ClpP Peptidase as a Plausible Target for the Discovery of Novel Antibiotics.

Antimicrobial resistance (AMR) to currently available antibiotics/drugs is a global threat. It is desirable to develop new drugs that work through a novel target(s) to avoid drug resistance. This review discusses the potential of the caseinolytic protease P (ClpP) peptidase complex as a novel target for finding novel antibiotics, emphasising the ClpP's structure and function. ClpP contributes to the survival of bacteria via its ability to destroy misfolded or aggregated proteins. In consequence, its inhibition may lead to microbial death. Drugs inhibiting ClpP activity are currently being tested, but no drug against this target has been approved yet. It was demonstrated that Nblocked dipeptides are essential for activating ClpP's proteolytic activity. Hence, compounds mimicking these dipeptides could act as inhibitors of the formation of an active ClpP complex. Drugs, including Bortezomib, Cisplatin, Cefmetazole, and Ixazomib, inhibit ClpP activation. However, they were not approved as drugs against the target because of their high toxicity, likely due to the presence of strong electrophiles in their warheads. The modifications of these warheads could be a good strategy to reduce the toxicity of these molecules. For instance, a boronate warhead was replaced by a chloromethyl ketone, and this new molecule was shown to exhibit selectivity for prokaryotic ClpP. A better understanding of the structure and function of the ClpP complex would benefit the search for compounds mimicking N-blocked dipeptides that would inhibit ClpP complex activity and cause bacterial death.

Deciphering insights into the binding mechanism and plasticity of Telacebec with M. tuberculosis cytochrome bcc-aa3 supercomplex through an unbiased molecular dynamics simulation, free-energy analysis, and DFT study.

The cytochrome bcc-aa3 supercomplex, a key component in the electron transport chain pathway involved in bacterial energy production and homeostasis, is a clinically validated target for tuberculosis (TB), leading to Telacebec (Q203). Telacebec is a potent candidate drug under Phase II clinical development for the treatment of drug-sensitive and drug-resistant TB. Recently, the cryo-electron microscopy structure of this supercomplex from Mycobacterium tuberculosis (Mtb) complexed with Q203 was resolved at 6.9 Å resolution (PDB ID: 7E1W). To understand the binding site (QP site) flexibility and Q203's stability at the QP site of the Mtb cytochrome bcc complex, we conducted molecular dynamics (MD) simulation and free energy analysis on this complex in an explicit hydrated lipid bilayer environment for 500 ns. Through this study, the persistence of a range of direct and indirect interactions was observed over the course of the simulation. The significance of the interactions with His375, Tyr161, Ala178, Ala179, Ile183, His355, Leu356, and Thr313 is underlined. Electrostatic energy was the primary source of the net binding free energy, regardless of the important interacting residues. The overall binding free energy for Q203 was -112.84 ± 7.73 kcal/mol, of which the electrostatic and lipophilic energy contributions were -116.31 ± 1.14 and -21.32 ± 2.35 kcal/mol, respectively. Meanwhile, DFT calculations were utilized to elucidate Q203's molecular properties. Overall, this study deciphers key insights into the cytochrome bcc-aa3 supercomplex with Q203 on the ground of molecular mechanics and quantum mechanics that may facilitate structure-based drug design and optimization for the discovery of the next-generation antitubercular drug(s).Communicated by Ramaswamy H. Sarma.

Rosmarinic acid and its derivative's duel as antitubercular agents: insights from computational prediction to functional response in vitro.

