Development and validation of a genetic algorithm for flexible docking

Cyclization of acyl thiosemicarbazides led to new Helicobacter pylori α-carbonic anhydrase inhibitors

The eradication of Helicobacter pylori, the etiologic agent of gastric ulcer and adenocarcinoma, is a big concern in clinics due to the increasing drug resistance phenomena and the limited number of efficacious treatment options. The exploitation of the H. pylori carbonic anhydrases (HpCAs) as promising pharmacological targets has been validated by the antibacterial activity of previously reported CA inhibitors due to the role of these enzymes in the bacterium survival in the gastric mucosa. The development of new HpCA inhibitors seems to be on the way to filling the existing antibiotics gap. Due to the recent evidence on the ability of the coumarin scaffold to inhibit microbial α-CAs, a large library of derivatives has been developed by means of a pH-regulated cyclization reaction of coumarin-bearing acyl thiosemicarbazide intermediates. The obtained 1,3,4-thiadiazoles (10-18a,b) and 1,2,4-triazole-3-thiones (19-26a,b) were found to strongly and selectively inhibit HpαCA and computational studies were fundamental to gaining an understanding of the interaction networks governing the enzyme-inhibitor complex. Antibacterial evaluations on H. pylori ATCC 43504 highlighted some compounds that maintained potency on a resistant clinical isolate. Also, their combinations with metronidazole decreased both the minimal inhibitory concentration and minimal bactericidal concentration values of the antibiotic, with no synergistic effect.

Computational toolbox for the analysis of protein-glycan interactions

Protein-glycan interactions play pivotal roles in numerous biological processes, ranging from cellular recognition to immune response modulation. Understanding the intricate details of these interactions is crucial for deciphering the molecular mechanisms underlying various physiological and pathological conditions. Computational techniques have emerged as powerful tools that can help in drawing, building and visualising complex biomolecules and provide insights into their dynamic behaviour at atomic and molecular levels. This review provides an overview of the main computational tools useful for studying biomolecular systems, particularly glycans, both in free state and in complex with proteins, also with reference to the principles, methodologies, and applications of all-atom molecular dynamics simulations. Herein, we focused on the programs that are generally employed for preparing protein and glycan input files to execute molecular dynamics simulations and analyse the corresponding results. The presented computational toolbox represents a valuable resource for researchers studying protein-glycan interactions and incorporates advanced computational methods for building, visualising and predicting protein/glycan structures, modelling protein-ligand complexes, and analyse MD outcomes. Moreover, selected case studies have been reported to highlight the importance of computational tools in studying protein-glycan systems, revealing the capability of these tools to provide valuable insights into the binding kinetics, energetics, and structural determinants that govern specific molecular interactions.

Discovery of Novel, Selective, and Nonbasic Agonists for the Kappa-Opioid Receptor Determined by Salvinorin A-Based Virtual Screening

Modulating the kappa-opioid receptor (KOR) is a promising strategy for treating various human diseases. KOR agonists show potential for treating pain, pruritus, and epilepsy, while KOR antagonists show potential for treating depression, anxiety, and addiction. The diterpenoid Salvinorin A (SalA), a secondary metabolite of Salvia divinorum, is a potent and selective KOR agonist. Unlike typical opioids, SalA lacks a basic nitrogen, which encouraged us to search for nonbasic KOR ligands. Through structure-based virtual screening using 3D pharmacophore models based on the binding mode of SalA, we identified novel, nonbasic, potent, and selective KOR agonists. In vitro studies confirmed two virtual hits, SalA-VS-07 and SalA-VS-08, as highly selective for the KOR and showing G protein-biased KOR agonist activity. Both KOR ligands share a novel spiro-moiety and a nonbasic scaffold. Our findings provide novel starting points for developing therapeutics aimed at treating pain and other conditions in which KOR is a central player.

Substrate-Based Ligand Design for Phenazine Biosynthesis Enzyme PhzF

The phenazine pyocyanin is an important virulence factor of the pathogen Pseudomonas aeruginosa, which is on the WHO list of antibiotic resistant "priority pathogens". In this study the isomerase PhzF, a key bacterial enzyme of the pyocyanin biosynthetic pathway, was investigated as a pathoblocker target. The aim of the pathoblocker strategy is to reduce the virulence of the pathogen without killing it, thus preventing the rapid development of resistance. Based on crystal structures of PhzF, derivatives of the inhibitor 3-hydroxyanthranilic acid were designed. Co-crystal structures of the synthesized derivatives with PhzF revealed spacial limitations of the binding pocket of PhzF in the closed conformation. In contrast, ligands aligned to the open conformation of PhzF provided more room for structural modifications. The intrinsic fluorescence of small 3-hydroxyanthranilic acid derivatives enabled direct affinity determinations using FRET assays. The analysis of structure-activity relationships showed that the carboxylic acid moiety is essential for binding to the target enzyme. The results of this study provide fundamental structural insights that will be useful for the design of PhzF-inhibitors.

Alteration of Neuropilin-1 and Heparan Sulfate Interaction Impairs Murine B16 Tumor Growth

Neuropilin-1 acts as a coreceptor with vascular endothelial growth factor receptors to facilitate binding of its ligand, vascular endothelial growth factor. Neuropilin-1 also binds to heparan sulfate, but the functional significance of this interaction has not been established. A combinatorial library screening using heparin oligosaccharides followed by molecular dynamics simulations of a heparin tetradecasaccharide suggested a highly conserved binding site composed of amino acid residues extending across the b1 and b2 domains of murine neuropilin-1. Mutagenesis studies established the importance of arginine513 and lysine514 for binding of heparin to a recombinant form of Nrp1 composed of the a1, a2, b1, and b2 domains. Recombinant Nrp1 protein bearing R513A,K514A mutations showed a significant loss of heparin-binding, heparin-induced dimerization, and heparin-dependent thermal stabilization. Isothermal calorimetry experiments suggested a 1:2 complex of heparin tetradecasaccharide:Nrp1. To study the impact of altered heparin binding in vivo, a mutant allele of Nrp1 bearing the R513A,K514A mutations was created in mice (Nrp1D) and crossbred to Nrp1+/- mice to examine the impact of altered heparan sulfate binding. Analysis of tumor formation showed variable effects on tumor growth in Nrp1D/D mice, resulting in a frank reduction in tumor growth in Nrp1D/- mice. Expression of mutant Nrp1D protein was normal in tissues, suggesting that the reduction in tumor growth was due to the altered binding of heparin/heparan sulfate to neuropilin-1. These findings suggest that the interaction of neuropilin-1 with heparan sulfate modulates its stability and its role in tumor formation and growth.

