Anti-Toxoplasma gondii effect of lupane-type triterpenes from the bark of black alder (Alnus glutinosa) and identification of a potential target by reverse docking

Toxoplasmosis is a worldwide parasitosis that is generally benign. The infestation may pose a risk to immunocompromized patients and to fetuses when pregnant women have recently seroconverted. Current treatments have numerous side effects and chemoresistance is emerging, hence the need to find new anti-Toxoplasma gondii substances. This study focuses on the antiparasitic potential of lupane-type pentacyclic triterpenes isolated from the bark of black alder (Alnus glutinosa), as well as the hypothesis of their macromolecular target by an original method of reverse docking. Among the isolated triterpenes, betulone was the most active compound with an IC₅₀ of 2.7 ± 1.2 μM, a CC₅₀ greater than 80 μM, and a selectivity index of over 29.6. An additional study of the anti-T. gondii potential of commercially available compounds (betulonic acid methyl ester and betulonic acid) showed the important role of the C3 ketone function and the C28 oxidation level on the lupane-type triterpene in the antiparasitic activity since their IC₅₀ and CC₅₀ were similar to that of betulone. Finally, the most active compounds were subjected to the AMIDE reverse docking workflow. A dataset of 87 T. gondii proteins from the Protein Data Bank was created. It identified calcium-dependent protein kinase CDPK3 as the most likely target of betulin derivatives.

Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking

Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identified several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specifically against this pathogen requires unambiguous identification of their corresponding targets, something the high-throughput screens are not typically designed to reveal. We present here a new computational inverse-docking protocol that uses all-atom protein structures and a combination of docking methods to rank-order targets for each of several existing drugs for which a plurality of recent high-throughput screens detected anti-SARS-CoV-2 activity. We demonstrate validation of this method with known drug-target pairs, including both non-antiviral and antiviral compounds. We subjected 152 distinct drugs potentially suitable for repurposing to the inverse docking procedure. The most common preferential targets were the human enzymes TMPRSS2 and PIKfyve, followed by the viral enzymes Helicase and PLpro. All compounds that selected TMPRSS2 are known serine protease inhibitors, and those that selected PIKfyve are known tyrosine kinase inhibitors. Detailed structural analysis of the docking poses revealed important insights into why these selections arose, and could potentially lead to more rational design of new drugs against these targets.

LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds

Target prediction is a crucial step in modern drug discovery. However, existing experimental approaches to target prediction are time-consuming and costly. Here, we introduce LigTMap, an online server with a fully automated workflow that can identify protein targets of chemical compounds among 17 classes of therapeutic proteins extracted from the PDBbind database. It combines ligand similarity search with docking and binding similarity analysis to predict putative targets. In the validation experiment of 1251 compounds, targets were successfully predicted for more than 70% of the compounds within the top-10 list. The performance of LigTMap is comparable to the current best servers SwissTargetPrediction and SEA. When testing with our newly compiled compounds from recent literature, we get improved top 10 success rate (66% ours vs. 60% SwissTargetPrediction and 64% SEA) and similar top 1 success rate (45% ours vs. 51% SwissTargetPrediction and 41% SEA). LigTMap directly provides ligand docking structures in PDB format, so that the results are ready for further structural studies in computer-aided drug design and drug repurposing projects. The LigTMap web server is freely accessible at https://cbbio.online/LigTMap. The source code is released on GitHub (https://github.com/ShirleyWISiu/LigTMap) under the BSD 3-Clause License to encourage re-use and further developments.

MDock: A Suite for Molecular Inverse Docking and Target Prediction

Molecular docking is commonly used for identification of drug candidates targeting a specified protein of known structure. With the increasing emphasis on drug repurposing over recent decades, molecular inverse docking has been widely applied to prediction of the potential protein targets of a specified molecule. In practice, inverse docking has many advantages, including early supervision of drugs' side effects and toxicity. MDock developed from our laboratory is a protein-ligand docking software based on a knowledge-based scoring function and has numerous applications to lead identification. In addition to its computational efficiency on ensemble docking for multiple protein conformations, MDock is well suited for inverse docking. In this chapter, we focus on introducing the protocol of inverse docking with MDock. For academic users, the MDock package is freely available at http://zoulab.dalton.missouri.edu/mdock.htm .

