Structure-based virtual screening for insect ecdysone receptor ligands using MM/PBSA

Design, synthesis, and biological evaluation of insect hormone agonists

Agonists of insect hormones, namely molting hormone (MH) and juvenile hormone (JH), disrupt the normal growth of insects and can be employed as insecticides that are harmless to vertebrates. In this study, a series of experiments and computational analyses were conducted to rationally design novel insect hormone agonists. Syntheses and quantitative structure-activity relationship (QSAR) analyses of two MH agonist chemotypes, imidazothiadiazoles and tetrahydroquinolines, revealed that the structural factors important for the ligand-receptor interactions are significantly different between these chemotypes. On the other hand, a virtual screening cascade combining ligand- and structure-based methods identified a piperazine derivative as a novel JH agonist. The results obtained in this study will be useful for the future development of novel insect growth regulators.

Derisking Future Agrochemicals before They Are Made: Large-Scale In Vitro Screening for In Silico Modeling of Thyroid Peroxidase Inhibition

Inhibition of thyroid peroxidase (TPO) is a known molecular initiating event for thyroid hormone dysregulation and thyroid toxicity. Consequently, TPO is a critical off-target for the design of safer agrochemicals. To date, fewer than 500 structurally characterized TPO inhibitors are known, and the most comprehensive result set generated under identical conditions encompasses approximately 1000 compounds from a subset of the ToxCast compound collection. Here we describe a collaboration between wet lab and data scientists combining a large in vitro screen and the subsequent development of an in silico model for predicting TPO inhibition. The screen encompassed more than 100,000 diverse drug-like agrochemical compounds and yielded more than 6000 structurally novel TPO inhibitors. On this foundation, we applied different machine learning techniques and compared their performance. We discuss use cases for in silico TPO models in agrochemical research and explain that model recall is of particular importance when selecting compounds from large virtual compound collections. Furthermore, we show that due to the higher structural diversity of our training data, our final model allowed better generalization than models trained on the ToxCast data set. We now have a tool to predict TPO inhibition even for molecules that are only available virtually, such as hits from virtual screenings, or compounds under consideration for inclusion in our screening collection. Structures and activity data for 34,524 compounds are provided. This data set includes almost all inhibitors, including more than 3000 proprietary structures, and a large proportion of the inactives.

Discovery of ZJCK-6-46: A Potent, Selective, and Orally Available Dual-Specificity Tyrosine Phosphorylation-Regulated Kinase 1A Inhibitor for the Treatment of Alzheimer's Disease

Targeting dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) has been verified to regulate the progression of tau pathology as a promising treatment for Alzheimer's disease (AD), while the research progress on DYRK1A inhibitors seemed to be in a bottleneck period. In this work, we identified 32 (ZJCK-6-46) as the most potential DYRK1A inhibitor (IC50 = 0.68 nM) through rational design, systematic structural optimization, and comprehensive evaluation. Compound 32 exhibited acceptable in vitro absorption, distribution, metabolism, and excretion (ADME) properties and significantly reduced the expression of p-Tau Thr212 in Tau (P301L) 293T cells and SH-SY5Y cells. Moreover, compound 32 showed favorable bioavailability, blood-brain barrier (BBB) permeability, and the potential of ameliorating cognitive dysfunction by obviously reducing the expression of phosphorylated tau and neuronal loss in vivo, which was deserved as a valuable molecular tool to reveal the role of DYRK1A in the pathogenesis of AD and to further promote the development of anti-AD drugs.

A Potential Multitarget Insect Growth Regulator Candidate: Design, Synthesis, and Biological Activity of Novel Acetamido Derivatives Containing Hexacyclic Pyrazole Carboxamides