FitScore: a fast machine learning-based score for 3D virtual screening enrichment

Enhancing virtual screening enrichment has become an urgent problem in computational chemistry, driven by increasingly large databases of commercially available compounds, without a commensurate drop in in vitro screening costs. Docking these large databases is possible with cloud-scale computing. However, rapid docking necessitates compromises in scoring, often leading to poor enrichment and an abundance of false positives in docking results. This work describes a new scoring function composed of two parts - a knowledge-based component that predicts the probability of a particular atom type being in a particular receptor environment, and a tunable weight matrix that converts the probability predictions into a dimensionless score suitable for virtual screening enrichment. This score, the FitScore, represents the compatibility between the ligand and the binding site and is capable of a high degree of enrichment across standardized docking test sets.

HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery

We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed for the effective representation of molecular structures and interactions in protein-ligand binding. We designed an end-to-end pipeline for high-throughput screening and lead optimization, targeting applications in structure-based drug design. We assessed our approach using established public benchmarks based on the CASF-2016 core set, achieving top-tier results in affinity and pose prediction (Pearson's r = 0.86, RMSE = 1.15, Top-1 = 0.95). We introduced a novel approach for interaction profiling, aimed at detecting potential biases within both the model and data sets. This approach not only enhanced interpretability but also reinforced the impartiality of our methodology. Finally, we demonstrated HydraScreen's ability to generalize effectively across novel proteins and ligands through a temporal split. We also provide insights into potential avenues for future development aimed at enhancing the robustness of machine learning scoring functions. HydraScreen (accessible at http://hydrascreen.ro5.ai/paper) provides a user-friendly GUI and a public API, facilitating the easy-access assessment of protein-ligand complexes.

Targeting N-Acetylglucosaminidase in Staphylococcus aureus with Iminosugar Inhibitors

Bacteria are capable of remarkable adaptations to their environment, including undesirable bacterial resistance to antibacterial agents. One of the most serious cases is an infection caused by multidrug-resistant Staphylococcus aureus, which has unfortunately also spread outside hospitals. Therefore, the development of new effective antibacterial agents is extremely important to solve the increasing problem of bacterial resistance. The bacteriolytic enzyme autolysin E (AtlE) is a promising new drug target as it plays a key role in the degradation of peptidoglycan in the bacterial cell wall. Consequently, disruption of function can have an immense impact on bacterial growth and survival. An in silico and in vitro evaluation of iminosugar derivatives as potent inhibitors of S. aureus (AtlE) was performed. Three promising hit compounds (1, 3 and 8) were identified as AtlE binders in the micromolar range as measured by surface plasmon resonance. The most potent compound among the SPR response curve hits was 1, with a KD of 19 μM. The KD value for compound 8 was 88 μM, while compound 3 had a KD value of 410 μM.

Building shape-focused pharmacophore models for effective docking screening

The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins' inverted binding cavities. The effectiveness of these pseudo-ligands or negative image-based models in docking rescoring is boosted further by performing enrichment-driven optimization. Here, we introduce a novel shape-focused pharmacophore modeling algorithm O-LAP that generates a new class of cavity-filling models by clumping together overlapping atomic content via pairwise distance graph clustering. Top-ranked poses of flexibly docked active ligands were used as the modeling input and multiple alternative clustering settings were benchmark-tested thoroughly with five demanding drug targets using random training/test divisions. In docking rescoring, the O-LAP modeling typically improved massively on the default docking enrichment; furthermore, the results indicate that the clustered models work well in rigid docking. The C+ +/Qt5-based algorithm O-LAP is released under the GNU General Public License v3.0 via GitHub ( https://github.com/jvlehtonen/overlap-toolkit ). SCIENTIFIC CONTRIBUTION: This study introduces O-LAP, a C++/Qt5-based graph clustering software for generating new type of shape-focused pharmacophore models. In the O-LAP modeling, the target protein cavity is filled with flexibly docked active ligands, the overlapping ligand atoms are clustered, and the shape/electrostatic potential of the resulting model is compared against the flexibly sampled molecular docking poses. The O-LAP modeling is shown to ensure high enrichment in both docking rescoring and rigid docking based on comprehensive benchmark-testing.

Repurposing Hsp90 inhibitors as antimicrobials targeting two-component systems identifies compounds leading to loss of bacterial membrane integrity

The discovery of antimicrobials with novel mechanisms of action is crucial to tackle the foreseen global health crisis due to antimicrobial resistance. Bacterial two-component signaling systems (TCSs) are attractive targets for the discovery of novel antibacterial agents. TCS-encoding genes are found in all bacterial genomes and typically consist of a sensor histidine kinase (HK) and a response regulator. Due to the conserved Bergerat fold in the ATP-binding domain of the TCS HK and the human chaperone Hsp90, there has been much interest in repurposing inhibitors of Hsp90 as antibacterial compounds. In this study, we explore the chemical space of the known Hsp90 inhibitor scaffold 3,4-diphenylpyrazole (DPP), building on previous literature to further understand their potential for HK inhibition. Six DPP analogs inhibited HK autophosphorylation in vitro and had good antimicrobial activity against Gram-positive bacteria. However, mechanistic studies showed that their antimicrobial activity was related to damage of bacterial membranes. In addition, DPP analogs were cytotoxic to human embryonic kidney cell lines and induced the cell arrest phenotype shown for other Hsp90 inhibitors. We conclude that these DPP structures can be further optimized as specific disruptors of bacterial membranes providing binding to Hsp90 and cytotoxicity are lowered. Moreover, the X-ray crystal structure of resorcinol, a substructure of the DPP derivatives, bound to the HK CheA represents a promising starting point for the fragment-based design of novel HK inhibitors.

IMPORTANCE

The discovery of novel antimicrobials is of paramount importance in tackling the imminent global health crisis of antimicrobial resistance. The discovery of novel antimicrobials with novel mechanisms of actions, e.g., targeting bacterial two-component signaling systems, is crucial to bypass existing resistance mechanisms and stimulate pharmaceutical innovations. Here, we explore the possible repurposing of compounds developed in cancer research as inhibitors of two-component systems and investigate their off-target effects such as bacterial membrane disruption and toxicity. These results highlight compounds that are promising for further development of novel bacterial membrane disruptors and two-component system inhibitors.

Synthesis and Biological Properties of Ferrocenyl and Organic Methotrexate Derivatives

Synthesis and biological activity of two series of modified side chain methotrexate (MTX) derivatives are presented, one with a ferrocenyl moiety inserted between the pteroyl and glutamate portions of the molecule and the other with glutamate substituted for short chain amino acids. Ferrocenyl derivatives of MTX turned out to be rather moderate inhibitors of dihydrofolate reductase (DHFR) although molecular modeling suggested more effective interactions between these compounds and the target enzyme. More interestingly, ferrocene-decorated MTX derivatives were able to impede the proliferation of four murine and human cell lines as well as their methotrexate-resistant counterparts, overcoming the multidrug resistance (MDR) barrier. They were also able to directly interact with Abcc1, an MDR protein. Of the amino acid pteroyl conjugates, the γ-aminobutyric acid derivative was an efficient inhibitor of DHFR but had no effect on cell proliferation in the concentration range studied while a taurine conjugate was a poor DHFR inhibitor but able to affect cell viability. We postulate that modification of the methotrexate side chain may be an efficient strategy to overcome efflux-dependent methotrexate resistance.

