scholarly journals QSAR-Based Computational Approaches to Accelerate the Discovery of Sigma-2 Receptor (S2R) Ligands as Therapeutic Drugs

Molecules ◽  
2021 ◽  
Vol 26 (17) ◽  
pp. 5270
Author(s):  
Yangxi Yu ◽  
Hiep Dong ◽  
Youyi Peng ◽  
William J. Welsh
Keyword(s):  
Binding Affinity ◽  
Model Building ◽  
Present Report ◽  
Antidepressant Drug ◽  
Biological Evaluation ◽  
Qsar Modeling ◽  
Therapeutic Drugs ◽  
First Case ◽  
Qsar Models ◽  
Approved Drugs

S2R overexpression is associated with various forms of cancer as well as both neuropsychiatric disorders (e.g., schizophrenia) and neurodegenerative diseases (Alzheimer’s disease: AD). In the present study, three ligand-based methods (QSAR modeling, pharmacophore mapping, and shape-based screening) were implemented to select putative S2R ligands from the DrugBank library comprising 2000+ entries. Four separate optimization algorithms (i.e., stepwise regression, Lasso, genetic algorithm (GA), and a customized extension of GA called GreedGene) were adapted to select descriptors for the QSAR models. The subsequent biological evaluation of selected compounds revealed that three FDA-approved drugs for unrelated therapeutic indications exhibited sub-1 uM binding affinity for S2R. In particular, the antidepressant drug nefazodone elicited a S2R binding affinity Ki = 140 nM. A total of 159 unique S2R ligands were retrieved from 16 publications for model building, validation, and testing. To our best knowledge, the present report represents the first case to develop comprehensive QSAR models sourced by pooling and curating a large assemblage of structurally diverse S2R ligands, which should prove useful for identifying new drug leads and predicting their S2R binding affinity prior to the resource-demanding tasks of chemical synthesis and biological evaluation.

2D- and 3D-QSAR Modeling of Imidazole-Based Glutaminyl Cyclase Inhibitors

2019 ◽  
Vol 15 ◽  
Author(s):  
Omar Husham Ahmed Al-Attraqchi ◽  
Katharigatta N. Venugopala
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Virtual Screening ◽  
Neurodegenerative Disorder ◽  
3D Qsar ◽  
Biological Evaluation ◽  
Qsar Modeling ◽  
Glutaminyl Cyclase ◽  
Validation Parameters ◽  
Qsar Models

Background: Glutaminyl cyclase (QC) is a novel target in the battle against Alzheimer’s disease, a highly prevalent neurodegenerative disorder. QC inhibitors have the potential to be developed as therapeutically useful anti-Alzheimer’s disease agents. Methods: Linear and non-linear 2D-quantitative structure–activity relationship (QSAR) models were developed using stepwise-multiple linear regression (S-MLR) and neural networks. Partial least squares (PLS) method was used to develop a 3D-QSAR model. Also, the developed models were used in a virtual screening of the ZINC database to identify potential QC inhibitors. Results: The 2D neural network model showed superior predictive ability, as demonstrated by the validation parameters R2 = 0.933, Q2 = 0.886 and R2pred = 0.911. The 3D-QSAR model’s steric and electrostatic fields’ isocontour maps were visualized and revealed important structural requirements associated with good activity. The virtual screening identified six compounds as potentially active QC inhibitors with improved pharmacokinetic profiles. Conclusion: The developed QSAR models can be used to predict the activity of compounds not yet synthesized and prioritize their synthesis and biological evaluation. Also, potentially active QC inhibitors have been identified with attractive lead-like properties that can be used to develop anti-Alzheimer’s disease agents.

