantification. In this note, we describe the method and implementation of REAP-2 with a highlight on potency estimation and drug comparison.

Vitamin D Receptor Antagonist MeTC7 Inhibits PD-L1.

Small-molecule inhibitors of PD-L1 are postulated to control immune evasion in tumors similar to antibodies that target the PD-L1/PD-1 immune checkpoint axis. However, the identity of targetable PD-L1 inducers is required to develop small-molecule PD-L1 inhibitors. In this study, using chromatin immunoprecipitation (ChIP) assay and siRNA, we demonstrate that vitamin D/VDR regulates PD-L1 expression in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) cells. We have examined whether a VDR antagonist, MeTC7, can inhibit PD-L1. To ensure that MeTC7 inhibits VDR/PD-L1 without off-target effects, we examined competitive inhibition of VDR by MeTC7, utilizing ligand-dependent dimerization of VDR-RXR, RXR-RXR, and VDR-coactivators in a mammalian 2-hybrid (M2H) assay. MeTC7 inhibits VDR selectively, suppresses PD-L1 expression sparing PD-L2, and inhibits the cell viability, clonogenicity, and xenograft growth of AML cells. MeTC7 blocks AML/mesenchymal stem cells (MSCs) adhesion and increases the efferocytotic efficiency of THP-1 AML cells. Additionally, utilizing a syngeneic colorectal cancer model in which VDR/PD-L1 co-upregulation occurs in vivo under radiation therapy (RT), MeTC7 inhibits PD-L1 and enhances intra-tumoral CD8+T cells expressing lymphoid activation antigen-CD69. Taken together, MeTC7 is a promising small-molecule inhibitor of PD-L1 with clinical potential.

Urolithin A analog inhibits castration-resistant prostate cancer by targeting the androgen receptor and its variant, androgen receptor-variant 7.

We investigated the efficacy of a small molecule ASR-600, an analog of Urolithin A (Uro A), on blocking androgen receptor (AR) and its splice variant AR-variant 7 (AR-V7) signaling in castration-resistant prostate cancer (CRPC). ASR-600 effectively suppressed the growth of AR+ CRPC cells by inhibiting AR and AR-V7 expressions; no effect was seen in AR- CRPC and normal prostate epithelial cells. Biomolecular interaction assays revealed ASR-600 binds to the N-terminal domain of AR, which was further confirmed by immunoblot and subcellular localization studies. Molecular studies suggested that ASR-600 promotes the ubiquitination of AR and AR-V7 resulting in the inhibition of AR signaling. Microsomal and plasma stability studies suggest that ASR-600 is stable, and its oral administration inhibits tumor growth in CRPC xenografted castrated and non-castrated mice. In conclusion, our data suggest that ASR-600 enhances AR ubiquitination in both AR+ and AR-V7 CRPC cells and inhibits their growth in vitro and in vivo models.

Peptidomimetics in cancer targeting.

The low efficiency of treatment strategies is one of the main obstacles to developing cancer inhibitors. Up to now, various classes of therapeutics have been developed to inhibit cancer progression. Peptides due to their small size and easy production compared to proteins are highly regarded in designing cancer vaccines and oncogenic pathway inhibitors. Although peptides seem to be a suitable therapeutic option, their short lifespan, instability, and low binding affinity for their target have not been widely applicable against malignant tumors. Given the peptides' disadvantages, a new class of agents called peptidomimetic has been introduced. With advances in physical chemistry and biochemistry, as well as increased knowledge about biomolecule structures, it is now possible to chemically modify peptides to develop efficient peptidomimetics. In recent years, numerous studies have been performed to the evaluation of the effectiveness of peptidomimetics in inhibiting metastasis, angiogenesis, and cancerous cell growth. Here, we offer a comprehensive review of designed peptidomimetics to diagnose and treat cancer.

Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation.

The median-effect equation has been widely used to describe the dose-response relationship and identify compounds that activate or inhibit specific disease targets in contemporary drug discovery. However, the experimental data often contain extreme responses, which may significantly impair the estimation accuracy and impede valid quantitative assessment in the standard estimation procedure. To improve the quantitative estimation of the dose-response relationship, we introduce a novel approach based on robust beta regression. Substantive simulation studies under various scenarios demonstrate solid evidence that the proposed approach consistently provides robust estimation for the median-effect equation, particularly when there are extreme outcome observations. Moreover, simulation studies illustrate that the proposed approach also provides a narrower confidence interval, suggesting a higher power in statistical testing. Finally, to efficiently and conveniently perform common lab data analyses, we develop a freely accessible web-based analytic tool to facilitate the quantitative implementation of the proposed approach for the scientific community.

