Binding Site Detection Remastered: Enabling Fast, Robust, and Reliable Binding Site Detection and Descriptor Calculation with DoGSite3

Evaluation of the intrinsic antibacterial and antibiotic potentiating activity against antibiotic resistance in Staphylococcus aureus and inhibition of the NorA and MepA efflux pumps by a hydrazone derivative of isoniazid

Hydrazones are organic compounds with promising antimicrobial properties, particularly in the fight against resistant microorganisms. The aim of this study was to synthesize and evaluate the antibacterial activity of the hydrazone derivative of isoniazid N'-[[4-({[(pyridin-4-yl)formamido]imino] methyl)phenyl]methylidene]pyridine-4 carbohydrazide (BISHDZHI) against Staphylococcus aureus overexpressing NorA and MepA efflux pumps. The broth microdilution methodology was used in the microbiological tests to evaluate the antibacterial potential of the BISHDZHI compound and its ability to inhibit efflux pump resistance mechanisms. To elucidate the mechanism of action, molecular docking simulations were conducted to assess the binding affinity of BISHDZHI to the NorA and MepA efflux pumps. Minimum inhibitory concentration (MIC) tests showed that BISHDZHI in association with norfloxacin moderately reduced the MIC of the antibiotic, indicating the enhancement of its efficacy. However, an antagonistic effect was observed in combination with ethidium bromide, suggesting that the compound does not directly inhibit bacterial efflux pumps, but may act on other intracellular targets, such as the enzyme topoisomerase IV. The docking studies revealed strong interactions between BISHDZHI and key amino acid residues within the efflux pumps, particularly Tyr225, Val302, and Phe306 in NorA and Leu59, Phe280, and Tyr276 in MepA. The docking scores indicated favorable binding energies, suggesting potential inhibitory effects on efflux activity. This study highlights the potential of the hydrazone BISHDZHI as a promising candidate for treating infections caused by the bacterium Staphylococcus aureus.

Structural Basis and Recognition Mechanism of Host-Derived Volatiles by Olfactory Proteins in the Agricultural Pest Bactrocera correcta (Diptera: Tephritidae)

Host-derived volatiles play a critical role in mediating plant-insect interactions. Bactrocera correcta is a destructive pest of fruit crops. In this study, we investigated the recognition mechanisms of three key volatiles─β-caryophyllene, ethyl decanoate, and hexyl hexanoate─derived from the host fruits of B. correcta. Using transcriptomic analysis, fluorescence binding assays, molecular docking, and molecular dynamics simulations, we identified BcorOBP19d-2 as a key odorant-binding protein that binds multiple volatiles and facilitates their stabilization and transport. Odorant receptors (BcorOR7a-13, BcorOR74a-3, and BcorOR7a-3) selectively recognize these volatiles, with hydrophobic interactions as the primary driving force for binding. β-Caryophyllene exhibited the highest binding specificity with BcorOR7a-13, ethyl decanoate demonstrated the strongest binding affinity with BcorOR74a-3, and hexyl hexanoate showed moderate stability with BcorOR7a-3. These findings provide structural insights into volatile recognition in polyphagous insects and offer a basis for developing attractants or repellents for pest management.

ProteinsPlus: a publicly available resource for protein structure mining

The openly accessible ProteinsPlus web server at https://proteins.plus is a unique resource enabling protein structure mining and modeling, focussing on protein-ligand interactions. Since its launch in 2017, the number of tools is steadily increasing. Currently, the server comprises six methods for protein structure analysis, four tools for mining the Protein Data Bank (PDB), and five prediction approaches regarding protein-ligand complex modeling. Users can use experimental structures from the PDB or computationally predicted structures from the AlphaFold Protein Structure Database as starting points. Alternatively, they can upload individual structure files. Recent updates include novel methods for detecting binding sites and predicting solvent channels in crystallographic structures, as well as updates of tools for protein-ligand interaction depiction in 2D and binding site mining. Given these updates, we present a real-life application scenario that underpins the novelties and applicability of the web server's tools for modern structure-based design projects. It also highlights the next steps for the web server, which will be redesigned using a different technology stack to improve the inter-usability of the tools, ease maintainability, and make it future-proof.

AlloBench: A Data Set Pipeline for the Development and Benchmarking of Allosteric Site Prediction Tools

Allostery refers to the activity regulation of biological macromolecules originating from the binding of an effector molecule at the allosteric site that is distant from the active site. The few existing allosteric data sets have not been updated with recent discoveries of allosteric proteins and are challenging to use for data-intensive tasks. Instead of providing another data set bound to become outdated, we present the AlloBench pipeline to create high-quality data sets of biomolecules with allosteric and active site information suitable for computational and data-driven studies of protein allostery. The pipeline produces a data set of 2141 allosteric sites from 2034 protein structures with 418 unique protein chains by integrating information from AlloSteric Database, UniProt, Mechanism and Catalytic Site Atlas, and Protein Data Bank. Furthermore, we use a subset of 100 proteins from the AlloBench data set to quantitatively compare the performance of currently available allosteric site prediction tools: APOP, PASSer, Ohm, ALLO, Allosite, STRESS, and AlloPred. Such a large-scale benchmarking of these programs has not been undertaken on a common test set. The results show a significant need for improvement, as the accuracy for all programs is well below 60%, with PASSer (Ensemble) outperforming the rest. The AlloBench pipeline will not only promote the development of improved allosteric site prediction tools but also serve as a reference for studying allostery in general.

Activated effect of chondroitin sulfate on α-glucosidase: An in vitro and in silico approach

Chondroitin sulfate (CS), a glycosaminoglycan (GAG), plays a pivotal role in various physiological functions and is extensively utilized in medical and clinical applications. This study aimed to explore the enhancing effects and underlying mechanisms of three commonly encountered sulfated glycosaminoglycans CS-A, CS-C and CS-D on α-glucosidase activity. In vitro enzyme kinetic studies demonstrated that all three types of CS promoted α-glucosidase activity, with CS-D exhibiting the most pronounced effect, reaching 124.7 %. Fluorescence and circular dichroism (CD) spectroscopy, along with molecular docking experiments, revealed that CSs spontaneously interacted with the enzyme's active site, forming hydrogen bonds with Arg600 and His674. Additionally, hydrophobic interactions with Trp376 and Trp481 further strengthened these hydrogen bonds. These interactions increased the flexibility of the α-glucosidase polypeptide backbone, leading to greater solvent exposure of Trp residues and alterations in the enzyme's secondary structure composition. Furthermore, trajectory analysis from kinetic simulations indicated that activation of the α-glucosidase active site induced an inward folding and contraction of the region, thereby enlarging the internal cavity and enhancing its hydrophobic nature. This structural reconfiguration not only provided additional space for substrate hydrolysis but also minimized interference from water molecules, collectively contributing to an overall enhancement of α-glucosidase hydrolytic activity. In conclusion, this study identifies CS as an α-glucosidase activator and elucidates its interaction mechanisms through both in vitro and in silico approaches, highlighting its potential applications in the food industry.

Mechanism of influence of nattokinase terminal sequence on catalytic performance and molecular modification

Nattokinase from traditional food natto has the potential to be a thrombolytic agent. Its terminal sequence has an important effect on the catalytic performance of nattokinase, but the specific mechanism is still unclear. In this study, computational simulation combined with truncated mutagenesis and alanine scanning technology were used to identify the key sites affecting the catalytic performance of nattokinase. Subsequently, mutants Q10L and Q275G with 4.00-fold and 4.83-fold increased half-lives at 55 °C were screened by site-directed saturation mutagenesis. Constraint network analysis and molecular dynamics simulation revealed that the thermal stability of the two mutants was enhanced by solvent interaction and indirect effects on the Ca2+ binding sites. However, the combined mutation Q10L-Q275G did not demonstrate additive thermal stability. This study provides technical support for the engineering modification of nattokinase.

