Structure-based Virtual Screening Campaign Research Articles

Identification of small molecules affecting the interaction between human hemoglobin and Staphylococcus aureus IsdB hemophore

Human hemoglobin (Hb) is the preferred iron source of Staphylococcus aureus. This pathogenic bacterium exploits a sophisticated protein machinery called Iron-regulated surface determinant (Isd) system to bind Hb, extract and internalize heme, and finally degrade it to complete iron acquisition. IsdB, the surface exposed Hb receptor, is a proven virulence factor of S. aureus and the inhibition of its interaction with Hb can be pursued as a strategy to develop new classes of antimicrobials. To identify small molecules able to disrupt IsdB:Hb protein–protein interactions (PPIs), we carried out a structure-based virtual screening campaign and developed an ad hoc immunoassay to screen the retrieved set of commercially available compounds. Saturation-transfer difference (STD) NMR was applied to verify specific interactions of a sub-set of molecules, chosen based on their efficacy in reducing the amount of Hb bound to IsdB. Among molecules for which direct binding was verified, the best hit was submitted to ITC analysis to measure the binding affinity to Hb, which was found to be in the low micromolar range. The results demonstrate the viability of the proposed in silico/in vitro experimental pipeline to discover and test IsdB:Hb PPI inhibitors. The identified lead compound will be the starting point for future SAR and molecule optimization campaigns.

Targeting the pyruvate dehydrogenase complex/pyruvate dehydrogenase kinase (PDC/PDK) axis to discover potent PDK inhibitors through structure-based virtual screening and pharmacological evaluation

Proliferating cancer cells are characterized by the Warburg effect, a metabolic alteration in which ATP is generated from cytoplasmic glycolysis instead of oxidative phosphorylation. The pyruvate dehydrogenase complex/pyruvate dehydrogenase kinase (PDC/PDK) axis plays a crucial role in this effect and has been identified as a potential target for anticancer drug development. Herein, we present the discovery and pharmacological evaluation of potent PDK inhibitors targeting the PDK/PDC axis. We successfully identified 6 compounds from a small molecule library through a structure-based virtual screening campaign and evaluated their enzymatic inhibitory potencies for PDK1-4. Our results indicated that compound 1 exhibited submicromolar inhibitory activities against PDK1-3 (IC50 = 109.3, 135.8, and 458.7 nM, respectively), but is insensitive to PDK4 (IC50 = 8.67 μM). Furthermore, compound 1 inhibited the proliferation of A549 cells with an EC50 value of 10.7 μM. In addition, compound 1 induced cell apoptosis, arrested the cell cycle at the S phase, and reduced cell invasion and migration, while showing low in vivo toxicity at a high dose. Based on these observations, it can be concluded that compound 1 is a promising anti-PDK1-3 lead that merits further investigation.

Exploring the Translational Gap of a Novel Class of Escherichia coli IspE Inhibitors.

Discovery of novel antibiotics needs multidisciplinary approaches to gain target enzyme and bacterial activities while aiming for selectivity over mammalian cells. Here, we report a multiparameter optimisation of a fragment-like hit that was identified through a structure-based virtual-screening campaign on Escherichia coli IspE crystal structure. Subsequent medicinal-chemistry design resulted in a novel class of E. coli IspE inhibitors, exhibiting activity also against the more pathogenic bacteria Pseudomonas aeruginosa and Acinetobacter baumannii. While cytotoxicity remains a challenge for the series, it provides new insights on the molecular properties for balancing enzymatic target and bacterial activities simultaneously as well as new starting points for the development of IspE inhibitors with a predicted new mode of action.

Discovery of novel methionine adenosyltransferase 2A (MAT2A) allosteric inhibitors by structure-based virtual screening

Methionine adenosyltransferase 2A (MAT2A) has been indicated as a drug target for oncology indications. Clinical trials with MAT2A inhibitors are currently on-going. Here, a structure-based virtual screening campaign was performed on the commercially available chemical space which yielded two novel MAT2A-inhibitor chemical series. The binding modes of the compounds were confirmed with X-ray crystallography. Both series have acceptable physicochemical properties and show nanomolar activity in the biochemical MAT2A inhibition assay and single-digit micromolar activity in the proliferation assay (MTAP -/- cell line). The identified compounds and the relating structural data could be helpful in related drug discovery projects.