Finding a new drug which is both safe and efficient is an expensive and time-consuming endeavour. In particular, establishing the 'dose-effect relationship' ­ how beneficial a drug is at different dosages ­ can be challenging. Predicting this curve requires gathering experimental data by exposing and recording how cells respond to various levels of the drug. However, extreme values are often observed at low and high dosages, potentially introducing errors that are hard to correct in the prediction process. Yet, these extreme observations are sometimes genuine so researchers cannot just ignore them. To improve dose-effect estimation, Zhou, Liu, Fang et al. developed a new general-purpose approach. It uses advanced statistical modelling to account for extremes in lab data. This strategy outperformed other methods when dealing with these observations while also providing higher efficiency in data analysis with more uniform data in experiments. To facilitate implementation, Zhou, Liu, Fang et al. set up a user-friendly tool baptized 'REAP'; this free online resource allows scientists without advanced statistical experience to harness the new approach and to perform dose-effect analysis more easily and accurately. This could boost research across many different disciplines that examine the effects of chemicals on cells.

Evaluation of pH change effects on the HSA folding and its drug binding characteristics, a computational biology investigation.

The binding of therapeutics to human serum albumin (HSA), which is an abundant protein in plasma poses a major challenge in drug discovery. Although HSA has several binding pockets, the binding site I on D2 and binding site II on D3 are the main binding pockets of HSA. To date, a few experiments have been conducted to examine the effects of the potential of hydrogen (pH) changes on HSA attributes. In the present investigation, the effect of acidic (pH 7.1) and basic states (pH 7.7) on HSA structure and its drug binding potency were examined in comparison with the physiological state (pH 7.4). For this purpose, molecular dynamics (MD), free energy landscape (FEL), principal component analysis (PCA), probability distribution function (PDF), tunnel-cavity investigation, secondary structure analysis, docking study, and free energy investigation were employed to investigate the effect of pH changes on the structural characteristics of HSA at the atomic level. The results obtained from this study revealed the significant effect of pH alterations on the secondary and tertiary structure of HSA. In addition, HSA stability and its drug binding ability can be severely affected following pH changes. Given that pH change frequently occurs in various diseases such as cancer, diabetes, and kidney failure, therefore, pharmaceutical companies should allocate specific consideration to this subject throughout their drug design experiments.

Identification of a Vitamin-D Receptor Antagonist, MeTC7, which Inhibits the Growth of Xenograft and Transgenic Tumors In Vivo.

Vitamin-D receptor (VDR) mRNA is overexpressed in neuroblastoma and carcinomas of lung, pancreas, and ovaries and predicts poor prognoses. VDR antagonists may be able to inhibit tumors that overexpress VDR. However, the current antagonists are arduous to synthesize and are only partial antagonists, limiting their use. Here, we show that the VDR antagonist MeTC7 (5), which can be synthesized from 7-dehydrocholesterol (6) in two steps, inhibits VDR selectively, suppresses the viability of cancer cell-lines, and reduces the growth of the spontaneous transgenic TH-MYCN neuroblastoma and xenografts in vivo. The VDR selectivity of 5 against RXRα and PPAR-γ was confirmed, and docking studies using VDR-LBD indicated that 5 induces major changes in the binding motifs, which potentially result in VDR antagonistic effects. These data highlight the therapeutic benefits of targeting VDR for the treatment of malignancies and demonstrate the creation of selective VDR antagonists that are easy to synthesize.

mRNA vaccines for cancer immunotherapy.

Immunotherapy has emerged as a breakthrough strategy in cancer treatment. mRNA vaccines are an attractive and powerful immunotherapeutic platform against cancer because of their high potency, specificity, versatility, rapid and large-scale development capability, low-cost manufacturing potential, and safety. Recent technological advances in mRNA vaccine design and delivery have accelerated mRNA cancer vaccines' development and clinical application. In this review, we present various cancer vaccine platforms with a focus on nucleic acid vaccines. We discuss rational design and optimization strategies for mRNA cancer vaccine development. We highlight the platforms available for delivery of the mRNA vaccines with a focus on lipid nanoparticles (LNPs) based delivery systems. Finally, we discuss the limitations of mRNA cancer vaccines and future challenges.

Whole proteome mapping of compound-protein interactions.

