Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies

Caryophyllene-type sesquiterpenes from the endophytic fungus Pestalotiopsis lespedezae through an OSMAC approach

Two new caryophyllene-type sesquiterpenes pestalotiopsins U and V (1 and 2) and three known compounds pestalotiopsin B (7), pestaloporinate B (8), and pestalotiopsin C (9) were isolated by the cultivation of the endophytic fungus Pestalotiopsis lespedezae on solid rice medium, while four additional new caryophyllene pestalotiopsins W-Z (3-6) were obtained when 3.5% NaI was added to the fungal culture medium. The structures of the new compounds were determined by HRESIMS and 1D/2D nuclear magnetic resonance data. Compounds 1-9 were tested for cytotoxicity against the mouse lymphoma cell line L5178Y, but only 6 displayed significant activity with an IC50 value of 2.4 μM.

CYP1A inhibitors: Recent progress, current challenges, and future perspectives

Mammalian cytochrome P450 1A (CYP1A) are key phase I xenobiotic-metabolizing enzymes that play a distinctive role in metabolic activation or metabolic clearance of a variety of procarcinogens, drugs, and endogenous substances. Human CYP1A subfamily contains two members (hCYP1A1 and hCYP1A2), which are known to catalyze the oxidative activation of some environmental procarcinogens into carcinogenic species. Increasing evidence has demonstrated that CYP1A inhibitor therapies are promising strategies for cancer chemoprevention or overcoming CYP1A-associated drug toxicity and resistance. Herein, we reviewed recent advances in the discovery and characterization of hCYP1A inhibitors, from the discovery approaches to structural features and biomedical applications of hCYP1A inhibitors. The inhibition potentials, inhibition modes, and inhibition constants of all reported hCYP1A inhibitors are comprehensively summarized. Meanwhile, the structural features and structure-activity relationships of different classes of hCYP1A1 and hCYP1A2 inhibitors are analyzed and discussed in depth. Furthermore, the major challenges and future directions for this field are presented and highlighted. Collectively, the information and knowledge presented here will strongly facilitate the researchers to discover and develop more efficacious CYP1A inhibitors for specific purposes, such as chemo-preventive agents or as tool molecules in hCYP1A-related fundamental studies.

Screening and Activity Evaluation of Novel BCR-ABL/T315I Tyrosine Kinase Inhibitors

INTRODUCTION

Chronic myeloid leukemia (CML) is a kind of malignant tumor formed by the clonal proliferation of bone marrow hematopoietic stem cells. BCR-ABL fusion protein, found in more than 90% of patients, is a vital target for discovering anti- CML drugs. Up to date, imatinib is the first BCR-ABL tyrosine kinase inhibitor (TKI) approved by the FDA for treating CML. However, the drug resistance problems appeared for many reasons, especially the T135I mutation, a "gatekeeper" of BCR-ABL. Currently, there is no long-term effective and low side effect drug in clinical.

METHODS

This study intends to find novel TKIs targeting BCR-ABL with high inhibitory activity against T315I mutant protein by combining artificial intelligence technology and cell growth curve, cytotoxicity, flow cytometry and Western blot experiments.

RESULTS

The obtained compound was found to kill leukemia cells, which had good inhibitory efficacy in BaF3/T315I cells. Compound no 4 could induce cell cycle arrest, cause autophagy and apoptosis, and inhibit the phosphorylation of BCR-ABL tyrosine kinase, STAT5 and Crkl proteins.

CONCLUSION

The results indicated that the screened compound could be used as a lead compound for further research to discover ideal chronic myeloid leukemia therapeutic drugs.

