Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation

Copaifera spp. oleoresins and two isolated compounds (ent-kaurenoic and ent-polyalthic acid) inhibit Toxoplasma gondii growth in vitro

Toxoplasmosis affects about one-third of the world's population. The disease treatment methods pose several side effects and do not efficiently eliminate the parasite, making the search for new therapeutic approaches necessary. We aimed to assess the anti-Toxoplasma gondii activity of four Copaifera oleoresins (ORs) and two isolated diterpene acids, named ent-kaurenoic and ent-polyalthic acid. We used HeLa cells as an experimental model of toxoplasmosis. Uninfected and infected HeLa cells were submitted to the treatments, and the parasite intracellular proliferation, cytokine levels and ROS production were measured. Also, tachyzoites were pre-treated and the parasite invasion was determined. Finally, an in silico analysis was performed to identify potential parasite targets. Our data show that the non-cytotoxic concentrations of ORs and diterpene acids controlled the invasion and proliferation of T. gondii in HeLa cells, thus highlighting the possible direct action on parasites. In addition, some compounds tested controlled parasite proliferation in an irreversible manner. An additional and non-exclusive mechanism of action involves the modulation of host cell components, by affecting the upregulation of the IL-6. Additionally, molecular docking suggested that ent-polyalthic acid has a high affinity for the active site of the TgCDPK1 protein. Copaifera ORs have great antiparasitic activity against T. gondii, and this effect can be partially explained by the presence of the isolated compounds ent-kaurenoic and ent-polyalthic acid.

Novel peptide inhibitor of human tumor necrosis factor-α has antiarthritic activity

The inhibition of tumor necrosis factor (TNF)-α trimer formation renders it inactive for binding to its receptors, thus mitigating the vicious cycle of inflammation. We designed a peptide (PIYLGGVFQ) that simulates a sequence strand of human TNFα monomer using a series of in silico methods, such as active site finding (Acsite), protein-protein interaction (PPI), docking studies (GOLD and Flex-X) followed by molecular dynamics (MD) simulation studies. The MD studies confirmed the intermolecular interaction of the peptide with the TNFα. Fluorescence-activated cell sorting and fluorescence microscopy revealed that the peptide effectively inhibited the binding of TNF to the cell surface receptors. The cell culture assays showed that the peptide significantly inhibited the TNFα-mediated cell death. In addition, the nuclear translocation of the nuclear factor kappa B (NFκB) was significantly suppressed in the peptide-treated A549 cells, as observed in immunofluorescence and gel mobility-shift assays. Furthermore, the peptide protected against joint damage in the collagen-induced arthritis (CIA) mouse model, as revealed in the micro focal-CT scans. In conclusion, this TNFα antagonist would be helpful for the prevention and repair of inflammatory bone destruction and subsequent loss in the mouse model of CIA as well as human rheumatoid arthritis (RA) patients. This calls upon further clinical investigation to utilize its potential effect as an antiarthritic drug.

Assessment of fragment docking and scoring with the endothiapepsin model system

Fragment-based screening has become indispensable in drug discovery. Yet, the weak binding affinities of these small molecules still represent a challenge for the reliable detection of fragment hits. The extent of this issue was illustrated in the literature for the aspartic protease endothiapepsin: When seven biochemical and biophysical in vitro screening methods were applied to screen a library of 361 fragments, very poor overlap was observed between the hit fragments identified by the individual approaches, resulting in high levels of false positive and/or false negative results depending on the mutually compared methods. Here, the reported in vitro findings are juxtaposed with the results from in silico docking and scoring approaches. The docking programs GOLD and Glide were considered with the scoring functions ASP, ChemScore, ChemPLP, GoldScore, DSXCSD, and GlideScore. First, the ranking power and scoring power were assessed for the named scoring functions. Second, the capability of reproducing the crystallized fragment binding modes was tested in a structure-based redocking approach. The redocking success notably depended on the ligand efficiency of the considered fragments. Third, a blinded virtual screening approach was employed to evaluate whether in silico screening can compete with in vitro methods in the enrichment of fragment databases.

Structural insight into the binding mode of cefotaxime and meropenem to TEM-1, SHV-1, KPC-2, and Amp-C type beta-lactamases

Antimicrobial resistance is an emerging threat to public health around the world. The study employs computational and biophysical methods to investigate the properties of cefotaxime and meropenem's binding to various beta-lactamases like TEM-1, SHV-1, KPC-2, and Amp-C. The enzyme kinetics of purified proteins revealed an increase in Michaelis constant (Km) value in the presence of meropenem and cefotaxime, indicating a decrease in enzyme affinity for nitrocefin. Proteins interact with meropenem/cefotaxime, causing quenching through complex formation. All proteins have one binding site, and binding constant (Kb) values are 104, indicating strong interaction. The study found that meropenem and cefotaxime had high fitness scores for Amp-C, KPC-2,TEM-1 and SHV-1, with binding energy ranging from -7.4 to -7.8, and hydrogen bonds between them. Molecular Dynamic simulation of protein-ligand complexes revealed cefotaxime-binding proteins have slightly lower Root Mean Square Deviation(RMSD) than meropenem-binding proteins, indicating stable association antibiotics with these proteins.

Discovery of selective TYK2 inhibitors: Design, synthesis, in vitro and in silico studies of promising hits with triazolopyrimidinone scaffold

The Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway mediates many cytokine and growth factor signals. Tyrosine kinase 2 (TYK2), one of the members of this pathway and the first described member of the JAK family. TYK2 associates with inflammatory and autoimmune diseases, cancer and diabetes. Here, we present novel compounds as selective inhibitors of the canonical kinase domain of TYK2 enzyme. These compounds were rationally designed and synthesized with appropriate reactions. Molecular modeling techniques were used to design and optimize the candidates for TYK2 inhibition and to determine the estimated binding orientations of them inside JAKs. Designed compounds potently inhibited TYK2 with good selectivity against other JAKs as determined by in vitro assays. In order to verify its selectivity properties, compound A8 was tested against 58 human kinases (KinaseProfiler™ assay). The effects of the selected seven compounds on the protein levels of members of the JAK/STAT family were also detected in THP-1 monocytes although the basal level of these proteins is poorly detectable. Therefore, their expression was induced by lipopolysaccharide treatment and compounds A8, A15, A18, and A19 were found to be potent inhibitors of the TYK2 enzyme, (9.7 nM, 6.0 nM, 5.0 nM and 10.3 nM, respectively), and have high selectivity index for the JAK1, JAK2, and JAK3 enzymes. These findings suggest that triazolo[1,5-a]pyrimidinone derivatives may be lead compounds for developing potent TYK2-selective inhibitors targeting enzymes' active site.

Design, synthesis and preliminary biological evaluation of rivastigmine-INDY hybrids as multitarget ligands against Alzheimer's disease by targeting butyrylcholinesterase and DYRK1A/CLK1 kinases

Based on a multitarget approach implementing rivastigmine-INDY hybrids 1, we identified a set of pseudo-irreversible carbamate-type inhibitors of eqBuChE that, after carbamate transfer at the active site serine residue, released the corresponding INDY analogues 2 endowed with hDYRK1A/hCLK1 kinases inhibitory properties. A SAR study and molecular docking investigation of both series of compounds 1 and 2 revealed that appropriate structural modifications at the carbamate moiety and at the N-appendage of the benzothiazole core led to potent and selective eqBuChE inhibitors with IC50 up to 27 nM and potent hDYRK1A and hCLK1 inhibitors with IC50 up to 106 nM and 17 nM respectively. Pleasingly, identification of the matched pair of compounds 1b/2b with a good balance between inhibition of eqBuChE and hDYRK1A/hCLK1 kinases (IC50 = 68 nM and IC50 = 529/54 nM, respectively) further validated our multitarget approach based on a sequential mechanism of action. In addition, target compound 1b exhibited a suitable ADMET profile, including good brain permeability and high stability in PBS, encouraging further biological investigation as a drug candidate.

