Structure-based Virtual Screening Protocol Research Articles

Structural insights into the inhibition of bacterial RecA by naphthalene polysulfonated compounds.

SummaryAs a promising target for alternative antimicrobials, bacterial recombinase A (RecA) protein has attracted much attention for its roles in antibiotic-driven SOS response and mutagenesis. Naphthalene polysulfonated compounds (NPS) such as suramin have previously been explored as antibiotic adjuvants targeting RecA, although the underlying structural bases for RecA-ligand interactions remain obscure. Based on our in silico predictions and documented activity of NPS in vitro, we conclude that the analyzed NPS likely interact with Tyr103 (Y103) and other key residues in the ATPase activity center (pocket A). For validation, we generated recombinant RecA proteins (wild-type versus Y103 mutant) to determine the binding affinities for RecA protein interactions with suramin and underexamined NPS in isothermal titration calorimetry. The corresponding dissociation constants (Kd) ranged from 11.5 to 18.8 μM, and Y103 was experimentally shown to be critical to RecA-NPS interactions.

Structure-Based Design and Molecular Dynamics Simulations of Pentapeptide AEYTR as a Potential Acetylcholinesterase Inhibitor

Structure-based virtual screening protocol to identify potent acetylcholinesterase inhibitors was retrospectively validated. The protocol could be employed to examine the potential of designed compounds as novel acetylcholinesterase inhibitors. In a research project designing short peptides as acetylcholinesterase inhibitors, peptide AEYTR emerged as one of the potential inhibitors. This article presents the design of AEYTR assisted by the validated protocol and guided by literature reviews followed by molecular dynamics studies to examine the interactions of the pentapeptide in the binding pocket of the acetylcholinesterase enzyme. The molecular dynamics simulations were performed using YASARA Structure in Google Cloud Platform. The peptide AEYTR was identified in silico as a potent acetylcholinesterase inhibitor with the average free energy of binding (DG) of -19.138 kcal/mol.

Pembuatan Protokol Penapisan Virtual Berbasis Stuktur (pvbs) untuk Identifikasi Ligan Inhibitor Reseptor Platelet-Activating Factor (PAF-r) sebagai Target Terapeutik Asma menggunakan YASARA

Platelet-activating factor receptors (PAF-r) is known as one of the receptors that affect asthma, while the Y-21480 ligand is reported as an effective, specific, and active PAF-r antagonist for asthma patients. Research in building structure-based virtual screening protocol (SBVS) for identification of PAF-r ligand inhibitors has been performed, the receptor crystal structure was obtained from the Protein Data Bank (PDB ID: 5zkp), while the ligand used as a leading compound is Y-24180, obtained from U.S. National Library of Medicine. Interactions between ligands and receptors are observed through molecular dynamics simulations using the YASARA program at intervals up to 20 nanoseconds, ligand-receptor binding stability occurs after a time interval of 2 nanoseconds, the lowest ligand-receptor binding energy occurs at a time interval of 1,401 picoseconds. Internal validation by re-docking 1,000 times the ligand to receptor resulted in a value of Root Mean Square Deviation (RMSD) of 0.6037 Å, confirmed that SBVS protocol was accurately able to reproduce the Y-24180 ligand pose on the 5zkp crystal structure, the protocol can be used as a new approach for investigation or design of compounds that have therapeutic potential as anti-asthma.

Structure-Based Virtual Screening, Molecular Dynamics and Binding Free Energy Calculations of Hit Candidates as ALK-5 Inhibitors.

Activin-like kinase 5 (ALK-5) is involved in the physiopathology of several conditions, such as pancreatic carcinoma, cervical cancer and liver hepatoma. Cellular events that are landmarks of tumorigenesis, such as loss of cell polarity and acquisition of motile properties and mesenchymal phenotype, are associated to deregulated ALK-5 signaling. ALK-5 inhibitors, such as SB505154, GW6604, SD208, and LY2157299, have recently been reported to inhibit ALK-5 autophosphorylation and induce the transcription of matrix genes. Due to their ability to impair cell migration, invasion and metastasis, ALK-5 inhibitors have been explored as worthwhile hits as anticancer agents. This work reports the development of a structure-based virtual screening (SBVS) protocol aimed to prospect promising hits for further studies as novel ALK-5 inhibitors. From a lead-like subset of purchasable compounds, five molecules were identified as putative ALK-5 inhibitors. In addition, molecular dynamics and binding free energy calculations combined with pharmacokinetics and toxicity profiling demonstrated the suitability of these compounds to be further investigated as novel ALK-5 inhibitors.