Exploring the mechanism of the PTP1B inhibitors by molecular dynamics and experimental study

Protein tyrosine phosphatase 1B (PTP1B) has proven to be an attractive target for the treatment of cancer, diabetes and other diseases. Although many PTP1B inhibitors with various scaffolds have been developed, there is still a lack of PTP1B inhibitor with high specificity and acceptable pharmacological properties. Therefore, it is urgent to develop more methods to explore complex action mode of PTP1B and ligands for designing ideal PTP1B modulators. In this work, we developed a potential molecular dynamics (MD) analytic mode to analyze the mechanism of active compounds 6a and 6e against PTP1B from different perspectives, including the stable ability, interactions and binding site of ligand and protein, the binding energy, relative movement between residues and changes in protein internal interactions. The simulated results demonstrated that compound 6a bound more stably to the active pocket of PTP1B than 6e due to its smaller molecular volume (326 Å3), matched electronegativity, and enhanced the positive correlation motion of residues, especially for WPD loop and P loop. Lastly, compound 6a as a competitive inhibitor for PTP1B was verified by enzyme kinetic assay. This work successfully studied the mechanism of compound 6a against PTP1B from various aspects, enriched the analysis of interaction mode between PTP1B and inhibitors. In summary, we hope that this work could provide more theoretical information for designing and developing more novel and ideal PTP1B inhibitors in the future.

Discovery of novel JAK1 inhibitors through combining machine learning, structure-based pharmacophore modeling and bio-evaluation

BACKGROUND

Janus kinase 1 (JAK1) plays a critical role in most cytokine-mediated inflammatory, autoimmune responses and various cancers via the JAK/STAT signaling pathway. Inhibition of JAK1 is therefore an attractive therapeutic strategy for several diseases. Recently, high-performance machine learning techniques have been increasingly applied in virtual screening to develop new kinase inhibitors. Our study aimed to develop a novel layered virtual screening method based on machine learning (ML) and pharmacophore models to identify the potential JAK1 inhibitors.

METHODS

Firstly, we constructed a high-quality dataset comprising 3834 JAK1 inhibitors and 12,230 decoys, followed by establishing a series of classification models based on a combination of three molecular descriptors and six ML algorithms. To further screen potential compounds, we constructed several pharmacophore models based on Hiphop and receptor-ligand algorithms. We then used molecular docking to filter the recognized compounds. Finally, the binding stability and enzyme inhibition activity of the identified compounds were assessed by molecular dynamics (MD) simulations and in vitro enzyme activity tests.

RESULTS

The best performance ML model DNN-ECFP4 and two pharmacophore models Hiphop3 and 6TPF 08 were utilized to screen the ZINC database. A total of 13 potentially active compounds were screened and the MD results demonstrated that all of the above molecules could bind with JAK1 stably in dynamic conditions. Among the shortlisted compounds, the four purchasable compounds demonstrated significant kinase inhibition activity, with Z-10 being the most active (IC50 = 194.9 nM).

CONCLUSION

The current study provides an efficient and accurate integrated model. The hit compounds were promising candidates for the further development of novel JAK1 inhibitors.

Antimicrobial peptides as drugs with double response against Mycobacterium tuberculosis coinfections in lung cancer

Tuberculosis and lung cancer are, in many cases, correlated diseases that can be confused because they have similar symptoms. Many meta-analyses have proven that there is a greater chance of developing lung cancer in patients who have active pulmonary tuberculosis. It is, therefore, important to monitor the patient for a long time after recovery and search for combined therapies that can treat both diseases, as well as face the great problem of drug resistance. Peptides are molecules derived from the breakdown of proteins, and the membranolytic class is already being studied. It has been proposed that these molecules destabilize cellular homeostasis, performing a dual antimicrobial and anticancer function and offering several possibilities of adaptation for adequate delivery and action. In this review, we focus on two important reason for the use of multifunctional peptides or peptides, namely the double activity and no harmful effects on humans. We review some of the main antimicrobial and anti-inflammatory bioactive peptides and highlight four that have anti-tuberculosis and anti-cancer activity, which may contribute to obtaining drugs with this dual functionality.