Anti-leishmanial activity of Eleutherine plicata Herb. and predictions of isoeleutherin and its analogues

Introduction: Leishmaniasis is caused by protozoa of the genus Leishmania, classified as tegumentary and visceral. The disease treatment is still a serious problem, due to the toxic effects of available drugs, the costly treatment and reports of parasitic resistance, making the search for therapeutic alternatives urgent. This study assessed the in vitro anti-leishmanial potential of the extract, fractions, and isoeleutherin from Eleutherine plicata, as well as the in silico interactions of isoeleutherin and its analogs with Trypanothione Reductase (TR), in addition to predicting pharmacokinetic parameters. Methods: From the ethanolic extract of E. plicata (EEEp) the dichloromethane fraction (FDEp) was obtained, and isoeleutherin isolated. All samples were tested against promastigotes, and parasite viability was evaluated. Isoeleutherin analogues were selected based on similarity in databases (ZINK and eMolecules) to verify the impact on structural change. Results and Discussion: The extract and its fractions were not active against the promastigote form (IC50 > 200 μg/mL), while isoeleutherin was active (IC50 = 25 μg/mL). All analogues have high intestinal absorption (HIA), cell permeability was moderate in Caco2 and low to moderate in MDCK. Structural changes interfered with plasma protein binding and blood-brain barrier permeability. Regarding metabolism, all molecules appear to be CYP3A4 metabolized and inhibited 2-3 CYPs. Molecular docking and molecular dynamics assessed the interactions between the most stable configurations of isoeleutherin, analogue compound 17, and quinacrine (control drug). Molecular dynamics simulations demonstrated stability and favorable interactions with TR. In summary, fractionation contributed to antileishmanial activity and isoleutherin seems to be promising. Structural alterations did not contribute to improve pharmacokinetic aspects and analogue 17 proved to be more promising than isoeleutherin, presenting better stabilization in TR.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

Inhibition of ADAM9 promotes the selective degradation of KRAS and sensitizes pancreatic cancers to chemotherapy

Kirsten rat sarcoma virus (KRAS) signaling drives pancreatic ductal adenocarcinoma (PDAC) malignancy, which is an unmet clinical need. Here, we identify a disintegrin and metalloproteinase domain (ADAM)9 as a modulator of PDAC progression via stabilization of wild-type and mutant KRAS proteins. Mechanistically, ADAM9 loss increases the interaction of KRAS with plasminogen activator inhibitor 1 (PAI-1), which functions as a selective autophagy receptor in conjunction with light chain 3 (LC3), triggering lysosomal degradation of KRAS. Suppression of ADAM9 by a small-molecule inhibitor restricts disease progression in spontaneous models, and combination with gemcitabine elicits dramatic regression of patient-derived tumors. Our findings provide a promising strategy to target the KRAS signaling cascade and demonstrate a potential modality to enhance sensitivity to chemotherapy in PDAC.

PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences

The last few years have seen the development of numerous deep learning-based protein-ligand docking methods. They offer huge promise in terms of speed and accuracy. However, despite claims of state-of-the-art performance in terms of crystallographic root-mean-square deviation (RMSD), upon closer inspection, it has become apparent that they often produce physically implausible molecular structures. It is therefore not sufficient to evaluate these methods solely by RMSD to a native binding mode. It is vital, particularly for deep learning-based methods, that they are also evaluated on steric and energetic criteria. We present PoseBusters, a Python package that performs a series of standard quality checks using the well-established cheminformatics toolkit RDKit. The PoseBusters test suite validates chemical and geometric consistency of a ligand including its stereochemistry, and the physical plausibility of intra- and intermolecular measurements such as the planarity of aromatic rings, standard bond lengths, and protein-ligand clashes. Only methods that both pass these checks and predict native-like binding modes should be classed as having "state-of-the-art" performance. We use PoseBusters to compare five deep learning-based docking methods (DeepDock, DiffDock, EquiBind, TankBind, and Uni-Mol) and two well-established standard docking methods (AutoDock Vina and CCDC Gold) with and without an additional post-prediction energy minimisation step using a molecular mechanics force field. We show that both in terms of physical plausibility and the ability to generalise to examples that are distinct from the training data, no deep learning-based method yet outperforms classical docking tools. In addition, we find that molecular mechanics force fields contain docking-relevant physics missing from deep-learning methods. PoseBusters allows practitioners to assess docking and molecular generation methods and may inspire new inductive biases still required to improve deep learning-based methods, which will help drive the development of more accurate and more realistic predictions.

High-efficiency removal of pyrethroids using a redesigned odorant binding protein

Pyrethroids are ubiquitously present in environmental media and threaten both the ecosystem and human health. To explore effective ways to remove pyrethroids from the environment, an odorant binding protein (OBP) with affinity for various pyrethroids was investigated. Initially, the target OBP, Spodoptera littoralis pheromone binding protein 1 (SlitPBP1), underwent redesign to enhance its affinity for pyrethroids. The modified SlitPBP1E97ND106E demonstrated a substantially increased affinity for deltamethrin (DeltaM), with a dissociation constant of 0.77 ± 0.17 μM. The affinity of SlitPBP1E97ND106E for other pyrethroids also increased to varying extents. Consequently, SlitPBP1E97ND106E displayed a markedly enhanced capability to adsorb and remove pyrethroids. When exposed to free SlitPBP1E97ND106E in solution, the reduction in DeltaM surged from 16.78 ± 0.32% to 97.51 ± 0.56%. SlitPBP1E97ND106E was immobilized by coupling the protein to Ni2+-NTA agarose resin. Liquid chromatography results attested to the superior efficacy of immobilized SlitPBP1E97ND106E in removing pyrethroids, especially DeltaM. No significant differences in pyrethroid removal were detected across various water samples. Our findings introduce a potent tool for pyrethroid removal. A wider range of OBPs can similarly be optimized and applied to remove organic pollutants, including but not limited to pesticides.

Stimulation of platelet P2Y1 receptors by different endogenous nucleotides leads to functional selectivity via biased signalling

BACKGROUND AND PURPOSE

Platelet function during inflammation is dependent on activation by endogenous nucleotides. Non-canonical signalling via the P2Y1 receptor is important for these non-thrombotic functions of platelets. However, apart from ADP, the role of other endogenous nucleotides acting as agonists at P2Y1 receptors is unknown. This study compared the effects of ADP, Ap3A, NAD+ , ADP-ribose, and Up4A on platelet functions contributing to inflammation or haemostasis.

EXPERIMENTAL APPROACH

Platelets obtained from healthy human volunteers were incubated with ADP, Ap3A, NAD+ , ADP-ribose, or Up4A, with aggregation and fibrinogen binding measured (examples of function during haemostasis) or before exposure to fMLP to measure platelet chemotaxis (an inflammatory function). In silico molecular docking of these nucleotides to the binding pocket of P2Y1 receptors was then assessed.

KEY RESULTS

Platelet aggregation and binding to fibrinogen induced by ADP was not mimicked by NAD+ , ADP-ribose, and Up4A. However, these endogenous nucleotides induced P2Y1 -dependent platelet chemotaxis, an effect that required RhoA and Rac-1 activity, but not canonical PLC activity. Analysis of molecular docking of the P2Y1 receptor revealed distinct differences of amino acid interactions and depth of fit within the binding pocket for Ap3A, NAD+ , ADP-ribose, or Up4A compared with ADP.

CONCLUSION AND IMPLICATIONS

Platelet function (aggregation vs motility) can be differentially modulated by biased-agonist activation of P2Y1 receptors. This may be due to the character of the ligand-binding pocket interaction. This has implications for future therapeutic strategies aimed to suppress platelet activation during inflammation without affecting haemostasis as is the requirement of current ant-platelet drugs.

LINKED ARTICLES

This article is part of a themed issue on Platelet purinergic receptor and non-thrombotic disease. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.4/issuetoc.