Tuberculosis is one of the most dreadful infectious diseases, afflicting global populations with anguish. With the emergence of multi-drug resistant strains of mycobacteria, the imperative for new anti-tuberculosis drugs has grown exponentially. Thus, the current study delves into evaluating the impact of Perovskia abrotanoides and its active metabolites-namely, rosmarinic acid and its derivatives-against strains of Mycobacterium tuberculosis (Mtb). Through the use of the CRI assay, the antimycobacterial potential of the high-altitude medicinal plant P. abrotanoides was gauged, while docking and molecular dynamics simulations unveiled plausible targets. Of these, the peak antimycobacterial effectiveness was observed in the P. abrotanoides ethyl acetate extract with 125 µg/mL as minimum inhibitory concentration against various strains of M. tuberculosis, encompassing H37Rv and strains resistant to multiple drugs. Following bioassay-guided fractionation and isolation, rosmarinic acid and rosmarinic acid methyl ester emerged as potent molecules against H37Rv and multidrug-resistant M. tuberculosis strains; minimum inhibitory concentration ranging from 15 to 32 µg/mL. Additionally, out of 22 targets explored, Mtb lipoamide dehydrogenase (PDB: 3II4) and Rv2623 (PDB: 3CIS) were forecasted as potential Mtb targets for rosmarinic acid and rosmarinic acid methyl ester, respectively, a supposition further affirmed by molecular simulations (100 ns). The stability of both complexes throughout the simulation was measured by protein backbone root-mean-square deviation, substantiating their roles as respective targets for antimycobacterial activities.Communicated by Ramaswamy H. Sarma.

The Potential of Mur Enzymes as Targets for Antimicrobial Drug Discovery.

The extensive development in the strains of resistant bacteria is a potential hazard to public health worldwide. This necessitates the development of newer agents with the antibacterial property having new mechanisms of action. Mur enzymes catalyze the steps related to the biosynthesis of peptidoglycan, which constitutes a major part of the cell wall in bacteria. Peptidoglycan increases the stiffness of the cell wall, helping it to survive in unfavorable conditions. Therefore, the inhibition of Mur enzymes may lead to novel antibacterial agents that may help in controlling or overcoming bacterial resistance. Mur enzymes are classified into MurA, MurB, MurC, MurD, MurE, and MurF. Until-date, multiple inhibitors are reported for each class of the Mur enzymes. In this review, we have summarized the development of Mur enzyme inhibitors as antibacterial agents in the last few decades.

Identification and validation of novel non-nucleoside class of molecules inhibiting the dengue virus replication.

There is currently no drug available to treat mosquito-borne dengue. The C-terminal RNA-dependent RNA polymerase (RdRp) domain in the non-structural type 5 (NS5) protein of the dengue virus (DENV) is essential for viral RNA synthesis and replication, and therefore, it is an attractive target for the anti-dengue drug development. We report herein the discovery and validation of two novel non-nucleoside classes of small molecules as DENV RdRp inhibitors. Firstly, using the refined X-ray structure of the DENV NS5 RdRp domain (PDB-ID: 4V0R), we conducted docking, binding free-energy studies, and short-scale molecular dynamics simulation to investigate the binding sites of known small molecules that led to the optimized protein-ligand complex. Subsequently, protein structure-based screening of a commercial database (∼500,000 synthetic compounds), pre-filtered for the drug-likeness, led to the top-ranked 171 molecules, which was then subjected to structural diversity analysis and clustering. This process led to six structurally distinct and best-scored compounds that were procured from the commercial vendor, and then subjected to the in vitro testing in the MTT and dengue infection assays. It revealed two unique and structurally unique compounds, KKR-D-02 and KKR-D-03, exhibiting 84 and 81% reductions, respectively, in DENV copy number in repeated assays in comparison to the virus-infected cell controls. These active compounds represent novel scaffolds for further structure-based discovery of novel candidate molecules for the intervention of dengue.Communicated by Ramaswamy H. Sarma.

The Abundant Phytocannabinoids in Rheumatoid Arthritis: Therapeutic Targets and Molecular Processes Identified Using Integrated Bioinformatics and Network Pharmacology.