Development of a Graphical User Interface Application to Identify Marginal and Potent Ligands for Estrogen Receptor Alpha

Employing ensemble Protein-Ligand Interaction Fingerprints (ensPLIF) as descriptors in post retrospective Structure-Based Virtual Screening (SBVS) campaigns Quantitative Structure-Activity Relationship (QSAR) analysis has been proven to significantly increase the predictive ability in the identification of potent ligands for estrogen receptor alpha (ERα). In the research presented in this article, similar approaches have been performed to construct and retrospectively validate an SBVS protocol to identify marginal ligands for ERα. Based on both validated SBVS protocols, a graphical-user-interface (GUI) application to identify if a compound is a non-, moderate or potent ligand for ERα was developed. The GUI application was subsequently used to virtually screen genistin, genistein, daidzin, and daidzein, followed by in vitro test employing a cytotoxic assay using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) method.

Structure-based identification of potent VEGFR-2 inhibitors from in vivo metabolites of a herbal ingredient.

Vascular endothelial growth factor receptor-2 (VEGFR-2) is one of the regulatory elements of angiogenesis that is expressed highly in various diseases and is also essential for solid tumor growth. The present study was aimed at identifying potent inhibitors of VEGFR-2 by considering herbal secondary metabolites; as natural molecules are less toxic than synthetic derivatives. A structure-based virtual screening protocol consisting of molecular docking, MM-GBSA and ADME/T analysis was initially used to screen a library of in vivo metabolites of the herbal ingredient. Using a fixed cutoff value, four potent virtual hits were identified from molecular docking, ADME/T and binding affinity calculations, which were considered further for molecular dynamics (MD) simulation to broadly describe the binding mechanisms to VEGFR-2. The results suggested that these molecules have high affinity for the catalytic region of VEGFR-2, and form strong hydrophobic and polar interactions with the amino acids involved in the binding site of ATP and linker regions of the catalytic site. Subsequently, the stability of the docked complexes and binding mechanisms were evaluated by MD simulations, and the energy of binding was calculated through MM-PBSA analysis. The results uncovered two virtual hits, designated ZINC14762520 and ZINC36470466, as VEGFR-2 inhibitors, and suggested that they bind to kinase domainin an ATP-competitive manner. These virtual hits will offer a suitable starting point for the further design of their various analogs, allowing a rational search for more effective inhibitors in the future. Graphical abstract.

Structure-based virtual screening for novel chymase inhibitors by in silico fragment mapping

The term chymase refers to a family of chymotrypsin-like serine proteases stored within the secretory granules of mast cells. Recently, a variety of small molecule inhibitors for chymase have been developed with a primary focus on the treatment of cardiovascular diseases. Despite the expected therapeutic benefit of these chymase inhibitors, they have not been used clinically. Here, we attempted to identify new chymase inhibitors using a multistep structure-based virtual screening protocol combined with our knowledge-based in silico fragment mapping technique. The mapping procedure identified fragments with novel modes of interaction at the oxyanion hole of chymase. Next, we constructed a three-dimensional (3D) pharmacophore model and retrieved eight candidate chymase inhibitors from a commercial database that included approximately five million compounds. This selection was achieved using a multistep virtual screening protocol, which combined a 3D pharmacophore-based search, docking calculations, and analyses of binding free energy. One of the eight compounds exhibited concentration-dependent chymase inhibitory activity, which could be further optimized to develop more potent chymase inhibitors.

Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space

Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain. Although these are selective to calpains over other cysteine proteases, their mode of action has remained elusive due to their ability to inhibit the active site domain with and without the presence of PEF(S), with similar potency. These findings have led to the question of whether the inhibitory response can be attributed to an allosteric mode of action or alternatively to inhibition at the active site. In order to address this problem, we report a structure-based virtual screening protocol as a novel approach for the discovery of PEF(S) binders that populate a novel chemical space. We have identified compound 1, Vidupiprant, which is shown to bind to the PEF(S) domain by the TNS displacement method, and it exhibited specificity in its allosteric mode of inhibition. Compound 1 inhibited the full-length calpain-1 complex with a higher potency (IC50 = 7.5 μM) than the selective, cell-permeable non-peptide calpain inhibitor, PD150606 (IC50 = 19.3 μM), where the latter also inhibited the active site domain in the absence of PEF(S) (IC50 = 17.8 μM). Hence the method presented here has identified known compounds with a novel allosteric mechanism for the inhibition of calpain-1. We show for the first time that the inhibition of enzyme activity can be attributed to an allosteric mode of action, which may offer improved selectivity and a reduced side-effects profile.

Practices in Molecular Docking and Structure-Based Virtual Screening.

Drug discovery has evolved significantly over the past two decades. Progress in key areas such as molecular and structural biology has contributed to the elucidation of the three-dimensional structure and function of a wide range of biological molecules of therapeutic interest. In this context, the integration of experimental techniques, such as X-ray crystallography, and computational methods, such as molecular docking, has promoted the emergence of several areas in drug discovery, such as structure-based drug design (SBDD). SBDD strategies have been broadly used to identify, predict and optimize the activity of small molecules toward a molecular target and have contributed to major scientific breakthroughs in pharmaceutical R&D. This chapter outlines molecular docking and structure-based virtual screening (SBVS) protocols used to predict the interaction of small molecules with the phosphatidylinositol-bisphosphate-kinase PI3Kδ, which is a molecular target for hematological diseases. A detailed description of the molecular docking and SBVS procedures and an evaluation of the results are provided.

BINARY QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS IN RETROSPECTIVE STRUCTURE-BASED VIRTUAL SCREENING CAMPAIGNS TARGETING ESTROGEN RECEPTOR ALPHA

Objective: The objective of this study is to construct predictive unbiased structure-based virtual screening (SBVS) protocols to identify potent ligands for estrogen receptor alpha by combining molecular docking, protein-ligand interaction fingerprinting (PLIF), and binary quantitative structure-activity relationship (QSAR) analysis using recursive partition and regression tree method.Methods: Employing the enhanced version of a directory of useful decoys, SBVS protocols using molecular docking simulations, and PLIF were constructed and retrospectively validated. To avoid bias, SMILES format of the compounds was used. The predictive abilities of the SBVS protocols were then compared based on the enrichment factor (EF) and the F-measure values.Results: The SBVS protocols resulted in this research were SBVS_1 (employing docking scores of the best pose on every compound to rank the results and selecting compounds within 1% false positives as positive), SBVS_2 (employing decision tree resulted from the binary QSAR analysis using docking scores and PLIF bitstrings of the best pose of every compound as descriptors), and SBVS_3 (employing decision tree resulted from the binary QSAR analysis using ensemble PLIF of the selected poses from optimized docking score as the cutoff). The EF values of SBVS_1, SBVS_2, and SBVS_3 are 28.315, 576.084, and 713.472, respectively, while their F-measure values are 0.310, 0.573, and 0.769, respectively.Conclusion: Highly predictive unbiased SBVS protocols to identify potent estrogen receptor alpha ligands were constructed. Further application in prospective screening is therefore highly suggested.

3D-QSAR, Virtual Screening, Docking and Design of Dual PI3K/mTOR Inhibitors with Enhanced Antiproliferative Activity.