Discovery of new Schistosoma mansoni aspartyl protease inhibitors by structure-based virtual screening.

Schistosomiasis is a neglected tropical disease caused by trematodes of the genus Schistosoma, with a limited treatment, mainly based on the use of praziquantel (PZQ). Currently, several aspartic proteases genes have already been identified within the genome of Schistosoma species. At least one enzyme encoded from this gene family (SmAP), named SmCD1, has been validated for the development of schistosomicidal drugs, since it has a key role in haemoglobin digestion by worms. In this work, we integrated a structure-based virtual screening campaign, enzymatic assays and adult worms ex vivo experiments aiming to discover the first classes of SmCD1 inhibitors. Initially, the 3D-structures of SmCD1, SmCD2 and SmCD3 were generated using homology modelling approach. Using these models, we prioritised 50 compounds from 20,000 compounds from ChemBridge database for further testing in adult worm aqueous extract (AWAE) and recombinant SmCD1 using enzymatic assays. Seven compounds were confirmed as hits and among them, two compounds representing new chemical scaffolds, named 5 and 19, had IC50 values against SmCD1 close to 100 μM while presenting binding efficiency indexes comparable to or even higher than pepstatin, a classical tight-binding peptide inhibitor of aspartyl proteases. Upon activity comparison against mammalian enzymes, compound 50 was selective and the most potent against the AWAE aspartic protease activity (IC50 = 77.7 μM). Combination of computational and experimental results indicate that compound 50 is a selective inhibitor of SmCD2. Compounds 5, 19 and 50 tested at low concentrations (10 uM) were neither cytotoxic against WSS-1 cells (48 h) nor could kill adult worms ex-vivo, although compounds 5 and 50 presented a slight decrease on female worms motility on late incubations times (48 or 72 h). Overall, the inhibitors identified in this work represent promising hits for further hit-to-lead optimisation.

Discovery of novel human lactate dehydrogenase inhibitors: Structure-based virtual screening studies and biological assessment

Most cancer cells switch their metabolism from mitochondrial oxidative phosphorylation to aerobic glycolysis to generate ATP and precursors for the biosynthesis of key macromolecules. The aerobic conversion of pyruvate to lactate, coupled to oxidation of the nicotinamide cofactor, is a primary hallmark of cancer and is catalyzed by lactate dehydrogenase (LDH), a central effector of this pathological reprogrammed metabolism. Hence, inhibition of LDH is a potential new promising therapeutic approach for cancer. In the search for new LDH inhibitors, we carried out a structure-based virtual screening campaign. Here, we report the identification of a novel specific LDH inhibitor, the pyridazine derivative 18 (RS6212), that exhibits potent anticancer activity within the micromolar range in multiple cancer cell lines and synergizes with complex I inhibition in the suppression of tumor growth. Altogether, our data support the conclusion that compound 18 deserves to be further investigated as a starting point for the development of LDH inhibitors and for novel anticancer strategies based on the targeting of key metabolic steps.

Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo.

The transient receptor potential vanilloid 1 (TRPV1) receptor is a nonselective cation channel, known to be involved in the regulation of many important physiological and pathological processes. In the last few years, it has been proposed as a promising target to develop novel anticonvulsant compounds. However, thermoregulatory effects associated with the channel inhibition have hampered the path for TRPV1 antagonists to become marketed drugs. In this regard, we conducted a structure-based virtual screening campaign to find potential TRPV1 modulators among approved drugs, which are known to be safe and thermally neutral. To this end, different docking models were developed and validated by assessing their pose and score prediction powers. Novobiocin, montelukast, and cinnarizine were selected from the screening as promising candidates for experimental testing and all of them exhibited nanomolar inhibitory activity. Moreover, the in vivo profiles showed promising results in at least one of the three models of seizures tested.

Accelerating high-throughput virtual screening through molecular pool-based active learning.