Off-target binding is one of the primary causes of toxic side effects of drugs in clinical development, resulting in failures of clinical trials. While off-target drug binding is a known phenomenon, experimental identification of the undesired protein binders can be prohibitively expensive due to the large pool of possible biological targets. Here, we propose a new strategy combining chemical similarity principle and deep learning to enable proteome-wide mapping of compound-protein interactions. We have developed a pipeline to identify the targets of bioactive molecules by matching them with chemically similar annotated "bait" compounds and ranking them with deep learning. We have constructed a user-friendly web server for drug-target identification based on chemical similarity (DRIFT) to perform searches across annotated bioactive compound datasets, thus enabling high-throughput, multi-ligand target identification, as well as chemical fragmentation of target-binding moieties.

Mechanical Counterbalance of Kinesin and Dynein Motors in a Microtubular Network Regulates Cell Mechanics, 3D Architecture, and Mechanosensing.

Microtubules (MTs) and MT motor proteins form active 3D networks made of unstretchable cables with rod-like bending mechanics that provide cells with a dynamically changing structural scaffold. In this study, we report an antagonistic mechanical balance within the dynein-kinesin microtubular motor system. Dynein activity drives the microtubular network inward compaction, while isolated activity of kinesins bundles and expands MTs into giant circular bands that deform the cell cortex into discoids. Furthermore, we show that dyneins recruit MTs to sites of cell adhesion, increasing the topographic contact guidance of cells, while kinesins antagonize it via retraction of MTs from sites of cell adhesion. Actin-to-microtubule translocation of septin-9 enhances kinesin-MT interactions, outbalances the activity of kinesins over that of dyneins, and induces the discoid architecture of cells. These orthogonal mechanisms of MT network reorganization highlight the existence of an intricate mechanical balance between motor activities of kinesins and dyneins that controls cell 3D architecture, mechanics, and cell-microenvironment interactions.

Identification and characterization of novel candidate compounds targeting 6- and 7-transmembrane µ-opioid receptor isoforms.

BACKGROUND AND PURPOSE: The µ-opioid receptor (µ receptor) is the primary target for opioid analgesics. The 7-transmembrane (TM) and 6TM µ receptor isoforms mediate inhibitory and excitatory cellular effects. Here, we developed compounds selective for 6TM- or 7TM-µ receptors to further our understanding of the pharmacodynamic properties of µ receptors. EXPERIMENTAL APPROACH: We performed virtual screening of the ZINC Drug Now library of compounds using in silico 7TM- and 6TM-µ receptor structural models and identified potential compounds that are selective for 6TM- and/or 7TM-µ receptors. Subsequently, we characterized the most promising candidate compounds in functional in vitro studies using Be2C neuroblastoma transfected cells, behavioural in vivo pain assays using various knockout mice and in ex vivo electrophysiology studies. KEY RESULTS: Our virtual screen identified 30 potential candidate compounds. Subsequent functional in vitro cellular assays shortlisted four compounds (#5, 10, 11 and 25) that demonstrated 6TM- or 7TM-µ receptor-dependent NO release. In in vivo pain assays these compounds also produced dose-dependent hyperalgesic responses. Studies using mice that lack specific opioid receptors further established the µ receptor-dependent nature of identified novel ligands. Ex vivo electrophysiological studies on spontaneous excitatory postsynaptic currents in isolated spinal cord slices also validated the hyperalgesic properties of the most potent 6TM- (#10) and 7TM-µ receptor (#5) ligands. CONCLUSION AND IMPLICATIONS: Our novel compounds represent a new class of ligands for µ receptors and will serve as valuable research tools to facilitate the development of opioids with significant analgesic efficacy and fewer side-effects.

Activating Sphingosine-1-phospahte signaling in endothelial cells increases myosin light chain phosphorylation to decrease endothelial permeability thereby inhibiting cancer metastasis.

Targeting the metastatic process to prevent disease dissemination in cancer remains challenging. One step in the metastatic cascade involves cancer cells transiting through the vascular endothelium after inflammation has increased the permeability of this cellular layer. Reducing inflammation-mediated gaps in the vascular endothelium could potentially be used to retard metastasis. This study describes the development of a novel ASR396-containing nanoparticle designed to activate the Sphingosine-1-Phosphate Receptor 1 (S1PR1) in order to tighten the junctions between the endothelial cells lining the vascular endothelium thereby inhibiting metastasis. ASR396 was derived from the S1PR1 agonist SEW2871 through chemical modification enabling the new compound to be loaded into a nanoliposome. ASR396 retained S1PR1 binding activity and the nanoliposomal formulation (nanoASR396) made it systemically bioavailable upon intravenous injection. Studies conducted in microvessels demonstrated that nanoASR396 significantly attenuated inflammatory mediator-induced permeability increase through the S1PR1 activation. Similarly, nanoASR396 inhibited gap formation mediated by inflammatory agents on an endothelial cell monolayer by decreasing levels of phosphorylated myosin light chain protein thereby inhibiting cellular contractility. In animal models, nanoASR396 inhibited lung metastasis by up to 80%, indicating its potential for retarding melanoma metastasis. Thus, a novel bioavailable nanoparticle-based S1PR1 agonist has been developed to negate the effects of inflammatory mediators on the vascular endothelium in order to reduce the metastatic dissemination of cancer cells.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis.