The endocannabinoid system consists of several phytocannabinoids, cannabinoid receptors, and enzymes that aid in numerous steps necessary to manifest any pharmacological activity. It is well known that the endocannabinoid system inhibits the pathogenesis of the inflammatory and autoimmune disease rheumatoid arthritis (RA). To the best of our knowledge, no research has been done that explains the network-pharmacology-based anti-rheumatic processes by focusing on the endocannabinoid system. Therefore, the purpose of this study is to further our understanding of the signaling pathways, associated proteins, and genes underlying RA based on the abundant natural endocannabinoids. The knowledge on how the phytocannabinoids in Cannabis sativa affect the endocannabinoid system was gathered from the literature. SwissTarget prediction and BindingDB databases were used to anticipate the targets for the phytocannabinoids. The genes related to RA were retrieved from the DisGeNET and GeneCards databases. Protein-protein interactions (high confidence > 0.7) were carried out with the aid of the string web server and displayed using Cytoscape. The Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis was used to perform enrichment analyses on the endocannabinoid-RA common targets. ShinyGO 0.76 was used to predict the biological processes listed in the Gene Ontology (GO) classification system. The binding affinity between the ligand and the receptors was precisely understood using molecular docking, induced-fit docking, and a molecular dynamics simulation. The network pharmacology analyses predicted that processes like response to oxygen-containing compounds and peptodyl-amino acid modification are related to the potential mechanisms of treatment for RA. These biological actions are coordinated by cancer, neuroactive ligand-receptor interaction, lipids and atherosclerosis, the calcium signaling pathway, and the Rap1 signaling pathway. According to the results of molecular docking, in the context of RA, phytocannabinoids may bind to important target proteins such PIK3CA, AKT1, MAPK9, PRKCD, BRAF, IGF1R, and NOS3. This entire study predicted the phytocannabinoids' systemic biological characteristics. Future experimental research is needed, however, to confirm the results so far.

Identification of 5-(3-(methylsulfonyl)phenyl)-3-(4-(methylsulfonyl)phenyl)-3H-imidazo[4,5-b]pyridine as novel orally bioavailable and metabolically stable antimalarial compound for further exploration.

Malaria continues to be a significant public health problem threatened by the emergence and spread of resistance to artemisinin-based combination therapies and marked half a million deaths in 2016. A new imidazopyridine chemotype has been envisaged through scaffold-hopping approach combined with docking studies for putative-binding interactions with Plasmodium falciparum phosphatidylinositol-4-kinase (PfPI4K) target. The docking results steered to the synthesis of compound 1 [5-(3-(methylsulfonyl)phenyl)-3-(4-(methylsulfonyl)phenyl)-3H-imidazo[4,5-b]pyridine] followed by the in vitro screening for antiplasmodial activity and ADME-PK studies. Combined with potent antimalarial activity of compound 1 (Pf3D7 IC50  = 29 nM) with meager in vitro intrinsic clearance, moderate plasma-protein binding, and acceptable permeability, compound 1 displayed sustained exposure and high oral bioavailability in mice and can thus have the potential as next generation PI4K inhibitor for in vivo studies.

Emerging Roles and Potential Applications of Non-Coding RNAs in Cervical Cancer.

Cervical cancer (CC) is a preventable disease using proven interventions, specifically prophylactic vaccination, pervasive disease screening, and treatment, but it is still the most frequently diagnosed cancer in women worldwide. Patients with advanced or metastatic CC have a very dismal prognosis and current therapeutic options are very limited. Therefore, understanding the mechanism of metastasis and discovering new therapeutic targets are crucial. New sequencing tools have given a full visualization of the human transcriptome's composition. Non-coding RNAs (NcRNAs) perform various functions in transcriptional, translational, and post-translational processes through their interactions with proteins, RNA, and even DNA. It has been suggested that ncRNAs act as key regulators of a variety of biological processes, with their expression being tightly controlled under physiological settings. In recent years, and notably in the past decade, significant effort has been made to examine the role of ncRNAs in a variety of human diseases, including cancer. Therefore, shedding light on the functions of ncRNA will aid in our better understanding of CC. In this review, we summarize the emerging roles of ncRNAs in progression, metastasis, therapeutics, chemo-resistance, human papillomavirus (HPV) regulation, metabolic reprogramming, diagnosis, and as a prognostic biomarker of CC. We also discussed the role of ncRNA in the tumor microenvironment and tumor immunology, including cancer stem cells (CSCs) in CC. We also address contemporary technologies such as antisense oligonucleotides, CRISPR-Cas9, and exosomes, as well as their potential applications in targeting ncRNAs to manage CC.

