Homology models of the alpha7 acetylcholine receptor based upon bacterial receptors: Comparison of experimental and in silico derived data

Objective: In silico design and molecular docking of 1,2-benzisoxazole derivatives for their analgesic and anti-inflammatory activity using computational methods.Methods: In silico molecular properties of 1,2-benzisoxazole derivatives were predicted using various software’s such as Chemsketch, Molinspiration, PASS and Schrodinger to select compounds having optimum drug-likeness, molecular descriptors resembling those of standard drugs and not violating the ‘Lipinski rule of 5’. Molecular docking was performed on active site of nicotinic acetylcholine receptor (PDB: 2KSR) for analgesic activity and COX-2 (PDB: 6COX) for anti-inflammatory activity using Schrodinger under maestro molecular modelling environment.Results: From the results of molecular docking studies of 1,2-benzisoxazole derivatives, all the compounds showed good binding interactions with Nicotinic acetylcholine receptor and COX-2. Compounds 4a and 4c showed highest binding scores (-7.46 and-7.21 respectively) with nicotinic acetylcholine receptor and exhibited maximum analgesic activity. Compound 4a showed highest binding score (-7.8) with COX-2 and exhibited maximum anti-inflammatory activity.Conclusion: All the derivatives of 1,2-benzisoxazole showed good analgesic and anti-inflammatory activity as predicted using molecular docking on respective receptors.

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PRIMEval: Optimization and screening of multiplex oligonucleotide assays

Scientific Reports ◽

10.1038/s41598-019-55883-4 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 3

Author(s):

Rick Conzemius ◽

Michaela Hendling ◽

Stephan Pabinger ◽

Ivan Barišić

Keyword(s):

In Silico ◽

Multiplex Polymerase Chain Reaction ◽

Data Sets ◽

Use Case ◽

Chain Reaction ◽

Experimental Conditions ◽

Oligonucleotide Hybridization ◽

Polymerase Chain ◽

Derived Data ◽

By Products

AbstractThe development of multiplex polymerase chain reaction and microarray assays is challenging due to primer dimer formation, unspecific hybridization events, the generation of unspecific by-products, primer depletion, and thus lower amplification efficiencies. We have developed a software workflow with three underlying algorithms that differ in their use case and specificity, allowing the complete in silico evaluation of such assays on user-derived data sets. We experimentally evaluated the method for the prediction of oligonucleotide hybridization events including resulting products and probes, self-dimers, cross-dimers and hairpins at different experimental conditions. The developed method allows explaining the observed artefacts through in silico WGS data and thermodynamic predictions. PRIMEval is available publicly at https://primeval.ait.ac.at.

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ANALYSIS OF MOLECULAR DOCKING EFFICIENCY OF CLEISTANTHIN-A, AS AN ALTERNATIVE FOR NICOTINE ADDICTION

International Journal of Pharmacy and Pharmaceutical Sciences ◽

10.22159/ijpps.2018v10i4.24637 ◽

2018 ◽

Vol 10 (4) ◽

pp. 98

Author(s):

A. Amala Lourthuraj ◽

M. Masilamani Selvam ◽

Bharathi Ravikrishnan ◽

M. Vinoth ◽

Waheeta Hopper

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Protein Data Bank ◽

Acetylcholine Receptor ◽

Nicotinic Acetylcholine Receptor ◽

High Throughput ◽

In Silico ◽

Data Bank ◽

Tobacco Consumption ◽

Nicotinic Acetylcholine

Objective: The present research was aimed to understand the molecular docking efficiency of a plant-derived compound cleistanthin-A and a common ingredient in tobacco consumption nicotine with nicotinic acetylcholine receptor (nAChR).Methods: The 3-D structure of nAChR was retrieved from the protein data bank (ID 5AFH). Ligand was obtained from the PUBCHEM. The in silico protocol comprised of three steps: high-throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). The screened molecules were ranked accordingly using glide score. Schrödinger tool was used to perform the docking analysis.Results: The binding efficiency of the nicotine and cleistanthin-A was found to be docked at the cys-cys loop of the receptor. Based upon the glide score and glide energy it can be reported that, nicotine binding can be inhibited by the binding of cleistanthin-A to the nAChR.Conclusion: The docking efficiency of cleistanthin-A was good compared to nicotine towards nAChR. Hence, cleistanthin–A was derived as a better choice as an alternative for nicotine in smoke therapy.