Inhibitors against New Delhi metallo-betalactamase-1 (NDM-1) and its variants endemic in Indian settings along with the laboratory functional gain mutant of NDM-1

PURPOSE

The emergence of NDM-1 producing bacteria has become common in both hospital and community settings, but no inhibitor has yet been available for clinical treatment. Hence, demanding the urgent need of NDM-1 inhibitors, we initiated to screen broad spectrum inhibitors against NDM natural variants and laboratory mutant.

METHODS

We used docking and molecular dynamics simulations, in silico pharmacokinetic investigations, and density functional theory calculation to characterize molecules. Furthermore, an in vitro study, including MIC, kinetics, and fluorescence study were carried out to confirm the efficacies of the selected compounds.

RESULTS

According to the findings of the computational studies, three compounds were effective against NDM variants. Fourfold reduction in MIC of imipenem and meropenem was observed when combined with inhibitors (D2573, D2148, and D63) against blaNDM-1, blaNDM-4, blaNDM-6, and blaNDM-1Q123A, while twofold reduction in MIC of imipenem and meropenem was observed against blaNDM-5 and blaNDM-7. Similarly in the presence of inhibitors (D2573, D2148, and D63) the efficiency of nitrocefin hydrolysis by NDM-4, NDM-6, and Q123A decreases to much more extent as compared to NDM-5 and NDM-7. These results showed that the efficacy of these broad spectrum inhibitors decreases with increasing resistance of NDM variants.

CONCLUSION

This is the first time inhibitors were tested against different NDM natural variants which are endemic in Indian settings. Moreover, a functional gain laboratory mutant was also checked for their efficacies. We may propose these molecules for the pre-clinical trial to further translate.

Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative

Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction. In detail, the docking simulations submitted to the MEDIATE initiative are utilized to predict the viral targets involved in the hits retrieved by a recently published cytopathic screening. Multiple docking results are combined by the EFO approach to develop target-specific consensus models. The combination of multiple docking simulations enhances the performances of the developed consensus models (average increases in EF1% value of 40% and 25% when combining three and two docking runs, respectively). These models are able to propose reliable targets for about half of the retrieved hits (31 out of 59). Thus, the study emphasizes that docking simulations might be effective in target identification and provide a convincing validation for the collaborative strategies that inspire the MEDIATE initiative. Disappointingly, cross-target and cross-program correlations suggest that common scoring functions are not specific enough for the simulated target.

Mechanistic Approach of Effective Combination of Antibiotics Against Clinical Bacterial Strains Having New Delhi Metallo-Beta-Lactamase Variants and Functional Gain Laboratory Mutant

Antimicrobial resistance has emerged as a serious issue for physicians and health-care workers treating infections that could lead to the next pandemic. One of the key resistance mechanisms is beta-lactamases. Although several beta-lactamase inhibitors in combination with antibiotics have been created and are being utilized in clinical settings, resistance to these formulations has also been evolving in the bacterial population due to their distinct targets. In this study we used effective combination of antibiotic as an approach to inhibit multidrug resistance bacteria. We used four combinations and checked its efficacy against NDM (New Delhi Metallo-beta-lactamase) variants and functional gain laboratory mutant by employing FICI, enzyme kinetics, fluorescence and computational biology approaches (Docking and Molecular Dynamics Simulation). FICI values of all the combinations were either less than 0.5 or equal to 0.5. Binding features acquired by spectroscopic techniques showed important interaction and complex formation between drugs and enzymes with decreased ksv and kq values. In steady-state kinetics, a reduction in hydrolytic efficiency of enzymes was shown by cooperative binding behaviour when they were treated with different drugs. We have also tested functional gain laboratory mutant developed in our lab, keeping in view that if in future upcoming variants of this kind be emerged then these mutants could also be subsided by combinational therapy. This study identifies three other combinations better than fluoroquinolones effective against NDM variants and laboratory mutant.

Structural and clinical characterization of CYP11B2 inhibition by dexfadrostat phosphate

Aldosterone synthase (CYP11B2) represents a promising drug target because its genetic dysregulation is causally associated with cardiovascular disease, its autonomous activity leads to primary aldosteronism, and its deficiency leads to salt wasting syndromes. The serendipitous discovery that the dextro-rotatory stereoisomer of the racemic aromatase (CYP19A1) inhibitor CGS16949A mediates potent CYP11B2 inhibition led to the purification and clinical development of dexfadrostat phosphate. To characterize the pharmacophore of dexfadrostat phosphate, structure-based enzyme coordination with CYP11B2, CYP11B1 and CYP19A1 was combined with steroid turnover upon in vitro and clinical treatment. Dexfadrostat, but not its 5S-enantiomer (5S-fadrozole), precisely coordinates with the catalytic heme moiety in the space of the CYP11B2 substrate binding pocket forming a tight and stable complex. Conversely, neither rigid nor flexible docking led to a plausible coordination geometry for dexfadrostat in steroid 11β-hydroxylase (CYP11B1 - orthologue to CYP11B2) or in CYP19A1. The inhibitory preference of dexfadrostat was confirmed in vitro using an adrenal cortex-derived cell line. Dexfadrostat phosphate treatment of healthy subjects in the context of a clinical phase 1 study led to a dose-dependent decrease in urinary aldosterone secretion, accompanied by an increase in urinary corticosterone and deoxycorticosterone metabolites. Increased urinary corticosterone metabolites are indicative of CYP11B2 (18-oxidase) inhibition with clinical features reminiscent of patients with inborn corticosterone methyloxidase type II deficiency. An off-target effect on CYP19A1 was not observed as indicated by no clinical changes in testosterone and estradiol levels. Therefore, dexfadrostat exhibits the ideal structural features for binding and catalytic inhibition of CYP11B2 but not CYP11B1. Clinically, treatment with dexfadrostat phosphate leads to suppression of aldosterone levels by inhibiting predominantly one or both final CYP11B2-mediated reactions.

Ab initio and comparative 3D modeling of FAM222A-encoded protein and target-driven-based virtual screening for the identification of novel therapeutics against Alzheimer's disease

The complex nature of Alzheimer's disease (AD) makes it difficult to understand the exact molecular processes leading to neuron death. However, two molecular factors - the production of amyloid-beta plaques and tau tangles - are considered to be linked to AD. A genetic marker for brain atrophy, FAM222A, has been identified by the unique cross-phenotype meta-analysis of genetics imaging and the molecular features show an interaction between the protein aggregatin encoded by FAM222A and amyloid beta (Aβ)-peptide (1-42) via its N-terminal Aβ binding domain, thus increasing Aβ aggregation. Function of Aggregatin protein is unclear, and its 3D structure has not been investigated in experimental analysis, so far. Hence, in the present study, first time in literature, 3D models of FAM222A-encoded Aggregatin were systematically constructed by applying diverse homology modeling approaches and they were used as target structures at the virtual screening of FDA-approved drugs and drugs currently under research in clinical trials. Then, the identified hit molecules were chosen for further molecular dynamics (MD) simulations and post-MD analyses. Our integrated ligand-based and protein-driven-based virtual screening results show that Cefpiramide, Diniprofylline, Fostriecin, and Droperidol may target Aggregatin.