Structural insights of an LCP protein-LytR-from Streptococcus dysgalactiae subs. dysgalactiae through biophysical and in silico methods

The rise of antibiotic-resistant bacterial strains has become a critical health concern. According to the World Health Organization, the market introduction of new antibiotics is alarmingly sparse, underscoring the need for novel therapeutic targets. The LytR-CpsA-Psr (LCP) family of proteins, which facilitate the insertion of cell wall glycopolymers (CWGPs) like teichoic acids into peptidoglycan, has emerged as a promising target for antibiotic development. LCP proteins are crucial in bacterial adhesion and biofilm formation, making them attractive for disrupting these processes. This study investigated the structural and functional characteristics of the LCP domain of LytR from Streptococcus dysgalactiae subsp. dysgalactiae. The protein structure was solved by X-ray Crystallography at 2.80 Å resolution. Small-angle X-ray scattering (SAXS) data were collected to examine potential conformational differences between the free and ligand-bound forms of the LytR LCP domain. Additionally, docking and molecular dynamics (MD) simulations were used to predict the interactions and conversion of ATP to ADP and AMP. Experimental validation of these predictions was performed using malachite green activity assays. The determined structure of the LCP domain revealed a fold highly similar to those of homologous proteins while SAXS data indicated potential conformational differences between the ligand-free and ligand-bound forms, suggesting a more compact conformation during catalysis, upon ligand binding. Docking and MD simulations predicted that the LytR LCP domain could interact with ADP and ATP and catalyze their conversion to AMP. These predictions were experimentally validated by malachite green activity assays, confirming the protein's functional versatility. The study provides significant insights into the structural features and functional capabilities of the LCP domain of LytR from S. dysgalactiae subsp. dysgalactiae. These findings pave the way for designing targeted therapies against antibiotic-resistant bacteria and offer strategies to disrupt bacterial biofilm formation.

Azobenzenesulfonamide Carbonic Anhydrase Inhibitors as New Weapons to Fight Helicobacter pylori: Synthesis, Bioactivity Evaluation, In Vivo Toxicity, and Computational Studies

Research into novel anti-Helicobacter pylori agents represents an important approach for the identification of new treatments for chronic gastritis and peptic ulcers, which are associated with a high risk of developing gastric carcinoma. In this respect, two series of azobenzenesulfonamides were designed, synthesized, and tested against a large panel of human and bacterial CAs to evaluate their inhibitory activity. In addition, computational studies of the novel primary benzenesulfonamides (4a-j) were performed to predict the putative binding mode to both HpCAs. Then, the antimicrobial activity versus H. pylori of the two series was also studied. The best-in-class compounds were found to be 4c and 4e among the primary azobenzenesulfonamides and 5c and 5f belonging to the secondary azobenzenesulfonamides series, showing themselves to exert a promising anti-H. pylori activity, with MIC values of 4-8 μg/mL and MBCs between 4 and 16 μg/mL. Moreover, the evaluation of their toxicity on a G. mellonella larva in vivo model indicated a safe profile for 4c,e and 5c,f. The collected results warrant considering these azobenzenesulfonamides as an interesting starting point for the development of a new class of anti-H. pylori agents.

Suppressed basal mitophagy drives cellular aging phenotypes that can be reversed by a p62-targeting small molecule

Selective degradation of damaged mitochondria by autophagy (mitophagy) is proposed to play an important role in cellular homeostasis. However, the molecular mechanisms and the requirement of mitochondrial quality control by mitophagy for cellular physiology are poorly understood. Here, we demonstrated that primary human cells maintain highly active basal mitophagy initiated by mitochondrial superoxide signaling. Mitophagy was found to be mediated by PINK1/Parkin-dependent pathway involving p62 as a selective autophagy receptor (SAR). Importantly, this pathway was suppressed upon the induction of cellular senescence and in naturally aged cells, leading to a robust shutdown of mitophagy. Inhibition of mitophagy in proliferating cells was sufficient to trigger the senescence program, while reactivation of mitophagy was necessary for the anti-senescence effects of NAD precursors or rapamycin. Furthermore, reactivation of mitophagy by a p62-targeting small molecule rescued markers of cellular aging, which establishes mitochondrial quality control as a promising target for anti-aging interventions.

In silico identification of D449-0032 compound as a putative SARS-CoV-2 Mpro inhibitor

The SARS-CoV-2 pandemic originated the urgency in developing therapeutic resources for the treatment of COVID-19. Despite the current availability of vaccines and some antivirals, the occurence of severe cases of the disease and the risk of the emergence of new virus variants still motivate research in this field. In this context, this study aimed at the computational prospection of likely inhibitors of the main protease (Mpro) of SARS-CoV-2 since inhibiting this enzyme leads to disruption of the viral replication process. The virtual screening of the antiviral libraries Asinex, ChemDiv, and Enamine targeting SARS-CoV-2 Mpro was performed, indicating the D449-0032 compound as a promising inhibitor. Molecular dynamics simulations showed the stability of the protein-ligand complex and in silico predictions of toxicity and pharmacokinetic parameters indicated the probable drug-like behavior of the compound. In vitro and in vivo studies are essential to confirm the Mpro inhibition by the D449-0032.Communicated by Ramaswamy H. Sarma.

Cyclopenta[b]indoles as novel antimicrotubule agents with antileukemia activity

Acute leukemias present therapeutic challenges despite advances in treatments. Microtubule inhibitors have played a pivotal role in cancer therapy, inspiring exploration into novel compounds like C2E1 from the cyclopenta[b]indole class. In the present study, we investigated C2E1's potential as a therapeutic agent for acute leukemia at molecular, cellular, and genetic levels. C2E1 demonstrated tubulin depolarization activity, significantly reducing leukemia cell viability. Its impact involved multifaceted mechanisms: inducing apoptosis, arrest of cell cycle progression, and inhibition of clonogenicity and migration in leukemia cells. At a molecular level, C2E1 triggered DNA damage, antiproliferative, and apoptosis markers and altered gene expression related to cytoskeletal regulation, disrupting essential cellular processes crucial for leukemia cell survival and proliferation. These findings highlight C2E1's promise as a potential candidate for novel anti-cancer therapies. Notably, its distinct mode of action from conventional microtubule-targeting drugs suggests the potential to bypass common resistance mechanisms encountered with existing treatments. In summary, C2E1 emerges as a compelling compound with diverse effects on leukemia cells, showcasing promising antineoplastic properties. Its ability to disrupt critical cellular functions selective to leukemia cells positions it as a candidate for future therapeutic development.