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aß, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Modifications to the Framework Regions Eliminate Chimeric Antigen Receptor Tonic Signaling.

Chimeric antigen receptor (CAR) tonic signaling, defined as spontaneous activation and release of proinflammatory cytokines by CAR-T cells, is considered a negative attribute because it leads to impaired antitumor effects. Here, we report that CAR tonic signaling is caused by the intrinsic instability of the mAb single-chain variable fragment (scFv) to promote self-aggregation and signaling via the CD3ζ chain incorporated into the CAR construct. This phenomenon was detected in a CAR encoding either CD28 or 4-1BB costimulatory endodomains. Instability of the scFv was caused by specific amino acids within the framework regions (FWR) that can be identified by computational modeling. Substitutions of the amino acids causing instability, or humanization of the FWRs, corrected tonic signaling of the CAR, without modifying antigen specificity, and enhanced the antitumor effects of CAR-T cells. Overall, we demonstrated that tonic signaling of CAR-T cells is determined by the molecular instability of the scFv and that computational analyses of the scFv can be implemented to correct the scFv instability in CAR-T cells with either CD28 or 4-1BB costimulation.

Alternative Splicing of Opioid Receptor Genes Shows a Conserved Pattern for 6TM Receptor Variants.

The opioid receptor (OPR) family comprises the mu-, delta-, and kappa-opioid, and nociceptin receptors that belong to the superfamily of 7-transmembrane spanning G protein-coupled receptors (GPCRs). The mu-opioid receptor is the main target for clinically used opioid analgesics, and its biology has been extensively studied. The N-terminally truncated 6TM receptors isoform produced through alternative splicing of the OPRM1 gene displays unique signaling and analgesic properties, but it is unclear if other OPRs have the same ability. In this study, we have built a comprehensive map of alternative splicing events that produce 6TM receptor variants in all the OPRs and demonstrated their evolutionary conservation. We then obtained evidence for their translation through ribosomal footprint analysis. We discovered that N-terminally truncated 6TM GPCRs are rare in the human genome and OPRs are overrepresented in this group. Finally, we also observed a significant enrichment of 6TM GPCR genes among genes associated with pain, psychiatric disorders, and addiction. Understanding the biology of 6TM receptors and leveraging this knowledge for drug development should pave the way for novel therapies.

ASR490, a Small Molecule, Overrides Aberrant Expression of Notch1 in Colorectal Cancer.

Notch1 activation triggers significant oncogenic signaling that manifests as enhanced metastatic potential and tumorigenesis in colorectal cancer. Novel small-molecule inhibitors, mainly plant-derived analogs, have low toxicity profiles and higher bioavailability. In this study, we have developed a small molecule, ASR490, by modifying structure of naturally occurring compound Withaferin A. ASR490 showed a growth-inhibitory potential by downregulating Notch1 signaling in HCT116 and SW620 cell lines. Docking studies and thermal shift assays confirmed that ASR490 binds to Notch1, whereas no changes in Notch2 and Notch3 expression were seen in colorectal cancer cells. Notch1 governs epithelial-to-mesenchymal transition signaling and is responsible for metastasis, which was abolished by ASR490 treatment. To further confirm the therapeutic potential of ASR490, we stably overexpressed Notch1 in HCT-116 cells and determined its inhibitory potential in transfected colorectal cancer (Notch1/HCT116) cells. ASR490 effectively prevented cell growth in both the vector (P = 0.005) and Notch1 (P = 0.05) transfectants. The downregulation of Notch1 signaling was evident, which corresponded with downregulation of mesenchymal markers, including N-cadherin and ß-catenin and induction of E-cadherin in HCT-116 transfectants. Intraperitoneal administration of a 1% MTD dose of ASR490 (5 mg/kg) effectively suppressed the tumor growth in control (pCMV/HCT116) and Notch1/HCT116 in xenotransplanted mice. In addition, downregulation of Notch1 and survival signaling in ASR-treated tumors confirmed the in vitro results. In conclusion, ASR490 appears to be a potent agent that can inhibit Notch1 signaling in colorectal cancer.