Anticancer activity, phytochemical investigation and molecular docking insights of Citrullus colocynthis (L.) fruits

Cancer disease is regarded as one of the most significant public health issues, regardless of economic standards. Medicinal plants are now regarded as a natural source of anticancer medicines due to their antioxidant and anti-mutagenic actions. Cucurbitaceae is considered to be one of the most economically significant families. One family species is Citrullus colocynthis (L.), which has a high concentration of many active secondary chemical metabolites. Various C. colocynthis plant extracts showed cytotoxicity against some cancer cells. This study aims to identify the C. colocynthis fruit components and determine whether they have anticancer action against MIA PaCa-2 and A431 cells. High-Performance Liquid Chromatography/Quadrupole Time of Flight/Mass Spectrometry (HPLC/QTOF/MS); the technique was accustomed to investigate the compounds of the ethyl acetate (EtOAc) fruit extract. Anticancer activity was investigated on both MIAPaCa-2 and A-431 cell lines. DPPH assay for antioxidant activity was carried out. Molecular modelling was employed to help understand the molecular basis for the observed anticancer activity. 24 compounds were tentatively identified by comparing the extract's fragmentation pattern in positive mode against reference compounds spectra and literature. The EtOAc extract of C. colocynthis had effective positive results on cancer cells (MIAPaCa-2 and A-431) and was characterized by slight or no harmful effect on normal (healthy) cells. For the DPPH assay, EtOAc and BuOH extracts exhibited high antioxidant activity (86 and 76%, respectively) compared with the oxidative potential of the standard compound (Caffeic acid, 98%). One of the major cucurbitacin derivatives that LC/MS tentatively identified in the EtOAc extract was Cucurbita-5(10),6,23-triene-3β,25-diol. During this study, docking experiments and MD simulations were carried out, which suggested the anti-pancreatic cancer activity of C. colocynthis extract to be attributed to EGFR inhibition by Cucurbita-5(10),6,23-triene-3β,25-diol. Therefore, expansion of this type of research should be encouraged in the hope of obtaining natural therapeutics for cancerous tumors in the future, having the advantage of being cheaper, safer, and with fewer side effects.

Development of novel ligands against SARS-CoV-2 Mpro enzyme: an in silico and in vitro Study

BACKGROUND

Despite tremendous efforts made by scientific community during the outbreak of COVID-19 pandemic, this disease still remains as a public health concern. Although different types of vaccines were globally used to reduce the mortality, emergence of new variants of SARS-CoV-2 is a challenging issue in COVID-19 pharmacotherapy. In this context, target therapy of SARS-CoV-2 by small ligands is a promising strategy.

METHODS

In this investigation, we applied ligand-based virtual screening for finding novel molecules based on nirmatrelvir structure. Various criteria including drug-likeness, ADME, and toxicity properties were applied for filtering the compounds. The selected candidate molecules were subjected to molecular docking and dynamics simulation for predicting the binding mode and binding free energy, respectively. Then the molecules were experimentally evaluated in terms of antiviral activity against SARS-CoV-2 and toxicity assessment.

RESULTS

The results demonstrated that the identified compounds showed inhibitory activity towards SARS-CoV-2 Mpro .

CONCLUSION

In summary, the introduced compounds may provide novel scaffold for further structural modification and optimization with improved anti SARS-CoV-2 Mpro activity.

Repurposing FDA approved drug molecules against A B C classes of β-lactamases: a computational biology and molecular dynamics simulations study

β-lactamase are the main resistance factor for β-lactam antibiotics in Gram-negative bacteria. Since β-lactam antibiotics are being utilised as an antimicrobial agents extensively for the past 70 years, a large number of β-lactam-inactivating β-lactamases have been produced by bacteria. Here, we employed a structure-based drug discovery approach to identify and assess the efficacy of a potential medication that might block the β-lactamases which hydrolyse antibiotics. The FDA-approved medications were subjected to virtual screening, molecular docking, molecular dynamics simulations, density functional theory, and covalent docking against the β-lactamases. We identified diosmin, hidrosmin, monoxuritin and solasulfone as β-lactamase inhibitors which are authorised for therapeutic use in humans. These medications interact in a remarkable variety of non-covalent ways with the conserved residues in the substrate-binding pocket of the β-lactamases. Diosmin has been identified as an inhibitor that binds covalently to the NDM-1 a class B metallo-betalactamase. After experimental validation and clinical demonstration, this study offers adequate evidence for the therapeutic use of these drugs for controlling multidrug resistance.Communicated by Ramaswamy H. Sarma.

L protein characterization and in silico screening of putative broad range target molecules for pathogenic mammarenaviruses from South America

The genus Mammarenavirus belonging to the family Arenaviridae encompasses pathogenic viral species capable of triggering severe diseases in humans, causing concern for the health system due to the high fatality rate associated with them. Currently, there is a dearth of specific therapies against pathogens of the genus. Natural products isolated from plants have impacted the development of drugs against several diseases. The Núcleo de Bioensaios, Biossíntese e Ecofisiologia de Produtos Naturais (NuBBE) database offers several natural compounds with antimicrobial activities that can be used in the development of new antiviral drugs. In this context, here we modeled the arenavirus L protein, multifunctional machinery essential for the viral replicative cycle, making this enzyme a potential candidate for targeting the development of antivirals against genus pathogens. Using the modeled L protein, a virtual screening was performed, which suggested eleven molecules from the NuBBE database that binds to the active site of the L protein, which was promising in the in silico predictions of absorption and toxicity analysis. The NuBBE 1642 molecule proved to be the best candidate for four of the five species evaluated, acting as a possible broad-spectrum molecule. Additionally, our results showed that the L protein is highly conserved among species of the genus, as well as presenting close phylogenetic relationships between many of the species studied, strengthening its candidacy as a therapeutic target. The data presented here demonstrate that some NuBBE molecules are potential ligands for the L protein of arenaviruses, which may help to contain possible outbreaks.Communicated by Ramaswamy H. Sarma.

Molecular interaction analysis of the lignans from Piper cubeba in complex with Haemonchus contortus phosphomethyltransferase

In vitro larvicidal assays carried out previously by our research group with cubebin, dihydrocubebin and hinokinin, lignans extracted from the fruits of Piper cubeba, against Haemonchus contortus larvae showed strong action larvicidal these compounds. Hinokinin was the most active (EC50 = 0.34 µg/mL) with strong action on the cuticle of the larvae as observed by scanning electron microscopy of the L3 stage. Therefore, to understand the mechanism of action of these compounds in silico studies were carried out using the enzyme phosphomethyltransferase of Haemonchus contortus that contain PMT-1 and PMT-2 di-domains responsible for phosphocholine synthesis, which is one of the main lipids in nematodes. This pathway is not found in mammals, so this enzyme is an important biological target for the development of new anthelmintics. Results of molecular docking, molecular dynamic and a density functional theory calculations studies with the three lignans show few interactions with PMT-1. However, hinokinin has important interactions with PMT-2, that can deactivate the enzyme and interrupt the phosphocholine synthesis, which is an essential compound for the development and maintenance of the nematode cuticle and its survive. Therefore, the previous results of the in vitro assay allied with in silico results, now realized; suggest that hinokinin may be a possible selective target for the development of new anthelmintics against Haemonchus contortus since the PMT-2 domain is present in this nematode.

Leonotis ocymifolia (Burm.f.) Iwarsson aerial parts aqueous extract mitigates cisplatin-induced nephrotoxicity via attenuation of inflammation, and DNA damage

Herein, we explored the protective effect of Leonotis ocymifolia (Burm.f.) Iwarsson aerial parts extract (LO) against cisplatin (CP)-induced nephrotoxicity in rats and profiled their phytocontents. A total of 31 compounds belonging to organic and phenolic acids and their glycosides as well as flavonoids and their O- and C-glycosides were identified through LC-MS/MS. The DPPH and FRAP assays revealed that the extract had powerful antioxidant properties. The in vivo results demonstrated that administering LO extract for 30 days (40 and 80 mg/kg b. w.) significantly improved the altered renal injury markers via reducing creatinine (high dose only) and uric acid levels compared to the Cp-group. The deleterious action of cisplatin on renal oxidative stress markers (GSH, MDA, SOD, and CAT) were also mitigated by LO-pretreatment. The reduction of the inflammatory marker (IL-6), and inhibition of DNA fragmentation, highlighted the prophylactic action of LO in kidney tissue. Molecular docking followed by a 100 ns molecular dynamic simulation analyses revealed that, amongst the 31 identified compounds in LO, chlorogenic and caffeoylmalic acids had the most stable binding to IL-6. The nephroprotective effects were further confirmed by histopathological observations, which showed improvement in ultrastructural changes induced by cisplatin. The observed findings reinforce the conclusion that L. ocymifolia extract exerts nephroprotective properties, which could be related to its antioxidant and anti-inflammatory activities. Further studies are required to determine the therapeutic doses and the proper administration time.