Insect growth regulators (IGRs) are important green insecticides that disrupt normal growth and development in insects to reduce the harm caused by pests to crops. The ecdysone receptor (EcR) and three chitinases OfChtI, OfChtII, and OfChi-h are closely associated with the molting stage of insects. Thus, they are considered promising targets for the development of novel insecticides such as IGRs. Our previous work identified a dual-target compound 6j, which could act simultaneously on both EcR and OfChtI. In the present study, 6j was first found to have inhibitory activities against OfChtII and OfChi-h, too. Subsequently, taking 6j as a lead compound, 19 novel acetamido derivatives were rationally designed and synthesized by introducing an acetamido moiety into the amide bridge based on the flexibility of the binding cavities of 6j with EcR and three chitinases. Then, their insecticidal activities against Plutella xylostella (P. xylostella), Ostrinia furnacalis (O. furnacalis), and Spodoptera frugiperda (S. frugiperda) were carried out. The bioassay results revealed that most of these acetamido derivatives possessed moderate to good larvicidal activities against three lepidopteran pests. Especially, compound I-17 displayed excellent insecticidal activities against P. xylostella (LC50, 93.32 mg/L), O. furnacalis (LC50, 114.79 mg/L), and S. frugiperda (86.1% mortality at 500 mg/L), significantly better than that of 6j. In addition, further protein validation and molecular docking demonstrated that I-17 could act simultaneously on EcR (17.7% binding activity at 8 mg/L), OfChtI (69.2% inhibitory rate at 50 μM), OfChtII (71.5% inhibitory rate at 50 μM), and OfChi-h (73.9% inhibitory rate at 50 μM), indicating that I-17 is a potential lead candidate for novel multitarget IGRs. This work provides a promising starting point for the development of novel types of IGRs as pest management agents.

Targeting Toxoplasma gondii ME49 TgAPN2: A Bioinformatics Approach for Antiparasitic Drug Discovery

As fewer therapeutic options are available for treating toxoplasmosis, newer antiparasitic drugs that can block TgAPN2 M1 aminopeptidase are of significant value. Herein, we employed several computer-aided drug-design approaches with the objective of identifying drug molecules from the Asinex library with stable conformation and binding energy scores. By a structure-based virtual screening process, three molecules—LAS_52160953, LAS_51177972, and LAS_52506311—were identified as promising candidates, with binding affinity scores of −8.6 kcal/mol, −8.5 kcal/mol, and −8.3 kcal/mol, respectively. The compounds produced balanced interacting networks of hydrophilic and hydrophobic interactions, vital for holding the compounds at the docked cavity and stable binding conformation. The docked compound complexes with TgAPN2 were further subjected to molecular dynamic simulations that revealed mean RMSD for the LAS_52160953 complex of 1.45 Å), LAS_51177972 complex 1.02 Å, and LAS_52506311 complex 1.087 Å. Another round of binding free energy validation by MM-GBSA/MM-PBSA was done to confirm docking and simulation findings. The analysis predicted average MM-GBSA value of <−36 kcal/mol and <−35 kcal/mol by MM-PBSA. The compounds were further classified as appropriate candidates to be used as drug-like molecules and showed favorable pharmacokinetics. The shortlisted compounds showed promising biological potency against the TgAPN2 enzyme and may be used in experimental validation. They may also serve as parent structures to design novel derivatives with enhanced biological potency.

In Vitro Binding Effects of the Ecdysone Receptor-Binding Domain and PonA in Plutella xylostella

Both insect ecdysone receptors and ultraspiracle belong to the nuclear receptor family. They form a nanoscale self-assembling complex with ecdysteroids in cells, transit into the nucleus, bind with genes to initiate transcription, and perform specific biological functions to regulate the molting, metamorphosis, and growth processes of insects. Therefore, this complex is an important target for the development of eco-friendly insecticides. The diamondback moth (Plutella xylostella) is a devastating pest of cruciferous vegetable crops, wreaking havoc worldwide and causing severe economic losses, and this pest has developed resistance to most chemical insecticides. In this study, highly pure EcR and USP functional domains were obtained by constructing a prokaryotic expression system for the diamondback moth EcR and USP functional domain genes, and the differences between EcR and USP binding domain monomers and dimers were analyzed using transmission electron microscopy and zeta potential. Radioisotope experiments further confirmed that the binding affinity of PonA to the EcR/USP dimer was enhanced approximately 20-fold compared with the binding affinity to the PxGST-EcR monomer. The differences between PonA and tebufenozide in binding with EcR/USP were examined. Molecular simulations showed that the hydrogen bonding network formed by Glu307 and Arg382 on the EcR/USP dimer was a key factor in the affinity enhancement. This study provides a rapid and sensitive method for screening ecdysone agonists for ecdysone receptor studies in vitro.