Effective Immobilization of hnRNPA2B1 Protein in a PEI Layer on a QCM Gold Electrode

RNA-binding proteins (RBPs) play a crucial role in RNA metabolism, influencing processes like transcription, splicing, transport, and stability, as well as cell proliferation and immune responses. Their links to diseases, such as cancer and neurological disorders, make them prime candidates for therapeutic targeting. Among these, heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is notable for its regulation of gene expression and involvement in telomere maintenance and DNA repair. Its activity in various cancers and neurodegenerative diseases positions it as a promising target for drug development. The quartz crystal microbalance (QCM) method offers an efficient alternative to traditional binding affinity assessments such as spectroscopy, allowing experiments with minimal reagents and without extensive modifications. A key to effective QCM analysis is immobilization of the target protein to prevent denaturation. This study outlines a strategy for immobilizing hnRNPA2B1 onto a gold electrode using a polyethylenimine (PEI) layer. Adsorption processes and stability were monitored via frequency shift (Δf/n) and dissipation change (ΔD/n) measurements. The results showed that hnRNPA2B1's adsorption on branched PEI resulted in weak binding interactions, while adsorption on a linear PEI layer led to a negative frequency shift of -21 Hz. Increasing the ionic strength to 0.1 mM significantly enhanced protein adsorption (Δf/n = -69 Hz). These findings emphasize the role of the PEI layer structure in optimizing protein immobilization, paving the way for further exploration of RBPs and their ligands.

Molecular dynamic simulations to assess the structural variability of ClpV from Enterobacter cloacae

The Enterobacter cloacae complex (ECC) consists of six Enterobacter species (E. cloacae, hormaechei, kobei, ludwigii, nimipressuralis and asburiae) that have emerged as nosocomial pathogens of interest, with E. cloacae and Enterobacter hormachei being the most frequently isolated ECC species in human clinical specimens and intensive care unit (ICU) patients. Many nosocomial outbreaks of E. cloacae have been related to transmission through contaminated surgical equipment and operative cleaning solutions. As this pathogen evades the action of antibiotics, it is important to find alternative targets to limit the devastating effects of these pathogens. ClpV is a Clp ATPase which dissociates and recycles the contracted sheath of the bacterial type VI secretion system (T6SS), thereby regulating bacterial populations and facilitating environmental colonization. Seventy-one Enterobacter strains were mined for Clp ATPase proteins. All the investigated strains contained ClpA, ClpB, ClpX and ClpV while only 20% contained ClpK. All the investigated strains contained more than one ClpV protein, and the ClpV proteins showed significant variations. Three ClpV proteins from E. cloacae strain E3442 were then investigated to determine the structural difference between each protein. Homology modelling showed the proteins to be structurally similar to each other, however the physicochemical characteristics of the proteins vary. Additionally, physicochemical analysis and molecular dynamic simulations showed that the proteins were highly dynamic and not significantly different from each other. Further investigation of the proteins in silico and in vitro in the presence and absence of various ligands and proteins could be performed to determine whether the proteins all interact with their surroundings in the same manner. This would allow one to determine why multiple homologs of the same protein are expressed by pathogens.

In Vitro Evaluation of Esters of Quinoxaline-1,4-di-N-oxide Derivatives as New Antitaeniasis Agents and Their Inhibitory Activity Against Triosephosphate Isomerase

Background/Objectives: Pork tapeworm Taenia solium is the causative agent of cysticercosis which may develop in muscle tissue, skin, eyes, and the central nervous system (neurocysticercosis). It is estimated by the World Health Organization (WHO) that about 2.56-8.30 million are infected worldwide. Praziquantel and albendazole are used for anthelminthic treatment of neurocysticercosis; however, not all patients have a complete elimination of cysts, which makes it necessary to seek new and improved treatment options. Methods: In this study, methyl, ethyl, n-propyl, and iso-propyl quinoxaline-7-carboxylate-1,4-di-N-oxide derivatives were evaluated in vitro against Taenia crassiceps (T. crassiceps) cysts. Additionally, to know their potential mode of action, a molecular docking analysis on T. solium triosephosphate isomerase (TsTIM) and an enzyme inactivation assay on recombinant TsTIM were carried out. Results: Nine compounds had time- and concentration-dependent cysticidal activity. Particularly, compounds TS-12, TS-19, and TS-20 (EC50 values 0.58, 1.02, and 0.80 µM, respectively) were equipotent to albendazole sulfoxide (EC50 = 0.68 µM). However, TS-12 compounds only cause a slight inhibition of TsTIM (<40% at 1000 µM), suggested that another drug target is implicated in the biological effects. Conclusions: These results demonstrated that quinoxaline 1,4-di-N-oxide is a scaffold to develop new and more potent antitaeniasis agents, although it is necessary to explore other pharmacological targets to understand their mode of action.

Unraveling Interleukin-1β inhibition: Computational insights into anti-inflammatory compound selection for inflammatory disorders

The multifaceted impact of IL-1β has been proposed to have a central role in a spectrum of immunological responses spanning physiological reactions to aggressive inflammatory reactions and autoimmune disorders. Once IL-1β binds to its cognate receptor it initiates IL-1R1/TLR4 signaling cascade, leading to transcriptional modifications that sustain the inflammatory response. Extensive structural and functional investigations on IL-1β have yielded various inhibitors aimed at disrupting the formation of ligand receptor complex. Unfortunately, most have proven unsuccessful in clinical trials. Therefore, directing efforts towards IL-1β/IL-1R1 presents a unique opportunity to formulate an alternative therapy for the treatment of inflammatory disorders. In view of this, the present study aimed to identify small molecules obstructing protein-protein interactions (PPIs) to impede heterocomplex formation. In this context, a search query was formulated by integrating a ligand-based pharmacophore mapping alongside a multi-stage molecular docking to assess the potential of the predicted hits in terms of binding modes within the targeted cavity of the IL-1β and the associated binding affinities. Thus, via a stepwise screening process starting from an initial pool of 40,000 compounds, 8 potential hits were identified for detailed atomic studies employing molecular dynamic simulation encompassing a total time frame of 0.9 μs. The investigation in dynamic behavior was followed by the estimation of free energies using molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations. The stability matrices revealed that the chosen virtual hits possess a notable potential to hinder the complex formation between IL-1β/IL-1RI. The average backbone deviations recorded for the conformational ensembles of the ligand free IL-1β/IL-1RI exhibited significant dynamics, featuring the average value of 0.35 nm. Conversely, the identified hits particularly, inhouse-2603 and inhouse-1325 demonstrated a high degree of stability with mean values of 0.32 ± 0.05, 0.31 ± 0.03, respectively. The residue-wise fluctuations were maximum for Compound-1303, with the mean value of 0.31 nm and minimal for Compound-2691 with the mean value 0.21 nm. The MMPBSA revealed the highest binding energy of -89.50 ± 10.63, and -81.32 ± 14.9 kcal/mol, for the IL-1β/IL-1RI complex with compound-2603, and Compound-1325 respectively. The principal component analysis (PCA) in conjunction with free energy landscape (FEL) further shed light on the conformational space in terms of energetic stability. Considering the essential role of IL-1β in mediating several inflammatory cascades, it is proposed that the identified PPI inhibitors since demonstrated stable behavior and promising attributes in regard to inhibitory potential as outlined by mechanistic exploration, may serve as new chemotypes for the future exploration aimed at mitigation inflammatory disorders.

