Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication.

BACKGROUND: Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered. AIM: To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy. METHODS: Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature. RESULTS: The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis. CONCLUSION: The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

Exploring the regulatory mechanism of intestinal flora based on PD-1 receptor/ligand targeted cancer immunotherapy.

Serving as a pivotal immunotherapeutic approach against tumors, anti-PD-1/PD-L1 therapy amplifies the immune cells' capability to eliminate tumors by obstructing the interaction between PD-1 and PD-L1. Research indicates that immune checkpoint inhibitors are effective when a patient's gut harbors unique beneficial bacteria. As such, it has further been revealed that the gut microbiome influences tumor development and the efficacy of cancer treatments, with metabolites produced by the microbiome playing a regulatory role in the antitumor efficacy of Immune checkpoint inhibitors(ICBs). This article discusses the mechanism of anti-PD-1 immunotherapy and the role of intestinal flora in immune regulation. This review focuses on the modulation of intestinal flora in the context of PD-1 immunotherapy, which may offer a new avenue for combination therapy in tumor immunotherapy.

Chromatography affinity resin with photosynthetically-sourced protein A ligand.

Green, photosynthesizing plants can be proficiently used as cost-effective, single-use, fully biodegradable bioreactors for environmentally-friendly production of a variety of valuable recombinant proteins. Being near-infinitely scalable and most energy-efficient in generating biomass, plants represent profoundly valid alternatives to conventionally used stationary fermenters. To validate this, we produced a plastome-engineered tobacco bioreactor line expressing a recombinant variant of the protein A from Staphylococcus aureus, an affinity ligand widely useful in antibody purification processes, reaching accumulation levels up to ~ 250 mg per 1 kg of fresh leaf biomass. Chromatography resin manufactured from photosynthetically-sourced recombinant protein A ligand conjugated to agarose beads demonstrated the innate pH-driven ability to bind and elute IgG-type antibodies and allowed one-step efficient purification of functional monoclonal antibodies from the supernatants of the producing hybridomas. The results of this study emphasize the versatility of plant-based recombinant protein production and illustrate its vast potential in reducing the cost of diverse biotechnological applications, particularly the downstream processing and purification of monoclonal antibodies.

Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch.

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

The Three-Dimensional Reference Interaction Site Model Approach as a Promising Tool for Studying Hydrated Viruses and Their Complexes with Ligands.

Viruses are the most numerous biological form living in any ecosystem. Viral diseases affect not only people but also representatives of fauna and flora. The latest pandemic has shown how important it is for the scientific community to respond quickly to the challenge, including critically assessing the viral threat and developing appropriate measures to counter this threat. Scientists around the world are making enormous efforts to solve these problems. In silico methods, which allow quite rapid obtention of, in many cases, accurate information in this field, are effective tools for the description of various aspects of virus activity, including virus-host cell interactions, and, thus, can provide a molecular insight into the mechanism of virus functioning. The three-dimensional reference interaction site model (3D-RISM) seems to be one of the most effective and inexpensive methods to compute hydrated viruses, since the method allows us to provide efficient calculations of hydrated viruses, remaining all molecular details of the liquid environment and virus structure. The pandemic challenge has resulted in a fast increase in the number of 3D-RISM calculations devoted to hydrated viruses. To provide readers with a summary of this literature, we present a systematic overview of the 3D-RISM calculations, covering the period since 2010. We discuss various biophysical aspects of the 3D-RISM results and demonstrate capabilities, limitations, achievements, and prospects of the method using examples of viruses such as influenza, hepatitis, and SARS-CoV-2 viruses.

Identifying Residues for Substrate Recognition in Human GPAT4 by Molecular Dynamics Simulations.

Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the first step in triacylglycerol synthesis. Understanding its substrate recognition mechanism may help to design drugs to regulate the production of glycerol lipids in cells. In this work, we investigate how the native substrate, glycerol-3-phosphate (G3P), and palmitoyl-coenzyme A (CoA) bind to the human GPAT isoform GPAT4 via molecular dynamics simulations (MD). As no experimentally resolved GPAT4 structure is available, the AlphaFold model is employed to construct the GPAT4-substrate complex model. Using another isoform, GPAT1, we demonstrate that once the ligand binding is properly addressed, the AlphaFold complex model can deliver similar results to the experimentally resolved structure in MD simulations. Following the validated protocol of complex construction, we perform MD simulations using the GPAT4-substrate complex. Our simulations reveal that R427 is an important residue in recognizing G3P via a stable salt bridge, but its motion can bring the ligand to different binding hotspots on GPAT4. Such high flexibility can be attributed to the flexible region that exists only on GPAT4 and not on GPAT1. Our study reveals the substrate recognition mechanism of GPAT4 and hence paves the way towards designing GPAT4 inhibitors.