Exploring the mechanism of C473D mutation on CDC25B causing weak binding affinity with CDK2/CyclinA by molecular dynamics study

CDC25B belongs to the CDC25 family, and it plays an important part in regulating the activity of CDK/CyclinA. Studies have shown that CDC25B is closely related to cancer development. When CYS473 on CDC25B is mutated into ASP, the affinity between CDC25B and CDK2/CyclinA weakens, and their dissociation speed is greatly improved. However, the mechanism by which the CDC25BC473D mutant weakens its binding to CDK2/CyclinA is unclear. In order to study the effect of CDC25BC473D mutants on CDK2/CyclinA substrates, we constructed and verified the rationality of the CDC25BWT:CDK2/CyclinA system and CDC25BC473D:CDK2/CyclinA system and conducted molecular dynamics (MD) simulation analysis. In the post-analysis, the fluctuations of residues ARG488-SER499, LYS541-TRP550 on CDC25B and residues ASP206-ASP210 on CDK2 were massive in the mutant CDC25BC473D:CDK2/CyclinA system. And the interactions between residue ARG492 and residue GLU208, residue ARG544 and residue GLU42, residue ARG544 and TRP550 were weakened in the mutant CDC25BC473D:CDK2/CyclinA system. The results showed that when CYS473 on CDC25B was mutated into ASP473, the mutant CDC25BC473D:CDK2/CyclinA system was less stable than the wild-type CDC25BWT:CDK2/CyclinA system. Finally, active site CYS473 of CDC25B was speculated to be the key residue, which had great effects on the binding between CDC25BCYS473 and CDK2 in the CDC25BC473D:CDK2/CyclinA system. Consequently, overall analyses appeared in this study ultimately provided a useful understanding of the weak interactions between CDC25BCYS473D and CDK2/CyclinA.Communicated by Ramaswamy H. Sarma.

Discovery of ZQ-, a Novel Starting Point To Develop Inhibitors against the Potent Molecular Target Chitinase

In a previous study, we found that compound ZQ-8 had a strong impact on the growth and development of Helicoverpa armigera. However, the mechanism and target of ZQ-8 are not clear, which makes it difficult to optimize the structure of this compound. In this study, the preliminary mode of action of ZQ-8 was studied through RNA sequencing and molecular docking. We also analyzed the underlying mechanisms from the aspect of ZQ-8 with respect to chitinase. The results showed that ZQ-8 mainly affects chitinase activity in the epidermis of H. armigera. ZQ-8 can competitively combine with chitinase 2 and endochitinase to form a relatively stable complex of ZQ-8, resulting in the failure of chitinase to degrade chitin. These findings indicate that the epidermis of H. armigera was identified as the action site of ZQ-8 and chitinase 2 and endochitinase were potential targets.

A luciferase reporter assay for ecdysone agonists using HEK293T cells

Ecdysone agonists are a class of insecticides that activate the ecdysone receptor (EcR) heterodimerized with the ultraspiracle (USP). Here, we report a new luciferase reporter assay for ecdysone agonists. The assay employs mammalian HEK293T cells transiently transfected with the EcR and USP genes of Chilo suppressalis, along with the taiman (Tai) gene of Drosophila melanogaster that encodes a steroid receptor coactivator. This assay system gave results consistent with those of radioligand binding assays and showed sensitivity superior to that of the existing in vitro methods. In addition, use of the heterologous host cells precludes perturbation from intrinsic players of the ecdysone signaling, which is a potential drawback of insect cell-based methods. This reporter system is suitable for detailed structure-activity analysis of ecdysone agonists and will serve as a valuable tool for the rational design of novel insect growth regulators.