Chemical Composition and Larvicidal Activity Against Aedes aegypti of the Leaf Essential Oils from Croton blanchetianus

The Aedes aegypti mosquito is the primary vector of dengue, a neglected disease and a serious public health problem in tropical countries. The control of this vector has been carried out using chemical insecticides, which impact human health. Thus, it is essential to develop natural larvicides that are less harmful to the environment. This study investigates the circadian cycle and larvicidal activity of essential oils from Croton blanchetianus against Aedes aegypti. The leaf oils were extracted by hydrodistillation and analyzed by GC-MS and GC-FID. The circadian study revealed variations in the chemical composition of oils extracted at different times of the day. The main constituents were α-pinene, β-phellandrene, eucalyptol, β-caryophyllene, bicyclogermacrene, and spathulenol. The larvicidal activity showed LC50 values at the following different collection times: 55.294 ± 3.209 μg/mL at 08:00 h; 95.485 ± 2.684 μg/mL at 12:00 h; and 64.883 ± 1.780 μg/mL at 17:00 h. Molecular docking simulations indicated that α-pinene, β-phellandrene, eucalyptol, and β-caryophyllene strongly interact with the active site of the sterol carrier protein, suggesting their role in larvicidal activity. These findings reinforce the potential of C. blanchetianus essential oils as an alternative for Aedes aegypti control. The predictive pharmacokinetic tests showed a PAMPA profile associated with high effective cellular permeability and microsomal stability, resulting from the metabolic stability of the derivatives (3) eucalyptol and (6) spathulenol, indicating that these compounds have the highest pharmacokinetic viability and low reactivity with respect to organ toxicity.

Synthesis strategies and anti-parasitic evaluation of novel compounds for chagas disease: Advancing drug discovery through structure-activity relationships

This study presents a comprehensive exploration of the synthesis of novel compounds targeting Chagas Disease (CD) caused by Trypanosoma cruzi. It is a global health threat with over 6-7 million infections worldwide. Addressing challenges in current treatments, the investigation explores diverse compound classes, including thiazoles, thiazolidinone, imidazole, pyrazole, 1,6-diphenyl-1H-pyrazolo[3,4-b] pyridine, pyrrole, naphthoquinone, neolignan, benzeneacyl hydrazones, and chalcones-based compounds. Highlighting compounds with superior trypanocidal activity compared to standard drugs. The study elucidates structure-activity relationships, emphasizing the impact of substituents, fluorine presence, and substitution patterns. Noteworthy findings include neolignan derivatives demonstrating efficacy against intracellular amastigotes and free-moving trypomastigotes, with unsaturated side chains. Benzeneacylhydrazones and chalcones, as novel classes, showed varied efficacy, with certain compounds surpassing benznidazole. A novel series of triketone compounds exhibited strong anti-parasitic activity, outperforming standard drugs. Docking study revealed that the halogen and methoxy substituted phenyl ring, thiazole, thiazolidine-4-one, quinoline, isoindoline-1,3-dione, pyrrole heterocyclic motifs can play the key role in the designing of effective inhibitors of T. cruzi. Mutually, these insights placed the foundation for the development of innovative and effective treatments for CD, addressing the urgent need for improved therapeutic options.

MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction

Predicting drug-target binding affinity (DTA) is a crucial task in drug discovery research. Recent studies have demonstrated that pocket features and interactions between targets and drugs significantly improve the understanding of DTA. However, challenges remain, particularly in the detailed consideration of both global and local information and the further modeling of pocket features. In this paper, we propose a novel multimodal deep learning model named MMPD-DTA for predicting drug-target binding affinity to address these challenges. The MMPD-DTA model integrates graph and sequence modalities of targets, pockets, and drugs to capture both global and local target and drug information. The model introduces a novel pocket-drug graph (PD graph) that simultaneously models atomic interactions within the target, within the drug, and between the target and drug. We employ GraphSAGE for graph representation learning from the PD graph, complemented by sequence representation learning via transformers for the target sequence and graph representation learning via a graph isomorphism network for the drug molecular graph. These multimodal representations are then concatenated, and a multilayer perceptron generates the final binding affinity predictions. Experimental results on three real-world test sets demonstrate that the MMPD-DTA model outperforms baseline methods. Ablation studies further confirm the effectiveness of each module within the MMPD-DTA model. Our code is available at https://github.com/zhc-moushang/MMPD-DTA.

CCL21-CCR7 blockade prevents neuroinflammation and degeneration in Parkinson's disease models

Parkinson's disease (PD) is a progressive degenerative disease of the central nervous system associated with neuroinflammation and microglial cell activation. Chemokine signaling regulates neuron-glia communication and triggers a microglial inflammatory profile. Herein, we identified the neuronal chemokine CCL21 as a major cause of microglial cell imbalance through the CCR7 receptor pathway with therapeutic implications for PD. In humans, we found that CCL21 transcript expression was increased in dopaminergic neurons (DANs) of the substantia nigra in PD patients. CCL21 and CCR7 expressions were spatially associated with brain regional vulnerability to synucleinopathies, as well as with the expression of microglial activation, neuroinflammation, and degeneration-related genes. Also, in mouse models of PD, we showed that CCL21 was overexpressed in DANs in vivo and in vitro. Mechanistically, neuronal CCL21 was shown to regulate microglial cell migration, proliferation, and activation in a CCR7-dependent manner through both canonical (PI3K/AKT) and non-canonical (ERK1/2/JNK) signaling pathways. Finally, we demonstrated that navarixin, a clinically relevant chemokine inhibitor with high affinity for the CCR7 receptor, could block CCL21 effects on microglia and prevent neurodegeneration and behavioral deficits in two mouse models of PD induced with either α-synuclein oligomers (αSynO) or 3,4-dihydroxyphenylacetaldehyde (DOPAL). Altogether, our data indicate that navarixin blocks CCL21/CCR7-mediated neuron-microglia communication and could be used as a therapeutic strategy against PD.

Characterization of the host specificity of the SH3 cell wall binding domain of the staphylococcal phage 88 endolysin

Bacteriophages produce endolysins at the end of the lytic cycle, which are crucial for lysing the host cells and releasing virion progeny. This lytic feature allows endolysins to act as effective antimicrobial alternatives when applied exogenously. Staphylococcal endolysins typically possess a modular structure with one or two enzymatically active N-terminal domains (EADs) and a C-terminal cell wall binding domain (CBD). The EADs degrade the peptidoglycan layer, leading to bacterial lysis, while the CBD binds to the specific host cell wall, and therefore, influences specificity of the endolysin. This study aimed to alter and characterize the host specificity of the CBD by exploring the impact of amino acid modifications within the CBD of a staphylococcal endolysin, Endo88. Endo88 was able to lyse Staphylococcus spp. and Enterococcus faecalis. However, despite attempts to mutate amino acids hypothesized for binding with cell wall components, the host-range was not affected but the lytic activity was severely reduced instead, although no alterations were performed on the EADs (Cysteine, histidine-dependent aminohydrolases/peptidases domain and Amidase domain). Further investigations of the CBD alone (Src homology3 domain, SH3) without the EADs suggested that binding and lytic activity may not be correlated in some cases since Endo88 and its mutants could lyse Staphylococcus epidermidis well but no binding activity was observed in the flow cytometry analysis. Molecular docking was used to gain insights on the observations for the binding and lytic activity which may help future strategies in designing enhanced engineered endolysins.