Synthesis, identification and evaluation of molecular docking and experimental anti-cancer and antioxidant activity of new spiro four membered ring derivatives bearing 5-nitro isatin

Spiro-5-nitro isatino aza-β-lactams were produced by a [2 + 2] cycloaddition of 5-nitro isatin Schiff bases [1-5] with different aromatic isocyanate and thioisocyanate. 1HNMR and 13CNMR as well as FTIR spectroscopies, were used to identify the structures of the obtained compounds. These spiro-5-nitro isatin aza- β-lactams interest to us due to their potential antioxidant and anticancer properties. The MTT assay was used to examine in vitro bioactivity testing against breast cancer (MCF-7) cell lines. From result data, compound 14 displayed IC50 values that were lower than those of the clinically used anticancer drug tamoxifen toward MCF-7 cells after 24 h while compound 9 after 48 h synthesized compounds [6-20] were evaluated for against antioxidant activity by using DPPH assay. In molecular docking, Promising compounds were used to reveal potential cytotoxic activity mechanisms.

Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Accurate prediction of dynamic protein-ligand binding using P-score ranking

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.

Advances in Parkinson's disease research - A computational network pharmacological approach

Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is projected to see a significant rise in incidence over the next three decades. The precise treatment of PD remains a formidable challenge, prompting ongoing research into early diagnostic methodologies. Network pharmacology, a burgeoning field grounded in systems biology, examines the intricate networks of biological systems to identify critical signal nodes, facilitating the development of multi-target therapeutic molecules. This approach systematically maps the components of Parkinson's disease, thereby reducing its complexity. In this review, we explore the application of network pharmacology workflows in PD, discuss the techniques employed in this field, and evaluate the current advancements and status of network pharmacology in the context of Parkinson's disease. The comprehensive insights will pave newer paths to explore early disease biomarkers and to develop diagnosis with a holistic in silico, in vitro, in vivo and clinical studies.

Novel Inhibitory Site Revealed by Mode of Action on the Metabotropic Glutamate 7 Receptor Venus Flytrap Domain

Metabotropic glutamate (mGlu) receptors play a key role in modulating most synapses in the brain. The mGlu7 receptors inhibit presynaptic neurotransmitter release and offer therapeutic possibilities for post-traumatic stress disorders or epilepsy. Screening campaigns provided mGlu7-specific allosteric modulators as the inhibitor XAP044 (Gee et al. J. Biol. Chem. 2014). In contrast to other mGlu receptor allosteric modulators, XAP044 does not bind in the transmembrane domain but to the extracellular domain of the mGlu7 receptor and not at the orthosteric site. Here, we identified the mode of action of XAP044, combining synthesis of derivatives, modeling and docking experiments, and mutagenesis. We propose a unique mode of action of these inhibitors, preventing the closure of the Venus flytrap agonist binding domain. While acting as a noncompetitive antagonist of L-AP4, XAP044 and derivatives act as apparent competitive antagonists of LSP4-2022. These data revealed more potent XAP044 analogues and new possibilities to target mGluRs.

Are the metal identity and stoichiometry of metal complexes important for colchicine site binding and inhibition of tubulin polymerization?

Quite recently we discovered that copper(II) complexes with isomeric morpholine-thiosemicarbazone hybrid ligands show good cytotoxicity in cancer cells and that the molecular target responsible for this activity might be tubulin. In order to obtain better lead drug candidates, we opted to exploit the power of coordination chemistry to (i) assemble structures with globular shape to better fit the colchicine pocket and (ii) vary the metal ion. We report the synthesis and full characterization of bis-ligand cobalt(III) and iron(III) complexes with 6-morpholinomethyl-2-formylpyridine 4N-(4-hydroxy-3,5-dimethylphenyl)-3-thiosemicarbazone (HL1), 6-morpholinomethyl-2-acetylpyridine 4N-(4-hydroxy-3,5-dimethylphenyl)-3-thiosemicarbazone (HL2), and 6-morpholinomethyl-2-formylpyridine 4N-phenyl-3-thiosemicarbazone (HL3), and mono-ligand nickel(II), zinc(II) and palladium(II) complexes with HL1, namely [CoIII(HL1)(L1)](NO3)2 (1), [CoIII(HL2)(L2)](NO3)2 (2), [CoIII(HL3)(L3)](NO3)2 (3), [FeIII(L2)2]NO3 (4), [FeIII(HL3)(L3)](NO3)2 (5), [NiII(L1)]Cl (6), [Zn(L1)Cl] (7) and [PdII(HL1)Cl]Cl (8). We discuss the effect of the metal identity and metal complex stoichiometry on in vitro cytotoxicity and antitubulin activity. The high antiproliferative activity of complex 4 correlated well with inhibition of tubulin polymerization. Insights into the mechanism of antiproliferative activity were supported by experimental results and molecular docking calculations.

A Robust Induced Fit Docking Approach with the Combination of the Hybrid All-Atom/United-Atom/Coarse-Grained Model and Simulated Annealing

Molecular docking remains an indispensable tool in computational biology and structure-based drug discovery. However, the correct prediction of binding poses remains a major challenge for molecular docking, especially for target proteins where a substrate binding induces significant reorganization of the active site. Here, we introduce an Induced Fit Docking (IFD) approach named AA/UA/CG-SA-IFD, which combines a hybrid All-Atom/United-Atom/Coarse-Grained model with Simulated Annealing. In this approach, the core region is represented by the All-Atom(AA) model, while the protein environment beyond the core region and the solvent are treated with either the United-Atom (UA) or the Coarse-Grained (CG) model. By combining the Elastic Network Model (ENM) for the CG region, the hybrid model ensures a reasonable description of ligand binding and the environmental effects of the protein, facilitating highly efficient and reliable sampling of ligand binding through Simulated Annealing (SA) at a high temperature. Upon validation with two testing sets, the AA/UA/CG-SA-IFD approach demonstrates remarkable accuracy and efficiency in induced fit docking, even for challenging cases where the docked poses significantly deviate from crystal structures.

Exploring a New Generation of Pyrimidine and Pyridine Derivatives as Anti-Influenza Agents Targeting the Polymerase PA-PB1 Subunits Interaction

The limited range of available flu treatments due to virus mutations and drug resistance have prompted the search for new therapies. RNA-dependent RNA polymerase (RdRp) is a heterotrimeric complex of three subunits, i.e., polymerase acidic protein (PA) and polymerase basic proteins 1 and 2 (PB1 and PB2). It is widely recognized as one of the most promising anti-flu targets because of its critical role in influenza infection and high amino acid conservation. In particular, the disruption of RdRp complex assembly through protein-protein interaction (PPI) inhibition has emerged as a valuable strategy for discovering a new therapy. Our group previously identified the 3-cyano-4,6-diphenyl-pyridine core as a privileged scaffold for developing PA-PB1 PPI inhibitors. Encouraged by these findings, we synthesized a small library of pyridine and pyrimidine derivatives decorated with a thio-N-(m-tolyl)acetamide side chain (compounds 2a-n) or several amino acid groups (compounds 3a-n) at the C2 position. Interestingly, derivative 2d, characterized by a pyrimidine core and a phenyl and 4-chloro phenyl ring at the C4 and C6 positions, respectively, showed an IC50 value of 90.1 μM in PA-PB1 ELISA, an EC50 value of 2.8 μM in PRA, and a favorable cytotoxic profile, emerging as a significant breakthrough in the pursuit of new PPI inhibitors. A molecular modeling study was also completed as part of this project, allowing us to clarify the biological profile of these compounds.