Altered activity of PI3K/mTOR signaling pathway is one of the most common aberrations found in various forms of neoplastic lesions. Dual inhibition of PI3K and mTOR represents a reasonably attractive concept in potential cancer treatment. The main aim of this work was to design novel PI3K/mTOR inhibitors with enhanced antiproliferative activity. 3D-QSAR pharmacophore modeling studies were performed on two groups comprised of 37 and 48 dual PI3K/mTOR inhibitors. Obtained 3D-pharmacophores were used in design of new dual PI3K/mTOR inhibitors. Based on the in silico ADMET data, structure-based virtual screening and docking studies, the most promising novel candidates were selected. Four reliable PLS models with good statistical parameters (q2 = 0.72, r2 pred = 0.93; q2 = 0.81, r2 pred= 0.88 for 3D-QSAR (mTOR) models and q2 = 0.79, r2pred = 0.93; q2 = 0.79, r2 pred = 0.94 for 3D-QSAR (PI3K) models) were obtained and new highly selective and potent dual PI3K/mTOR inhibitors were designed. Further in silico ADMET profiling of the designed compounds selected the most promising novel PI3K/mTOR inhibitors as drug candidates. Results of the 3D-QSAR studies were confirmed by structure-based virtual screening protocol that identified selected designed compounds as a best fit for PI3K and mTOR receptors. Molecular docking studies on PI3K and mTOR crystal structures revealed the key active site residues involved in binding of PI3K/mTOR ligands. After combining the results of 3D-QSAR, ADMET profiling, virtual screening and docking, compounds 56-57 and 56-62 were chosen as the most promising new dual PI3K/mTOR inhibitors.

Computer-aided Design of Chalcone Derivatives as Lead Compounds Targeting Acetylcholinesterase

One of well-established biological activities for chalcone derivatives is as acetylcholinesterase inhibitors, which can be developed for the therapy of Alzheimer’s disease. Assisted byretrospectively validated structure-based virtual screening (SBVS) protocol to identify potent acetylcholinesterase inhibitors, 80chalcone derivatives were designed and virtually screened. The F -measure value as the parameter of the predictive ability of the SBVS protocol developed in the research presented in this article was 0.413, which was considerably better than the original SBVS protocol ( F -measure = 0.226). Among the screened chalcone derivatives two were selected as potential lead compounds to designpotent inhibitors for acetylcholinesterase: 3-[4-(benzyloxy)-3-methoxyphenyl]-1-(4-hydroxy-3-methoxyphenyl)prop-2-en-1-one( 3k ) and 3-[4-(benzyloxy)-3-methoxyphenyl]-1-(4-hydroxyphenyl)prop-2-en-1-one ( 4k ).

Vitual screening and binding mode elucidation of curcumin analogues on Cyclooxygenase-2 using AYO_COX2_V1.1 protocol

Curcumin is yellow colored phenolic compounds contained in Curcuma longa. Curcumin is known to have biological activities as anti-inflammatory, antiviral, antioxidant, and anti-infective agent [1]. Synthesis of curcumin analogue compounds has been done and some of them had biological activity like curcumin. In this research, the virtual screening of curcumin analogue compounds has been conducted. The purpose of this research was to determine the activity of these compounds as selective Cyclooxygenase-2inhibitors in in-silico. Binding mode elucidation was made by active and inactive representative compounds to see the interaction of the amino acids in the binding site of the compounds. This research used AYO_COX2_V.1.1, a structure-based virtual screening protocol (SBVS) that has been validated by Mumpuni E et al, 2014 [2]. AYO_COX2_V.1.1 protocol using a variety of integrated applications such as SPORES, PLANTS, BKchem, OpenBabel and PyMOL. The results of virtual screening conducted on 49 curcumin analogue compounds obtained 8 compounds with 4 active amino acid residues (GLY340, ILE503, PHE343, and PHE367) that were considered active as COX-2 inhibitor.

An in vitro and in vivo evaluation of new potential trans-sialidase inhibitors of Trypanosoma cruzi predicted by a computational drug repositioning method

