A role of salt bridges in mediating drug potency: A lesson from the N-myristoyltransferase inhibitors

Decoding the bitter taste of Idesia polycarpa var. vestita Diels fruit: Bitterness contribution and mechanisms

To comprehensively explore the contribution and mechanisms of identified low-threshold bitter substances in Idesia polycarpa var. vestita Diels (I. vestita) fruit, we performed quantification and elucidated their interactions with main bitter taste receptors through molecular docking. The established method for quantifying bitter compounds in I. vestita fruit was validated, yielding satisfactory parameters for linearity, stability, and accuracy. Idescarpin (17.71-101.05 mg/g) and idesin (7.88-77.14 mg/g) were the predominant bitter compounds in terms of content. Taste activity values (TAVs) exceeded 10 for the bitter substances, affirming their pivotal role as major contributors to overall bitterness of I. vestita fruit. Notably, idescarpin with the highest TAV, played a crucial role in generating the bitterness of I. vestita fruit. Hydrogen bonds and hydrophobic interactions were the main driving forces. This study holds potential implications for industrial development of I. vestita fruit by providing novel insights into the mechanism underlying its bitterness formation.

Design, Synthesis, Antitumor Activity and NMR-Based Metabolomics of Novel Amino Substituted Tetracyclic Imidazo[4,5-b]Pyridine Derivatives

Newly prepared tetracyclic imidazo[4,5-b]pyridine derivatives were synthesized to study their antiproliferative activity against human cancer cells. Additionally, the structure-activity was studied to confirm the impact of the N atom position in pyridine nuclei as well as the chosen amino side chains on antiproliferative activity. Targeted amino substituted regioisomers were prepared by using uncatalyzed amination from corresponding chloro substituted precursors. The most active compounds 6 a, 8 and 10 showed improved activity in comparison to standard drug etoposide with IC50 values in a nanomolar range of concentration (0.2-0.9 μM). NMR-based metabolomics is a powerful instrument to elucidate activity mechanism of new chemotherapeutics. Multivariate and univariate statistical analysis of metabolic profiles of non-small cell lung cancer cells before and after exposure to 6 a revealed significant changes in metabolism of essential amino acids, glycerophospholipids and oxidative defense. Insight into the changes of metabolic pathways that are heavily involved in cell proliferation and survival provide valuable guidelines for more detailed analysis of activity metabolism and possible targets of this class of bioactive compounds.

Antihypertensive and Antidiabetic Drug Candidates from Milkfish (Chanos chanos)-Identification and Characterization through an Integrated Bioinformatic Approach

Integrated bioinformatics tools have created more efficient and robust methods to overcome in vitro challenges and have been widely utilized for the investigation of food proteins and the generation of peptide sequences. This study aimed to analyze the physicochemical properties and bioactivities of novel peptides derived from hydrolyzed milkfish (Chanos chanos) protein sequences and to discover their potential angiotensin-converting enzyme (ACE)- and dipeptidyl peptidase-4 (DPPIV)-inhibitory activities using machine learning-based tools, including BIOPEP-UWM, PeptideRanker, and the molecular docking software HADDOCK 2.4. Nine and three peptides were predicted to have ACE- and DPPIV-inhibitory activities, respectively. The DPPIV-inhibitory peptides were predicted to inhibit the compound with no known specific mode. Meanwhile, two tetrapeptides (MVWH and PPPS) were predicted to possess a competitive mode of ACE inhibition by directly binding to the tetra-coordinated Zn ion. Among all nine discovered ACE-inhibitory peptides, only the PPPS peptide satisfied the drug-likeness analysis requirements with no violations of the Lipinski rule of five and should be further investigated in vitro.

The Circadian Clock Component RORA Increases Immunosurveillance in Melanoma by Inhibiting PD-L1 Expression

Circadian clock perturbation frequently occurs in cancer and facilitates tumor progression by regulating malignant growth and shaping the immune microenvironment. Emerging evidence has indicated that clock genes are disrupted in melanoma and linked to immune escape. Herein, we found that the expression of retinoic acid receptor-related orphan receptor-α (RORA) is downregulated in melanoma patients and that patients with higher RORA expression have a better prognosis after immunotherapy. Additionally, RORA was significantly positively correlated with T-cell infiltration and recruitment. Overexpression or activation of RORA stimulated cytotoxic T-cell-mediated antitumor responses. RORA bound to the CD274 promoter and formed an inhibitory complex with HDAC3 to suppress PD-L1 expression. In contrast, the DEAD-box helicase family member DDX3X competed with HDAC3 for binding to RORA, and DDX3X overexpression promoted RORA release from the suppressive complex and thereby increased PD-L1 expression to generate an inhibitory immune environment. The combination of a RORA agonist with an anti-CTLA4 antibody synergistically increased T-cell antitumor immunity in vivo. A score based on the combined expression of HDAC3, DDX3X, and RORA correlated with immunotherapy response in melanoma patients. Together, this study elucidates a mechanism of clock component-regulated antitumor immunity, which will help inform the use of immunotherapy and lead to improved outcomes for melanoma patients receiving combined therapeutic treatments. Significance: RORA forms a corepressor complex to inhibit PD-L1 expression and activate antitumor T-cell responses, indicating that RORA is a potential target and predictive biomarker to improve immunotherapy response in melanoma patients.