Structural displacement model of chitooligosaccharide transport through chitoporin

VhChiP is a chitooligosaccharide-specific porin identified in the outer membrane of Vibrio campbellii type strain American Type Culture Collection BAA 1116. VhChiP contains three identical subunits, and in each subunit, the 19-amino acid N-terminal segment serves as a molecular plug (the "N-plug") that controls the closed/open dynamics of the neighboring pores. In this study, the crystal structures of VhChiP lacking the N-plug were determined in the absence and presence of chitohexaose. Binding studies of sugar-ligand interactions by single-channel recordings and isothermal microcalorimetry experiments suggested that the deletion of the N-plug peptide significantly weakened the sugar-binding affinity due to the loss of hydrogen bonds around the central affinity sites. Steered molecular dynamic simulations revealed that the movement of the sugar chain along the sugar passage triggered the ejection of the N-plug, while the H-bonds transiently formed between the reducing end GlcNAc units of the sugar chain with the N-plug peptide may help to facilitate sugar translocation. The findings enable us to propose the structural displacement model, which enables us to understand the molecular basis of chitooligosaccharide uptake by marine Vibrio bacteria.

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices

The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the 'best' program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research.

Interaction studies of oxindole-derivatives with β-amyloid peptides inhibiting its aggregation induced by metal ions

Some hydrazones and Schiff bases derived from isatin, an endogenous oxindole formed in the metabolism of tryptophan, were obtained to investigate their effects on in vitro aggregation of β-amyloid peptides (Aβ), macromolecules implicated in Alzheimer's disease. Some hydrazone ligands, prepared by condensation reactions of isatin with hydrazine derivatives, showed a large affinity binding to the synthetic peptides Aβ, particularly to Aβ1-16. Measurements by NMR spectroscopy indicated that those interactions occur mainly at the metal binding site of the peptide, involving His6, His13, and His14 residues, and that hydrazone E-diastereoisomer interacts preferentially with the amyloid peptides. Experimental results were consistent with simulations using a docking approach, where it is demonstrated that the amino acid residues Glu3, His6, His13, and His14 are those that mostly interact with the ligands. Further, these oxindole-derived ligands can efficiently chelate copper(II) and zinc(II) ions, forming moderate stable [ML] 1:1 species. The corresponding formation constants were determined by UV/Vis spectroscopy, by titrations of the ligands with increasing amounts of metal salts, and the obtained log K values were in the range 2.74 to 5.11. Both properties, good affinity for amyloid peptides, and reasonably good capacity of chelating biometal ions, like copper and zinc, can explain the efficient inhibition of Aβ fragments aggregation, as shown by experiments carried out with the oxindole derivatives in the presence of metal ions.

Discrete Dynamics of Warhead Modulation on Covalent Inhibition of Oxyr: A QM/MM Study

The bacterial transcriptional factor OxyR, a peroxide sensor conserved in bacterial virulence pathways, has the capability to exhibit exceptional reactivity toward hydrogen peroxide (H₂O₂). H₂O₂ is essential for oxidizing cysteine thiolates to maintain cellular redox homeostasis and is dispensable for bacterial growth that can potentially mitigate drug resistance, thus underlining OxyR as a valuable target. We employ quantum mechanics/molecular mechanics (QM/MM) umbrella sampling (US) simulations at the DFTB3/MM level of theory and propose a reaction mechanism with four potential covalent inhibitors. The potential of mean force reveals the direct role of intrinsic reactivity of inhibitors, for instance, benzothiophenes and modified experimental inhibitors with methyl oxo-enoate warhead-activated carbonyl samples in the first step of reaction, which shed light on the significance of proton transfer indispensable for full inhibition, whereas the nitrile inhibitor undergoes a stepwise mechanism with a small proton-transfer energy barrier and lower imaginary frequencies that materialize instantly after nucleophilic attack. To unveil the molecular determinants of respective binding affinities, transition states along the reaction path are optimized and characterized with B3LYP 6-31+G(d,p). Furthermore, the post-simulation analysis indicates the catalytic triad (His130/Cys199/Thr129), thermodynamically favored for inhibition, which restricts water molecules from acting as the potential source of protonation/deprotonation. This study thus serves as a preamble to add variation in the proposed structures and unveils the impact of functional groups lying in warheads that modulate the kinetics of proton transfer, which will certainly aid to design more selective and efficient irreversible inhibitors of OxyR.

6D-QSAR for predicting biological activity of human aldose reductase inhibitors using quasar receptor surface modeling

The application of QSAR analysis dates back a half-century ago and is currently continuously employed in any rational drug design. The multi-dimensional QSAR modeling can be a promising tool for researchers to develop reliable predictive QSAR models for designing novel compounds. In the present work, we studied inhibitors of human aldose reductase (AR) to generate multi-dimensional QSAR models using 3D- and 6D-QSAR methods. For this purpose, Pentacle and Quasar's programs were used to produce the QSAR models using corresponding dissociation constant (K_d) values. By inspecting the performance metrics of the generated models, we achieved similar results with comparable internal validation statistics. However, considering the externally validated values, 6D-QSAR models provide significantly better prediction of endpoint values. The obtained results suggest that the higher the dimension of the QSAR model, the higher the performance of the generated model. However, more studies are required to verify these outcomes.

Structure-Based Design of Novel MAO-B Inhibitors: A Review

With the significant growth of patients suffering from neurodegenerative diseases (NDs), novel classes of compounds targeting monoamine oxidase type B (MAO-B) are promptly emerging as distinguished structures for the treatment of the latter. As a promising function of computer-aided drug design (CADD), structure-based virtual screening (SBVS) is being heavily applied in processes of drug discovery and development. The utilization of molecular docking, as a helping tool for SBVS, is providing essential data about the poses and the occurring interactions between ligands and target molecules. The current work presents a brief discussion of the role of MAOs in the treatment of NDs, insight into the advantages and drawbacks of docking simulations and docking software, and a look into the active sites of MAO-A and MAO-B and their main characteristics. Thereafter, we report new chemical classes of MAO-B inhibitors and the essential fragments required for stable interactions focusing mainly on papers published in the last five years. The reviewed cases are separated into several chemically distinct groups. Moreover, a modest table for rapid revision of the revised works including the structures of the reported inhibitors together with the utilized docking software and the PDB codes of the crystal targets applied in each study is provided. Our work could be beneficial for further investigations in the search for novel, effective, and selective MAO-B inhibitors.

Serotonin type-3 receptor antagonists selectively kill melanoma cells through classical apoptosis, microtubule depolymerisation, ERK activation, and NF-κB downregulation

Malignant melanoma is a highly metastatic tumour, resistant to treatment. Serotonin type-3 (5-HT3) receptor antagonists, such as tropisetron and ondansetron, are well-tolerated antiemetic drugs commonly used to prevent nausea caused by chemotherapy or radiotherapy. We investigated the anticancer effects of these drugs on melanoma cancer cell lines WM-266-4 and B16F10 with or without paclitaxel. We constructed IC50 curves and performed Chou-Talalay analysis, using data obtained with the MTT assay. Flow cytometry and fluorescent microscopy were used to examine characteristics of the cell cycle, cell death and cytoskeleton changes. Protein levels and activation were analysed by western blotting and molecular docking studies carried out. Data were analysed by one way ANOVA and post hoc testing. Ondansetron and tropisetron showed selective concentration-dependent cytotoxicity in melanoma cell lines WM-266-4 and B16F10. The effect in combination with paclitaxel was synergistic. The drugs did not cause cell cycle arrest but did promote characteristics of classical apoptosis, including accumulation of subG1 DNA, cleaved caspase-3, mitochondrial membrane permeability and phosphatidylserine exposure. As well, the cytosolic calcium level in the melanoma cells was enhanced, phosphorylated ERK1/2 induced and NF-κB inhibited. Finally, the formation of microtubules was shown to be impaired in melanoma cells treated with ondansetron or tropisetron. Docking studies were used to predict that these drugs could bind to the colchicine binding site on the tubulin molecule. Antiemetic drugs, already given in combination with chemotherapy, may enhance the cytotoxic effect of chemotherapy, following successful delivery to the tumour site.