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic mycobacteria have been a global threat urging the need of new drug discovery and development. However, considering the fact that the new drug discovery and development is commonly lengthy and costly processes, strategic use of the cutting-edge machine learning (ML) algorithms may be very supportive in reducing both the cost and time involved. Considering the urgency of new drugs for TB, herein, we have attempted to develop predictive ML algorithms-based models useful in the selection of novel potential small molecules for subsequent in vitro validation. For this purpose, we used the GlaxoSmithKline (GSK) TCAMS TB dataset comprising a total of 776 hits that were made publicly available to the wider scientific community through the ChEMBL Neglected Tropical Diseases (ChEMBL-NTD) database. After exploring the different ML classifiers, viz. decision trees (DT), support vector machine (SVM), random forest (RF), Bernoulli Naive Bayes (BNB), K-nearest neighbors (k-NN), and linear logistic regression (LLR), and ensemble learning models (bagging and Adaboost) for training the model using the GSK dataset, we concluded with three best models, viz. Adaboost decision tree (ABDT), RF classifier, and k-NN models that gave the top prediction results for both the training and test sets. However, during the prediction of the external set of known anti-tubercular compounds/drugs, it was realized that each of these models had some limitations. The ABDT model correctly predicted 22 molecules as actives, while both the RF and k-NN models predicted 18 molecules correctly as actives; a number of molecules were predicted as actives by two of these models, while the third model predicted these compounds as inactives. Therefore, we concluded that while deciding the anti-tubercular potential of a new molecule, one should rely on the use of consensus predictions using these three models; it may lessen the attrition rate during the in vitro validation. We believe that this study may assist the wider anti-tuberculosis research community by providing a platform for predicting small molecules with subsequent validation for drug discovery and development.

Structural basis for the binding of a selective inverse agonist AF64394 with the human G-protein coupled receptor 3 (GPR3).

The orphan class A G-protein coupled receptor 3 (GPR3) is highly expressed in brain and linked with various neuronal functions, and therefore, expected to play a vital role in the progression of Alzheimer's disease. In view of the lack of its experimental structure, we describe herein the three-dimensional structure and conformational dynamics of GPR3 complexed with the inverse agonist AF64394. The GPR3 model was predicted using the Iterative Threading ASSEmbly Refinement (I-TASSER) method. The Induced Fit Docking predicted two unique poses, Pose 1 and Pose 2, for AF64394, and then, molecular dynamics (MD) simulations followed by binding free-energy calculation revealed the Pose 1 as a very stable pose with the least fluctuation during the MD simulation while the Pose 2 underwent a significant fluctuation. The [1,2,4]triazolo[1,5-a]pyrimidine core was engaged in multiple hydrogen bonds (H-bonds), such as a water-mediated H-bond between the triazole nitrogen and T31, two direct H-bonds between the protonated triazole-ring nitrogen and V186 and T279, a direct H-bond between the secondary amine and V187. The phenyl substituent of AF64394 exhibited aromatic π-π stacking interactions with F97, F101, W43 and Y280. AF64394 showed a direct interaction with E28 and polar interactions with H96, T31 and T279. Throughout the MD simulation, the toggle switch residues, F120 and W260, remained in close contact, indicating that the GPR3 conformation represented an inactive state. The 4-(3-chloro-5-isopropoxyphenethyl) group resided near to the toggle switch residues. The insights gained here are expected to be useful in the structure-based design of new ligands targeting GPR3 modulation. Communicated by Ramaswamy H. Sarma.

Structure-based discovery of (S)-2-amino-6-(4-fluorobenzyl)-5,6,11,11a-tetrahydro-1H-imidazo[1',5':1,6]pyrido[3,4-b]indole-1,3(2H)-dione as low nanomolar, orally bioavailable autotaxin inhibitor.