Structure-based virtual screening is an important tool in early stage drug discovery that scores the interactions between a target protein and candidate ligands. As virtual libraries continue to grow (in excess of 108 molecules), so too do the resources necessary to conduct exhaustive virtual screening campaigns on these libraries. However, Bayesian optimization techniques, previously employed in other scientific discovery problems, can aid in their exploration: a surrogate structure–property relationship model trained on the predicted affinities of a subset of the library can be applied to the remaining library members, allowing the least promising compounds to be excluded from evaluation. In this study, we explore the application of these techniques to computational docking datasets and assess the impact of surrogate model architecture, acquisition function, and acquisition batch size on optimization performance. We observe significant reductions in computational costs; for example, using a directed-message passing neural network we can identify 94.8% or 89.3% of the top-50 000 ligands in a 100M member library after testing only 2.4% of candidate ligands using an upper confidence bound or greedy acquisition strategy, respectively. Such model-guided searches mitigate the increasing computational costs of screening increasingly large virtual libraries and can accelerate high-throughput virtual screening campaigns with applications beyond docking.

Repositioning Dequalinium as Potent Muscarinic Allosteric Ligand by Combining Virtual Screening Campaigns and Experimental Binding Assays.

Structure-based virtual screening is a truly productive repurposing approach provided that reliable target structures are available. Recent progresses in the structural resolution of the G-Protein Coupled Receptors (GPCRs) render these targets amenable for structure-based repurposing studies. Hence, the present study describes structure-based virtual screening campaigns with a view to repurposing known drugs as potential allosteric (and/or orthosteric) ligands for the hM2 muscarinic subtype which was indeed resolved in complex with an allosteric modulator thus allowing a precise identification of this binding cavity. First, a docking protocol was developed and optimized based on binding space concept and enrichment factor optimization algorithm (EFO) consensus approach by using a purposely collected database including known allosteric modulators. The so-developed consensus models were then utilized to virtually screen the DrugBank database. Based on the computational results, six promising molecules were selected and experimentally tested and four of them revealed interesting affinity data; in particular, dequalinium showed a very impressive allosteric modulation for hM2. Based on these results, a second campaign was focused on bis-cationic derivatives and allowed the identification of other two relevant hM2 ligands. Overall, the study enhances the understanding of the factors governing the hM2 allosteric modulation emphasizing the key role of ligand flexibility as well as of arrangement and delocalization of the positively charged moieties.

PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results of AutoDock Vina and PLANTS.

We describe here our tool named PyPLIF HIPPOS, which was newly developed to analyze the docking results of AutoDock Vina and PLANTS. Its predecessor, PyPLIF (https://github.com/radifar/pyplif), is a molecular interaction fingerprinting tool for the docking results of PLANTS, exclusively. Unlike its predecessor, PyPLIF HIPPOS speeds up the computational times by separating the reference generation and docking analysis. PyPLIF HIPPOS also offers more options compared to PyPLIF. PyPLIF HIPPOS for Linux is stored as the Supporting Information in this application note and can be accessed in GitHub (https://github.com/radifar/PyPLIF-HIPPOS). Additionally, we present here the application of the tool in a retrospective structure-based virtual screening campaign targeting neuraminidase.

Molecular dynamics, MM/PBSA and in vitro validation of a novel quinazoline-based EGFR tyrosine kinase inhibitor identified using structure-based in silico screening

EGFR-TK has been a target strongly associated with the development of NSCLCs. A structure-based virtual screening campaign was launched against EGFR-TK by virtual screening a 3D library of 167 commercially available small molecules downloaded from ChemBridge Corporation. The virtual screen identified 12 virtual hit molecules, which were biologically evaluated against an EGFR-TK inhibitor-sensitive NSCLC cell line, A549. A quinazoline-based molecule 1, was most active and displayed ∼58% cytotoxicity at 20 μM single dose. The mode of cell death suggests molecule 1 induced apoptosis, which is characteristic of EGFR-TK pathway inhibition. A 50 ns MD simulation was conducted on three different systems: free EGFR-TK, molecule 1 complexed to EGFR-TK, and the positive control, lapatinib, complexed to EGFR-TK. The MD simulations showed increase in stabilisation of the EGFR-TK structure for the complexed systems, i.e., lower RMSDs and RMSFs for complexed EGFR-TK structures compared to the free EGFR-TK system. The binding affinities were estimated using MM/PBSA in the last 10 ns of the MD simulation that revealed comparable binding free energies between molecule 1 and lapatinib, ΔGbind = −25.0 and −23.9 kcal/mol, respectively. Per residue binding free energy decomposition studies revealed non-polar interactions contributed mostly to the binding free energies. Residues Leu718, Arg841 and Phe856 were predicted to contribute most to the binding free energies for molecule 1.