Roles of Virtual Screening and Molecular Dynamics Simulations in Discovering and Understanding Antimalarial Drugs

Malaria continues to be a global health threat, with approximately 247 million cases worldwide. Despite therapeutic interventions being available, patient compliance is a problem due to the length of treatment. Moreover, drug-resistant strains have emerged over the years, necessitating urgent identification of novel and more potent treatments. Given that traditional drug discovery often requires a great deal of time and resources, most drug discovery efforts now use computational methods. In silico techniques such as quantitative structure-activity relationship (QSAR), docking, and molecular dynamics (MD) can be used to study protein-ligand interactions and determine the potency and safety profile of a set of candidate compounds to help prioritize those tested using assays and animal models. This paper provides an overview of antimalarial drug discovery and the application of computational methods in identifying candidate inhibitors and elucidating their potential mechanisms of action. We conclude with the continued challenges and future perspectives in the field of antimalarial drug discovery.

Monoterpenoid aryl hydrocarbon receptor allosteric antagonists protect against ultraviolet skin damage in female mice

The human aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that is a pivotal regulator of human physiology and pathophysiology. Allosteric inhibition of AhR was previously thought to be untenable. Here, we identify carvones as noncompetitive, insurmountable antagonists of AhR and characterize the structural and functional consequences of their binding. Carvones do not displace radiolabeled ligands from binding to AhR but instead bind allosterically within the bHLH/PAS-A region of AhR. Carvones do not influence the translocation of ligand-activated AhR into the nucleus but inhibit the heterodimerization of AhR with its canonical partner ARNT and subsequent binding of AhR to the promoter of CYP1A1. As a proof of concept, we demonstrate physiologically relevant Ahr-antagonism by carvones in vivo in female mice. These substances establish the molecular basis for selective targeting of AhR regardless of the type of ligand(s) present and provide opportunities for the treatment of disease processes modified by AhR.

AmiP from hyperthermophilic Thermus parvatiensis prophage is a thermoactive and ultrathermostable peptidoglycan lytic amidase

Bacteriophages encode a wide variety of cell wall disrupting enzymes that aid the viral escape in the final stages of infection. These lytic enzymes have accumulated notable interest due to their potential as novel antibacterials for infection treatment caused by multiple-drug resistant bacteria. Here, the detailed functional and structural characterization of Thermus parvatiensis prophage peptidoglycan lytic amidase AmiP, a globular Amidase_3 type lytic enzyme adapted to high temperatures is presented. The sequence and structure comparison with homologous lytic amidases reveals the key adaptation traits that ensure the activity and stability of AmiP at high temperatures. The crystal structure determined at a resolution of 1.8 Å displays a compact α/β-fold with multiple secondary structure elements omitted or shortened compared with protein structures of similar proteins. The functional characterization of AmiP demonstrates high efficiency of catalytic activity and broad substrate specificity toward thermophilic and mesophilic bacteria strains containing Orn-type or DAP-type peptidoglycan. The here presented AmiP constitutes the most thermoactive and ultrathermostable Amidase_3 type lytic enzyme biochemically characterized with a temperature optimum at 85°C. The extraordinary high melting temperature T_m 102.6°C confirms fold stability up to approximately 100°C. Furthermore, AmiP is shown to be more active over the alkaline pH range with pH optimum at pH 8.5 and tolerates NaCl up to 300 mM with the activity optimum at 25 mM NaCl. This set of beneficial characteristics suggests that AmiP can be further exploited in biotechnology.

Antimelanoma effect of manool in 2D cell cultures and reconstructed human skin models

Melanoma is the most aggressive and lethal type of skin cancer, characterized by therapeutic resistance. In this context, the present study aimed to investigate the cytotoxic potential of manool, a diterpene from Salvia officinalis L., in human (A375) and murine (B16F10) melanoma cell lines. The analysis of cytotoxicity using the XTT assay showed the lowest IC₅₀ after 48 h of treatment with the manool, being 17.6 and 18.2 µg/ml for A375 and B16F10, respectively. A selective antiproliferative effect of manool was observed on the A375 cells based on the colony formation assay, showing an IC₅₀ equivalent to 5.6 µg/ml. The manool treatments led to 43.5% inhibition of the A375 cell migration at a concentration of 5.0 µg/ml. However, it did not affect cell migration in the B16F10 cells. Cell cycle analysis revealed that the manool interfered in the cell cycle of the A375 cells, blocking the G2/M phase. No changes in the cell cycle were observed in the B16F10 cells. Interestingly, manool did not induce apoptosis in the A375 cells, but apoptosis was observed after treatment of the B16F10 cells. Additionally, manool showed an antimelanoma effect in a reconstructed human skin model. Furthermore, in silico studies, showed that manool is stabilized in the active sites of the tubulin dimer with comparable energy concerning taxol, indicating that both structures can inhibit the proliferation of cancer cells. Altogether, it is concluded that manool, through the modulation of the cell cycle, presents a selective antiproliferative activity and a potential antimelanoma effect.

Entropy-based lamarckian quantum-behaved particle swarm optimization for flexible ligand docking

AutoDock is a widely used software for flexible ligand docking problems since it is open source and easy to be implemented. In this paper, a novel hybrid algorithm is proposed and applied in the docking environment of AutoDock version 4.2.6 in order to enhance the accuracy and the efficiency for dockings with flexible ligands. This search algorithm, called entropy-based Lamarckian quantum-behaved particle swarm optimization (ELQPSO), is a combination of the QPSO with an entropy-based update strategy and the Solis and Wet local search (SWLS) method. By using the PDBbind core set v.2016, the ELQPSO is compared with the Lamarckian genetic algorithm (LGA), Lamarckian particle swarm optimization (LPSO) and Lamarckian QPSO (LQPSO). The experimental results reveal that the corresponding docking program of ELQPSO, named as EQDOCK in this paper, has a competitive performance in dealing with the protein-ligand docking problems. Moreover, for the test cases with different number of torsions, the EQDOCK outperforms the other three docking programs in finding docking conformations with small root mean squared deviation (RMSD) values in most cases. In particular, it has an advantage of solving highly flexible ligand docking problems over the others.

Computational assessment of the impact of Cu(II) and Al(III) on β-amyloid42 fibrils: Binding sites, structural stability, and possible physiological implications

One of Alzheimer's disease major hallmarks is the aggregation of β-amyloid peptide, a process in which metal ions play an important role. In the present work, an integrative computational study has been performed to identify the metal-binding regions and determine the conformational impact of Cu(II) and Al(III) ion binding to the β-amyloid (Aβ₄₂) fibrillary structure. Through classical and Gaussian accelerated molecular dynamics, it has been observed that the metal-free fiber shows a hinge fan-like motion of the S-shaped structure, maintaining the general conformation. Upon metal coordination, distinctive patterns are observed depending on the metal. Cu(II) binds to the flexible N-terminal region and induces structural changes that could ultimately disrupt the fibrillary structure. In contrast, Al(III) binding takes place with the residues Glu22 and Asp23, and its binding reinforces the core stability of the system. These results give clues on the molecular impact of the interaction of metal ions with the aggregates and sustain their non-innocent roles in the evolution of the illness.