Systematic computational strategies for identifying protein targets and lead discovery

Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein-ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.

Uncovering potential CDK9 inhibitors from natural compound databases through docking-based virtual screening and MD simulations

CONTEXT

Cyclin-dependent kinase 9 (CDK9) plays a significant role in gene regulation and RNA polymerase II transcription under basal and stimulated conditions. The upregulation of transcriptional homeostasis by CDK9 leads to various malignant tumors and therefore acts as a valuable drug target in addressing cancer incidences. Ongoing drug development endeavors targeting CDK9 have yielded numerous clinical candidate molecules currently undergoing investigation as potential CDK9 modulators, though none have yet received Food and Drug Administration (FDA) approval.

METHODS

In this study, we employ in silico approaches including the molecular docking and molecular dynamics simulations for the virtual screening over the natural compounds library to identify novel promising selective CDK9 inhibitors. The compounds derived from the initial virtual screening were subsequently employed for molecular dynamics simulations and binding free energy calculations to study the compound's stability under virtual physiological conditions. The first-generation CDK inhibitor Flavopiridol was used as a reference to compare with our novel hit compound as a CDK9 antagonist. The 500-ns molecular dynamics simulation and binding free energy calculation showed that two natural compounds showed better binding affinity and interaction mode with CDK9 receptors over the reference Flavopiridol. They also showed reasonable figures in the predicted absorption, distribution, metabolism, excretion, and toxicity (ADMET) calculations as well as in computational cytotoxicity predictions. Therefore, we anticipate that the proposed scaffolds could contribute to developing potential and selective CDK9 inhibitors subjected to further validations.

Antitumoral activity of different Amaryllidaceae alkaloids: In vitro and in silico assays

ETHNOPHARMACOLOGY RELEVANCE

The plants of Amaryllidaceae family, such as Amaryllis belladonna L., have been used as herbal remedies for thousands of years to address various disorders, including diseases that might today be identified as cancer.

AIM OF THE STUDY

The objective of this work was to evaluate the potential of three Amaryllidaceae alkaloids against four cancer cell lines.

MATERIAL AND METHODS

The alkaloids lycorine, 1-O-acetylcaranine, and montanine were evaluated in vitro against colon adenocarcinoma cell line (HCT-116) and breast carcinoma cell lines (MCF-7, MDAMB231, and Hs578T). Computational experiments (target prediction and molecular docking) were conducted to gain a deeper comprehension of possible interactions between these alkaloids and potential targets associated with these tumor cells.

RESULTS

Montanine presented the best results against HCT-116, MDAMB231, and Hs578T cell lines, while lycorine was the most active against MCF-7. In alignment with the target prediction outcomes and existing literature, four potential targets were chosen for the molecular docking analysis: CDK8, EGFR, ER-alpha, and dCK. The docking scores revealed two potential targets for the alkaloids with scores similar to co-crystallized inhibitors and substrates: CDK8 and dCK. A visual analysis of the optimal docked configurations indicates that the alkaloids may interact with some key residues in contrast to the other docked compounds. This observation implies their potential to bind effectively to both targets.

CONCLUSIONS

In vitro and in silico results corroborate with data literature suggesting the Amaryllidaceae alkaloids as interesting molecules with antitumoral properties, especially montanine, which showed the best in vitro results against colorectal and breast carcinoma. More studies are necessary to confirm the targets and pharmaceutical potential of montanine against these cancer cell lines.

Potent anti-coronaviral activity of pateamines and new insights into their mode of action

Pateamines, derived from the sponge Mycale hentscheli, function as inhibitors of the RNA helicase eIF4A and exhibit promising antiviral and anticancer properties. eIF4A plays a pivotal role in unwinding stable RNA structures within the 5'-UTR of selected mRNAs, facilitating the binding of the 43S preinitiation complex during translation initiation. Pateamines function by clamping RNA substrates onto the eIF4A surface, effectively preventing eIF4A from carrying out the unwinding step. Rocaglates, a compound class isolated from plants of the genus Aglaia, target the same binding pocket on eIF4A, and based on structural data, a similar mode of action has been proposed for pateamines and rocaglates. In this study, we conducted a detailed characterization of pateamines' binding mode and assessed their antiviral activity against human pathogenic coronaviruses (human coronavirus 229E (HCoV-229E), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)). Our findings reveal significant differences in the binding behavior of pateamines compared to rocaglates when interacting with an eIF4A-RNA complex. We also observed that pateamines do not depend on the presence of a polypurine tract in the RNA substrate for efficient RNA clamping, as it is the case for rocaglates. Most notably, pateamines demonstrate potent antiviral activity against coronaviruses in the low nanomolar range. Consequently, pateamines broaden our toolbox for combating viruses that rely on the host enzyme eIF4A to conduct their viral protein synthesis, indicating a possible future treatment strategy against new or re-emerging pathogenic viruses.

Discovery of Novel Allosteric SHP2 Inhibitor Using Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation, and Principal Component Analysis

SHP2 belongs to a cytoplasmic non-receptor protein tyrosine phosphatase class. It plays a critical role in the development of various cancers, such as gastric cancer, leukemia, and breast cancer. Thus, SHP2 has gained the interest of researchers as a potential target for inhibiting tumor cell proliferation in SHP2-dependent cancers. This study employed pharmacophore-based virtual screening, molecular docking, molecular dynamic (MD) simulations, MM/PBSA, and principal component analysis (PCA), followed by ADME prediction. We selected three potential hits from a collective database of more than one million chemical compounds. The stability of these selected hit-protein complexes was analyzed using 500 ns MD simulations and binding free energy calculations. The identified hits Lig_1, Lig_6, and Lig_14 demonstrated binding free energies of -161.49 kJ/mol, -151.28 kJ/mol, and -107.13 kJ/mol, respectively, compared to the reference molecule (SHP099) with a ΔG of -71.48 kJ/mol. Our results showed that the identified compounds could be used as promising candidates for selective SHP2 allosteric inhibition in cancer.

Rationalization of a Streptavidin Based Enantioselective Artificial Suzukiase: An Integrative Computational Approach

An Artificial Metalloenzyme (ArM) built employing the streptavidin-biotin technology has been used for the enantioselective synthesis of binaphthyls by means of asymmetric Suzuki-Miyaura cross-coupling reactions. Despite its success, it remains a challenge to understand how the length of the biotin cofactors or the introduction of mutations to streptavidin leads the preferential synthesis of one atropisomer over the other. In this study, we apply an integrated computational modeling approach, including DFT calculations, protein-ligand dockings and molecular dynamics to rationalize the impact of mutations and length of the biotion cofactor on the enantioselectivities of the biaryl product. The results unravel that the enantiomeric differences found experimentally can be rationalized by the disposition of the first intermediate, coming from the oxidative addition step, and the entrance of the second substrate. The work also showcases the difficulties facing to control the enantioselection when engineering ArM to catalyze enantioselective Suzuki-Miyaura couplings and how the combination of DFT calculations, molecular dockings and MD simulations can be used to rationalize artificial metalloenzymes.