The story of clobenpropit and CXCR4: can be an effective drug in cancer and autoimmune diseases?

Clobenpropit is a histamine H3 receptor antagonist and has developed as a potential therapeutic drug due to its ability to inhibit CXCR4, a chemokine receptor involved in autoimmune diseases and cancer pathogenesis. The CXCL12/CXCR4 axis involves several biological phenomena, including cell proliferation, migration, angiogenesis, inflammation, and metastasis. Accordingly, inhibiting CXCR4 can have promising clinical outcomes in patients with malignancy or autoimmune disorders. Based on available knowledge, Clobenpropit can effectively regulate the release of monocyte-derived inflammatory cytokine in autoimmune diseases such as juvenile idiopathic arthritis (JIA), presenting a potential targeted target with possible advantages over current therapeutic approaches. This review summarizes the intricate interplay between Clobenpropit and CXCR4 and the molecular mechanisms underlying their interactions, comprehensively analyzing their impact on immune regulation. Furthermore, we discuss preclinical and clinical investigations highlighting the probable efficacy of Clobenpropit for managing autoimmune diseases and cancer. Through this study, we aim to clarify the immunomodulatory role of Clobenpropit and its advantages and disadvantages as a novel therapeutic opportunity.

Binding Affinity Determination in Drug Design: Insights from Lock and Key, Induced Fit, Conformational Selection, and Inhibitor Trapping Models

Binding affinity is a fundamental parameter in drug design, describing the strength of the interaction between a molecule and its target protein. Accurately predicting binding affinity is crucial for the rapid development of novel therapeutics, the prioritization of promising candidates, and the optimization of their properties through rational design strategies. Binding affinity is determined by the mechanism of recognition between proteins and ligands. Various models, including the lock and key, induced fit, and conformational selection, have been proposed to explain this recognition process. However, current computational strategies to predict binding affinity, which are based on these models, have yet to produce satisfactory results. This article explores the connection between binding affinity and these protein-ligand interaction models, highlighting that they offer an incomplete picture of the mechanism governing binding affinity. Specifically, current models primarily center on the binding of the ligand and do not address its dissociation. In this context, the concept of ligand trapping is introduced, which models the mechanisms of dissociation. When combined with the current models, this concept can provide a unified theoretical framework that may allow for the accurate determination of the ligands' binding affinity.

Antifouling activities of proteinase K and α-amylase enzymes: Laboratory bioassays and in silico analysis

The application of enzymes as antifoulants is one of the environment-friendly strategies in biofouling management. In this study, antifouling activities of commercially available proteinase K and α-amylase enzymes were evaluated using barnacle larva and biofilm-forming bacteria as test organisms. The enzymes were also tested against barnacle cement protein through in silico analysis. The results showed that both enzymes inhibited the attachment of bacteria and settlement of barnacle larvae on the test surface. The lowest minimum inhibitory concentration of 0.312 mg ml-1 was exhibited by proteinase K against biofilm-forming bacteria. The calculated LC50 values for proteinase K and α-amylase against the barnacle nauplii were 91.8 and 230.96 mg ml-1 respectively. While α-amylase showed higher antibiofilm activity, proteinase K exhibited higher anti-larval settlement activity. Similarly, in silico analysis of the enzymes revealed promising anti-settlement activity, as the enzymes showed good binding scores with barnacle cement protein. Overall, the results suggested that the enzymes proteinase K and α-amylase could be used in antifouling coatings to reduce the settlement of biofouling on artificial materials in the marine environment.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Balancing the Affinity and Tumor Cell Binding of a Two-in-One Antibody Simultaneously Targeting EGFR and PD-L1

The optimization of the affinity of monoclonal antibodies is crucial for the development of drug candidates, as it can impact the efficacy of the drug and, thus, the dose and dosing regimen, limit adverse effects, and reduce therapy costs. Here, we present the affinity maturation of an EGFR×PD-L1 Two-in-One antibody for EGFR binding utilizing site-directed mutagenesis and yeast surface display. The isolated antibody variants target EGFR with a 60-fold-improved affinity due to the replacement of a single amino acid in the CDR3 region of the light chain. The binding properties of the Two-in-One variants were confirmed using various methods, including BLI measurements, real-time antigen binding measurements on surfaces with a mixture of both recombinant proteins and cellular binding experiments using flow cytometry as well as real-time interaction cytometry. An AlphaFold-based model predicted that the amino acid exchange of tyrosine to glutamic acid enables the formation of a salt bridge to an arginine at EGFR position 165. This easily adaptable approach provides a strategy for the affinity maturation of bispecific antibodies with respect to the binding of one of the two antigens.