Therapeutic potential of human serum albumin nanoparticles encapsulated actinonin in murine model of lung adenocarcinoma

Non-small cell lung cancer comprises 85% of the global lung cancer cases. Conventional chemotherapeutics possess certain limitations like systemic toxicity and drug resistance that requires the development of new therapeutic agents for successful treatment of lung cancer. Actinonin, a human peptide deformylase inhibitor, has demonstrated anti-cancerous properties in various leukemias and solid cancer types. However, it has limited therapeutic application because of its low bioavailability and systemic toxicity if administered in free form. This limitation can be overcome by using nano-delivery systems that will increase the therapeutic efficacy of actinonin. In the present study, human serum albumin actinonin nanoparticles were prepared using a desolvation technique and folic acid was conjugated to lysine residues of albumin for effective delivery to the lung. The lung adenocarcinoma model was established 24 weeks after intraperitoneal administration of urethane and chemotherapeutic efficacy of free as well as nanoencapsulated actinonin was evaluated. This study demonstrated anti-proliferative potential of folic acid conjugated human serum albumin nanoparticles encapsulating actinonin. The intraperitoneally administered nanoformulation exhibited sustain release profile of actinonin with longer half-life and mean retention time. The reduced dose frequency resulted in therapeutic efficacy comparable to free drug in vivo in terms of 100% survival and reduced tumor burden along with downregulation of epidermal growth factor receptor, folate receptor α and peptide deformylase expression in lung adenocarcinoma mice model. Therefore, actinonin encapsulated albumin nanoparticles-based therapy holds great potential as an alternative strategy to improve its anti-cancerous activity against lung adenocarcinoma.

Design of novel quinoline derivatives as antibreast cancer using 3D-QSAR, molecular docking and pharmacokinetic investigation

Breast cancer has been one of the most challenging women's cancers and leading cause of mortality for decades. There are several studies being conducted all the time to find a cure for breast cancer. Quinoline derivatives have shown their potential as antitumor agents in breast cancer therapy. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking with aromatase enzyme (Protein Data Bank: 3S7S) studies were performed to suggest the current scenario of quinoline derivatives as antitumor agents and to refine the path of these derivatives to discover and develop new drugs against breast cancer. For developing the 3D-QSAR model, comparative molecular similarity indices analysis (CoMSIA) and comparative molecular field analysis (CoMFA) were included. To attain the high level of predictability, the best CoMSIA model was applied. External validation utilizing a test set has been used in order to validate the predictive capabilities of the built model. According to the findings, electrostatic, hydrophobic and hydrogen bond donor, and acceptor fields had a significant impact on antibreast cancer activity. Thus, we generated a variety of novel effective aromatase inhibitors based on prior findings and we predicted their inhibitory activity using the built model. In addition, absorption, distribution, metabolism, elimination and toxicity properties were employed to explore the effectiveness of new drug candidates.

Atomic level and structural understanding of natural ligands inhibiting Helicobacter pylori peptide deformylase through ligand and receptor based screening, SIFT, molecular dynamics and DFT - a structural computational approach

Helicobacter pylori is a Gram-negative microaerophilic gastric pathogen, responsible for the cause of peptic ulcer around half of the global population. Although several antibiotics and combination therapies have been employed for H. pylori-related gastric ulcer and cancer regiments, identifying potent inhibitors for specific targets of this bacterium will help assessing better treatment periodicity and methods to eradicate H. pylori. Herein, 1,000,000 natural compounds were virtually screened against Helicobacter pylori Peptide deformylase (HpPDF). Pharmacophore hypotheses were created using ligand and receptor-based pharmacophore modeling of GLIDE. Stringent HTVS and IFD docking protocol of GLIDE predicted leads with stable intermolecular bonds and scores. Molecular dynamics simulation of HpPDF was carried out for 100 ns using GROMACS. Hits ZINC00225109 and ZINC44896875 came up with a glide score of -9.967 kcal/mol and -12.114 kcal/mol whereas; reference compound actinonin produced a glide score of -9.730 kcal/mol. Binding energy values of these hits revealed the involvement of significant Van der Waals and Coulomb forces and the deduction of lipophilic forces that portray the deep hydrophobic residues in the S1pocket of H. pylori. The DFT analysis established the electron density-based features of the molecules and observed that the results correlate with intermolecular docking interactions. Analysis of the MD trajectories revealed the crucial residues involved in HpPDF - ligand binding and the conformational changes in the receptor. We have identified and deciphered the crucial features necessary for the potent ligand binding at catalytic site of HpPDF. The resulting ZINC natural compound hits from the study could be further employed for potent drug development.Communicated by Ramaswamy H. Sarma.