Structure-Based Design and Synthesis of Covalent Inhibitors for Deubiquitinase and Acetyltransferase ChlaDUB1 of Chlamydia trachomatis

Upon infection by an intracellular pathogen, host cells activate apoptotic pathways to limit pathogen replication. Consequently, efficient proliferation of the obligate intracellular pathogen Chlamydia trachomatis, a major cause of trachoma and sexually transmitted diseases, depends on the suppression of host cell apoptosis. C. trachomatis secretes deubiquitinase ChlaDUB1 into the host cell, leading among other interactions to the stabilization of antiapoptotic proteins and, thus, suppression of host cell apoptosis. Targeting the bacterial effector protein may, therefore, lead to new therapeutic possibilities. To explore the active site of ChlaDUB1, an iterative cycle of computational docking, synthesis, and enzymatic screening was applied with the aim of lead structure development. Hereby, covalent inhibitors were developed, which show enhanced inhibition with a 22-fold increase in IC50 values compared to previous work. Comprehensive insights into the binding prerequisites to ChlaDUB1 are provided, establishing the foundation for an additional specific antichlamydial therapy by small molecules.

Vaccine design and development: Exploring the interface with computational biology and AI

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.

Anti-Human Immunodeficiency Virus-1 Property of Thai Herbal Extract Kerra™

Kerra™, a Thai traditional herbal medicine derived from the "Tak-Ka-Si-La Scripture" and composed of nine medicinal plants, has demonstrated potential antiviral properties against HIV. This study investigated the inhibitory effects of Kerra™ on HIV-1 reverse transcriptase (RT) and its ability to prevent pseudo-HIV viral infection in HEK293 cells. The results showed that Kerra™ extract achieved a 95.73 ± 4.24% relative inhibition of HIV-1 RT, with an IC50 value of 42.66 ± 8.74 µg/mL. Docking studies revealed that key phytochemicals in Kerra™, such as oleamide, formononetin, and biochanin A, interact with several residues in the RT non-nucleoside binding pocket, contributing to their inhibitory effects. Furthermore, Kerra™ was able to reduce pseudo-HIV infection in HEK293 cells at a concentration of 10 µg/mL, suggesting its potential as a supplementary treatment for HIV.

MolModa: accessible and secure molecular docking in a web browser

Molecular docking advances early-stage drug discovery by predicting the geometries and affinities of small-molecule compounds bound to drug-target receptors, predictions that researchers can leverage in prioritizing drug candidates for experimental testing. Unfortunately, existing docking tools often suffer from poor usability, data security, and maintainability, limiting broader adoption. Additionally, the complexity of the docking process, which requires users to execute a series of specialized steps, often poses a substantial barrier for non-expert users. Here, we introduce MolModa, a secure, accessible environment where users can perform molecular docking entirely in their web browsers. We provide two case studies that illustrate how MolModa provides valuable biological insights. We further compare MolModa to other docking tools to highlight its strengths and limitations. MolModa is available free of charge for academic and commercial use, without login or registration, at https://durrantlab.com/molmoda.

Disrupting TSLP-TSLP receptor interactions via putative small molecule inhibitors yields a novel and efficient treatment option for atopic diseases

Thymic stromal lymphopoietin (TSLP) is a key player in atopic diseases, which has sparked great interest in therapeutically targeting TSLP. Yet, no small-molecule TSLP inhibitors exist due to the challenges of disrupting the protein-protein interaction between TSLP and its receptor. Here, we report the development of small-molecule TSLP receptor inhibitors using virtual screening and docking of >1,000,000 compounds followed by iterative chemical synthesis. BP79 emerged as our lead compound that effectively abrogates TSLP-triggered cytokines at low micromolar concentrations. For in-depth analysis, we developed a human atopic disease drug discovery platform using multi-organ chips. Here, topical application of BP79 onto atopic skin models that were co-cultivated with lung models and Th2 cells effectively suppressed immune cell infiltration and IL-13, IL-4, TSLP, and periostin secretion, while upregulating skin barrier proteins. RNA-Seq analysis corroborate these findings and indicate protective downstream effects on the lungs. To the best of our knowledge, this represents the first report of a potent putative small molecule TSLPR inhibitor which has the potential to expand the therapeutic and preventive options in atopic diseases.

Phytochemical composition of aerial parts and roots of Pfaffia glomerata (Spreng.) Pedersen and anticholinesterase, antioxidant, and antiglycation activities

The Pfaffia glomerata, a plant popularly called Brazilian ginseng, is widely used in Brazil for the treatment of various pathologies, including those associated with the Central Nervous System. 20-hydroxyecdysone (20E), a phytosteroid present in this plant, can promote adaptogenic effects in the organism, providing greater body resistance to stressors. This study aimed to evaluate the phytochemical composition and the anticholinesterase, antioxidant, and antiglycation effects of extracts and fractions of aerial parts and roots of P. glomerata, also analyzing their possible cytotoxic effects. The fractions were obtained by partitioning methanol extracts from the aerial part and roots of P. glomerata with hexane, dichloromethane, ethyl acetate, n-butanol, and water. The samples were initially tested in anticholinesterase, antioxidant, and antiglycation assays, and the most promising samples were submitted for cytotoxicity and chromatographic analyses. Mass spectrometry and chromatography methods revealed that 20E was the main compound in the dichloromethane fractions, there being 35% more 20E in the aerial part (APD) than in the roots (RD). Added to the higher concentration of 20E, the APD fraction also presented more promising results than the RD fraction in anticholinesterase and antioxidant analyses, indicating that their effects may be related to the concentration of 20E. These same fractions showed no hemolytic effects but were cytotoxic in high concentrations. These new findings contribute to scientific information about P. glomerata and open more perspectives for the understanding of its therapeutic properties, allowing the association of biological activity with the presence of 20E.

Efficient, rapid, and high-yield synthesis of aryl Schiff base derivatives and their in vitro and in silico inhibition studies of hCA I, hCA II, AChE, and BuChE

This study reports a rapid and efficient synthesis of four novel aryl Schiff base derivatives. Biological activity and molecular modeling studies were conducted to evaluate the inhibitory effects of these compounds on human carbonic anhydrases (hCA) and cholinesterases. The results indicate that the triazole-ring-containing compounds have strong inhibitory effects on hCA I, hCA II, acetylcholinesterase (AChE), and butyrylcholinesterase (BuChE) targets. Besides comparing the Schiff bases synthesized in our study to reference molecules, we conducted in silico investigations to examine how these compounds interact with their targets. Our studies revealed that these compounds can occupy binding sites and establish interactions with crucial residues, thus inhibiting the functions of the targets. These findings have significant implications as they can be utilized to develop more potent compounds for treating the diseases that these target proteins play crucial roles in or to obtain drug precursors with enhanced efficacy.