Chagas disease is one of the most important neglected parasitic diseases afflicting developed and undeveloped countries. There are currently limited options for inexpensive and secure pharmacological treatment. In this study, we employed a structure-based virtual screening protocol for 3180 FDA-approved drugs for repositioning of them as potential trans-sialidase inhibitors. In vitro and in vivo evaluations were performed for the selected drugs against trypomastigotes from the INC-5 and NINOA strains of T. cruzi. Also, inhibition of sialylation by the trans-sialidase enzyme reaction was evaluated using high-performance anion-exchange chromatography with pulse amperometric detection to confirm the mechanism of action. Results from the computational study showed 38 top drugs with the best binding-energies. Four compounds with antihistaminic, anti-hypertensive, and antibiotic properties showed better trypanocidal effects (LC50 range = 4.5–25.8 μg/mL) than the reference drugs, nifurtimox and benznidazole (LC50 range = 36.1–46.8 μg/mL) in both strains in the in vitro model. The anti-inflammatory, sulfasalazine showed moderate inhibition (37.6%) of sialylation in a trans-sialidase enzyme inhibition reaction. Sulfasalazine also showed the best trypanocidal effects in short-term in vivo experiments on infected mice. This study suggests for the first time that the anti-inflammatory sulfasalazine could be used as a lead compound to develop new trans-sialidase inhibitors.

Structure-Based Virtual Screening Protocol for in Silico Identification of Potential Thyroid Disrupting Chemicals Targeting Transthyretin.

Thyroid disruption by xenobiotics is associated with a broad spectrum of severe adverse outcomes. One possible molecular target of thyroid hormone disrupting chemicals (THDCs) is transthyretin (TTR), a thyroid hormone transporter in vertebrates. To better understand the interactions between TTR and THDCs, we determined the crystallographic structures of human TTR in complex with perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and 2,2',4,4'-tetrahydroxybenzophenone (BP2). The molecular interactions between the ligands and TTR were further characterized using molecular dynamics simulations. A structure-based virtual screening (VS) protocol was developed with the intention of providing an efficient tool for the discovery of novel TTR-binders from the Tox21 inventory. Among the 192 predicted binders, 12 representatives were selected, and their TTR binding affinities were studied with isothermal titration calorimetry, of which seven compounds had binding affinities between 0.26 and 100 μM. To elucidate structural details in their binding to TTR, crystal structures were determined of TTR in complex with four of the identified compounds including 2,6-dinitro-p-cresol, bisphenol S, clonixin, and triclopyr. The compounds were found to bind in the TTR hormone binding sites as predicted. Our results show that the developed VS protocol is able to successfully identify potential THDCs, and we suggest that it can be used to propose THDCs for future toxicological evaluations.

Identification and Molecular Interaction Studies of Thyroid Hormone Receptor Disruptors among Household Dust Contaminants.

Thyroid hormone disrupting chemicals (THDCs), often found abundantly in the environment, interfere with normal thyroid hormone signaling and induce physiological malfunctions, possibly by affecting thyroid hormone receptors (THRs). Indoor dust ingestion is a significant human exposure route of THDCs, raising serious concerns for human health. Here, we developed a virtual screening protocol based on an ensemble of X-ray crystallographic structures of human THRβ1 and the generalized Born solvation model to identify potential THDCs targeting the human THRβ1 isoform. The protocol was applied to virtually screen an in-house indoor dust contaminant inventory, yielding 31 dust contaminants as potential THRβ1 binders. Five predicted binders and one negative control were tested using isothermal titration calorimetry, of which four, i.e., 2,4,5-trichlorophenoxyacetic acid (2,4,5-T), bisphenol A (3-chloro-2-hydroxypropyl) (2,3-dihydroxypropyl) ether (BADGE-HCl-H2O), 2,2',4,4'-tetrahydroxybenzophenone (BP2), and 2,4-dichlorophenoxyacetic acid (2,4-D), were identified as THRβ1 binders with binding affinities ranging between 60 μM and 460 μM. Molecular dynamics (MD) simulations were employed to examine potential binding modes of these binders and provided a rationale for explaining their specific recognition by THRβ1. The combination of in vitro binding affinity measurements and MD simulations allowed identification of four new potential THR-targeting THDCs that have been found in household dust. We suggest using the developed structure-based virtual screening protocol to identify and prioritize testing of potential THDCs.