Metal utilization in genome-reduced bacteria: Do human mycoplasmas rely on iron?

Mycoplasmas are parasitic bacteria with streamlined genomes and complex nutritional requirements. Although iron is vital for almost all organisms, its utilization by mycoplasmas is controversial. Despite its minimalist nature, mycoplasmas can survive and persist within the host, where iron availability is rigorously restricted through nutritional immunity. In this review, we describe the putative iron-enzymes, transporters, and metalloregulators of four relevant human mycoplasmas. This work brings in light critical differences in the mycoplasma-iron interplay. Mycoplasma penetrans, the species with the largest genome (1.36 Mb), shows a more classic repertoire of iron-related proteins, including different enzymes using iron-sulfur clusters as well as iron storage and transport systems. In contrast, the iron requirement is less apparent in the three species with markedly reduced genomes, Mycoplasma genitalium (0.58 Mb), Mycoplasma hominis (0.67 Mb) and Mycoplasma pneumoniae (0.82 Mb), as they exhibit only a few proteins possibly involved in iron homeostasis. The multiple facets of iron metabolism in mycoplasmas illustrate the remarkable evolutive potential of these minimal organisms when facing nutritional immunity and question the dependence of several human-infecting species for iron. Collectively, our data contribute to better understand the unique biology and infective strategies of these successful pathogens.

Ensembling machine learning models to boost molecular affinity prediction

This study unites six popular machine learning approaches to enhance the prediction of a molecular binding affinity between receptors (large protein molecules) and ligands (small organic molecules). Here we examine a scheme where affinity of ligands is predicted against a single receptor - human thrombin, thus, the models consider ligand features only. However, the suggested approach can be repurposed for other receptors. The methods include Support Vector Machine, Random Forest, CatBoost, feed-forward neural network, graph neural network, and Bidirectional Encoder Representations from Transformers. The first five methods use input features based on physico-chemical properties of molecules, while the last one is based on textual molecular representations. All approaches do not rely on atomic spatial coordinates, avoiding a potential bias from known structures, and are capable of generalizing for compounds with unknown conformations. Within each of the methods, we have trained two models that solve classification and regression tasks. Then, all models are grouped into a pipeline of two subsequent ensembles. The first ensemble aggregates six classification models which vote whether a ligand binds to a receptor or not. If a ligand is classified as active (i.e., binds), the second ensemble predicts its binding affinity in terms of the inhibition constant K_i.

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

Chronic myelogenous leukemia (CML) typically results from a reciprocal translocation between chromosomes 9 and 22 to produce the bcr-abl oncogene that when translated, yields the p210 BCR-ABL protein in more than 90% of all CML patients. This protein has constitutive tyrosine kinase activity that activates numerous downstream pathways that ultimately produces uncontrolled myeloid proliferation. Although the use of the BCR-ABL tyrosine kinase inhibitors (TKIs), such as imatinib, nilotinib, dasatinib, bosutinib, and ponatinib have increased the overall survival of CML patients, their use is limited by drug resistance and severe adverse effects. Therefore, there is the need to develop novel compounds that can overcome these problems that limit the use of these drugs. Therefore, in this study, we sought to find novel compounds using Hypogen and Hiphip pharmacophore models based on the structures of clinically approved BCR-ABL TKIs. We also used optimal pharmacophore models such as three-dimensional queries to screen the ZINC database to search for potential BCR-ABL inhibitors. The hit compounds were further screened using Lipinski’s rule of five, ADMET and molecular docking, and the efficacy of the hit compounds was evaluated. Our in vitro results indicated that compound ZINC21710815 significantly inhibited the proliferation of K562, BaF3/WT, and BaF3/T315I leukemia cells by inducing cell cycle arrest. The compound ZINC21710815 decreased the expression of p-BCR-ABL, STAT5, and Crkl and produced apoptosis and autophagy. Our results suggest that ZINC21710815 may be a potential BCR-ABL inhibitor that should undergo in vivo evaluation.

Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase

Xanthomonas oryzae pv. Oryzae (Xoo) causes bacterial leaf blight (BLB) of rice which results in a huge loss in production. Many chemicals are used to control BLB disease. However, these chemicals are toxic to the environments, animals and human beings. Thus, there is a demand to discover potential and safe natural pesticides to manage BLB disease successfully. Therefore, we screened a library of phytochemicals of different plants having antibacterial activity by targeting Peptide Deformylase (PDF) of Xoo using in silico techniques. A library of 318 phytochemicals was prepared and subjected to rigid and flexible molecular docking against PDF followed by molecular dynamics simulation and free energy analysis of protein-ligand complexes. The results of virtual screening showed that 14 compounds from different plants have good binding energy as compare to reference molecule (3 R)-2,3-dihydro[1,3] thiazolo [3,2 a]benzimidazol-3-ol) (-7.7 kcal mol^-1). Out of 14 hit compounds, eight compounds that were selected based on binding energy were analyzed by Molecular dynamic (MD) simulation. Analysis of MD simulation revealed that eight compounds namely; Bisdemethoxycurcumin, Rosmarinic acid, Piperanine, Dihydropiperlonguminine, Piperdardine, Dihydrocurcumin and Lonhumosides B achieved good stability during the 80 ns MD simulation at 300 K in term of the RMSD. Further, we calculated RMSF, RG, SASA, and interaction energy after 40 ns due to showing the stability of complexes. From our results, we conclude that these natural compounds could inhibit Xoo by targeting PDF receptor and can be used as potential bactericidal candidates against BLB disease of rice against Xoo and other bacteria. Communicated by Ramaswamy H. Sarma.

Identification of the potential dual inhibitor of protein tyrosine phosphatase sigma and leukocyte common antigen-related phosphatase by virtual screen, molecular dynamic simulations and post-analysis

Owing to their inhibitory role in regulating oligodendrocyte differentiation and apoptosis, protein tyrosine phosphatase sigma (PTPσ) and leukocyte common antigen-related phosphatase (LAR) play a crucial potential role in treating spinal cord injury (SCI) disease. In this research, the computer aided drug design (CADD) methods were applied to discover the potential dual-target drug involving virtual screen, molecular docking and molecular dynamic simulation. Initially, the top 20 compounds with higher docking score than the positive controls (ZINC13749892, ZINC14516161) were virtually screened out from NCI and ZINC databases, and then were submitted in ADMET to predict their drug properties. Among these potential compounds, ZINC72417086 showed a higher docking score and satisfied Lipinski's rule of five. In addition, the post-analysis demonstrated that when ZINC72417086 bound to PTPσ and LAR, it could stable proteins conformations and destroy the residues interactions between P-loop and other loop regions in active pocket. Meanwhile, residue ARG1595 and ARG1528 could play a crucial role in in the inhibition of PTPσ and LAR, respectively. This research offered a novel approach for rapid discovery of dual-target leads compounds to treat SCI.Communicated by Ramaswamy H. Sarma.

Antibacterial Effect and Mode of Action of Flavonoids From Licorice Against Methicillin-Resistant Staphylococcus aureus

Staphylococcus aureus is a bacterial pathogen that causes food poisoning, various infections, and sepsis. Effective strategies and new drugs are needed to control S. aureus associated infections due to the emergence and rapid dissemination of antibiotic resistance. In the present study, the antibacterial activity, potential mode of action, and applications of flavonoids from licorice were investigated. Here, we showed that glabrol, licochalcone A, licochalcone C, and licochalcone E displayed high efficiency against methicillin-resistant Staphylococcus aureus (MRSA). Glabrol, licochalcone A, licochalcone C, and licochalcone E exhibited low cytotoxicity without hemolytic activity based on safety evaluation. Glabrol displayed rapid bactericidal activity with low levels of resistance development in vitro. Meanwhile, glabrol rapidly increased bacterial membrane permeability and dissipated the proton move force. Furthermore, we found that peptidoglycan, phosphatidylglycerol, and cardiolipin inhibited the antibacterial activity of glabrol. Molecular docking showed that glabrol binds to phosphatidylglycerol and cardiolipin through the formation of hydrogen bonds. Lastly, glabrol showed antibacterial activity against MRSA in both in vivo and in vitro models. Altogether, these results suggest that glabrol is a promising lead compound for the design of membrane-active antibacterial agents against MRSA and can be used as a disinfectant candidate as well.