Potential Inhibitors of Lumpy Skin Disease's Viral Protein (DNA Polymerase): A Combination of Bioinformatics Approaches

Lumpy skin disease (LSD), caused by a virus within the Poxviridae family and Capripoxvirus genus, induces nodular skin lesions in cattle. This spreads through direct contact and insect vectors, significantly affecting global cattle farming. Despite the availability of vaccines, their efficacy is limited by poor prophylaxis and adverse effects. Our study aimed to identify the potential inhibitors targeting the LSDV-encoded DNA polymerase protein (gene LSDV039) for further investigation through comprehensive analysis and computational methods. Virtual screening revealed rhein and taxifolin as being potent binders among 380 phytocompounds, with respective affinities of -8.97 and -7.20 kcal/mol. Canagliflozin and tepotinib exhibited strong affinities (-9.86 and -8.86 kcal/mol) among 718 FDA-approved antiviral drugs. Simulating the molecular dynamics of canagliflozin, tepotinib, rhein, and taxifolin highlighted taxifolin's superior stability and binding energy. Rhein displayed compactness in RMSD and RMSF, but fluctuated in Rg and SASA, while canagliflozin demonstrated stability compared to tepotinib. This study highlights the promising potential of using repurposed drugs and phytocompounds as potential LSD therapeutics. However, extensive validation through in vitro and in vivo testing and clinical trials is crucial for their practical application.

Development of Hsp90 C-terminal inhibitors with noviomimetics that manifest anti-proliferative activities

Inhibition of the Hsp90 C-terminal domain offers a promising opportunity to treat numerous diseases/indications. Furthermore, the development of Hsp90 C-terminal inhibitors (CTIs) is advantageous over N-terminal inhibitors because it avoids the detriments associated with induction of the heat shock response (HSR). However, the lack of co-crystal structures of small molecules bound to the C-terminus have hindered their development. Therefore, structure-activity relationship (SAR) studies have been pursued to optimize such inhibitors. Noviose sugar surrogates, also known as noviomimetics have been prepared to investigate the size and nature of the C-terminal domain binding pocket. Herein, we report the synthesis and anti-proliferative activity manifested by this new series of Hsp90 C-terminal inhibitors.

Thermophilic β-mannanases from bacteria: production, resources, structural features and bioengineering strategies

β-mannanases are pivotal enzymes that cleave the mannan backbone to release short chain mannooligosaccharides, which have tremendous biotechnological applications including food/feed, prebiotics and biofuel production. Due to the high temperature conditions in many industrial applications, thermophilic mannanases seem to have great potential to overcome the thermal impediments. Thus, structural analysis of thermostable β-mannanases is extremely important, as it could open up new avenues for genetic engineering, and protein engineering of these enzymes with enhanced properties and catalytic efficiencies. Under this scope, the present review provides a state-of-the-art discussion on the thermophilic β-mannanases from bacterial origin, their production, engineering and structural characterization. It covers broad insights into various molecular biology techniques such as gene mutagenesis, heterologous gene expression, and protein engineering, that are employed to improve the catalytic efficiency and thermostability of bacterial mannanases for potential industrial applications. Further, the bottlenecks associated with mannanase production and process optimization are also discussed. Finally, future research related to bioengineering of mannanases with novel protein expression systems for commercial applications are also elaborated.

Molecular docking and dynamics simulation studies uncover the host-pathogen protein-protein interactions in Penaeus vannamei and Vibrio parahaemolyticus

Shrimp aquaculture contributes significantly to global economic growth, and the whiteleg shrimp, Penaeus vannamei, is a leading species in this industry. However, Vibrio parahaemolyticus infection poses a major challenge in ensuring the success of P. vannamei aquaculture. Despite its significance in this industry, the biological knowledge of its pathogenesis remains unclear. Hence, this study was conducted to identify the interaction sites and binding affinity between several immune-related proteins of P. vannamei with V. parahaemolyticus proteins associated with virulence factors. Potential interaction sites and the binding affinity between host and pathogen proteins were identified using molecular docking and dynamics (MD) simulation. The P. vannamei-V. parahaemolyticus protein-protein interaction of Complex 1 (Ferritin-HrpE/YscL family type III secretion apparatus protein), Complex 2 (Protein kinase domain-containing protein-Chemotaxis CheY protein), and Complex 3 (GPCR-Chemotaxis CheY protein) was found to interact with -4319.76, -5271.39, and -4725.57 of the docked score and the formation of intermolecular bonds at several interacting residues. The docked scores of Complex 1, Complex 2, and Complex 3 were validated using MD simulation analysis, which revealed these complexes greatly contribute to the interactions between P. vannamei and V. parahaemolyticus proteins, with binding free energies of -22.50 kJ/mol, -30.20 kJ/mol, and -26.27 kJ/mol, respectively. This finding illustrates the capability of computational approaches to search for molecular binding sites between host and pathogen, which could increase the knowledge of Vibrio spp. infection on shrimps, which then can be used to assist in the development of effective treatment.