Inhibition of extracellular secreted enzyme autotaxin (ATX) represents an attractive strategy for the development of new therapeutics to treat various diseases and a few inhibitors entered in clinical trials. We herein describe structure-based design, synthesis, and biological investigations revealing a potent and orally bioavailable ATX inhibitor 1. During the molecular docking and scoring studies within the ATX enzyme (PDB-ID: 4ZGA), the S-enantiomer (Gscore = -13.168 kcal/mol) of the bound ligand PAT-494 scored better than its R-enantiomer (Gscore = -9.562 kcal/mol) which corroborated with the reported observation and analysis of the results suggested the scope of manipulation of the hydantoin substructure in PAT-494. Accordingly, the docking-based screening of a focused library of 10 compounds resulted in compound 1 as a better candidate for pharmacological studies. Compound 1 was synthesized from L-tryptophan and evaluated against ATX enzymatic activities with an IC50 of 7.6 and 24.6 nM in biochemical and functional assays, respectively. Further, ADME-PK studies divulged compound 1 as non-cytotoxic (19.02% cell growth inhibition at 20 µM in human embryonic kidney cells), metabolically stable against human liver microsomes (CLint  = 15.6 µl/min/mg; T1/2  = 113.2 min) with solubility of 4.82 µM and orally bioavailable, demonstrating its potential to be used for in vivo experiments.

Machine learning-enabled predictive modeling to precisely identify the antimicrobial peptides.

The ubiquitous antimicrobial peptides (AMPs), with a broad range of antimicrobial activities, represent a great promise for combating the multi-drug resistant infections. In this study, using a large and diverse set of AMPs (2638) and non-AMPs (3700), we have explored a variety of machine learning classifiers to build in silico models for AMP prediction, including Random Forest (RF), k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Decision Tree (DT), Naive Bayes (NB), Quadratic Discriminant Analysis (QDA), and ensemble learning. Among the various models generated, the RF classifier-based model top-performed in both the internal [Accuracy: 91.40%, Precision: 89.37%, Sensitivity: 90.05%, and Specificity: 92.36%] and external validations [Accuracy: 89.43%, Precision: 88.92%, Sensitivity: 85.21%, and Specificity: 92.43%]. In addition, the RF classifier-based model correctly predicted the known AMPs and non-AMPs; those kept aside as an additional external validation set. The performance assessment revealed three features viz. ChargeD2001, PAAC12 (pseudo amino acid composition), and polarity T13 that are likely to play vital roles in the antimicrobial activity of AMPs. The developed RF-based classification model may further be useful in the design and prediction of the novel potential AMPs.

Puupehenone, a Marine-Sponge-Derived Sesquiterpene Quinone, Potentiates the Antifungal Drug Caspofungin by Disrupting Hsp90 Activity and the Cell Wall Integrity Pathway.

The cell wall-targeting echinocandin antifungals, although potent and well tolerated, are inadequate in treating fungal infections due to their narrow spectrum of activity and their propensity to induce pathogen resistance. A promising strategy to overcome these drawbacks is to combine echinocandins with a molecule that improves their activity and also disrupts drug adaptation pathways. In this study, we show that puupehenone (PUUP), a marine-sponge-derived sesquiterpene quinone, potentiates the echinocandin drug caspofungin (CAS) in CAS-resistant fungal pathogens. We have conducted RNA sequencing (RNA-seq) analysis, followed by genetic and molecular studies, to elucidate PUUP's CAS-potentiating mechanism. We found that the combination of CAS and PUUP blocked the induction of CAS-responding genes required for the adaptation to cell wall stress through the cell wall integrity (CWI) pathway. Further analysis showed that PUUP inhibited the activation of Slt2 (Mpk1), the terminal mitogen-activated protein (MAP) kinase in this pathway. We also found that PUUP induced heat shock response genes and inhibited the activity of heat shock protein 90 (Hsp90). Molecular docking studies predicted that PUUP occupies a binding site on Hsp90 required for the interaction between Hsp90 and its cochaperone Cdc37. Thus, we show that PUUP potentiates CAS activity by a previously undescribed mechanism which involves a disruption of Hsp90 activity and the CWI pathway. Given the requirement of the Hsp90-Cdc37 complex in Slt2 activation, we suggest that inhibitors of this complex would disrupt the CWI pathway and synergize with echinocandins. Therefore, the identification of PUUP's CAS-potentiating mechanism has important implications in the development of new antifungal combination therapies.IMPORTANCE Fungal infections cause more fatalities worldwide each year than malaria or tuberculosis. Currently available antifungal drugs have various limitations, including host toxicity, narrow spectrum of activity, and pathogen resistance. Combining these drugs with small molecules that can overcome these limitations is a useful strategy for extending their clinical use. We have investigated the molecular mechanism by which a marine-derived compound potentiates the activity of the antifungal echinocandin caspofungin. Our findings revealed a mechanism, different from previously reported caspofungin potentiators, in which potentiation is achieved by the disruption of Hsp90 activity and signaling through the cell wall integrity pathway, processes that play important roles in the adaptation to caspofungin in fungal pathogens. Given the importance of stress adaptation in the development of echinocandin resistance, this work will serve as a starting point in the development of new combination therapies that will likely be more effective and less prone to pathogen resistance.