Interaction with CT-DNA and in vitro cytotoxicity of two new copper(II)-based potential drugs derived from octanoic hydrazide ligands

Two copper(II) complexes [Cu(Hpmoh)(NO3)(NCS)] (1) and [Cu(peoh)(N3)]2 (2) were designed and synthesized by reaction of Cu(NO3)2·3H2O with hydrazone Schiff base ligands,abbreviated with Hpmoh and Hpeoh. Hpmoh and Hpeoh were prepared by condensation reaction of octanoic hydrazide with pyridine-2-carboxyaldehyde and 2-acetylpyridine, respectively. Complexes 1 and 2 were characterized using different analytical techniques such as FT-IR, UV-Vis, IR, EPR and single X-ray diffraction (XRD) analyses as well as computational methods (DFT). The XRD of 1 and 2 shows a mononuclear or a dinuclear structure with the copper(II) centre adopting a slightly distorted square pyramidal geometry. In water-containing solution and in DMSO, 1 and 2 undergo a partial transformation with formation of [Cu(Hpmoh)(NO3)(NCS)] (1) and [Cu(Hpmoh)(NO3)(H2O/DMSO)] (1a) in one system and [Cu(peoh)(N3)] (2a) in the other one, as supported by DFT calculations. Docking simulations confirmed that the intercalation is the preferred binding mode with DNA for 1, 1a and 2a, but suggested that the minor groove binding is also possible. A significant fluorescence quenching of the DNA-ethidium bromide conjugate was observed upon the addition of complexes 1 and 2 with a quenching constant around 104 M-1 s-1. Finally, both 1 and 2 were examined for anti-cancer activity using MDA-MB-231 (human breast adenocarcinoma) and A375 (malignant melanoma) cell lines through in vitro MTT assay which suggest comparable cancer cell killing efficacy, with the higher effectiveness of 2 due to the dissociation into two [Cu(peoh)(N3)] units.

LIKE EARLY STARVATION 1 interacts with amylopectin during starch biosynthesis

Starch is the major energy storage compound in plants. Both transient starch and long-lasting storage starch accumulate in the form of insoluble, partly crystalline granules. The structure of these granules is related to the structure of the branched polymer amylopectin: linear chains of glucose units organized in double helices that align to form semicrystalline lamellae, with branching points located in amorphous regions between them. EARLY STARVATION 1 (ESV1) and LIKE EARLY STARVATION 1 (LESV) proteins are involved in the maintenance of starch granule structure and in the phase transition of amylopectin, respectively, in Arabidopsis (Arabidopsis thaliana). These proteins contain a conserved tryptophan-rich C-terminal domain folded into an antiparallel β-sheet, likely responsible for binding of the proteins to starch, and different N-terminal domains whose structure and function are unknown. In this work, we combined biochemical and biophysical approaches to analyze the structures of LESV and ESV1 and their interactions with the different starch polyglucans. We determined that both proteins interact with amylopectin but not with amylose and that only LESV is capable of interacting with amylopectin during starch biosynthesis. While the C-terminal domain interacts with amylopectin in its semicrystalline form, the N-terminal domain of LESV undergoes induced conformational changes that are probably involved in its specific function of mediating glucan phase transition. These results clarify the specific mechanism of action of these 2 proteins in the biosynthesis of starch granules.

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.

Synthesis of Chiral Acyclic Pyrimidine Nucleoside Analogues from DHAP-Dependent Aldolases

Dihydroxyacetone phosphate (DHAP)-dependent aldolases catalyze the aldol addition of DHAP to a variety of aldehydes and generate compounds with two stereocenters. This reaction is useful to synthesize chiral acyclic nucleosides, which constitute a well-known class of antiviral drugs currently used. In such compounds, the chirality of the aliphatic chain, which mimics the open pentose residue, is crucial for activity. In this work, three DHAP-dependent aldolases: fructose-1,6-biphosphate aldolase from rabbit muscle, rhanmulose-1-phosphate aldolase from Thermotoga maritima, and fuculose-1-phosphate aldolase from Escherichia coli, were used as biocatalysts. Aldehyde derivatives of thymine and cytosine were used as acceptor substrates, generating new acyclic nucleoside analogues containing two new stereocenters with conversion yields between 70% and 90%. Moreover, structural analyses by molecular docking were carried out to gain insights into the diasteromeric excess observed.

Bioinformatics tools for the study of bioactive peptides from vegetal sources: evolution and future perspectives

Bioactive peptides from vegetal sources have been shown to have functional properties as anti-inflammatory, antioxidant, antihypertensive or antidiabetic capacity. For this reason, they have been proposed as an interesting and promising alternative to improve human health. In recent years, the numerous advances in the bioinformatics field for in silico prediction have speeded up the discovery of bioactive peptides, also reducing the associated costs when using an integrated approach between the classical and bioinformatics discovery. This review aims to provide an overview of the evolution, limitations and latest advances in the field of bioinformatics and computational tools, and specifically make a critical and comprehensive insight into computational techniques used to study the mechanism of interaction that allows the explanation of plant bioactive peptide functionality. In particular, molecular docking is considered key to explain the different functionalities that have been previously identified. The assumptions to simplify such a high complex environment implies a degree of uncertainty that can only be guaranteed and validated by in vitro or in vivo studies, however, the combination of databases, software and bioinformatics applications with the classical approach has become a promising procedure for the study of bioactive peptides.

A Structure-Activity Investigation of the Fungal Metabolite (-)-TAN-2483B: Inhibition of Bruton's Tyrosine Kinase

The natural product (-)-TAN-2483B is a fungal secondary metabolite which displays promising anti-cancer and immunomodulatory activity. Our previous syntheses of (-)-TAN-2483B and sidechain analogues uncovered inhibitory activity against Bruton's tyrosine kinase (Btk), an established drug target for various leukaemia and immunological diseases. A structure-based computational study using ensemble docking and molecular dynamics was performed to determine plausible binding modes for (-)-TAN-2483B and analogues in the Btk binding site. These hypotheses guided the design of new analogues which were synthesised and their inhibitory activities determined, providing insights into the structural determinants of the furopyranone scaffold that confer both activity and selectivity for Btk. These findings offer new perspectives for generating optimised (-)-TAN-2483B-based kinase inhibitors for the treatment of leukaemia and immunological diseases.

Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme

The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.