Zinc(II) Iminopyridine Complexes as Antibacterial Agents: A Structure-to-Activity Study.

Antibiotic resistance is currently a global health emergency. Metallodrugs, especially metal coordination complexes, comprise a broad variety of candidates to combat antibacterial infections. In this work, we designed a new family of Schiff base zinc(II) complexes with iminopyridine as an organic ligand and different inorganic ligands: chloride, nitrate, and acetate. The antibacterial effect of the Zn(II) complexes was studied against planktonic bacterial cells of Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative) strains. The results showed a moderate biocide activity in both types of planktonic bacteria, which arises from the metal complexation to the Schiff base ligand. Importantly, we confirmed the crucial effect of the metal, with Zn(II) improving the activity of Cu(II) counterparts previously reported. On the other hand, the impact of the inorganic ligands was not significant for the antibacterial effect but was relevant for the complex solubility. Finally, as proof of concept of topical antibacterial formulation, we formulated an emulsion containing the most lipophilic Zn(II) complex and confirmed a sustained release for 24 h in a vertical cell diffusion assay. The promising activity of iminopyridine Zn(II) complexes is potentially worth exploring in more detailed studies.

In Vitro and In Vivo Pharmacological Profiles of LENART01, a Dermorphin-Ranatensin Hybrid Peptide.

Diverse chemical and pharmacological strategies are currently being explored to minimize the unwanted side effects of currently used opioid analgesics while achieving effective pain relief. The use of multitarget ligands with activity at more than one receptor represents a promising therapeutic approach. We recently reported a bifunctional peptide-based hybrid LENART01 combining dermorphin and ranatensin pharmacophores, which displays activity to the mu-opioid receptor (MOR) and dopamine D2 receptor (D2R) in rat brains and spinal cords. In this study, we investigated the in vitro binding and functional activities to the human MOR and the in vivo pharmacology of LENART01 in mice after subcutaneous administration. In vitro binding assays showed LENART01 to bind and be selective to the human MOR over the other opioid receptor subtypes and delta, kappa and nociceptin receptors. In the [35S]GTPγS binding assay, LENART01 acted as a potent and full agonist to the human MOR. In mice, LENART01 produced dose-dependent antinociceptive effects in formalin-induced inflammatory pain, with increased potency than morphine. Antinociceptive effects were reversed by naloxone, indicating MOR activation in vivo. Behavioral studies also demonstrated LENART01's properties to induce less adverse effects without locomotor dysfunction and withdrawal syndrome compared to conventional opioid analgesics, such as morphine. LENART01 is the first peptide-based MOR-D2R ligand known to date and the first dual MOR-dopamine D2R ligand for which in vivo pharmacology is reported with antinociceptive efficacy and reduced opioid-related side effects. Our current findings may pave the way to new pain therapeutics with limited side effects in acute and chronic use.

Conformation-Associated C···dz2-PtII Tetrel Bonding: The Case of Cyclometallated Platinum(II) Complex with 4-Cyanopyridyl Urea Ligand.

The nucleophilic addition of 3-(4-cyanopyridin-2-yl)-1,1-dimethylurea (1) to cis-[Pt(CNXyl)2Cl2] (2) gave a new cyclometallated compound 3. It was characterized by NMR spectroscopy (1H, 13C, 195Pt) and high-resolution mass spectrometry, as well as crystallized to obtain two crystalline forms (3 and 3·2MeCN), whose structures were determined by X-ray diffraction. In the crystalline structure of 3, two conformers (3A and 3B) were identified, while the structure 3·2MeCN had only one conformer 3A. The conformers differed by orientation of the N,N-dimethylcarbamoyl moiety relative to the metallacycle plane. In both crystals 3 and 3·2MeCN, the molecules of the Pt(II) complex are associated into supramolecular dimers, either {3A}2 or {3B}2, via stacking interactions between the planes of two metal centers, which are additionally supported by hydrogen bonding. The theoretical consideration, utilizing a number of computational approaches, demonstrates that the C···dz2(Pt) interaction makes a significant contribution in the total stacking forces in the geometrically optimized dimer [3A]2 and reveals the dz2(Pt)→π*(PyCN) charge transfer (CT). The presence of such CT process allowed for marking the C···Pt contact as a new example of a rare studied phenomenon, namely, tetrel bonding, in which the metal site acts as a Lewis base (an acceptor of noncovalent interaction).