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation-π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.

Predicting the changes in neutralizing antibody interaction with G protein derived from Bangladesh isolates of Nipah virus: molecular dynamics based approach

The infectious Nipah virus (NiV) is categorized into NiV-M (Malaysia) and NiV-B (Bangladesh) groups based on its genome comparison, pathogenicity, and mortality rate. The development of therapeutic molecules has used NiV-M-derived data in multiple studies than NiV-B. In continuation with this, the protein level investigation is also less explored to understand the interaction with therapeutic neutralizing antibodies for NiV-B. So, this study focuses on understanding the impact of NiV-B-specific mutations on the interaction of therapeutic neutralizing antibodies with the G protein. The population-based comparative analysis of NiV-B G protein sequences with NiV-M sequence identified twenty-six mutations. These predominantly polar mutations were then used to model the mutant protein (G_MT). In a comparative study, the G protein G_MT and reference protein G_WT (Malaysian origin) were subjected to a protein docking with neutralizing human monoclonal antibody HENV26. The binding affinity and the free binding energy of the glycoprotein in complex with G-WT and G_MT were calculated using PRODIGY and MM/PBSA tools respectively. Based on the PRODIGY report, G-WT showed stronger binding (-13.8 kcal/mol) compared to that of the G_MT (-9.0 kcal/mol) with the HENV26 antibody. The stability of the complexes was evaluated using MM/PBSA which showed higher binding energy with HENV26 for G_WT (-75.11 kcal/mol) in contrast to G_MT (-41.66 kcal/mol). The results indicate that the mutant G protein has a reduced ability to bind to neutralizing antibodies, resulting in a decreased effectiveness against strains carrying these mutations.Communicated by Ramaswamy H. Sarma.

Protein Profiling of Aedes aegypti Treated with Streptomyces sp. KSF103 Ethyl Acetate Extract Reveals Potential Insecticidal Targets and Metabolic Pathways

The insecticidal activity of Streptomyces sp. KSF103 ethyl acetate (EA) extract against mosquitoes is known; however, the underlying mechanism behind this activity remains elusive. In this study, liquid chromatography with tandem mass spectrometry (LC-MS/MS) was employed to investigate changes in the protein profile of Aedes aegypti larvae and adults treated with lethal concentrations of 50 (LC50) EA extract. By comparing the treated and untreated mosquitoes, this study aimed to identify proteins or pathways that exhibit alterations, potentially serving as targets for future insecticide development. Treatment with a lethal concentration of EA extract upregulated 15 proteins in larvae, while in adults, 16 proteins were upregulated, and two proteins were downregulated. These proteins were associated with metabolism, protein regulation/degradation, energy production, cellular organization and structure, enzyme activity, and catalysis, as well as calcium ion transport and homeostasis. Notably, ATP synthase, fructose-bisphosphate aldolase (FBA), and ATP citrate synthase were significantly expressed in both groups. Gene ontology analysis indicated a focus on energy metabolic processes. Molecular docking revealed a strong interaction between dodemorph, selagine (compounds from the EA extract), and FBA, suggesting FBA as a potential protein target for insecticide development. Further studies such as Western blot and transcriptomic analyses are warranted to validate the findings.

Inhibitor Trapping in N-Myristoyltransferases as a Mechanism for Drug Potency

Predicting inhibitor potency is critical in drug design and development, yet it has remained one of computational biology's biggest unresolved challenges. Here, we show that in the case of the N-myristoyltransferase (NMT), this problem could be traced to the mechanisms by which the NMT enzyme is inhibited. NMT adopts open or closed conformations necessary for orchestrating the different steps of the catalytic process. The results indicate that the potency of the NMT inhibitors is determined by their ability to stabilize the enzyme conformation in the closed state, and that in this state, the small molecules themselves are trapped and locked inside the structure of the enzyme, creating a significant barrier for their dissociation. By using molecular dynamics simulations, we demonstrate that the conformational stabilization of the protein molecule in its closed form is highly correlated with the ligands activity and can be used to predict their potency. Hence, predicting inhibitor potency in silico might depend on modeling the conformational changes of the protein molecule upon binding of the ligand rather than estimating the changes in free binding energy that arise from their interaction.