Negative allosteric modulators of cannabinoid receptor 2: protein modeling, binding site identification and molecular dynamics simulations in the presence of an orthosteric agonist.

Selective activation of the cannabinoid receptor subtype 2 (CB2) shows promise for treating pain, inflammation, multiple sclerosis, cancer, ischemic/reperfusion injury and osteoporosis. Target selectivity and off-target side effects are two major limiting factors for orthosteric ligands, and therefore, the search for allosteric modulators (AMs) is a widely used drug discovery approach. To date, only a limited number of negative CB2 AMs have been identified, possessing only micromolar activity at best, and the CB2 receptor's allosteric site(s) are not well characterized. Herein, we used computational approaches including receptor modeling, site mapping, docking, molecular dynamics (MD) simulations and binding free energy calculations to predict, characterize and validate allosteric sites within the complex of the CB2 receptor with bound orthosteric agonist CP55,940. After docking of known negative CB2 allosteric modulators (NAMs), dihydro-gambogic acid (DHGA) and trans-ß-caryophyllene (TBC) (note that TBC also shows agonist activity), at the predicted allosteric sites, the best total complex with CB2, CP55,940 and NAM was embedded into a hydrated lipid bilayer and subjected to a 200 ns MD simulation. The presence of an AM affected the CB2-CP55,940 complex, altering the relative positioning of the toggle switch residues and promoting a strong π-π interaction between Phe1173.36 and Trp2586.48. Binding of either TBC or DHGA to a putative allosteric pocket directly adjacent to the orthosteric ligand reduced the binding free energy of CP55,940, which is consistent with the expected effect of a negative AM. The identified allosteric sites present immense scope for the discovery of novel classes of CB2 AMs.

A systematic computational analysis of human matrix metalloproteinase 13 (MMP-13) crystal structures and structure-based identification of prospective drug candidates as MMP-13 inhibitors repurposable for osteoarthritis.

Osteoarthritis (OA) is the most common form of arthritis with no available disease-modifying treatments, and is a major cause of disability. Matrix metalloproteinase 13 (MMP-13) is vital for OA progression and thus, inhibition of MMP-13 is an effective strategy to treat OA. Since the past few decades, drug repurposing has gained substantial popularity worldwide as a time- and cost-effective approach to find new indications for the existing drugs. Therefore, more than 40 X-ray co-crystal structures of the human MMP-13 with bound inhibitors are investigated to gain the structural insights such as conserved direct interactions with binding site residues, namely Ala-238, Thr-245 and Thr-247. Afterwards, enrichment study using active and decoy set of ligands revealed three MMP-13 structures (PDB-IDs: 1XUC, 3WV1 and 5BPA) with optimal enrichment performance. Docking-based screening of existing drugs against the three crystal structures followed by binding free-energy calculation suggested drugs namely eltrombopag, cilostazol and domperidone as potential MMP-13 inhibitors that need further experimental validation. These insights may serve as a potential starting point of further experimental validation and structure-based drug design/repurposing of MMP-13 inhibitors for the treatment of OA. Abbreviations2Dtwo-dimensional3Dthree-dimensionalFDAFood and Drug AdministrationMM-GBSAMolecular Mechanics Generalized Born Surface AreaMMPsmatrix metalloproteinasesMMP-13matrix metalloproteinase 13NMRnuclear magnetic resonanceOAosteoarthritisPDBProtein Data BankPDB-IDProtein Data Bank IDPLIPprotein-ligand interaction profilerROCreceiver operating characteristic,RMSDroot mean square deviationCommunicated by Ramaswamy H. Sarma.