Elaboration of Novel TTK1 Inhibitory Leads via QSAR-Guided Selection of Crystallographic Pharmacophores Followed By In vitro Assay

2020 ◽  
Vol 16 ◽  
Author(s):  
Mahmoud A. Al-Sha'er ◽  
Mutasem O. Taha
Keyword(s):  
Standard Error ◽  
Qsar Model ◽  
Qsar Modeling ◽  
Vitro Assay ◽  
Physicochemical Descriptors ◽  
Qsar Models ◽  
Ic50 Values ◽  
Pharmacophore Hypotheses ◽  
Selection Of

Introduction: Tyrosine threonine kinase (TTK1) is a key regulator of chromosome segregation. TTK targeting received recent concern for the enhancement of possible anticancer therapies. Objective: In this regard we employed our well-known method of QSAR-guided selection of best crystallographic pharmacophore(s) to discover considerable binding interactions that anchore inhibitors into TTK1 binding site. Method:Sixtyone TTK1 crystallographic complexes were used to extract 315 pharmacophore hypotheses. QSAR modeling was subsequently used to choose a single crystallographic pharmacophore that when combined with other physicochemical descriptors elucidates bioactivity discrepancy within a list of 55 miscellaneous inhibitors. Results: The best QSAR model was robust and predictive (r2(55) = 0.75, r2LOO = 0.72 , r2press against external testing list of 12 compounds = 0.67), Standard error of estimate (training set) (S)= 0.63 , Standard error of estimate (testing set)(Stest) = 0.62. The resulting pharmacophore and QSAR models were used to scan the National Cancer Institute (NCI) database for new TTK1 inhibitors. Conclusion: Five hits confirmed significant TTK1 inhibitory profiles with IC50 values ranging between 11.7 and 76.6 micM.

QSAR modeling of cumulative environmental end-points for the prioritization of hazardous chemicals

2018 ◽  
Vol 20 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Paola Gramatica ◽  
Ester Papa ◽  
Alessandro Sangion
Keyword(s):  
Hazardous Chemicals ◽  
Qsar Modeling ◽  
End Points ◽  
Qsar Models

Indexes for the prioritization of potential hazardous chemicals can be derived and modelled by combining PCA and QSAR models.

CUBITAL TUNNEL SYNDROME DUE TO GIANT CELL TUMOUR OF TENDON SHEATHS

Hand Surgery ◽  
2006 ◽  
Vol 11 (01n02) ◽  
pp. 89-91 ◽  
Author(s):  
G. Mitsionis ◽  
E. E. Pakos ◽  
I. Gavriilidis ◽  
Anna Batistatou
Keyword(s):  
Giant Cell ◽  
Giant Cell Tumour ◽  
Present Report ◽  
Cubital Tunnel Syndrome ◽  
Cell Tumour ◽  
Cubital Tunnel ◽  
Malignant Neoplasms ◽  
Entrapment Neuropathies ◽  
First Case ◽  
Tunnel Syndrome

Cubital tunnel syndrome is one of the most common entrapment neuropathies in adults. It is mainly caused by the depression of ulnar nerve from normal structures at the elbow area. Despite the fact that several pathgological entities can be potential mechanisms of the syndrome, the pathogenesis due to benign or malignant neoplasms is extremely rare. In the present report we describe the first case of cubital tunnel syndrome due to giant cell tumour of the tendon sheaths.

scholarly journals Design, Synthesis, Biological Evaluation, and Molecular Modeling of 2-Difluoromethylbenzimidazole Derivatives as Potential PI3Kα Inhibitors

Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 387
Author(s):  
Xiangcong Wang ◽  
Moxuan Zhang ◽  
Ranran Zhu ◽  
Zhongshan Wu ◽  
Fanhong Wu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Modeling ◽  
3D Qsar ◽  
Binding Mode ◽  
Biological Evaluation ◽  
Field Analysis ◽  
Dynamics Simulation ◽  
Comfa Model ◽  
Qsar Models