Guttiferone E Displays Antineoplastic Activity Against Melanoma Cells

Guttiferone E (GE) is a benzophenone found in Brazilian red propolis. In the present study, the effect of GE on human (A-375) and murine (B16-F10) melanoma cells was investigated. GE significantly reduced the cellular viability of melanoma cells in a time-dependent manner. In addition, GE demonstrated antiproliferative effect, with IC₅₀ values equivalent to 9.0 and 6.6 µM for A-375 and B16-F10 cells, respectively. The treatment of A-375 cells with GE significantly increased cell populations in G0/G1 phase and decreased those in G2/M phase. Conversely, on B16-F10 cells, GE led to a significant decrease in the populations of cells in G0/G1 phase and concomitantly an increase in the population of cells in phase S. A significantly higher percentage of apoptotic cells was observed in A-375 (43.5%) and B16-F10 (49.9%) cultures after treatment with GE. Treatments with GE caused morphological changes and significant decrease to the melanoma cells' density. GE (10 µM) inhibited the migration of melanoma cells, with a higher rate of inhibition in B16-F10 cells (73.4%) observed. In addition, GE significantly reduced the adhesion of A375 cells, but showed no effect on B16-F10. Treatment with GE did not induce changes in P53 levels in A375 cultures. Molecular docking calculations showed that GE is stable in the active sites of the tubulin dimer with a similar energy to taxol chemotherapy. Taken together, the data suggest that GE has promising antineoplastic potential against melanoma.

Binding of RPR260243 at the intracellular side of the hERG1 channel pore domain slows closure of the helix bundle crossing gate

The opening and closing of voltage-dependent potassium channels is dependent on a tight coupling between movement of the voltage sensing S4 segments and the activation gate. A specific interaction between intracellular amino- and carboxyl-termini is required for the characteristically slow rate of channel closure (deactivation) of hERG1 channels. Compounds that increase hERG1 channel currents represent a novel approach for prevention of arrhythmia associated with prolonged ventricular repolarization. RPR260243 (RPR), a quinoline oxo-propyl piperidine derivative, inhibits inactivation and dramatically slows the rate of hERG1 channel deactivation. Here we report that similar to its effect on wild-type channels, RPR greatly slows the deactivation rate of hERG1 channels missing their amino-termini, or of split channels lacking a covalent link between the voltage sensor domain and the pore domain. By contrast, RPR did not slow deactivation of C-terminal truncated hERG1 channels or D540K hERG1 mutant channels activated by hyperpolarization. Together, these findings indicate that ability of RPR to slow deactivation requires an intact C-terminus, does not slow deactivation by stabilizing an interaction involving the amino-terminus or require a covalent link between the voltage sensor and pore domains. All-atom molecular dynamics simulations using the cryo-EM structure of the hERG1 channel revealed that RPR binds to a pocket located at the intracellular ends of helices S5 and S6 of a single subunit. The slowing of channel deactivation by RPR may be mediated by disruption of normal S5-S6 interactions.

Evaluation of In Vitro and In Silico Anti-Alzheimer Potential of Nonpolar Extracts and Essential Oil from Mentha piperita

The anticholinesterase and antioxidant activities with chemical composition and molecular docking of essential oil and nonpolar extracts of Mentha piperita were evaluated using enzymatic and chemical methods. Molecular docking tools were used to explain the interaction of the major chemical constituents with the enzymes. GC/MS analyses revealed that the main compounds in M. piperita essential oil were l-menthone (43.601%) followed by pulegone (21.610%), linolenic acid (25.628%), and l-menthone (10.957%), representing the major compounds of the petroleum ether extract. Imidazoquinoline (7.767%) and 17-N-acetyl-oroidine (5.363%) were the major constituents of the chloroform extract. Linolenic acid (19.397%) and l-menthone (6.336%) were the most abundant compounds in the hexane extract. The M. piperita essential oil and nonpolar extracts showed moderate antioxidant activity. The essential oil showed the most promising anticholinesterase activity with IC₅₀ = 10.66 ± 0.12 µg/mL and IC₅₀ = 16.33 ± 0.03 µg/mL against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), respectively, close to galantamine in AChE and more active in BChE, followed by the interesting activity in the petroleum ether extract with IC₅₀ = 23.42 ± 3.06 µg/mL in AChE and IC₅₀ = 62.00 ± 3.22 µg/mL in BChE. The docking experiments showed that among the seven major identified compounds, N-acetyl-17-oroidine showed the highest binding score (63.01 in AChE and 63.68 in BChE). This compound was found to bind the catalytic and peripheral sites, resulting in more potent inhibitory activity than galantamine, which only binds to the catalytic site. These findings suggested the possible use of M. piperita essential oil and nonpolar extracts as a potential source of alternative natural anti-Alzheimer compounds.

Straightforward Access to a New Class of Dual DYRK1A/CLK1 Inhibitors Possessing a Simple Dihydroquinoline Core

The DYRK (Dual-specificity tyrosine phosphorylation-regulated kinase) family of protein kinases is involved in the pathogenesis of several neurodegenerative diseases. Among them, the DYRK1A protein kinase is thought to be implicated in Alzheimer's disease (AD) and Down syndrome, and as such, has emerged as an appealing therapeutic target. DYRKs are a subset of the CMGC (CDK, MAPKK, GSK3 and CLK) group of kinases. Within this group of kinases, the CDC2-like kinases (CLKs), such as CLK1, are closely related to DYRKs and have also sparked great interest as potential therapeutic targets for AD. Based on inhibitors previously described in the literature (namely TG003 and INDY), we report in this work a new class of dihydroquinolines exhibiting inhibitory activities in the nanomolar range on hDYRK1A and hCLK1. Moreover, there is overwhelming evidence that oxidative stress plays an important role in AD. Pleasingly, the most potent dual kinase inhibitor 1p exhibited antioxidant and radical scavenging properties. Finally, drug-likeness and molecular docking studies of this new class of DYRK1A/CLK1 inhibitors are also discussed in this article.

Computational studies on phylogeny and drug designing using molecular simulations for COVID-19

Since the first appearance of a novel coronavirus pneumonia (NCP) caused by a novel human coronavirus, and especially after the infection started its rapid spread over the world causing the COVID-19 (coronavirus disease 2019) pandemics, a very substantial part of the scientific community is engaged in the intensive research dedicated to finding of the potential therapeutics to cure this disease. As repurposing of existing drugs represents the only instant solution for those infected with the virus, we have been working on utilization of the structure-based virtual screening method to find some potential medications. In this study, we screened a library of 646 FDA approved drugs against the receptor-binding domain of the SARS-CoV-2 spike (S) protein and the main protease of this virus. Scoring functions revealed that some of the anticancer drugs (such as Pazopanib, Irinotecan, and Imatinib), antipsychotic drug (Risperidone), and antiviral drug (Raltegravir) have a potential to interact with both targets with high efficiency. Further we performed molecular dynamics simulations to understand the evolution in protein upon interaction with drug. Also, we have performed a phylogenetic analysis of 43 different coronavirus strains infecting 12 different mammalian species.Communicated by Ramaswamy H. Sarma.

Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor

The retrieval of hit/lead compounds with novel scaffolds during early drug development is an important but challenging task. Various generative models have been proposed to create drug-like molecules. However, the capacity of these generative models to design wet-lab-validated and target-specific molecules with novel scaffolds has hardly been verified. We herein propose a generative deep learning (GDL) model, a distribution-learning conditional recurrent neural network (cRNN), to generate tailor-made virtual compound libraries for given biological targets. The GDL model is then applied to RIPK1. Virtual screening against the generated tailor-made compound library and subsequent bioactivity evaluation lead to the discovery of a potent and selective RIPK1 inhibitor with a previously unreported scaffold, RI-962. This compound displays potent in vitro activity in protecting cells from necroptosis, and good in vivo efficacy in two inflammatory models. Collectively, the findings prove the capacity of our GDL model in generating hit/lead compounds with unreported scaffolds, highlighting a great potential of deep learning in drug discovery.