Emerging opportunities of exploiting mycobacterial electron transport chain pathway for drug-resistant tuberculosis drug discovery.

Introduction: Tuberculosis (TB) is a leading infectious disease worldwide whose chemotherapy is challenged by the continued rise of drug resistance. This epidemic urges the need to discover anti-TB drugs with novel modes of action.Areas covered: The mycobacterial electron transport chain (ETC) pathway represents a hub of anti-TB drug targets. Herein, the authors highlight the various targets within the mycobacterial ETC and highlight some of the promising ETC-targeted drugs and clinical candidates that have been discovered or repurposed. Furthermore, recent breakthroughs in the availability of X-ray and/or cryo-EM structures of some targets are discussed, and various opportunities of exploiting these structures for the discovery of new anti-TB drugs are emphasized.Expert opinion: The drug discovery efforts targeting the ETC pathway have led to the FDA approval of bedaquiline, a FOF1-ATP synthase inhibitor, and the discovery of Q203, a clinical candidate drug targeting the mycobacterial cytochrome bcc-aa3 supercomplex. Moreover, clofazimine, a proposed prodrug competing with menaquinone for its reduction by mycobacterial NADH dehydrogenase 2, has been repurposed for TB treatment. Recently available structures of the mycobacterial ATP synthase C9 rotary ring and the cytochrome bcc-aa3 supercomplex represent further opportunities for the structure-based drug design (SBDD) of the next-generation of inhibitors against Mycobacterium tuberculosis.

Structure investigation, enrichment analysis and structure-based repurposing of FDA-approved drugs as inhibitors of BET-BRD4.

We report herein detailed structural insights into the ligand recognition modes guiding bromodomain selectivity, enrichment analysis and docking-based database screening for the identification of the FDA-approved drugs that have potential to be the human BRD4 inhibitors. Analysis of multiple X-ray structures prevailed that the lysine-recognition sites are highly conserved, and apparently, the dynamic ZA loop guides the specific ligand-recognition. The protein-ligand interaction profiling revealed that both BRD2 and BRD4 shared hydrophobic interaction of bound ligands with PRO-98/PRO-82, PHE-99/PHE-83, LEU-108/LEU-92 and direct H-bonding with ASN-156/ASN-140 (BRD2/BRD4), while on the other hand the water-mediated H-bonding of bound ligands with PRO-82, GLN-85, PRO-86, VAL-87, ASP-88, LEU-92, TYR-97 and MET-132, and aromatic π-π stacking with TRP-81 prevailed as unique interaction in BRD4, and were not observed in BRD2. Subsequently, through ROC curve analysis, the best enrichment was found with PDB-ID 4QZS of BRD4 structures. Finally, through docking-based database screening study, we found that several drugs have better binding affinity than the control candidate lead (+)-JQ1 (Binding affinity = -7.9 kcal/mol), a well-known BRD4 inhibitor. Among the top-ranked drugs, azelastine, a selective histamine H1 receptor antagonist, showed the best binding affinity of -9.3 kcal/mol and showed interactions with several key residues of the acetyl lysine binding pocket. Azelastine may serve as a promising template for further medicinal chemistry. These insights may serve as basis for structure-based drug design, drug repurposing and the discovery of novel BRD4 inhibitors. Communicated by Ramaswamy H. Sarma.

Structure-Based Identification of Potent Natural Product Chemotypes as Cannabinoid Receptor 1 Inverse Agonists.