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Homology models of mouse and rat estrogen receptor-α ligand-binding domain created by in silico mutagenesis of a human template: Molecular docking with 17β-estradiol, diethylstilbestrol, and paraben analogs

Computational Toxicology ◽

10.1016/j.comtox.2018.11.003 ◽

2019 ◽

Vol 10 ◽

pp. 1-16 ◽

Cited By ~ 10

Author(s):

Thomas L. Gonzalez ◽

James M. Rae ◽

Justin A. Colacino ◽

Rudy J. Richardson

Keyword(s):

Estrogen Receptor ◽

Molecular Docking ◽

Ligand Binding ◽

In Silico ◽

Estrogen Receptor Α ◽

Binding Domain ◽

Ligand Binding Domain ◽

17Β Estradiol ◽

Homology Models

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In Silico Finding of Key Interaction Mediated α3β4 and α7 Nicotinic Acetylcholine Receptor Ligand Selectivity of Quinuclidine-Triazole Chemotype

International Journal of Molecular Sciences ◽

10.3390/ijms21176189 ◽

2020 ◽

Vol 21 (17) ◽

pp. 6189

Author(s):

Kuntarat Arunrungvichian ◽

Sumet Chongruchiroj ◽

Jiradanai Sarasamkan ◽

Gerrit Schüürmann ◽

Peter Brust ◽

...

Keyword(s):

Amino Acid ◽

Acetylcholine Receptor ◽

Nicotinic Acetylcholine Receptor ◽

In Silico ◽

Amino Acid Residues ◽

Nicotinic Acetylcholine ◽

Selective Binding ◽

Ligand Selectivity ◽

Α7 Nachr ◽

Nachr Subtype

The selective binding of six (S)-quinuclidine-triazoles and their (R)-enantiomers to nicotinic acetylcholine receptor (nAChR) subtypes α3β4 and α7, respectively, were analyzed by in silico docking to provide the insight into the molecular basis for the observed stereospecific subtype discrimination. Homology modeling followed by molecular docking and molecular dynamics (MD) simulations revealed that unique amino acid residues in the complementary subunits of the nAChR subtypes are involved in subtype-specific selectivity profiles. In the complementary β4-subunit of the α3β4 nAChR binding pocket, non-conserved AspB173 through a salt bridge was found to be the key determinant for the α3β4 selectivity of the quinuclidine-triazole chemotype, explaining the 47–327-fold affinity of the (S)-enantiomers as compared to their (R)-enantiomer counterparts. Regarding the α7 nAChR subtype, the amino acids promoting a however significantly lower preference for the (R)-enantiomers were the conserved TyrA93, TrpA149 and TrpB55 residues. The non-conserved amino acid residue in the complementary subunit of nAChR subtypes appeared to play a significant role for the nAChR subtype-selective binding, particularly at the heteropentameric subtype, whereas the conserved amino acid residues in both principal and complementary subunits are essential for ligand potency and efficacy.

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In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking

10.7287/peerj.preprints.1582v1 ◽

2015 ◽

Author(s):

Kamariah Ibrahim ◽

Abubakar Danjuma ◽

Chyan Leong Ng ◽

Nor Azian Abdul Murad ◽

Roslan Harun ◽

...

Keyword(s):

Virtual Screening ◽

High Throughput ◽

Energy Minimization ◽

In Silico ◽

Structural Information ◽

Homology Modelling ◽

Ligand Docking ◽

Nmr Studies ◽

Homology Models ◽

High Throughput Virtual Screening

Background: Glioblastoma multiforme (GBM) is a grade IV brain tumor that arises from star-shaped glial cells supporting neural cells called astrocytes. The survival of GBM patients remains poor despite many specific molecular targets have been developed. Tousled-like kinase 1 (TLK1), a serine-threonine kinase, was identified to be overexpressed in cancer such as GBM. TLK1 plays an important role in controlling chromosomal aggregation, cell survival and proliferation. In vitro studies suggested that TLK1 is a potential target for some cancers. Hence, identification of suitable molecular inhibitors for TLK1 is warranted as new therapeutic agents in GBM. To date, there is no direct structural information available from X-ray crystallography and NMR studies for TLK1. In this study, we aimed to create a homology model of TLK1 and to identify suitable molecular inhibitors or compounds that are likely to bind and inhibit TLK1 activity via in silico high-throughput virtual screening (HTVS) protein-ligand docking. Methods: 3D homology models of TLK1 were derived from various servers including HOmology ModellER, i-Tasser, Psipred and Swiss Model. All models were evaluated using Swiss-Model Q-Mean server. Only one model was selected for further analysis. Further validation was performed using PDBsum, 3d2go, ProSA, Procheck analysis and ERRAT. Energy minimization was performed using YASARA energy minimization server. Subsequently, HTVS was performed using Molegro Virtual Docker 6.0 and candidate ligands from ligand.info database. Ligand-docking procedures were analyzed at the catalytic site of TLK1. Drug-like molecules were filtered using FAFDrugs3 ADME-Tox filter. Results and conclusion: High quality homology models were obtained from the 4B8M Aurora B kinase derived from Xenopus levias structure that share 33% sequence identity to TLK1. From the HTVS ligand-docking, two compounds were identified to be the potential inhibitors as it did not violate the Lipinski rule of five and CNS-based filter as a potential drug-like molecule for GBM.