Synthesis, inverse docking-assisted identification and in vitro biological characterization of Flavonol-based analogs of fisetin as c-Kit, CDK2 and mTOR inhibitors against melanoma and non-melanoma skin cancers

Due to hurdles, including resistance, adverse effects, and poor bioavailability, among others linked with existing therapies, there is an urgent unmet need to devise new, safe, and more effective treatment modalities for skin cancers. Herein, a series of flavonol-based derivatives of fisetin, a plant-based flavonoid identified as an anti-tumorigenic agent targeting the mammalian targets of rapamycin (mTOR)-regulated pathways, were synthesized and fully characterized. New potential inhibitors of receptor tyrosine kinases (c-KITs), cyclin-dependent kinase-2 (CDK2), and mTOR, representing attractive therapeutic targets for melanoma and non-melanoma skin cancers (NMSCs) treatment, were identified using inverse-docking, in vitro kinase activity and various cell-based anticancer screening assays. Eleven compounds exhibited significant inhibitory activities greater than the parent molecule against four human skin cancer cell lines, including melanoma (A375 and SK-Mel-28) and NMSCs (A431 and UWBCC1), with IC50 values ranging from 0.12 to < 15 μM. Seven compounds were identified as potentially potent single, dual or multi-kinase c-KITs, CDK2, and mTOR kinase inhibitors after inverse-docking and screening against twelve known cancer targets, followed by kinase activity profiling. Moreover, the potent compound F20, and the multi-kinase F9 and F17 targeted compounds, markedly decreased scratch wound closure, colony formation, and heightened expression levels of key cancer-promoting pathway molecular targets c-Kit, CDK2, and mTOR. In addition, these compounds downregulated Bcl-2 levels and upregulated Bax and cleaved caspase-3/7/8 and PARP levels, thus inducing apoptosis of A375 and A431 cells in a dose-dependent manner. Overall, compounds F20, F9 and F17, were identified as promising c-Kit, CDK2 and mTOR inhibitors, worthy of further investigation as therapeutics, or as adjuvants to standard therapies for the control of melanoma and NMSCs.

Discovery of potential targets of Triptolide through inverse docking in ovarian cancer cells

Triptolide (TPL) is proposed as an effective anticancer agent known for its anti-proliferation of a variety of cancer cells including ovarian cancer cells. Although some studies have been conducted, the mechanism by which TPL acts on ovarian cancer remains to be clearly described. Herein, systematic work based on bioinformatics was carried out to discover the potential targets of TPL in SKOV-3 cells. TPL induces the early apoptosis of SKOV-3 cells in a dose- and time-dependent manner with an IC₅₀ = 40 ± 0.89 nM when cells are incubated for 48 h. Moreover, 20 nM TPL significantly promotes early apoptosis at a rate of 40.73%. Using a self-designed inverse molecular docking protocol, we fish the top 19 probable targets of TPL from the target library, which was built on 2,250 proteins extracted from the Protein Data Bank. The 2D-DIGE assay reveals that the expression of eight genes is affected by TPL. The results of western blotting and qRT-PCR assay suggest that 40 nM of TPL up-regulates the level of Annexin A5 (6.34 ± 0.07 fold) and ATP syn thase (4.08 ± 0.08 fold) and down-regulates the level of β-Tubulin (0.11 ± 0.12 fold) and HSP90 (0.21 ± 0.09 fold). More details of TPL affecting on Annexin A5 signaling pathway will be discovered in the future. Our results define some potential targets of TPL, with the hope that this agent could be used as therapy for the preclinical treatment of ovarian cancer.

Computational evaluation of interactions between organophosphate esters and nuclear hormone receptors

Organophosphate esters (OPEs) have gained considerable interest from many environmental chemists and toxicologists due to their frequent detection in the environment and potential adverse effects on health. Nuclear hormone receptors (NHRs) were found to mediate many of their adverse effects. However, our knowledge regarding the direct binding and interaction between OPEs and NHRs is limited. In this study, Endocrine Disruptome, an online computational tool based on the technique of inverse docking, was used to calculate the binding affinity score of 25 individual OPEs with 12 different human NHRs. Results showed that 20% of potential binding interactions between the OPEs and NHRs had medium-to-high probabilities. The accuracy, sensitivity and specificity of the predictions were 78.8, 60.0 and 80.9%, respectively. OPEs with a benzene ring were more active than those without, among which, tri-o-tolyl phosphate and tri-m-tolyl phosphate displayed the highest activities, suggesting that they might pose the greatest potential risks for interference with endocrine functions. In addition, the antagonistic conformations of androgen receptor and estrogen receptor β were found to be the two most vulnerable NHR conformations. Our findings can further the understanding about the health risk(s) of OPEs.