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

CONTEXT: SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R2 = 0.55), demonstrating a significant advantage over the MM/PBSA (R2 = 0.02) and MM/GBSA (R2 = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors. METHODS: All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.

Monophosphoryl Lipid A-based Adjuvant to Promote the Immunogenicity of Multivalent Meningococcal Polysaccharide Conjugate Vaccines.

Activation of the adaptive immune system requires the engagement of costimulatory pathways in addition to B and T cell Ag receptor signaling, and adjuvants play a central role in this process. Many Gram-negative bacterial polysaccharide vaccines, including the tetravalent meningococcal conjugate vaccines (MCV4) and typhoid Vi polysaccharide vaccines, do not incorporate adjuvants. The immunogenicity of typhoid vaccines is due to the presence of associated TLR4 ligands in these vaccines. Because the immunogenicity of MCV4 is poor and requires boosters, I hypothesized that TLR4 ligands are absent in MCV4 and that incorporation of a TLR4 ligand-based adjuvant would improve their immunogenicity. Consistent with this hypothesis, two Food and Drug Administration-approved MCV4 vaccines, MENVEO and MenQuadfi, lack TLR4 ligands. Admixing monophosphoryl lipid A, a TLR4 ligand-based adjuvant formulation named "Turbo" with MCV4 induced significantly improved IgM and IgG responses to all four meningococcal serogroup polysaccharides in adult and aged mice after a single immunization. Furthermore, in infant mice, a single booster was sufficient to promote a robust IgG response and 100% seroconversion when MCV4 was adjuvanted with Turbo. Turbo upregulated the expression of the costimulatory molecules CD40 and CD86 on B cells, and Turbo-driven adjuvanticity is lost in mice deficient in CD40 and CD86. These data suggest that Turbo induces the required costimulatory molecules for its adjuvant activity and that incorporation of Turbo could make bacterial polysaccharide vaccines more immunogenic, minimize booster requirements, and be cost-effective, particularly for those individuals in low- and middle-income and disease-endemic countries.

Programmed cell death-ligand 2: new insights in cancer.

Immunotherapy has revolutionized cancer treatment, with the anti-PD-1/PD-L1 axis therapy demonstrating significant clinical efficacy across various tumor types. However, it should be noted that this therapy is not universally effective for all PD-L1-positive patients, highlighting the need to expedite research on the second ligand of PD-1, known as Programmed Cell Death Receptor Ligand 2 (PD-L2). As an immune checkpoint molecule, PD-L2 was reported to be associated with patient's prognosis and plays a pivotal role in cancer cell immune escape. An in-depth understanding of the regulatory process of PD-L2 expression may stratify patients to benefit from anti-PD-1 immunotherapy. Our review focuses on exploring PD-L2 expression in different tumors, its correlation with prognosis, regulatory factors, and the interplay between PD-L2 and tumor treatment, which may provide a notable avenue in developing immune combination therapy and improving the clinical efficacy of anti-PD-1 therapies.

The predictive value of PD-L1 expression in response to anti-PD-1/PD-L1 therapy for biliary tract cancer: a systematic review and meta-analysis.