A structure-based approach towards the identification of novel antichagasic compounds: Trypanosoma cruzi carbonic anhydrase inhibitors

Trypanosoma cruzi carbonic anhydrase (TcCA) has recently emerged as an interesting target for the design of new compounds to treat Chagas disease. In this study we report the results of a structure-based virtual screening campaign to identify novel and selective TcCA inhibitors. The combination of properly validated computational methodologies such as comparative modelling, molecular dynamics and docking simulations allowed us to find high potency hits, with KI values in the nanomolar range. The compounds also showed trypanocidal effects against T. cruzi epimastigotes and trypomastigotes. All the candidates are selective for inhibiting TcCA over the human isoform CA II, which is encouraging in terms of possible therapeutic safety and efficacy.

WarpEngine, a Flexible Platform for Distributed Computing Implemented in the VEGA Program and Specially Targeted for Virtual Screening Studies.

The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of software for performing distributed simulations both in local and wide area networks. Despite being tailored for structure-based virtual screening campaigns, WarpEngine possesses the required flexibility to carry out distributed calculations utilizing various pieces of software, which can be easily encapsulated within this platform without changing their source codes. WarpEngine takes advantages of all cheminformatics features implemented in the VEGA ZZ program as well as of its largely customizable scripting architecture thus allowing an efficient distribution of various time-demanding simulations. To offer an example of the WarpEngine potentials, the manuscript includes a set of virtual screening campaigns based on the ACE data set of the DUD-E collections using PLANTS as the docking application. Benchmarking analyses revealed a satisfactory linearity of the WarpEngine performances, the speed-up values being roughly equal to the number of utilized cores. Again, the computed scalability values emphasized that a vast majority (i.e., >90%) of the performed simulations benefit from the distributed platform presented here. WarpEngine can be freely downloaded along with the VEGA ZZ program at www.vegazz.net .

Binary Quantitative Structure-Activity Relationship Analysis to Increase the Predictive Ability of Structure-Based Virtual Screening Campaigns Targeting Cyclooxygenase-2

Structure-Based Virtual Screening (SBVS) campaigns employing Protein-Ligand Interaction Fingerprints (PLIF) identification have served as a powerful strategy in fragments and ligands identification, both retro- and prospectively. Most of the SBVS campaigns employed PLIF by comparing them to a reference PLIF to calculate the Tanimoto-coefficient. Since the approach was reference dependent, it could lead to a very different discovery path if a different reference was used. In this article, references independent approach, i.e. decision trees construction using docking score and PLIF as the descriptors to increase the predictive ability of the SBVS campaigns in the identification of ligands for cyclooxygenase-2 is presented. The results showed that the binary Quantitative-Structure Activity Relationship (QSAR) analysis could significantly increase the predictive ability of the SBVS campaign. Moreover, the selected decision tree could also pinpoint the molecular determinants of the ligands binding to cyclooxygenase-2.

CONSTRUCTION AND RETROSPECTIVE VALIDATION OF STRUCTURE-BASED VIRTUAL SCREENING PROTOCOLS TO IDENTIFY POTENT LIGANDS FOR HUMAN ADRENERGIC BETA-2 RECEPTOR

Adrenergic Beta-2 Receptor (ADRB2) is a member of G-protein coupled receptors family, which has served as targets for more than 30% of top-selling drugs in the market. Recently, an enhanced dataset of ligands and decoys for ADRB2 has publicly available. However, the original retrospective structure-based virtual screening campaign accompanying the dataset showed relatively poor quality with enrichment factor of true positives at 1% false positives (EF 1% )value of 3.9. In this article, the construction and retrospective validation of a structure-based virtual screening protocol by employing PLANTS1.2 as the molecular docking software and PyPLIF as an alternative post docking scoring functions are presented. The results show that the developed protocols have better quality compared the original structure-based virtual screening with EF 1% values of 24.24 and 8.22 by using ChemPLP from PLANTS1.2 and by using Tc-PLIF from PyPLIF, respectively. Further investigation by performing systematic filtering resulted in the identification of D113, S203, and N293 as molecular determinants in ADRB2-ligand binding. Key words : Structure-based virtual screening, molecular docking, adrenergic beta-2 receptor, protein-ligand interaction fingerprinting, molecular determinants