Steroids-specific target library for steroids target prediction

Steroids exist universally and play critical roles in various biological processes. Identifying potential targets of steroids is of great significance in studying their physiological and biochemical activities, the side effects and for drug repurposing. Herein, aiming at more precise steroids targets prediction, a steroids-specific target library integrating 3325 PDB or homology modeling structures categorized into 196 proteins was built by considering chemical similarity from DrugBank and biological processes from KEGG. The main properties of this library include: (1) It was manually prepared and checked to eliminate mistakes. (2) The library enriched the possible steroids targets and could decrease the false positives of structure-based target screening for steroids. (3) The ranking by protein name instead of PDB ID could make the screening more efficiency and precise. (4) Protein flexibility was taken into account partially by the different active conformations through the structural redundancy of each category of protein, which leads to more accurate prediction. The case studies of glycocholic acid and 24-epibrassinolide proved its powerful predictive accuracy. In summary, our strategy to build the steroids-specific protein library for steroids target prediction is a promising approach and it provides a novel idea for the target prediction of small molecules.

Inverse docking based screening and identification of protein targets for Cassiarin alkaloids against Plasmodium falciparum

Various reports have shown Cassiarin alkaloids, selective in vitro activities against various strains of Plasmodium falciparum with low cytotoxicity, which indicates their possible candidature as antimalarial drug. However, poor recognition of their protein targets and molecular binding behaviour, certainly limits their exploration as antimalarial drug candidature. To address this, we utilises inverse screening, based on three different docking methodologies in order to find their most putative protein targets. In our study, we screened 1047 protein structures from protein data bank, which belongs to 147 different proteins. Our investigation identified 16 protein targets for Cassiarins. In few cases of identified protein targets, the binding site was poorly studied, which encouraged us to perform comparative sequence and structural studies with their homologous proteins, like as in case of Kelch motif associated protein, Armadillo repeats only protein and Methionine aminopeptidase 1b. In our study, we also found Tryptophanyl-tRNA synthetase and 1-Deoxy-D-Xylose-5-phosphate reductoisomerase proteins are the most common targets for Cassiarins.

Exploring Polypharmacology in Drug Design

Nowadays it is widely accepted that one compound can be able to hit several targets at once. This "magic shotgun" approach for drug development properly describes the mechanism of biomolecular recognition. The need to take into account the polypharmacology in structure-based drug design has led to the development of several computational tools. Here we present a computational protocol to identify promising compounds against several biological targets, a protocol known as inverse docking.

A high-throughput, computational system to predict if environmental contaminants can bind to human nuclear receptors

Some pollutants can bind to nuclear receptors (NRs) and modulate their activities. Predicting interactions of NRs with chemicals is required by various jurisdictions because these molecular initiating events can result in adverse, apical outcomes, such as survival, growth or reproduction. The goal of this study was to develop a high-throughput, computational method to predict potential agonists of NRs, especially for contaminants in the environment or to which people or wildlife are expected to be exposed, including both persistent and pseudo-persistent chemicals. A 3D-structure database containing 39 human NRs was developed. The database was then combined with AutoDock Vina to develop a System for Predicting Potential Effective Nuclear Receptors (SPEN), based on inverse docking of chemicals. The SPEN was further validated and evaluated by experimental results for a subset of 10 chemicals. Finally, to assess the robustness of SPEN, its ability to predict potentials of 40 chemicals to bind to some of the most studied receptors was evaluated. SPEN is rapid, cost effective and powerful for predicting binding of chemicals to NRs. SPEN was determined to be useful for screening chemicals so that pollutants in the environment can be prioritized for regulators or when considering alternative compounds to replace known or suspected contaminants with poor environmental profiles.

Prediction of protein targets of kinetin using in silico and in vitro methods: a case study on spinach seed germination mechanism

Kinetin, a cytokinin which promotes seed germination by inhibiting the action of abscisic acid, is an important molecule known to trigger various molecular mechanisms by interacting with an array of proteins shown from experimental observations in various model organisms. We report here the prediction of most probable protein targets of kinetin from spinach proteome using in silico approaches. Inverse docking and ligand-based similarity search was performed using kinetin as molecule. The former method prioritized six spinach proteins, whereas the latter method provided a list of protein targets retrieved from several model organisms. The most probable protein targets were selected by comparing the rank list of docking and ligand similarity methods. Both of these methods prioritized chitinase as the most probable protein target (ΔG pred = 5.064 kcal/mol) supported by the experimental structure of yeast chitinase 1 complex with kinetin (PDB: 2UY5) and Gliocladium roseum chitinase complex with 3,7-dihydro-1,3,7-trimethyl-1H-purine-2,6-dione (caffeine; 3G6M) which bears a 3D similarity of 0.43 with kinetin. An in vitro study to evaluate the effect of kinetin on spinach seed germination indicated that a very low concentration of kinetin (0.5 mg/l) did not show a significant effect compared to control in inducing seed germination process. Further, higher levels of kinetin (>0.5 mg/l) constituted an antagonist effect on spinach seed germination. It is anticipated that kinetin may have a molecular interaction with prioritized protein targets synthesized during the seed germination process and reduces growth. Thus, it appears that kinetin may not be a suitable hormone for enhancing spinach seed germination in vitro.