Background: Recently, anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) immunotherapy offers promising results for advanced biliary tract cancer (BTC). However, patients show highly heterogeneous responses to treatment, and predictive biomarkers are lacking. We performed a systematic review and meta-analysis to assess the potential of PD-L1 expression as a biomarker for treatment response and survival in patients with BTC undergoing anti-PD-1/PD-L1 therapy. Methods: We conducted a comprehensive systematic literature search through June 2023, utilizing the PubMed, EMBASE, and Cochrane Library databases. The outcomes of interest included objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) according to PD-L1 expression. Subgroup analyses and meta-regression were performed to identify possible sources of heterogeneity. Results: A total of 30 studies was included in the final analysis. Pooled analysis showed no significant differences in ORR (odds ratio [OR], 1.56; 95% confidence intervals [CIs], 0.94-2.56) and DCR (OR, 1.84; 95% CIs, 0.88-3.82) between PD-L1 (+) and PD-L1 (-) patients. In contrast, survival analysis showed improved PFS (hazard ratio [HR], 0.54, 95% CIs, 0.41-0.71) and OS (HR, 0.58; 95% CI, 0.47-0.72) among PD-L1 (+) patients compared to PD-L1 (-) patients. Sensitivity analysis excluding retrospective studies showed no significant differences with the primary results. Furthermore, meta-regression demonstrated that drug target (PD-1 vs. PD-L1), presence of additional intervention (monotherapy vs. combination therapy), and PD-L1 cut-off level (1% vs. ≥5%) significantly affected the predictive value of PD-L1 expression. Conclusion: PD-L1 expression might be a helpful biomarker for predicting PFS and OS in patients with BTC undergoing anti-PD-1/PD-L1 therapy. The predictive value of PD-L1 expression can be significantly influenced by diagnostic or treatment variables. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023434114.

Binding and unbinding of potent melatonin receptor ligands: Mechanistic simulations and experimental evidence.

The labeled ligand commonly employed in competition binding studies for melatonin receptor ligands, 2-[125I]iodomelatonin, showed slow dissociation with different half-lives at the two receptor subtypes. This may affect the operational measures of affinity constants, which at short incubation times could not be obtained in equilibrium conditions, and structure-activity relationships, as the Ki values of tested ligands could depend on either interaction at the binding site or the dissociation path. To address these issues, the kinetic and saturation binding parameters of 2-[125I]iodomelatonin as well as the competition constants for a series of representative ligands were measured at a short (2 h) and a long (20 h) incubation time. Concurrently, we simulated by molecular modeling the dissociation path of 2-iodomelatonin from MT1 and MT2 receptors and investigated the role of interactions at the binding site on the stereoselectivity observed for the enantiomers of the subtype-selective ligand UCM1014. We found that equilibrium conditions for 2-[125I]iodomelatonin binding can be reached only with long incubation times, particularly for the MT2 receptor subtype, for which a time of 20 h approximates this condition. On the other hand, measured Ki values for a set of ligands including agonists, antagonists, nonselective, and subtype-selective compounds were not significantly affected by the length of incubation, suggesting that structure-activity relationships based on data collected at shorter time reflect different interactions at the binding site. Molecular modeling simulations evidenced that the slower dissociation of 2-iodomelatonin from the MT2 receptor can be related to the restricted mobility of a gatekeeper tyrosine along a lipophilic path from the binding site to the membrane bilayer. The enantiomers of the potent, MT2-selective agonist UCM1014 were separately synthesized and tested. Molecular dynamics simulations of the receptor-ligand complexes provided an explanation for their stereoselectivity as due to the preference shown by the eutomer at the binding site for the most abundant axial conformation adopted by the ligand in solution. These results suggest that, despite the slow-binding kinetics occurring for the labeled ligand, affinity measures at shorter incubation times give robust results consistent with known structure-activity relationships and with interactions taken at the receptor binding site.

Deregulation in adult IgA vasculitis skin as the basis for the discovery of novel serum biomarkers.