Evaluating cutinase from Fusarium oxysporum as a biocatalyst for the degradation of nine synthetic polymer

Plastic poses a significant environmental impact due to its chemical resilience, leading to prolonged and degradation times and resulting in widespread adverse effects on global flora and fauna. Cutinases are essential enzymes in the biodegradation process of synthetic polymers like polyethylene terephthalate (PET), which recognized organisms can break down. Here, we used molecular dynamics and binding free energy calculations to explore the interaction of nine synthetic polymers, including PET, with Cutinase from Fusarium oxysporum (FoCut). According to our findings, the polymers poly(ethylene terephthalate) (PET), poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH), poly(butylene succinate) (PBS), poly(butylene adipate-co-terephthalate) (PBAT) and poly(ε-caprolactone) (PCL) can bind to the Cutinase enzyme from F. oxysporum, indicating potential biodegradation activity for these polymers. PET exhibited the highest binding affinity (- 34.26 kcal/mol). Besides PET, the polymers PHBH, PBS, PBAT, and PCL also demonstrated significant affinities for the FoCut enzyme, with binding values of - 18.44, - 29.71, - 22.78, and - 22.26 kcal/mol, respectively. Additionally, analysis of the phylogenetic tree of cutinases produced by different organisms demonstrated that even though the organisms belong to different kingdoms, the cutinase from F. oxysporum (FoCut) showed biological similarity in its activity in degrading polymers with the cutinase enzyme from the bacterium Kineococcus radiotolerans and the fungus Moniliophthora roreri. Furthermore, the phylogenetic analysis demonstrated that the PETase enzyme has a very high similarity with the bacterial cutinase enzyme than with the fungal cutinase, therefore demonstrating that the PETase enzyme from Ideonella sakaiensis can easily be a modified bacterial cutinase enzyme that created a unique feature in biodegrading only the pet polymer through an evolutionary process due to its environment and its biochemical need for carbon. Our data demonstrate that bacterial cutinase enzymes have the same common ancestor as the PETase enzyme. Therefore, cutinases and PETase are interconnected through their biological similarity in biodegrading polymers. We demonstrated that important conserved regions, such as the Ser-Asp-His catalytic triad, exist in the enzyme's catalytic site and that all Cut enzymes from different organisms have the same region to couple with the polymer structures.

Guanidines Conjugated with Cell-Penetrating Peptides: A New Approach for the Development of Antileishmanial Molecules

Leishmaniasis is a neglected tropical disease caused by a protozoan of the genus Leishmania, which has visceral and cutaneous forms. The symptoms of leishmaniasis include high fever and weakness, and the cutaneous infection also causes lesions under the skin. The drugs used to treat leishmaniasis have become less effective due to the resistance mechanisms of the protozoa. In addition, the current compounds have low selectivity for the pathogen, leading to various side effects, which results in lower adherence to treatment. Various strategies were developed to solve this problem. The bioconjugation between natural compounds with antimicrobial activity and cell-penetrating peptides could alleviate the resistance and toxicity of current treatments. This work aims to conjugate the cell penetration peptide TAT to the guanidine GVL1. The GVL1-TAT bioconjugate exhibited leishmanicidal activity against Leishmania amazonensis and Leishmania infantum with a high selectivity index. In addition, the bioconjugate was more active against the intracellular enzyme CPP than the individual compounds. This target is very important for the viability and virulence of the parasite within the host cell. Docking studies confirmed the higher interaction of the conjugate with CPP and suggested that other proteins, such as trypanothione reductase, could be targeted. Thus, the data indicated that guanidines conjugated with cell-penetrating peptides could be a good approach for developing antileishmanial molecules.

Comparative analysis of substrate- and regio-selectivity of HpaB monooxygenases and their application to hydroxydaidzein synthesis

4-Hydroxyphenylacetate 3-hydroxylase (HpaB) has high potential for use in polyphenol synthesis via ortho-hydroxylation. Although the HpaB enzymes from Pseudomonas aeruginosa (PaHpaB) and Escherichia coli (EcHpaB) have been well studied, few studies have compared their activity and substrate selectivity. Thus, which HpaB is optimal for use in the biotechnological production of polyphenols is unclear. In this study, we performed a comparative analysis of the substrate- and regio-selectivity of PaHpaB, EcHpaB, and the recently discovered enzyme from Rhodococcus opacus (RoHpaB). The activity of these enzymes was first compared toward representative aromatic substrates. PaHpaB and EcHpaB exhibited very similar catalytic activity toward p-coumaric acid and tyrosol with one benzene ring, whereas PaHpaB exhibited greater activity than EcHpaB toward resveratrol and naringenin with two benzene rings. These results suggest that PaHpaB is superior to EcHpaB in converting bulky compounds. Furthermore, PaHpaB also exhibited catalytic activity toward a flavonoid, daidzein (7,4'-dihydroxyisoflavone), whereas EcHpaB did not. RoHpaB also exhibited strong activity toward daidzein in addition to other aromatic substrates. Interestingly, PaHpaB hydroxylated the 6-position of daidzein, whereas RoHpaB hydroxylated the 3'-position. PaHpaB and RoHpaB enabled the facile synthesis of not only 6-hydroxydaidzein and 3'-hydroxydaidzein but also 6,3'-dihydroxydaidzein via the cascade reaction. This study is the first to demonstrate synthesis of hydroxydaidzeins using HpaB enzymes.

Rational fragment-based design of compounds targeting the PWWP domain of the HRP family

Lens epithelium-derived growth factor p75 (LEDGF/p75), member of the hepatoma-derived growth-factor-related protein (HRP) family, is a transcriptional co-activator and involved in several pathologies including HIV infection and malignancies such as MLL-rearranged leukemia. LEDGF/p75 acts by tethering proteins to the chromatin through its integrase binding domain. This chromatin interaction occurs between the PWWP domain of LEDGF/p75 and nucleosomes carrying a di- or trimethylation mark on histone H3 Lys36 (H3K36me2/3). Our aim is to rationally devise small molecule drugs capable of inhibiting such interaction. To bootstrap this development, we resorted to X-ray crystallography-based fragment screening (FBS-X). Given that the LEDGF PWWP domain crystals were not suitable for FBS-X, we employed crystals of the closely related PWWP domain of paralog HRP-2. As a result, as many as 68 diverse fragment hits were identified, providing a detailed sampling of the H3K36me2/3 pocket pharmacophore. Subsequent structure-guided fragment expansion in three directions yielded multiple compound series binding to the pocket, as verified through X-ray crystallography, nuclear magnetic resonance and differential scanning fluorimetry. Our best compounds have double-digit micromolar affinity and optimally sample the interactions available in the pocket, judging by the Kd-based ligand efficiency exceeding 0.5 kcal/mol per non-hydrogen atom. Beyond π-stacking within the aromatic cage of the pocket and hydrogen bonding, the best compounds engage in a σ-hole interaction between a halogen atom and a conserved water buried deep in the pocket. Notably, the binding pocket in LEDGF PWWP is considerably smaller compared to the related PWWP1 domains of NSD2 and NSD3 which feature an additional subpocket and for which nanomolar affinity compounds have been developed recently. The absence of this subpocket in LEDGF PWWP limits the attainable affinity. Additionally, these structural differences in the H3K36me2/3 pocket across the PWWP domain family translate into a distinct selectivity of the compounds we developed. Our top-ranked compounds are interacting with both homologous LEDGF and HRP-2 PWWP domains, yet they showed no affinity for the NSD2 PWWP1 and BRPF2 PWWP domains which belong to other PWWP domain subfamilies. Nevertheless, our developed compound series provide a strong foundation for future drug discovery targeting the LEDGF PWWP domain as they can further be explored through combinatorial chemistry. Given that the affinity of H3K36me2/3 nucleosomes to LEDGF/p75 is driven by interactions within the pocket as well as with the DNA-binding residues, we suggest that future compound development should target the latter region as well. Beyond drug discovery, our compounds can be employed to devise tool compounds to investigate the mechanism of LEDGF/p75 in epigenetic regulation.