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be assessed for toxicity to bees. Leveraging a dataset of 382 molecules with toxicity labels from honey bee exposure experiments, we train a support vector machine (SVM) to predict the toxicity of pesticides to honey bees. We compare two representations of the pesticide molecules: (i) a random walk feature vector listing counts of length- L walks on the molecular graph with each vertex- and edge-label sequence and (ii) the Molecular ACCess System (MACCS) structural key fingerprint (FP), a bit vector indicating the presence/absence of a list of pre-defined subgraph patterns in the molecular graph. We explicitly construct the MACCS FPs but rely on the fixed-length- L random walk graph kernel (RWGK) in place of the dot product for the random walk representation. The L-RWGK-SVM achieves an accuracy, precision, recall, and F1 score (mean over 2000 runs) of 0.81, 0.68, 0.71, and 0.69, respectively, on the test data set—with L = 4 being the mode optimal walk length. The MACCS-FP-SVM performs on par/marginally better than the L-RWGK-SVM, lends more interpretability, but varies more in performance. We interpret the MACCS-FP-SVM by illuminating which subgraph patterns in the molecules tend to strongly push them toward the toxic/non-toxic side of the separating hyperplane.

In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics

Tuberculosis caused by Mycobacterium tuberculosis (Mtb) is responsible for the highest global health problem, with the deaths of millions of people. With prevalence of multiple drug resistance (MDR) strains and extended therapeutic times, it is important to discover small molecule inhibitors against novel hypothetical proteins of the pathogen. In this study, a virtual screening protocol was carried out against MtbH37Rv hypothetical protein RipD (Rv1566c) for the identification of potential small molecule inhibitors. The 3D model of the protein structure binding site was used for virtual screening (VS) of inhibitors from the Pathogen Box, followed by its validation through a molecular docking study. The stability of the protein-ligand complex was assessed using a 150 ns molecular dynamics simulation. MM-PBSA and MM-GBSA are the two approaches that were used to perform the trajectory analysis and determine the binding free energies, respectively. The ligand binding was observed to be stable across the entire time frame with an approximate binding free energy of -22.9916 kcal/mol. The drug-likeness of the inhibitors along with a potential anti-tuberculosis compound was validated by ADMET prediction software. Furthermore, a CFU inhibition assay was used to validate the best hit compound's in vitro inhibitory efficacy against a non-pathogenic Mycobacterium smegmatis MC2155 under low nutrient culture conditions. The study reported that the compound proposed in our study (Pathogen Box ID: MMV687700) will be useful for the identification of potential inhibitors against Mtb in future.

Estrogen receptor potentially stable conformations from molecular dynamics as a structure-based pharmacophore model for mapping, screening, and identifying ligands-a new paradigm shift in pharmacophore screening

Despite rigorous research on breast cancer has increased in recent decades, only few drugs are in practice to combat against the disease. Due to excessive usage, these drugs attain resistance is an avertable phenomenon resulting from inadequate treatment. A novel, and real-time approaches are expected to overcome to find the solution for the drug resistance. The molecular dynamics based multi-conformational sampling technique via computer-aided drug-designing approach, may be a promising route to identify the lead candidates from real-time generated frames. The estrogenic receptor, being one of the most widely targeted receptors for various breast cancer drugs namely, tamoxifen, raloxifene and GW5 (tamoxifen-resistance inhibitor) was used for simulating the molecular dynamics to obtain various real time frames. The energetically stable frames were funnelled based on Gibbs free binding energy, interaction energy and active site interaction to generate pharmacophores model for virtual screening of compounds. Generated pharmacophores are validated by receiver operating characteristic area under curve greater than 0.8. Further, screening of compounds with validated structure-based pharmacophore model of different estrogen bound drug complex conformations and binding orientations are complement for tamoxifen and tamoxifen-resistance inhibitor frames. Moreover, the best mapped compounds were docked and probed for ADMET, TopKat® and Lipinski's rule of five is more favourable for compound Andrographidine F sourced from medicinal herbal plant Andrographis paniculata. Hence, this compound had to be further analysed in in-vitro and in-vivo to prove the same.Communicated by Ramaswamy H. Sarma.