Various miRNAs compensate the role of miR-122 on HCV replication.

One of the determinants for tissue tropism of hepatitis C virus (HCV) is miR-122, a liver-specific microRNA. Recently, it has been reported that interaction of miR-122 to HCV RNA induces a conformational change of the 5'UTR internal ribosome entry site (IRES) structure to form stem-loop II structure (SLII) and hijack of translating 80S ribosome through the binding of SLIII to 40S subunit, which leads to efficient translation. On the other hand, low levels of HCV-RNA replication have also been detected in some non-hepatic cells; however, the details of extrahepatic replication remain unknown. These observations suggest the possibility that miRNAs other than miR-122 can support efficient replication of HCV-RNA in non-hepatic cells. Here, we identified a number of such miRNAs and show that they could be divided into two groups: those that bind HCV-RNA at two locations (miR-122 binding sites I and II), in a manner similar to miR-122 (miR-122-like), and those that target a single site that bridges sites I and II and masking both G28 and C29 in the 5'UTR (non-miR-122-like). Although the enhancing activity of these non-hepatic miRNAs were lower than those of miR-122, substantial expression was detected in various normal tissues. Furthermore, structural modeling indicated that both miR-122-like and non-miR-122-like miRNAs not only can facilitate the formation of an HCV IRES SLII but also can stabilize IRES 3D structure in order to facilitate binding of SLIII to the ribosome. Together, these results suggest that HCV facilitates miR-122-independent replication in non-hepatic cells through recruitment of miRNAs other than miR-122. And our findings can provide a more detailed mechanism of miR-122-dependent enhancement of HCV-RNA translation by focusing on IRES tertiary structure.

Development of a Novel Multi-Isoform ALDH Inhibitor Effective as an Antimelanoma Agent.

The aldehyde dehydrogenases (ALDH) are a major family of detoxifying enzymes that contribute to cancer progression and therapy resistance. ALDH overexpression is associated with a poor prognosis in many cancer types. The use of multi-ALDH isoform or isoform-specific ALDH inhibitors as anticancer agents is currently hindered by the lack of viable candidates. Most multi-ALDH isoform inhibitors lack bioavailability and are nonspecific or toxic, whereas most isoform-specific inhibitors are not effective as monotherapy due to the overlapping functions of ALDH family members. The present study details the development of a novel, potent, multi-isoform ALDH inhibitor, called KS100. The rationale for drug development was that inhibition of multiple ALDH isoforms might be more efficacious for cancer compared with isoform-specific inhibition. Enzymatic IC50s of KS100 were 207, 1,410, and 240 nmol/L toward ALDH1A1, 2, and 3A1, respectively. Toxicity of KS100 was mitigated by development of a nanoliposomal formulation, called NanoKS100. NanoKS100 had a loading efficiency of approximately 69% and was stable long-term. NanoKS100 was 5-fold more selective for killing melanoma cells compared with normal human fibroblasts. NanoKS100 administered intravenously at a submaximal dose (3-fold lower) was effective at inhibiting xenografted melanoma tumor growth by approximately 65% without organ-related toxicity. Mechanistically, inhibition by KS100 significantly reduced total cellular ALDH activity to increase reactive oxygen species generation, lipid peroxidation, and accumulation of toxic aldehydes leading to apoptosis and autophagy. Collectively, these data suggest the successful preclinical development of a nontoxic, bioavailable, nanoliposomal formulation containing a novel multi-ALDH isoform inhibitor effective in the treatment of cancer.

Computationally Guided Design of Single-Chain Variable Fragment Improves Specificity of Chimeric Antigen Receptors.

Chimeric antigen receptor (CAR)-T cell-based immunotherapy of malignant disease relies on the specificity and association constant of single-chain variable fragments (scFvs). The latter are synthesized from parent antibodies by fusing their light (VL) and heavy (VH)-chain variable domains into a single chain using a flexible linker peptide. The fusion of VL and VH domains can distort their relative orientation, thereby compromising specificity and association constant of scFv, and reducing the lytic efficacy of CAR-T cells. Here, we circumvent the complications of domains' fusion by designing scFv mutants that stabilize interaction between scFv and its target, thereby rescuing scFv efficacy. We employ an iterative approach, based on structural modeling and mutagenesis driven by computational protein design. To demonstrate the power of this approach, we use the scFv derived from an antibody specific to a human leukocyte antigen A2 (HLA-A2)-HER2-derived peptide complex. Whereas the parental antibody is highly specific to its target, the scFv showed reduced specificity. Using our approach, we design mutations into scFvs that restore specificity of the original antibody.