Evolution of PqsE as a Pseudomonas aeruginosa -specific regulator of LuxR-type receptors: insights from Pseudomonas and Burkholderia

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that poses a significant public health threat, particularly in healthcare settings. A key determinant of P. aeruginosa virulence is the regulated synthesis and release of extracellular products, which is controlled by a cell density-dependent signaling system known as quorum sensing (QS). P. aeruginosa uses a complex QS network, including two systems that rely on diffusible N-acylhomoserine lactone (AHL) signal molecules. The LuxR-type receptor RhlR is unique in that it requires not only its cognate AHL but also the accessory protein PqsE to maximally bind to promoter DNA and to initiate transcription. Our group demonstrated that PqsE physically interacts with RhlR, enhancing its affinity for target promoters across the P. aeruginosa genome. Although LuxR-type receptors are widespread in Gram-negative bacteria and important for pathogenesis, PqsE orthologs are restricted to Pseudomonas and Burkholderia species. This study explored the conservation of PqsE and examined PqsE ortholog structure-function across different species. Our results show that PqsE in Pseudomonas retain their functional interactions with RhlR homologs, unlike PqsE orthologs in Burkholderia spp., which do not interact with their respective LuxR-type receptors. Additionally, we assessed the AHL preferences of different receptors and hypothesized that the PqsE-RhlR interaction evolved to stabilize the inherently unstable RhlR, preventing its degradation. Indeed, we observe higher levels of RhlR protein turnover in a strain lacking pqsE compared to WT, which can be rescued in a strain lacking the Lon protease.

IMPORTANCE

Pseudomonas aeruginosa , a major pathogen for patients with cystic fibrosis and a primary constituent of healthcare-associated infections, relies on a complex quorum-sensing (QS) network to coordinate virulence factor production. Central to this system is the interaction between two proteins, PqsE and RhlR, which drive gene expression essential for pathogenesis. Our study investigates the conservation of the PqsE-RhlR interaction across related bacterial species, revealing that PqsE in Pseudomonas can enhance RhlR activity, while orthologs in Burkholderia lack this capacity. These findings offer new insights into the specificity and evolution of QS mechanisms, highlighting the PqsE-RhlR interaction as a potentially selective target for treating P. aeruginosa infections.

Allosteric site identification, virtual screening and discovery of a sulfonamide Hsp110-STAT3 interaction inhibitor for the treatment of hypoxic pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a severe pulmonary vascular disorder marked by vascular remodeling, which is linked to the malignant phenotypes of pulmonary vascular cells. The prevailing therapeutic approaches for PAH tend to neglect the potential role of vascular remodeling, leading to the clinical prognosis remains poor. Previously, we first demonstrated that heat shock protein (Hsp110) was significantly activated to boost Hsp110-STAT3 interaction, which resulted in abnormal proliferation and migration of human pulmonary arterial endothelial cells (HPAECs) under hypoxia. In the present study, we initially postulated the allosteric site of Hsp110, performed a virtual screening and biological evaluation studies to discover novel Hsp110-STAT3 interaction inhibitors. Here, we identified compound 29 (AN-329/43448068) as the effective inhibitor of HPAECs proliferation and the Hsp110-STAT3 association with good druggability. In vitro, 29 significantly impeded the chaperone function of Hsp110 and the malignant phenotypes of HPAECs. In vivo, 29 remarkably attenuated pulmonary vascular remodeling and right ventricular hypertrophy in hypoxia-induced PAH rats (i.g). Altogether, our data support the conclusion that it not only provides a novel lead compound but also presents a promising approach for subsequent inhibitor development targeting Hsp110-STAT3 interaction.

Harnessing computational and experimental approaches to identify potent hits against Leishmania donovani sterol C-24 methyltransferase from ChemBridge library

Leishmaniasis is a neglected tropical disease and is one of the major causes of mortality in poverty-stricken areas. A limited chemotherapeutics arsenal is available to tackle this deadly infection. Thus, identifying novel potent scaffolds using innovative strategies is the need of the hour. High-throughput screening (HTS) is a critical technique that can accelerate the process of drug discovery by evaluating millions of drug-like molecules using various automation tools and biological assays. In the present study, we have employed the HTS strategy to identify potent hits against Leishmania donovani sterol C-24 methyltransferase (LdSMT) from the in-house ChemBridge library. Firstly, a robust dataset was prepared with previously reported sterol C-24 methyltransferase inhibitors, belonging to diverse structural classes. Then, ligand-based virtual screening using similarity search was performed to screen the ChemBridge library having ∼20,000 molecules. This computational approach yielded 81 candidate compounds, which were selected for further molecular docking and biological evaluation. Anti-leishmanial assays revealed that out of 81 molecules, seven showed potential parasitic killing. Three molecules namely IIIM-CB-14, IIIM-CB-29, and IIIM-CB-45 were the most potent ones with 50 % inhibitory concentration (IC50) of 5.76, 8.08, and 10.64 µg/mL, respectively. SEM analyses suggest that these potent hits cause considerable morphological alterations. ADME studies of the potent hit molecules indicate that all the hits have considerable drug-likeness properties. Further, molecular dynamics studies were also performed to check the stable confirmation of LdSMT protein with the top two hits (IIIM-CB-14 and IIIM-CB-45). Thus, the present study harnesses computational and experimental approaches to unravel potent anti-leishmanial scaffolds.

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

Unveiling a Hidden Pocket in HIV-1 Protease: New Insights Into Retroviral Protease Cantilever-Tip Region Characteristics

The HIV-1 protease is critical for the process of viral maturation and as such, it is one of the most well characterized proteins in the Protein Data Bank. There is some evidence to suggest that the HIV-1 protease is capable of accommodating small molecule fragments at several locations on its surface outside of the active site. However, some pockets on the surface of proteins remain unformed in the apo structure and are termed "cryptic sites." To date, no cryptic sites have been identified in the structure of HIV-1 protease. Here, we characterize a novel cryptic cantilever pocket on the surface of the HIV-1 protease through mixed-solvent molecular dynamics simulations using several probes. Interestingly, we noted that several homologous retroviral proteases exhibit evolutionarily conserved dynamics in the cantilever region and possess a conserved pocket in the cantilever region. Immobilization of the cantilever region of the HIV-1 protease via disulfide cross-linking resulted in curling-in of the flap tips and the propensity for the protease to adopt a semi-open flap conformation. Structure-based analysis and fragment-based screening of the cryptic cantilever pocket suggested that the pocket may be capable of accommodating ligand structures. Furthermore, molecular dynamics simulations of a top scoring fragment bound to the cryptic pocket illustrated altered flap dynamics of the fragment-bound enzyme. Together, these results suggest that the mobility of the cantilever region plays a key role in the global dynamics of retroviral proteases. Therefore, the cryptic cantilever pocket of the HIV-1 protease may represent an interesting target for future in vitro studies.