OPTIMIZING STRUCTURE-BASED VIRTUAL SCREENING PROTOCOL TO IDENTIFY PHYTOCHEMICALS AS CYCLOOXYGENASE-2 INHIBITORS

By employing Databases of Useful Decoys (DUD) and its enhanced version (DUD-E), several attempts to construct validated Structure-based Virtual Screening (SBVS) protocols to identify cyclooxygenase-2 (COX-2) inhibitors have been performed. Both databases tagged active COX-2 inhibitors for compounds with IC 50 values < 1mM. In the search for phytochemicals as natural COX-2 inhibitors, however, most of their IC 50 values are in the micromolar range, which will likely be identified as non-inhibitors for COX-2 by the available SBVS protocols. In this article, validation of an SBVS protocol by adding marginal active COX-2 inhibitors from DUD-E as active compounds is presented. Binary quantitative-structure activity relationship analysis by using recursive partition and regression tree method was performed subsequently to optimize the predictive ability of the protocol. The enrichment factor and the F -measure values of the optimized protocol could reach 44.78 and 0.47, respectively. The optimized protocol could identify 1 out of 9 phytochemicals as COX-2 inhibitors.

Determination of ligand position in aspartic proteases by correlating tanimoto coefficient and binding affinity with root mean square deviation

The objective of this study was to develop and validate of Structure-Based Virtual Screening (SBVS) protocol which was used to select the best pose of inhibitor-aspartic protease complex interaction in the active sites of HIV-1 protease, plasmepsin I, II, and IV. Retrospective validation was performed on enhanced dataset of ligands and decoys (DUD-E) for HIV-1 protease. The crystal structures 1XL2, 3QS1, 1SME, and 1LS5 were obtained from Protein Data Bank. The protocol was then challenged to re-dock the ligands to its origin places in the active sites by correlating Tanimoto coefficient (Tc) and binding affinity (Ei) with Root Mean Square Deviation (RMSD). Enrichment factor at 1% false positives (EF1%) values for Tc and Ei were 18.26 and 9.03, respectively, while the Area Under Curve (AUC) values for Tc and Ei were 76.84 and 60.95. The SBVS protocol was validand showed better virtual screening qualities in ligand identification for HIV-1 protease compared to the originalprotocol accompanying the release of DUD-E and showed its ability to reproduce the co-crystal pose in the HIV1 protease, plasmepsin I,II,and IV to its origin places in the active sites.

Homology Model-Based Virtual Screening for the Identification of Human Helicase DDX3 Inhibitors.

Targeting cellular cofactors instead of viral enzymes represents a new strategy to combat infectious diseases, which should help to overcome the problem of viral resistance. Recently, it has been revealed that the cellular ATPase/RNA helicase X-linked DEAD-box polypeptide 3 (DDX3) is an essential host factor for the replication of several viruses such as HIV, HCV, JEV, Dengue, and West Nile. Accordingly, a drug targeting DDX3 could theoretically inhibit all viruses that are dependent on this host factor. Herein, for the first time, a model of hDDX3 in its closed conformation, which binds the viral RNA was developed by using the homology module of Prime through the Maestro interface of Schrodinger. Next, a structure-based virtual screening protocol was applied to identify DDX3 small molecule inhibitors targeting the RNA binding pocket. As a result, an impressive hit rate of 40% was obtained with the identification of 10 active compounds out of the 25 tested small molecules. The best poses of the active ligands highlighted the crucial residues to be targeted for the inhibition of the helicase activity of DDX3. The obtained results confirm the reliability of the constructed DDX3/RNA model and the proposed computational strategy for investigating novel DDX3 inhibitors.

Structure-based virtual screening and discovery of New PPARδ/γ dual agonist and PPARδ and γ agonists.

Peroxisome proliferator-activated receptors (PPARs) are involved in the control of carbohydrate and lipid metabolism and are considered important targets to treat diabetes mellitus and metabolic syndrome. The available PPAR ligands have several side effects leading to health risks justifying the search for new bioactive ligands to activate the PPAR subtypes, in special PPARδ, the less studied PPAR isoform. Here, we used a structure-based virtual screening protocol in order to find out new PPAR ligands. From a lead-like subset of purchasable compounds, we identified 5 compounds with potential PPAR affinity and, from preliminary in vitro assays, 4 of them showed promising biological activity. Therefore, from our in silico and in vitro protocols, new PPAR ligands are potential candidates to treat metabolic diseases.