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In silico family-wide profiling and 3D modelling of the poly(ADP-ribose) polymerase superfamily

Future Medicinal Chemistry ◽

10.4155/fmc-2020-0274 ◽

2020 ◽

Vol 12 (23) ◽

pp. 2105-2122

Author(s):

Caleb M Kam ◽

Amanda L Tauber ◽

Dean L Oosthuizen ◽

Stephan M Levonis ◽

Stephanie S Schweiker

Keyword(s):

Crystal Structures ◽

In Silico ◽

Catalytic Domain ◽

Parp Inhibitors ◽

3D Modelling ◽

Selective Inhibitors ◽

X Ray ◽

Homology Models

Background: Due to the conserved nature of the poly(ADP-ribose) polymerase (PARP) catalytic domain, the identification of unique residues is critical for the design of selective inhibitors. With inhibitors of the DNA-dependent PARP members already clinically approved, new efforts lie in discovering selective inhibitors for PARP5a and beyond. Targeting the noncatalytic domains, such as the macro2 and WWE domains may also provide a way to achieve selectivity. Methodology & results: This paper details the in silico profiling of x-ray crystal structures and homology models of the PARP catalytic, WWE and macro2 domains. PARP10 was the least conserved catalytic domain, with the macro2 and WWE domains possessing more unique residues than their catalytic counterparts. Conclusion: Overall, we identify unique residues to target when designing selective PARP inhibitors including HIS1610, TYR1620, ALA1627 and ARG1658 of the PARP14 catalytic domain, along with multiple unique residues across the PARP WWE and macro2 domains.

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Angiotensin II Type 1 Receptor Homology Models: A Comparison Between In Silico and the Crystal Structures

Methods in Molecular Biology - Rational Drug Design ◽

10.1007/978-1-4939-8630-9_27 ◽

2018 ◽

pp. 449-460

Author(s):

Tahsin F. Kellici

Keyword(s):

Angiotensin Ii ◽

Crystal Structures ◽

In Silico ◽

Homology Models

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Discovery of peptide ligands through docking and virtual screening at nicotinic acetylcholine receptor homology models

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1703952114 ◽

2017 ◽

Vol 114 (38) ◽

pp. E8100-E8109 ◽

Cited By ~ 24

Author(s):

Abba E. Leffler ◽

Alexander Kuryatov ◽

Henry A. Zebroski ◽

Susan R. Powell ◽

Petr Filipenko ◽

...

Keyword(s):

Ion Channels ◽

Ion Channel ◽

Acetylcholine Receptor ◽

Nicotinic Acetylcholine Receptor ◽

Critical Role ◽

Nicotinic Acetylcholine ◽

Docking Algorithm ◽

Addiction Therapy ◽

Peptide Toxins ◽

Homology Models

Venom peptide toxins such as conotoxins play a critical role in the characterization of nicotinic acetylcholine receptor (nAChR) structure and function and have potential as nervous system therapeutics as well. However, the lack of solved structures of conotoxins bound to nAChRs and the large size of these peptides are barriers to their computational docking and design. We addressed these challenges in the context of the α4β2 nAChR, a widespread ligand-gated ion channel in the brain and a target for nicotine addiction therapy, and the 19-residue conotoxin α-GID that antagonizes it. We developed a docking algorithm, ToxDock, which used ensemble-docking and extensive conformational sampling to dock α-GID and its analogs to an α4β2 nAChR homology model. Experimental testing demonstrated that a virtual screen with ToxDock correctly identified three bioactive α-GID mutants (α-GID[A10V], α-GID[V13I], and α-GID[V13Y]) and one inactive variant (α-GID[A10Q]). Two mutants, α-GID[A10V] and α-GID[V13Y], had substantially reduced potency at the human α7 nAChR relative to α-GID, a desirable feature for α-GID analogs. The general usefulness of the docking algorithm was highlighted by redocking of peptide toxins to two ion channels and a binding protein in which the peptide toxins successfully reverted back to near-native crystallographic poses after being perturbed. Our results demonstrate that ToxDock can overcome two fundamental challenges of docking large toxin peptides to ion channel homology models, as exemplified by the α-GID:α4β2 nAChR complex, and is extendable to other toxin peptides and ion channels. ToxDock is freely available atrosie.rosettacommons.org/tox_dock.

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