Evolutionary insights into the stereoselectivity of imine reductases based on ancestral sequence reconstruction

The stereoselectivity of enzymes plays a central role in asymmetric biocatalytic reactions, but there remains a dearth of evolution-driven biochemistry studies investigating the evolutionary trajectory of this vital property. Imine reductases (IREDs) are one such enzyme that possesses excellent stereoselectivity, and stereocomplementary members are pervasive in the family. However, the regulatory mechanism behind stereocomplementarity remains cryptic. Herein, we reconstruct a panel of active ancestral IREDs and trace the evolution of stereoselectivity from ancestors to extant IREDs. Combined with coevolution analysis, we reveal six historical mutations capable of recapitulating stereoselectivity evolution. An investigation of the mechanism with X-ray crystallography shows that they collectively reshape the substrate-binding pocket to regulate stereoselectivity inversion. In addition, we construct an empirical fitness landscape and discover that epistasis is prevalent in stereoselectivity evolution. Our findings emphasize the power of ASR in circumventing the time-consuming large-scale mutagenesis library screening for identifying mutations that change functions and support a Darwinian premise from a molecular perspective that the evolution of biological functions is a stepwise process.

Exploration of phytochemical compounds against Marburg virus using QSAR, molecular dynamics, and free energy landscape

Marburg virus disease (MVD) is caused by the Marburg virus, a one-of-a-kind zoonotic RNA virus from the genus Filovirus. Thus, this current study employed AI-based QSAR and molecular docking-based virtual screening for identifying potential binders against the target protein (nucleoprotein (NP)) of the Marburg virus. A total of 2727 phytochemicals were used for screening, out of which the top three compounds (74977521, 90470472, and 11953909) were identified based on their predicted bioactivity (pIC50) and binding score (< - 7.4 kcal/mol). Later, MD simulation in triplicates and trajectory analysis were performed which showed that 11953909 and 74977521 had the most stable and consistent complex formations and had the most significant interactions with the highest number of hydrogen bonds. PCA (principal component analysis) and FEL (free energy landscape) analysis indicated that these compounds had favourable energy states for most of the conformations. The total binding free energy of the compounds using the MM/GBSA technique showed that 11953909 (ΔGTOTAL = - 30.78 kcal/mol) and 74977521 (ΔGTOTAL = - 30 kcal/mol) had the highest binding affinity with the protein. Overall, this in silico pipeline proposed that the phytochemicals 11953909 and 74977521 could be the possible binders of NP. This study aimed to find phytochemicals inhibiting the protein's function and potentially treating MVD.

Drug repositioning for rosacea disease: Biological TARGET identification, molecular docking, pharmacophore mapping, and molecular dynamics analysis

Rosacea is a chronic dermatological condition that currently lacks a clear treatment approach due to an uncomprehensive knowledge of its pathogenesis. The main obstacle lies in understanding its etiology and the mode of action of the different drugs used. This study aims to clarify these aspects by employing drug repositioning. Using an in silico approach, we performed a transcriptomic analysis comparing samples from individuals with diverse types of rosacea to those from healthy controls to identify genes deregulated in this disease. Subsequently, we realized molecular docking and molecular dynamics studies to assess the binding affinity of drugs currently used to treat rosacea and drugs that target proteins interacting with, and thus affecting, proteins deregulated in rosacea. Our findings revealed that the downregulation of SKAP2 and upregulation of S100A7A in rosacea, could be involved in the pathogenesis of the disease. Furthermore, considering the drugs currently used for rosacea management, we demonstrated stable interactions between isotretinoin and BFH772 with SKAP2, and permethrin and PAC-14028 with S100A7A. Similarly, considering drugs targeting SKAP2 and S100A7A interactome proteins, we found that pitavastatin and dasatinib exert stable interactions with SKAP2, and lovastatin and tirbanibulin with S100A7A. In addition, we determine that the types of bonds involved in the interactions were different in SKAP2 from S100A7A. The drug-SKAP2 interactions are hydrogen bonds, whereas the drug-S100A7A interactions are of the hydrophobic type. In conclusion, our study provides evidence for the possible contribution of SKAP2 and S100A7A to rosacea pathology. Furthermore, it provides significant information on the molecular interactions between drugs and these proteins, highlighting the importance of considering structural features and binding interactions in the design of targeted therapies for skin disorders such as rosacea.

PocketDTA: an advanced multimodal architecture for enhanced prediction of drug-target affinity from 3D structural data of target binding pockets

MOTIVATION

Accurately predicting the drug-target binding affinity (DTA) is crucial to drug discovery and repurposing. Although deep learning has been widely used in this field, it still faces challenges with insufficient generalization performance, inadequate use of 3D information, and poor interpretability.

RESULTS

To alleviate these problems, we developed the PocketDTA model. This model enhances the generalization performance by pre-trained models ESM-2 and GraphMVP. It ingeniously handles the first 3 (top-3) target binding pockets and drug 3D information through customized GVP-GNN Layers and GraphMVP-Decoder. In addition, it uses a bilinear attention network to enhance interpretability. Comparative analysis with state-of-the-art (SOTA) methods on the optimized Davis and KIBA datasets reveals that the PocketDTA model exhibits significant performance advantages. Further, ablation studies confirm the effectiveness of the model components, whereas cold-start experiments illustrate its robust generalization capabilities. In particular, the PocketDTA model has shown significant advantages in identifying key drug functional groups and amino acid residues via molecular docking and literature validation, highlighting its strong potential for interpretability.

AVAILABILITY AND IMPLEMENTATION

Code and data are available at: https://github.com/zhaolongNCU/PocketDTA.

In silico identification of putative druggable pockets in PRL3, a significant oncology target

Protein tyrosine phosphatases (PTP) have emerged as targets in diseases characterized by aberrant phosphorylations such as cancers. The activity of the phosphatase of regenerating liver 3, PRL3, has been linked to several oncogenic and metastatic pathways, particularly in breast, ovarian, colorectal, and blood cancers. Development of small molecules that directly target PRL3, however, has been challenging. This is partly due to the lack of structural information on how PRL3 interacts with its inhibitors. Here, computational methods are used to bridge this gap by evaluating the druggability of PRL3. In particular, web-based pocket prediction tools, DoGSite3 and FTMap, were used to identify binding pockets using structures of PRL3 currently available in the Protein Data Bank. Druggability assessment by molecular dynamics simulations with probes was also performed to validate these results and to predict the strength of binding in the identified pockets. While several druggable pockets were identified, those in the closed conformation show more promise given their volume and depth. These two pockets flank the active site loops and roughly correspond to pockets predicted by molecular docking in previous papers. Notably, druggability simulations predict the possibility of low nanomolar affinity inhibitors in these sites implying the potential to identify highly potent small molecule inhibitors for PRL3. Putative pockets identified here can be leveraged for high-throughput virtual screening to further accelerate the drug discovery against PRL3 and development of PRL3-directed therapeutics.

Structural basis for the ligand recognition and G protein subtype selectivity of kisspeptin receptor

Kisspeptin receptor (KISS1R), belonging to the class A peptide-GPCR family, plays a key role in the regulation of reproductive physiology after stimulation by kisspeptin and is regarded as an attractive drug target for reproductive diseases. Here, we demonstrated that KISS1R can couple to the Gi/o pathway besides the well-known Gq/11 pathway. We further resolved the cryo-electron microscopy (cryo-EM) structure of KISS1R-Gq and KISS1R-Gi complexes bound to the synthetic agonist TAK448 and structure of KISS1R-Gq complex bound to the endogenous agonist KP54. The high-resolution structures provided clear insights into mechanism of KISS1R recognition by its ligand and can facilitate the design of targeted drugs with high affinity to improve treatment effects. Moreover, the structural and functional analyses indicated that conformational differences in the extracellular loops (ECLs), intracellular loops (ICLs) of the receptor, and the "wavy hook" of the Gα subunit may account for the specificity of G protein coupling for KISS1R signaling.