Niosomes: a novel targeted drug delivery system for cancer

Recently, nanotechnology is involved in various fields of science, of which medicine is one of the most obvious. The use of nanoparticles in the process of treating and diagnosing diseases has created a novel way of therapeutic strategies with effective mechanisms of action. Also, due to the remarkable progress of personalized medicine, the effort is to reduce the side effects of treatment paths as much as possible and to provide targeted treatments. Therefore, the targeted delivery of drugs is important in different diseases, especially in patients who receive combined drugs, because the delivery of different drug structures requires different systems so that there is no change in the drug and its effectiveness. Niosomes are polymeric nanoparticles that show favorable characteristics in drug delivery. In addition to biocompatibility and high absorption, these nanoparticles also provide the possibility of reducing the drug dosage and targeting the release of drugs, as well as the delivery of both hydrophilic and lipophilic drugs by Niosome vesicles. Since various factors such as components, preparation, and optimization methods are effective in the size and formation of niosomal structures, in this review, the characteristics related to niosome vesicles were first examined and then the in silico tools for designing, prediction, and optimization were explained. Finally, anticancer drugs delivered by niosomes were compared and discussed to be a suitable model for designing therapeutic strategies. In this research, it has been tried to examine all the aspects required for drug delivery engineering using niosomes and finally, by presenting clinical examples of the use of these nanocarriers in cancer, its clinical characteristics were also expressed.

Broad-Spectrum Inhibitors against Class A, B, and C Type β-Lactamases to Block the Hydrolysis against Antibiotics: Kinetics and Structural Characterization

The emergence of antibiotic resistance has led to a global crisis for the physician to handle infection control issues. All antibiotics, including colistin, have lost efficiency against emerging drug-resistant bacterial strains due to the production of metallo-β-lactamases (MBLs) and serine-β-lactamases (SBLs). Therefore, it is of the utmost importance to design inhibitors against these enzymes to block the hydrolytic action against antibiotics being used. Although various novel β-lactamase inhibitors are being authorized or are under clinical studies, the coverage of their activity spectrum does not include MDR organisms expressing multiple classes of β-lactamases at a single time. This study reports three novel broad-spectrum inhibitors effective against both SBLs and MBLs. Virtual screening, molecular docking, molecular dynamics simulations, and an in silico pharmacokinetic study were performed to identify the lead molecules with broad-spectrum ability to inhibit the hydrolysis of β-lactam. The selected compounds were further assessed by in vitro cell assays (MIC, 50% inhibitory concentration [IC₅₀], kinetics, and fluorescence against class A, B, and C type β-lactamases) to confirm their efficacies. A 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay was performed to check the toxicity of screened lead molecules. All three selected inhibitors were found to reduce MIC and showed good affinity against all the SBLs and MBLs produced by class A, B, and C type β-lactamases. These nontoxic novel non-β-lactam broad-spectrum inhibitors bind to the active site residues of selected β-lactamases, which are crucial for β-lactam antibiotic hydrolysis. These inhibitors may be proposed as a future drug candidate in combination with antibiotics as a single formulation to control infection caused by resistant strains. Hence, this study plays a significant role in the cure of infections caused by antibiotic-resistant bacteria.

IMPORTANCE Several inhibitors for usage in conjunction with antibiotics have been developed. However, to date, there is no commercially available broad-spectrum β-lactamase inhibitor that targets both MBLs and SBLs. Here, we showed three novel broad-spectrum inhibitors with promising results through computational techniques and in vitro studies. These inhibitors are effective against both SBLs and MBLs and hence could be used as future drug candidates to treat infections caused by multidrug-resistant bacteria producing both types of enzymes (SBLs and MBLs).

Design, Synthesis and Pharmacological Evaluation of Novel Conformationally Restricted N-arylpiperazine Derivatives Characterized as D2/D3 Receptor Ligands, Candidates for the Treatment of Neurodegenerative Diseases

Most neurodegenerative diseases are multifactorial, and the discovery of several molecular mechanisms related to their pathogenesis is constantly advancing. Dopamine and dopaminergic receptor subtypes are involved in the pathophysiology of several neurological disorders, such as schizophrenia, depression and drug addiction. For this reason, the dopaminergic system and dopamine receptor ligands play a key role in the treatment of such disorders. In this context, a novel series of conformationally restricted N-arylpiperazine derivatives (5a–f) with a good affinity for D₂/D₃ dopamine receptors is reported herein. Compounds were designed as interphenylene analogs of the drugs aripiprazole (2) and cariprazine (3), presenting a 1,3-benzodioxolyl subunit as a ligand of the secondary binding site of these receptors. The six new N-arylpiperazine compounds were synthesized in good yields by using classical methodologies, and binding and guanosine triphosphate (GTP)-shift studies were performed. Affinity values below 1 μM for both target receptors and distinct profiles of intrinsic efficacy were found. Docking studies revealed that Compounds 5a–f present a different binding mode with dopamine D₂ and D₃ receptors, mainly as a consequence of the conformational restriction imposed on the flexible spacer groups of 2 and 3.

Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches

Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein-protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.

Covalent docking in CDOCKER

Targeted covalent inhibitors (TCIs) are considered to be an important component in the toolbox of drug discovery and about 30% of currently marketed drugs are TCIs. Although these drugs raise concerns about toxicity, their high potencies and prolonged effects result in less-frequent drug dosing and wide therapeutic margins for patients. This leads to increased interests in developing new computational methods to identify novel covalent inhibitors. The implementation of successful in silico docking algorithms have the potential to provide significant savings of time and money in the discovery of lead compounds. In this paper, we describe the implementation and testing of a covalent docking methodology in Rigid CDOCKER and the optimization of the corresponding physics-based scoring function with an additional customizable covalent bond grid potential which represents the free energy change of bond formation between the ligand and the receptor. We optimize the covalent bond grid potential for different common covalent bond formation reaction in TCIs. The average runtime for docking one covalent compound is 15 minutes which is comparable or faster than other well-established covalent docking methods. We demonstrate comparable top rank accuracy compared with other covalent docking algorithms using the pose prediction benchmark dataset for covalent docking algorithms developed by the Keserű group. Finally, we construct a retrospective virtual screening benchmark dataset containing 8 different receptor targets with different covalent bond formation reactions. To our knowledge, this is the largest dataset for benchmarking covalent docking methods. We show that our new covalent docking algorithm has the ability to identify lead compounds among a large chemical space. The largest AUC value is 0.909 for the target receptor CATK and the warhead chemistry of the covalent inhibitors is addition to the aldehyde functionality.

Application of InterCriteria Analysis to Assess the Performance of Scoring Functions in Molecular Docking Software Packages

(1) Background: In silico approaches to rational drug design are among the fastest evolving ones. Depending on the available structural information for the biomacromolecule and the small molecule, the in silico methods are classified as ligand- and structure-based. The latter predict ligand–receptor binding using 3D structures of both molecules, whose computational simulation is referred to as molecular docking. It aims at estimating the binding affinity (approximated by scoring function) and the ligand binding pose in the receptor’s active site, which postulates a key role of the scoring functions in molecular docking algorithms. This study focuses on the performance of different types of scoring functions implemented in molecular modelling software packages. (2) Methods: An InterCriteria analysis (ICrA) was applied to assess the performance of the scoring functions available in MOE, GOLD, SeeSAR, and AutoDock Vina software platforms. The InterCriteria analysis was developed to distinguish possible relations between pairs of criteria when multiple objects are considered. All 12 investigated scoring functions were tested by docking a set of protease inhibitors in the binding sites of two protein targets. The dataset consisted of 88 benzamidine-type compounds with experimentally measured inhibitory constants for thrombin and trypsin, which allows for the objective assessment of the scoring functions performance. The results generated by the molecular docking were subjected to ICrA in order to analyze both docking energies as approximations of the binding affinities and RMSDs (root-mean-square deviation) as measures of the experimental binding pose proximity between the compounds and the co-crystalized ligand, based on the atoms in the common scaffold. (3) Results: The results obtained for the best poses, the average of the best 5 or 30 poses retained after docking, were analyzed. A comparison with the experimentally observed inhibitory effects was also performed. The InterCriteria analysis application confirms that the performance of the scoring functions for the same dataset of ligands depends on the studied protein. The analysis reveals that none of the studied scoring functions is a good predictor of the compounds’ binding affinities for the considered protein targets. (4) Conclusion: In terms of this analysis, the investigated scoring functions do not produce equivalent results, which suggests the necessity for their combined use in consensus docking studies.