In Silico Study to Assess Antibacterial Activity from Cladophora Sp. on Peptide Deformylase: Molecular Docking Approach

Increasing antibiotic-resistant pathogenic bacteria is a severe problem in the world. Therefore, there is a need to identify new drugs from natural products and also new drug targets. Cladophora sp. is a marine organism which is known to have bioactive compounds and a potential antibacterial. On the other hand, Peptide Deformylase (PDf) may prove to be a novel drug target since it is crucial for native peptide functioning in most pathogenic bacteria. This study screens for PDf inhibition activity of compounds from Cladophora sp. using molecular docking approach and screening the binding affinity of bioactive compounds against the peptide receptor PDf using Pyrex Autodock Vina software. Docking results were stored and visualized using Biovia Discovery Studio and PyMOL ligand. Ligands were obtained from previous literature in PubChem, and receptor peptide PDf from pathogenic bacteria: Pseudomonas aeruginosa (PDB ID:1N5N), Escherichia coli (PDB ID:1BSK), Enterococcus faecium (PDB ID:3G6N) and Staphylococcus aureus (PDB ID:1LQW), was obtained from the peptide data bank. The results of this screening show with ligand the highest binding affinity against PDf of P. aeruginosa, E. coli, E. faecium, and S. aureus is stearic acid (-5.9 kcal/mol), eicosapentaenoic acid (-6.6 kcal/mol), stearic acid (-5.8 kcal/mol), and stearic acid (-6.2 kcal/mol) respectively. The binding of natural compounds from Cladophora sp. with PDf models may provide a new drug with a different drug target for antibacterial potential.

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Deregulation of Cdk5 is a hallmark in neurodegenerative diseases and its complex with p25 forms Cdk5/p25, thereby causes severe neuropathological insults. Cdk5/p25 abnormally phosphorylates tau protein, and induces tau-associated neurofibrillary tangles in neurological disorders. Therefore, the pharmacological inhibition of Cdk5/p25 alleviates tau-associated neurological disorders. Herein, computational simulations probed two candidate inhibitors of Cdk5/p25. Structure-based pharmacophore investigated the essential complementary chemical features of ATP-binding site of Cdk5 in complex with roscovitine. Resultant pharmacophore harbored polar interactions with Cys83 and Asp86 residues and non-polar interactions with Ile10, Phe80, and Lys133 residues of Cdk5. The chemical space of selected pharmacophore was comprised of two hydrogen bond donors, one hydrogen bond acceptor, and three hydrophobic features. Decoy test validation of pharmacophore obtained highest Guner-Henry score (0.88) and enrichment factor score (7.23). The screening of natural product drug-like databases by validated pharmacophore retrieved 1126 compounds as candidate inhibitors of Cdk5/p25. The docking of candidate inhibitors filtered 10 molecules with docking score >80.00 and established polar and non-polar interactions with the ATP-binding site residues of Cdk5/p25. Finally, molecular dynamics simulation and binding free energy analyses identified two candidate inhibitors of Cdk5/p25. During 30 ns simulation, the candidate inhibitors established <3.0 Å root mean square deviation and stable hydrogen bond interactions with the ATP-binding site residues of Cdk5/p25. The final candidate inhibitors obtained lowest binding free energies of -122.18 kJ/mol and - 117.26 kJ/mol with Cdk5/p25. Overall, we recommend two natural product candidate inhibitors to target the pharmacological inhibition of Cdk5/p25 in tau-associated neurological disorders.