Docking analysis of phenolic acid and flavonoids with selected TAS2R receptors and in vitro experiment

Cornelian cherry fruits contain a wide range of phenolic acids, flavonoids, and other secondary metabolites. Selected flavonoids may inhibit the perceiving of bitterness, however, the full mechanism with all TAS2R bitter taste receptors is not known. The aim of the study was to determine the inhibitory effect of Cornus mas phenolics against the bitterness receptors TAS2R13 and TAS2R3 through functional in vitro assays and coupling studies. The overall effect was validated by analysing the inhibition of the receptors activity in cells treated with tested cornelian cherry extracts. The strength of interaction with both TAS2R receptors varied between studied compounds with different binding affinity. Most compounds bonded with the TAS2R3 receptor through a long-distant hydrophobic interaction with Trp89A and π-π orbital overlapping-between phenolic and tryptophane aromatic rings. For TAS2R13 observed were various mechanisms of interaction with the compounds. Nonetheless, naringin and quercetin had most similar binding affinity to chloroquine and denatonium-the model agonists for the receptor.

Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets

SUMMARY

Protein Interaction Explorer (PIE) is a new web-based tool integrated to our database iPPI-DB, specifically crafted to support structure-based drug discovery initiatives focused on protein-protein interactions (PPIs). Drawing upon extensive structural data encompassing thousands of heterodimer complexes, including those with successful ligands, PIE provides a comprehensive suite of tools dedicated to aid decision-making in PPI drug discovery. PIE enables researchers/bioinformaticians to identify and characterize crucial factors such as the presence of binding pockets or functional binding sites at the interface, predicting hot spots, and foreseeing similar protein-embedded pockets for potential repurposing efforts.

AVAILABILITY AND IMPLEMENTATION

PIE is user-friendly and readily accessible at https://ippidb.pasteur.fr/targetcentric/. It relies on the NGL visualizer.

Valuation of the significant hypoglycemic activity of black currant anthocyanin extract by both starch structure transformation and glycosidase activity inhibition

The objective of this study was to investigate the impact of anthocyanin-rich black currant extract (BCE) on the structural properties of starch and the inhibition of glycosidases, gathering data and research evidence to support the use of low glycemic index (GI) foods. The BCE induced a change in the starch crystal structure from A-type to V-type, resulting in a drop in digestibility from 81.41 % to 65.57 %. Furthermore, the inhibitory effects of BCE on glycosidases activity (α-glucosidase: IC50 = 0.13 ± 0.05 mg/mL and α-amylase: IC50 = 2.67 ± 0.16 mg/mL) by inducing a change in spatial conformation were confirmed through in vitro analysis. The presence of a 5'-OH group facilitated the interaction between anthocyanins and receptors of amylose, α-amylase, and α-glucosidase. The glycosyl moiety enhanced the affinity for amylose yet lowered the inhibitory effect on α-amylase. The in vivo analysis demonstrated that BCE resulted in a reduction of 3.96 mM·h in blood glucose levels (Area Under Curve). The significant hypoglycemic activity, particularly the decrease in postprandial blood glucose levels, highlights the potential of utilizing BCE in functional foods for preventing diabetes.

User-centric design of a 3D search interface for protein-ligand complexes

In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest version. GeoMine is a search engine for ligand-bound and predicted empty binding sites in the Protein Data Bank. In addition to its basic text-based search functionalities, GeoMine offers a geometric query type for searching binding sites with a specific relative spatial arrangement of chemical features such as heavy atoms and intermolecular interactions. In contrast to a text search that requires simple and easy-to-formulate user input, a 3D input is more complex, and its specification can be challenging for users. GeoMine's new version aims to address this issue from the graphical user interface perspective by introducing an additional visualization concept and a new query template type. In its latest version, GeoMine extends its query-building capabilities primarily through input formulation in 2D. The 2D editor is fully synchronized with GeoMine's 3D editor and provides the same functionality. It enables template-free query generation and template-based query selection directly in 2D pose diagrams. In addition, the query generation with the 3D editor now supports predicted empty binding sites for AlphaFold structures as query templates. GeoMine is freely accessible on the ProteinsPlus web server ( https://proteins.plus ).

Undescribed Cyclohexene and Benzofuran Alkenyl Derivatives from Choerospondias axillaris, a Potential Hypoglycemic Fruit

The fruit of Choerospondias axillaris (Anacardiaceae), known as south wild jujube in China, has been consumed widely in several regions of the world to produce fruit pastille and leathers, juice, jam, and candy. A comprehensive chemical study on the fresh fruits led to the isolation and identification of 18 compounds, including 7 new (1-7) and 11 known (8-18) comprised of 5 alkenyl (cyclohexenols and cyclohexenones) derivatives (1-5), 3 benzofuran derivatives (6-8), 6 flavonoids (9-14) and 4 lignans (15-18). Their structures were elucidated by extensive spectroscopic analysis. The known lignans 15-18 were isolated from the genus Choerospondias for the first time. Most of the isolates exhibited significant inhibitory activity on α-glucosidase with IC50 values from 2.26 ± 0.06 to 43.9 ± 0.96 μM. Molecular docking experiments strongly supported the potent α-glucosidase inhibitory activity. The results indicated that C. axillaris fruits could be an excellent source of functional foods that acquire potential hypoglycemic bioactive components.

SiteMine: Large-scale binding site similarity searching in protein structure databases

Drug discovery and design challenges, such as drug repurposing, analyzing protein-ligand and protein-protein complexes, ligand promiscuity studies, or function prediction, can be addressed by protein binding site similarity analysis. Although numerous tools exist, they all have individual strengths and drawbacks with regard to run time, provision of structure superpositions, and applicability to diverse application domains. Here, we introduce SiteMine, an all-in-one database-driven, alignment-providing binding site similarity search tool to tackle the most pressing challenges of binding site comparison. The performance of SiteMine is evaluated on the ProSPECCTs benchmark, showing a promising performance on most of the data sets. The method performs convincingly regarding all quality criteria for reliable binding site comparison, offering a novel state-of-the-art approach for structure-based molecular design based on binding site comparisons. In a SiteMine showcase, we discuss the high structural similarity between cathepsin L and calpain 1 binding sites and give an outlook on the impact of this finding on structure-based drug design. SiteMine is available at https://uhh.de/naomi.

Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures

Protein-ligand binding site prediction is a useful tool for understanding the functional behaviour and potential drug-target interactions of a novel protein of interest. However, most binding site prediction methods are tested by providing crystallised ligand-bound (holo) structures as input. This testing regime is insufficient to understand the performance on novel protein targets where experimental structures are not available. An alternative option is to provide computationally predicted protein structures, but this is not commonly tested. However, due to the training data used, computationally-predicted protein structures tend to be extremely accurate, and are often biased toward a holo conformation. In this study we describe and benchmark IF-SitePred, a protein-ligand binding site prediction method which is based on the labelling of ESM-IF1 protein language model embeddings combined with point cloud annotation and clustering. We show that not only is IF-SitePred competitive with state-of-the-art methods when predicting binding sites on experimental structures, but it performs better on proxies for novel proteins where low accuracy has been simulated by molecular dynamics. Finally, IF-SitePred outperforms other methods if ensembles of predicted protein structures are generated.