Natural products are an abundant source of potential drugs, and their diversity makes them a rich and viable prospective source of bioactive cannabinoid ligands. Cannabinoid receptor 1 (CB1) antagonists are clinically established and well documented as potential therapeutics for treating obesity, obesity-related cardiometabolic disorders, pain, and drug/substance abuse, but their associated CNS-mediated adverse effects hinder the development of potential new drugs and no such drug is currently on the market. This limitation amplifies the need for new agents with reduced or no CNS-mediated side effects. We are interested in the discovery of new natural product chemotypes as CB1 antagonists, which may serve as good starting points for further optimization towards the development of CB1 therapeutics. In search of new chemotypes as CB1 antagonists, we screened the in silico purchasable natural products subset of the ZINC12 database against our reported CB1 receptor model using the structure-based virtual screening (SBVS) approach. A total of 18 out of 192 top-scoring virtual hits, selected based on structural diversity and key protein⁻ligand interactions, were purchased and subjected to in vitro screening in competitive radioligand binding assays. The in vitro screening yielded seven compounds exhibiting >50% displacement at 10 µM concentration, and further binding affinity (Ki and IC50) and functional data revealed compound 16 as a potent and selective CB1 inverse agonist (Ki = 121 nM and EC50 = 128 nM) while three other compounds-2, 12, and 18-were potent but nonselective CB1 ligands with low micromolar binding affinity (Ki). In order to explore the structure⁻activity relationship for compound 16, we further purchased compounds with >80% similarity to compound 16, screened them for CB1 and CB2 activities, and found two potent compounds with sub-micromolar activities. Most importantly, these bioactive compounds represent structurally new natural product chemotypes in the area of cannabinoid research and could be considered for further structural optimization as CB1 ligands.

Agonists of the γ-aminobutyric acid type B (GABAB) receptor derived from ß-hydroxy and ß-amino difluoromethyl ketones.

ß-Hydroxy difluoromethyl ketones represent the newest class of agonists of the GABA-B receptor, and they are structurally distinct from all other known agonists at this receptor because they do not display the carboxylic acid or amino group of γ-aminobutyric acid (GABA). In this report, the design, synthesis, and biological evaluation of additional analogues of ß-hydroxy difluoromethyl ketones characterized the critical nature of the substituted aromatic group on the lead compound. The importance of these new data is interpreted by docking studies using the X-ray structure of the GABA-B receptor. Moreover, we also report that the synthesis and biological evaluation of ß-amino difluoromethyl ketones provided the most potent compound across these two series.

Antimalarial naphthoquinones. Synthesis via click chemistry, in vitro activity, docking to PfDHODH and SAR of lapachol-based compounds.

Lapachol is an abundant prenyl naphthoquinone occurring in Brazilian Bignoniaceae that was clinically used, in former times, as an antimalarial drug, despite its moderate effect. Aiming to search for potentially better antimalarials, a series of 1,2,3-triazole derivatives was synthesized by chemical modification of lapachol. Alkylation of the hydroxyl group gave its propargyl ether which, via copper-catalyzed cycloaddition (CuAAC) click chemistry with different organic azides, afforded 17 naphthoquinonolyl triazole derivatives. All the synthetic compounds were evaluated for their in vitro activity against chloroquine resistant Plasmodium falciparum (W2) and for cytotoxicity to HepG2 cells. Compounds containing the naphthoquinolyl triazole moieties showed higher antimalarial activity than lapachol (IC50 123.5 µM) and selectivity index (SI) values in the range of 4.5-197.7. Molecular docking simulations of lapachol, atovaquone and all the newly synthesized compounds were carried out for interactions with PfDHODH, a mitochondrial enzyme of the parasite respiratory chain that is essential for de novo pyrimidine biosynthesis. Docking of the naphthoquinonolyl triazole derivatives to PfDHODH yielded scores between -9.375 and -14.55 units, compared to -9.137 for lapachol and -12.95 for atovaquone and disclosed the derivative 17 as a lead compound. Therefore, the study results show the enhancement of DHODH binding affinity correlated with improvement of SI values and in vitro activities of the lapachol derivatives.