Combinatorial Virtual Screening Revealed a Novel Scaffold for TNKS Inhibition to Combat Colorectal Cancer

The abnormal Wnt signaling pathway leads to a high expression of β-catenin, which causes several types of cancer, particularly colorectal cancer (CRC). The inhibition of tankyrase (TNKS) activity can reduce cancer cell growth, invasion, and resistance to treatment by blocking the Wnt signaling pathway. A pharmacophore search and pharmacophore docking were performed to identify potential TNKS inhibitors in the training databases. The weighted MM/PBSA binding free energy of the docking model was calculated to rank the databases. The reranked results indicated that 26.98% of TNKS inhibitors that were present in the top 5% of compounds in the database and near an ideal value ranked 28.57%. The National Cancer Institute database was selected for formal virtual screening, and 11 potential TNKS inhibitors were identified. An enzyme-based experiment was performed to demonstrate that of the 11 potential TNKS inhibitors, NSC295092 and NSC319963 had the most potential. Finally, Wnt pathway analysis was performed through a cell-based assay, which indicated that NSC319963 is the most likely TNKS inhibitor (pIC50 = 5.59). The antiproliferation assay demonstrated that NSC319963 can decrease colorectal cancer cell growth; therefore, the proposed method successfully identified a novel TNKS inhibitor that can alleviate CRC.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: an integrated computational approach

The global pandemic crisis, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines have not turned to be realistic within the timeframe needed to combat this pandemic. Here, we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, whichare crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 75 FDA-approved potential antiviral drugs against the target proteins, spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), cathepsin L (CTSL), nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and non-structural protein 6 (NSP6), resulted in the selection of seven drugs which preferentially bind to the target proteins. Further, the molecular interactions determined by molecular dynamics simulation revealed that among the 75 drug molecules, catechin can effectively bind to 3CLpro, CTSL, RBD of S protein, NSP6 and nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (CTSL) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values: -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favorable molecular interaction of catechin toward multiple target proteins signify that catechin can be potentially explored as a multi-targeted agent against COVID-19.

Nonsteroidal ecdysone receptor agonists use a water channel for binding to the ecdysone receptor complex EcR/USP

The ecdysone receptor (EcR) possesses the remarkable capacity to adapt structurally to different types of ligands. EcR binds ecdysteroids, including 20-hydroxyecdysone (20E), as well as nonsteroidal synthetic agonists such as insecticidal dibenzoylhydrazines (DBHs). Here, we report the crystal structures of the ligand-binding domains of Heliothis virescens EcR/USP bound to the DBH agonist BYI09181 and to the imidazole-type compound BYI08346. The region delineated by helices H7 and H10 opens up to tightly fit a phenyl ring of the ligands to an extent that depends on the bulkiness of ring substituent. In the structure of 20E-bound EcR, this part of the ligand-binding pocket (LBP) contains a channel filled by water molecules that form an intricate hydrogen bond network between 20E and LBP. The water channel present in the nuclear receptor bound to its natural hormone acts as a critical molecular adaptation spring used to accommodate synthetic agonists inside its binding cavity.

Virtual screening identifies a novel piperazine-based insect juvenile hormone agonist

Juvenile hormone (JH) agonists constitute a subclass of insect growth regulators and play important roles in insect pest management. In this work, a multi-step virtual screening program was executed to find novel JH agonists. A database of 5 million purchasable compounds was sequentially processed with three computational filters: (i) shape and chemical similarity as compared to known JH-active compounds; (ii) molecular docking simulations against a Drosophila JH receptor, methoprene-tolerant; and (iii) free energy calculation of ligand-receptor binding using a modified MM/PBSA (molecular mechanics/Poisson-Boltzmann surface area) protocol. The 11 candidates that passed the three filters were evaluated in a luciferase reporter assay, leading to the identification of a hit compound that contains a piperazine ring system (EC₅₀=870 nM). This compound is structurally dissimilar to known JH agonists and synthetically easy to access; therefore, it is a promising starting point for further structure optimization.