Novel Penicillin-Based Sulfone-Siderophore Conjugates for Restoring β-Lactam Antibiotic Efficacy

Membrane permeability is a natural defense barrier that contributes to increased bacterial drug resistance, particularly for Gram-negative pathogens. As such, accurate delivery of the antibacterial agent to the target has become a growing research area in the infectious diseases field as a means of improving drug efficacy. Although the efficient transport of siderophore-antibiotic conjugates into the cytosol still remains challenging, great success has been achieved in the delivery of β-lactam antibiotics into the periplasmic space via bacterial iron uptake pathways. Cefiderocol, the first siderophore-cephalosporin conjugate approved by the US Food and Drug Administration, is a good example. These conjugation strategies have also been applied to the precise delivery of β-lactamase inhibitors, such as penicillin-based sulfone 1, to restore β-lactam antibiotic efficacy in multidrug-resistant bacteria. Herein, we have explored the impact on the bacterial activity of 1 by modifying its iron chelator moiety. A set of derivatives functionalized with diverse iron chelator groups and linkages to the scaffold (compounds 2-8) were synthesized and assayed in vitro. The results on the ability of derivatives 2-8 to recover β-lactam antibiotic efficacy in difficult-to-treat pathogens that produce various β-lactamase enzymes, along with kinetic studies with the isolated enzymes, allowed us to identify compound 2, a novel β-lactamase inhibitor with an expanded spectrum of activity. Molecular dynamics simulation studies provided us with further information regarding the molecular basis of the relative inhibitory properties of the most relevant compound described herein.

Copper(II) Complexes with Isomeric Morpholine-Substituted 2-Formylpyridine Thiosemicarbazone Hybrids as Potential Anticancer Drugs Inhibiting Both Ribonucleotide Reductase and Tubulin Polymerization: The Morpholine Position Matters

The development of copper(II) thiosemicarbazone complexes as potential anticancer agents, possessing dual functionality as inhibitors of R2 ribonucleotide reductase (RNR) and tubulin polymerization by binding at the colchicine site, presents a promising avenue for enhancing therapeutic effectiveness. Herein, we describe the syntheses and physicochemical characterization of four isomeric proligands H2L3-H2L6, with the methylmorpholine substituent at pertinent positions of the pyridine ring, along with their corresponding Cu(II) complexes 3-6. Evidently, the position of the morpholine moiety and the copper(II) complex formation have marked effects on the in vitro antiproliferative activity in human uterine sarcoma MES-SA cells and the multidrug-resistant derivative MES-SA/Dx5 cells. Activity correlated strongly with quenching of the tyrosyl radical (Y•) of mouse R2 RNR protein, inhibition of RNR activity in the cancer cells, and inhibition of tubulin polymerization. Insights into the mechanism of antiproliferative activity, supported by experimental results and molecular modeling calculations, are presented.

Molecular modeling of multi-target analogs of huperzine A and applications in Alzheimer's disease

CONTEXT

Given the diverse pathophysiological mechanisms underlying Alzheimer's disease, it is improbable that a single targeted drug will prove successful as a therapeutic strategy. Therefore, exploring various hypotheses in drug design is imperative. The sequestration of Fe(II) and Zn(II) cations stands out as a crucial mechanism based on the mitigation of reactive oxygen species. Moreover, inhibiting acetylcholinesterase represents a pivotal strategy to enhance acetylcholine levels in the synaptic cleft. This research aims to investigate the analogs of Huperzine A, documented in scientific literature, considering of these two hypotheses. Consequently, the speciation chemistry of these structures with Fe(II) and Zn(II) was scrutinized using quantum chemistry calculations, molecular docking simulations, and theoretical predictions of pharmacokinetics properties. From the pharmacokinetic properties, only two analogs, HupA-A1 and HupA-A2, exhibited a theoretical permeability across the blood-brain barrier; on the other hand, from a thermodynamic standpoint, the enantiomers of HupA-A2 showed negligible chelation values. The enantiomers with the most favorable interaction parameters were S'R'HupA-A1 (ΔGBIND = -40.0 kcal mol-1, fitness score = 35.5) and R'R'HupA-A1 (ΔGBIND = -35.5 kcal mol-1, fitness score = 22.61), being compared with HupA (ΔGBIND = -41.75 kcal mol-1, fitness score = 39.95). From this study, some prime candidates for promising drug were S'R'HupA-A1 and R'R'HupA-A1, primarily owing to their favorable thermodynamic chelating capability and potential anticholinesterase mechanism.

METHODS

Quantum chemistry calculations were carried out at B3LYP/6-31G(d) level, considering the IEF-PCM(UFF) implicit solvent model for water. The coordination compounds were assessed using the Gibbs free energy variation and hard and soft acid theory. Molecular docking calculations were conducted using the GOLD program, based on the crystal structure of the acetylcholinesterase protein (PDB code = 4EY5), where the ChemScore function was employed with the active site defined as the region within a 15-Å radius around the centroid coordinates (X = -9.557583, Y = -43.910473, Z = 31.466687). Pharmacokinetic properties were predicted using SwissADME, focusing on Lipinski's rule of five.

Preferential HDAC6 inhibitors derived from HPOB exhibit synergistic antileukemia activity in combination with decitabine

Histone deacetylase 6 (HDAC6) is an emerging drug target to treat oncological and non-oncological conditions. Since highly selective HDAC6 inhibitors display limited anticancer activity when used as single agent, they usually require combination therapies with other chemotherapeutics. In this work, we synthesized a mini library of analogues of the preferential HDAC6 inhibitor HPOB in only two steps via an Ugi four-component reaction as the key step. Biochemical HDAC inhibition and cell viability assays led to the identification of 1g (highest antileukemic activity) and 2b (highest HDAC6 inhibition) as hit compounds. In subsequent combination screens, both 1g and especially 2b showed synergy with DNA methyltransferase inhibitor decitabine in acute myeloid leukemia (AML). Our findings highlight the potential of combining HDAC6 inhibitors with DNA methyltransferase inhibitors as a strategy to improve AML treatment outcomes.

Influence of heterochirality on the structure, dynamics, biological properties of cyclic(PFPF) tetrapeptides obtained by solvent-free ball mill mechanosynthesis

Cyclic tetrapeptides c(Pro-Phe-Pro-Phe) obtained by the mechanosynthetic method using a ball mill were isolated in a pure stereochemical form as a homochiral system (all L-amino acids, sample A) and as a heterochiral system with D configuration at one of the stereogenic centers of Phe (sample B). The structure and stereochemistry of both samples were determined by X-ray diffraction studies of single crystals. In DMSO and acetonitrile, sample A exists as an equimolar mixture of two conformers, while only one is monitored for sample B. The conformational space and energetic preferences for possible conformers were calculated using DFT methods. The distinctly different conformational flexibility of the two samples was experimentally proven by Variable Temperature (VT) and 2D EXSY NMR measurements. Both samples were docked to histone deacetylase HDAC8. Cytotoxic studies proved that none of the tested cyclic peptide is toxic.

Recent advances in computational and experimental protein-ligand affinity determination techniques

INTRODUCTION

Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.

AREAS COVERED

In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.

EXPERT OPINION

The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.