Discovery of Novel Tubulin Inhibitors via Structure-Based Hierarchical Virtual Screening

To discover novel tubulin inhibitors, we performed structure-based virtual screening against the colchicine binding pocket. In combination with a hierarchical docking and scoring procedure, the structural information of an additional subpocket in colchicine site was applied to filter out the undesired docking hits. This strategy automatically resulted in 63 candidates meeting the structural and energetic criteria from a screening library containing approximately 100,000 diverse druglike compounds. Among them, nine molecules were chosen for experimental validation, which all share the similar binding pose and contain an enriched scaffold bearing thiophene core. Encouragingly, five compounds are active in tubulin polymerization assay. The most potent inhibitor, 2-(2-fluorobenzamido)-3-carboxamide-4,5-dimethylthiophene, is structurally distinct to any known colchicine site binders and has higher ligand efficiency than colchicine. On the basis of its predicted binding pose, we systematically probed its binding characteristics by testing series of structural modifications. The obtained structure-activity relationship results are consistent with our binding model, and the inhibition activities of two analogues are improved by 2-fold. We expect that the novel structure discovered in the present study may serve as a starting point for developing tubulin inhibitors with improved efficacy and fewer side effects. We also expect that our hierarchical strategy may be generally applicable in structure-based virtual screening campaigns.

MurD ligase from Escherichia coli: C-terminal domain closing motion

MurD (UDP- N-acetylmuramoyl- l-alanine: d-glutamate ligase), a three domain bacterial protein, catalyzes a highly specific incorporation of the d-glutamate into the cytoplasmic intermediate UDP- N-acetyl-muramoyl- l-alanine (UMA) utilizing ATP hydrolysis to ADP and P i. This reaction is part of the biosynthetic pathway enabling bacterial peptidoglycan synthesis. During our previous investigations of this complex dynamic antibacterial target, Targeted Molecular Dynamics (TMDs) simulations were performed (Perdih et al., Proteins: Struct. Funct. Bioinf., 2007) in order to examine the UMA and ATP substrates binding process and gain insights into the structural changes that occur during the conformational transitions of the C-terminal domain from the experimentally determined open structures to its active closed conformation. Off-path simulation (OPS) technique, an extension of the well-established Replica Path Method (RPATh), was applied to compare the relative energy of the two by C-terminal domain closing motions generated by TMD simulations. The first C-terminal domain closing process commenced from the experimental open structure in which this domain is located out-of plane to the N-terminal and central domains (open structure pdb:1EEH). In the second trajectory the conformational movement is confined to this plane only (open structure pdb:1E0D). The obtained results indicated that the C-terminal domain movement occurring from the out-of-plane starting structure is coupled with much higher energy changes compared to the motion of this domain within this plane which is more freely available to the enzyme. The results nicely corroborate experimental findings from recent structural studies. The study offers valuable information for novel structure-based virtual screening campaigns exploiting protein conformational flexibility.

Tandem Application of Virtual Screening and NMR Experiments in the Discovery of Brand New DNA Quadruplex Groove Binders

In the past decade, DNA G-quadruplexes have come into the limelight thanks to their biological implications and to their potential druggability in anticancer therapy. In particular, it has been found that small molecules that stabilize G-quadruplex structures are effective inhibitors of telomerase which plays a critical role in tumorigenesis. So far, the quadruplex groove recognition, which is expected to give a higher degree of selectivity over the other DNA structures, has been demonstrated for very few compounds. Thus with the aim of detecting new and structurally diverse groove binders, a structure-based virtual screening campaign has been performed using the X-ray structure of the [d(TGGGGT)](4) quadruplex. Remarkable results were achieved, and six brand new different molecular entities have been found to interact with the groove through NMR experiments. The reported results will certainly stimulate further studies aimed at the design and optimization of new quadruplex-specific groove binders to be applied as anticancer agents and for other diseases.