Virtual screening and free energy estimation for identifying Mycobacterium tuberculosis flavoenzyme DprE1 inhibitors

In Mycobacterium tuberculosis (MTB), the cell wall synthesis flavoenzyme decaprenylphosphoryl-β-d-ribose 2'-epimerase (DprE1) plays a crucial role in host pathogenesis, virulence, lethality and survival under stress. The emergence of different variants of drug resistant MTB are a major threat worldwide which essentially requires more effective new drug molecules with no major side effects. Here, we used structure based virtual screening of bioactive molecules from the ChEMBL database targeting DprE1, having bioactive 78,713 molecules known for anti-tuberculosis activity. An extensive molecular docking, binding affinity and pharmacokinetics profile filtering results in the selection four compounds, C5 (ChEMBL2441313), C6 (ChEMBL2338605), C8 (ChEMBL441373) and C10 (ChEMBL1607606) which may explore as potential drug candidates. The obtained results were validated with thirteen known DprE1 inhibitors. We further estimated the free-binding energy, solvation and entropy terms underlying the binding properties of DprE1-ligand interactions with the implication of MD simulation, MM/GBSA, MM/PBSA and MM/3D-RISM. Interestingly, we find that C6 shows the highest ΔG scores (-41.28 ± 3.51, -22.36 ± 3.17, -10.33 ± 5.70 kcal mol^-1) in MM/GBSA, MM/PBSA and MM/3D-RISM assay, respectively. Whereas, the lowest ΔG scores (-35.31 ± 3.44, -13.67 ± 2.65, -3.40 ± 4.06 kcal mol^-1) observed for CT319, the inhibitor co-crystallized with DprE1. Collectively, the results demonstrated that hit-molecules: C5, C6, C8 and C10 having better binding free energy and molecular affinity as compared to CT319. Thus, we proposed that selected compounds may be explored as lead molecules in MTB therapy.

Identification of 1-phenyl-4-cyano-5-aminopyrazoles as novel ecdysone receptor ligands by virtual screening, structural optimization, and biological evaluations

Ecdysteroids initiate the molting process in insects by binding to the ecdysone receptor (EcR), which is a promising target for identifying insect growth regulators. This paper presents an in silico/in vitro screening procedure for identifying new EcR ligands. The three-step virtual screening procedure uses a three-dimensional pharmacophore model, docking and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) rescoring routine. A novel hit (VS14) with good binding activity against Plutella xylostella EcR was identified from a library of over 200,000 chemicals. Subsequently, the 1-phenyl-4-cyano-5-aminopyrazole scaffold and twelve EcR ligands were synthesized. Their IC₅₀ values against Plutella xylostella EcR ranged from 0.64 to 23.21 μm. Furthermore, a preliminary analysis of the structure-activity relationship for novel scaffolds provided a basis for designing new ligands with improved activity.

Design, Synthesis, and Biological Activity of Novel Heptacyclic Pyrazolamide Derivatives: A New Candidate of Dual-Target Insect Growth Regulators

Insect growth regulators (IGRs) can cause abnormal growth and development in insects, resulting in incomplete metamorphosis or even death of the larvae. Ecdysone receptor (EcR) and chitinase in insects play indispensable roles in the molting process. Ecdysone analogues and chitinase inhibitors are considered as potential IGRs. In order to find new and highly effective IGR candidates, based on the structure-activity relationship and molecular docking results of the active compound 6i (3-(tert-butyl)-N-(4-(tert-butyl)phenyl)-1-phenyl-1H-pyrazole-5-carboxamide) discovered in our previous work, we changed the t-butyl group on the pyrazole ring into heptacycle to enhance the hydrophobicity. Consequently, a series of novel heptacyclic pyrazolamide derivatives were designed and synthesized. The bioassay results demonstrated that some compounds showed obvious insecticidal activity. Especially, D-27 (N-(4-(tert-butyl)phenyl)-2-phenyl-2,4,5,6,7,8-hexahydrocyclohepta[c]pyrazole-5-carboxamide) showed good activities against Plutella xylostella (LC₅₀, 51.50 mg·L^-1) and Mythimna separata (100% mortality at 2.5 mg·L^-1). Furthermore, protein validation indicated that D-27 acts not only on the EcR but also on chitinase Of ChtI. Molecular docking and molecular dynamics simulation explained the vital factors in the interaction between D-27 and receptors. D-27 may be a new lead candidate with a dual target in which Of ChtI shall be the main one. This work created a new starting point for discovering a novel type of IGRs.