Novel SK channel positive modulators prevent ferroptosis and excitotoxicity in neuronal cells

Small conductance calcium-activated potassium (SK) channel activity has been proposed to play a role in the pathology of several neurological diseases. Besides regulating plasma membrane excitability, SK channel activation provides neuroprotection against ferroptotic cell death by reducing mitochondrial Ca2+ uptake and reactive oxygen species (ROS). In this study, we employed a multifaceted approach, integrating structure-based and computational techniques, to strategically design and synthesize an innovative class of potent small-molecule SK2 channel modifiers through highly efficient multicomponent reactions (MCRs). The compounds' neuroprotective activity was compared with the well-studied SK positive modulator, CyPPA. Pharmacological SK channel activation by selected compounds confers neuroprotection against ferroptosis at low nanomolar ranges compared to CyPPA, that mediates protection at micromolar concentrations, as shown by an MTT assay, real-time cell impedance measurements and propidium iodide staining (PI). These novel compounds suppress increased mitochondrial ROS and Ca2+ level induced by ferroptosis inducer RSL3. Moreover, axonal degeneration was rescued by these novel SK channel activators in primary mouse neurons and they attenuated glutamate-induced neuronal excitability, as shown via microelectrode array. Meanwhile, functional afterhyperpolarization of the novel SK2 channel modulators was validated by electrophysiological measurements showing more current change induced by the novel modulators than the reference compound, CyPPA. These data support the notion that SK2 channel activation can represent a therapeutic target for brain diseases in which ferroptosis and excitotoxicity contribute to the pathology.

Redocking the PDB

Molecular docking is a standard technique in structure-based drug design (SBDD). It aims to predict the 3D structure of a small molecule in the binding site of a receptor (often a protein). Despite being a common technique, it often necessitates multiple tools and involves manual steps. Here, we present the JAMDA preprocessing and docking workflow that is easy to use and allows fully automated docking. We evaluate the JAMDA docking workflow on binding sites extracted from the complete PDB and derive key factors determining JAMDA's docking performance. With that, we try to remove most of the bias due to manual intervention and provide a realistic estimate of the redocking performance of our JAMDA preprocessing and docking workflow for any PDB structure. On this large PDBScan22 data set, our JAMDA workflow finds a pose with an RMSD of at most 2 Å to the crystal ligand on the top rank for 30.1% of the structures. When applying objective structure quality filters to the PDBScan22 data set, the success rate increases to 61.8%. Given the prepared structures from the JAMDA preprocessing pipeline, both JAMDA and the widely used AutoDock Vina perform comparably on this filtered data set (the PDBScan22-HQ data set).

Ligand-binding properties of XaffOBP9, a Minus-C odorant-binding protein from Xyleborus affinis (Coleoptera: Curculionidae: Scolytinae)

Xyleborus affinis, one of the most important pests of rubber trees, has caused severe damage to the natural rubber industry in Hainan province. The ability to detect host plants through a sensitive and specific olfactory system is crucial for Xyleborus affinis. Odorant binding proteins (OBPs) are believed to bind and carry hydrophobic active compounds from the environment to the surface of olfactory receptor neurons. To investigate the potential functional role of the highly expressed XaffOBP9 in binding with semiochemicals, we cloned and analyzed the cDNA sequence of XaffOBP9. The results showed that XaffOBP9 contains a 411bp open reading frame that encodes 136 amino acids. Then XaffOBP9 was expressed in Escherichia coli. The binding affinity of the recombinant OBP to 15 different ligands (14 host plant volatiles and 1 aggregation pheromone) was then examined using a fluorescence competitive binding approach. The results demonstrated that XaffOBP9 exhibited broad binding capabilities and strong affinities for 14 ligands. The structure of XaffOBP9 and its interactions with fourteen ligands were further analyzed by modeling and molecular docking, respectively. Based on the docking result, we found hydrophobic interactions are important between XaffOBP9 to these ligands and three amino acid residues (L71, Y106, and L114) were highly overlapped and contributed to the interaction with ligands. Mutation functional assays confirmed that the mutant L114A showed significantly reduced binding capacity to these ligands. This study suggested that XaffOBP9 may be involved in the chemoreception of semiochemicals and that it is helpful for the integrated management of X. affinis.

Computational methods in glaucoma research: Current status and future outlook

Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and potential therapeutic targets. Systems genetics integrates genomic and clinical data, aiding in identifying drug targets, comprehending disease mechanisms, and personalizing treatment strategies for glaucoma. Molecular dynamics simulations offer valuable molecular-level insights into glaucoma-related biomolecule behavior and drug interactions, guiding experimental studies and drug discovery efforts. Artificial intelligence (AI) technologies hold promise in revolutionizing glaucoma research, enhancing disease diagnosis, target identification, and drug candidate selection. The generalized protocols for systems genetics, MD simulations, and AI model development are included as a guide for glaucoma researchers. These computational methods, however, are not separate and work harmoniously together to discover novel ways to combat glaucoma. Ongoing research and progresses in genomics technologies, MD simulations, and AI methodologies project computational methods to become an integral part of glaucoma research in the future.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams

In this article, we present PoseEdit, a new, interactive frontend of the popular pose visualization tool PoseView. PoseEdit automatically produces high-quality 2D diagrams of intermolecular interactions in 3D binding sites calculated from ligands in complex with protein, DNA, and RNA. The PoseView diagrams have been improved in several aspects, most notably in their interactivity. Thanks to the easy-to-use 2D editor of PoseEdit, the diagrams are extensively editable and extendible by the user, can be merged with other diagrams, and even be created from scratch. A large variety of graphical objects in the diagram can be moved, rotated, selected and highlighted, mirrored, removed, or even newly added. Furthermore, PoseEdit enables a synchronized 2D-3D view of macromolecule-ligand complexes simplifying the analysis of structural features and interactions. The representation of individual diagram objects regarding their visualized chemical properties, like stereochemistry, and general graphical styles, like the color of interactions, can additionally be edited. The primary objective of PoseEdit is to support scientists with an enhanced way to communicate ligand binding mode information through graphical 2D representations optimized with the scientist's input in accordance with objective criteria and individual needs. PoseEdit is freely available on the ProteinsPlus web server ( https://proteins.plus ).

Searching similar local 3D micro-environments in protein structure databases with MicroMiner

The available protein structure data are rapidly increasing. Within these structures, numerous local structural sites depict the details characterizing structure and function. However, searching and analyzing these sites extensively and at scale poses a challenge. We present a new method to search local sites in protein structure databases using residue-defined local 3D micro-environments. We implemented the method in a new tool called MicroMiner and demonstrate the capabilities of residue micro-environment search on the example of structural mutation analysis. Usually, experimental structures for both the wild-type and the mutant are unavailable for comparison. With MicroMiner, we extracted $>255 \times 10^{6}$ amino acid pairs in protein structures from the PDB, exemplifying single mutations' local structural changes for single chains and $>45 \times 10^{6}$ pairs for protein-protein interfaces. We further annotate existing data sets of experimentally measured mutation effects, like $\Delta \Delta G$ measurements, with the extracted structure pairs to combine the mutation effect measurement with the structural change upon mutation. In addition, we show how MicroMiner can bridge the gap between mutation analysis and structure-based drug design tools. MicroMiner is available as a command line tool and interactively on the https://proteins.plus/ webserver.