INTRODUCTION: Immunoglobulin A vasculitis (IgAV) in adults has a variable disease course, with patients often developing gastrointestinal and renal involvement and thus contributing to higher mortality. Due to understudied molecular mechanisms in IgAV currently used biomarkers for IgAV visceral involvement are largely lacking. Our aim was to search for potential serum biomarkers based on the skin transcriptomic signature. METHODS: RNA sequencing analysis was conducted on skin biopsies collected from 6 treatment-naïve patients (3 skin only and 3 renal involvement) and 3 healthy controls (HC) to get insight into deregulated processes at the transcriptomic level. 15 analytes were selected and measured based on the transcriptome analysis (adiponectin, lipopolysaccharide binding protein (LBP), matrix metalloproteinase-1 (MMP1), C-C motif chemokine ligand (CCL) 19, kallikrein-5, CCL3, leptin, C-X-C motif chemokine ligand (CXCL) 5, osteopontin, interleukin (IL)-15, CXCL10, angiopoietin-like 4 (ANGPTL4), SERPIN A12/vaspin, IL-18 and fatty acid-binding protein 4 (FABP4)) in sera of 59 IgAV and 22 HC. Machine learning was used to assess the ability of the analytes to predict IgAV and its organ involvement. RESULTS: Based on the gene expression levels in the skin, we were able to differentiate between IgAV patients and HC using principal component analysis (PCA) and a sample-to-sample distance matrix. Differential expression analysis revealed 49 differentially expressed genes (DEGs) in all IgAV patient's vs. HC. Patients with renal involvement had more DEGs than patients with skin involvement only (507 vs. 46 DEGs) as compared to HC, suggesting different skin signatures. Major dysregulated processes in patients with renal involvement were lipid metabolism, acute inflammatory response, and extracellular matrix (ECM)-related processes. 11 of 15 analytes selected based on affected processes in IgAV skin (osteopontin, LBP, ANGPTL4, IL-15, FABP4, CCL19, kallikrein-5, CCL3, leptin, IL-18 and MMP1) were significantly higher (p-adj < 0.05) in IgAV serum as compared to HC. Prediction models utilizing measured analytes showed high potential for predicting adult IgAV. CONCLUSION: Skin transcriptomic data revealed deregulations in lipid metabolism and acute inflammatory response, reflected also in serum analyte measurements. LBP, among others, could serve as a potential biomarker of renal complications, while adiponectin and CXCL10 could indicate gastrointestinal involvement.

Supramolecular Mimotope Peptide Nanofibers Promote Antibody-Ligand Polyvalent and Instantaneous Recognition for Biopharmaceutical Analysis.

Peptide-based supramolecules exhibit great potential in various fields due to their improved target recognition ability and versatile functions. However, they still suffer from numerous challenges for the biopharmaceutical analysis, including poor self-assembly ability, undesirable ligand-antibody binding rates, and formidable target binding barriers caused by ligand crowding. To tackle these issues, a "polyvalent recognition" strategy employing the CD20 mimotope peptide derivative NBD-FFVLR-GS-WPRWLEN (acting on the CDR domains of rituximab) was proposed to develop supramolecular nanofibers for target antibody recognition. These nanofibers exhibited rapid self-assembly within only 1 min and robust stability. Their binding affinity (179 nM) for rituximab surpassed that of the monomeric peptide (7 µM) by over 38-fold, highlighting that high ligand density and potential polyvalent recognition can efficiently overcome the target binding barriers of traditional supramolecules. Moreover, these nanofibers exhibited an amazing "instantaneous capture" rate (within 15 s), a high recovery (93 ± 3%), and good specificity for the target antibody. High-efficiency enrichment of rituximab was achieved from cell culture medium with good recovery and reproducibility. Intriguingly, these peptide nanofibers combined with bottom-up proteomics were successful in tracking the deamidation of asparagine 55 (from 10 to 16%) on the rituximab heavy chain after 21 day incubation in human serum. In summary, this study may open up an avenue for the development of versatile mimotope peptide supramolecules for biorecognition and bioanalysis of biopharmaceuticals.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

Ligand bias underlies differential signaling of multiple FGFs via FGFR1.

The differential signaling of multiple FGF ligands through a single fibroblast growth factor (FGF) receptor (FGFR) plays an important role in embryonic development. Here, we use quantitative biophysical tools to uncover the mechanism behind differences in FGFR1c signaling in response to FGF4, FGF8, and FGF9, a process which is relevant for limb bud outgrowth. We find that FGF8 preferentially induces FRS2 phosphorylation and extracellular matrix loss, while FGF4 and FGF9 preferentially induce FGFR1c phosphorylation and cell growth arrest. Thus, we demonstrate that FGF8 is a biased FGFR1c ligand, as compared to FGF4 and FGF9. Förster resonance energy transfer experiments reveal a correlation between biased signaling and the conformation of the FGFR1c transmembrane domain dimer. Our findings expand the mechanistic understanding of FGF signaling during development and bring the poorly understood concept of receptor tyrosine kinase ligand bias into the spotlight.