Application of MM-PBSA Methods in Virtual Screening

Computer-aided drug design techniques are today largely applied in medicinal chemistry. In particular, receptor-based virtual screening (VS) studies, in which molecular docking represents the gold standard in silico approach, constitute a powerful strategy for identifying novel hit compounds active against the desired target receptor. Nevertheless, the need for improving the ability of docking in discriminating true active ligands from inactive compounds, thus boosting VS hit rates, is still pressing. In this context, the use of binding free energy evaluation approaches can represent a profitable tool for rescoring ligand-protein complexes predicted by docking based on more reliable estimations of ligand-protein binding affinities than those obtained with simple scoring functions. In the present review, we focused our attention on the Molecular Mechanics-Poisson Boltzman Surface Area (MM-PBSA) method for the calculation of binding free energies and its application in VS studies. We provided examples of successful applications of this method in VS campaigns and evaluation studies in which the reliability of this approach has been assessed, thus providing useful guidelines for employing this approach in VS.

Combined strategies in structure-based virtual screening

The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines. As a powerful computational approach for the identification of hits with novel structural scaffolds, structure-based virtual screening (SBVS) has exhibited a remarkably increasing influence in the early stages of drug discovery. During the past decade, a variety of techniques and algorithms have been proposed and tested with different purposes in the scope of SBVS. Although SBVS has been a common and proven technology, it still shows some challenges and problems that are needed to be addressed, where the negative influence regardless of protein flexibility and the inaccurate prediction of binding affinity are the two major challenges. Here, focusing on these difficulties, we summarize a series of combined strategies or workflows developed by our group and others. Furthermore, several representative successful applications from recent publications are also discussed to demonstrate the effectiveness of the combined SBVS strategies in drug discovery campaigns.

Structure-based virtual screening, molecular dynamics simulation and MM-PBSA toward identifying the inhibitors for two-component regulatory system protein NarL of Mycobacterium Tuberculosis

The nitrate/nitrite response regulatory protein NarL belongs to the two-component regulatory system of Mycobacterium tuberculosis (MTB), plays a crucial role in anaerobic survival of mycobacteria in host. The absence of this protein in humans, makes it an attractive drug target for MTB treatment. However, the specific drug molecules targeting NarL are yet to be identified. In this study, we identified the promising drug candidates using structure based virtual screening of compounds from chemical libraries (ChEMBL and ZINC), followed by the extensive physicochemical properties analyses and molecular dynamics (MD) simulation. As the initial results, we obtained 4,754 bioactive compounds from ChEMBL having anti-tuberculosis activity which is finally narrowed down to the best 10 hits. A similar approach was applied to search for structurally similar compounds from ZINC data, corresponding to the top hits obtained from ChEMBL. Our collective results show that two compounds, ChEMBL509609 (Gscore - 5.054 kcal/mol, Xscore - 6.47 kcal/mol) and ZINC01843143 (Gscore - 5.114 kcal/mol, Xscore - 6.46 kcal/mol) having the best docking score and ADMET profile. The structural stability and dynamics of lead molecules at active site of NarL were examined using MD simulation and the binding free energies were estimated with MM-PBSA. Essential dynamics and MM-PBSA demonstrated that NarL-ChEMBL509609 complex remains the most stable during simulation of 100 ns with the higher binding free energy which may be a suitable candidate for further experimental analysis. AbbreviationsADMEAbsorption, Distribution, Metabolism, And ExcretionBCGBacillus Calmette-GuerinCNSCentral nervous systemDOTSDirectly observed treatment, short courseEDEssential dynamicsHIVHuman immunodeficiency virusHKHistidine kinaseHOAHuman oral absorptionHTVSHigh throughput virtual screeningIRRIIrritationMDMolecular dynamicsMDRMultidrug resistantMTBMycobacterium tuberculosisMUTMutagenicityMWMolecular weightPHOAPercentage of human oral absorptionREPReproductive developmentRgRadius of gyrationRMSDRoot mean square deviationRMSFRoot mean square fluctuationRO5Lipinski's rule of fiveRRResponse regulatorSPStandard precisionSPGStandard precision glideTBTuberculosisTCSTwo-component regulatory systemTDRTotally drug-resistantTUMOTumorigenicityWHOWorld health organizationXDRExtensively drug-resistantXPExtra precisionCommunicated by Ramaswamy H. Sarma.