PI3Kα is one of the potential targets for novel anticancer drugs. In this study, a series of 2-difluoromethylbenzimidazole derivatives were studied based on the combination of molecular modeling techniques 3D-QSAR, molecular docking, and molecular dynamics. The results showed that the best comparative molecular field analysis (CoMFA) model had q2 = 0.797 and r2 = 0.996 and the best comparative molecular similarity indices analysis (CoMSIA) model had q2 = 0.567 and r2 = 0.960. It was indicated that these 3D-QSAR models have good verification and excellent prediction capabilities. The binding mode of the compound 29 and 4YKN was explored using molecular docking and a molecular dynamics simulation. Ultimately, five new PI3Kα inhibitors were designed and screened by these models. Then, two of them (86, 87) were selected to be synthesized and biologically evaluated, with a satisfying result (22.8 nM for 86 and 33.6 nM for 87).

scholarly journals Epileptic Seizures Induced by a Spontaneous Carotid Cavernous Fistula

2016 ◽  
Vol 2016 ◽  
pp. 1-3
Author(s):  
Güner Koyuncu Çelik ◽  
Erkan Yildirim
Keyword(s):  
Present Report ◽  
Epileptic Seizures ◽  
Digital Subtraction ◽  
Resonance Imaging ◽  
Carotid Cavernous Fistula ◽  
Cavernous Fistula ◽  
The Past ◽  
First Case ◽  
Eye Symptoms ◽  
Magnetic Resonance Imaging Mri

A 79-year-old woman was admitted to our emergency department with complaints of fainting and loss of consciousness three times during the past month. She was diagnosed with epilepsy and started to be treated with antiepileptic drug. Physical examination showed, in the left eye, chemosis, limited eye movements in all directions, and minimal exophthalmos as unexisting symptoms on admission developed on the sixth day. Orbital magnetic resonance imaging (MRI) and digital subtraction angiography (DSA) imaging revealed a carotid cavernous fistula (CCF). Epileptic attacks and ophthalmic findings previously present but diagnosed during our examinations were determined to ameliorate completely after performing the coil embolization. Based on literature, we present the first case with nontraumatic CCF manifesting with epileptic seizures and intermittent eye symptoms in the present report.

QSAR modeling for reaction rate constants of eaq− with diverse organic compounds in water

2020 ◽  
Vol 6 (7) ◽  
pp. 1931-1938
Author(s):  
Shanshan Zheng ◽  
Chao Li ◽  
Gaoliang Wei
Keyword(s):  
Organic Compounds ◽  
Reaction Rate ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Reaction Rate Constants ◽  
Structure Activity ◽  
Qsar Models ◽  
The Impact

Two quantitative structure–activity relationship (QSAR) models to predict keaq− of diverse organic compounds were developed and the impact of molecular structural features on eaq− reactivity was investigated.

scholarly journals AcanthamoebaSpecies Keratitis in a Soft Contact Lens Wearer Molecularly Linked to Well Water

2006 ◽  
Vol 17 (2) ◽  
pp. 120-122 ◽  
Author(s):  
Samira Mubareka ◽  
Michelle Alfa ◽  
Godfrey K Harding ◽  
Gregory Booton ◽  
Marilyn Ekins ◽  
...  
Keyword(s):  
Contact Lens ◽  
Present Report ◽  
Well Water ◽  
Soft Contact ◽  
Contact Lens Wearer ◽  
Contact Lens Wear ◽  
Soft Contact Lens ◽  
First Case ◽  
Primary Care Practitioners ◽  
High Degree

Acanthamoebaspecies keratitis has been associated with soft contact lens wear. In the present report, an epidemiological link was established between the patient's isolate and well water from the home using molecular methods. To the authors' knowledge, this is the first case in Canada where such a link has been established. Primary care practitioners and specialists, including ophthalmologists and infectious diseases specialists, must maintain a high degree of clinical suspicion in soft contact lens wearers with keratitis unresponsive to conventional topical and systemic treatment.

scholarly journals Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models

Nanoscale ◽  
2016 ◽  
Vol 8 (13) ◽  
pp. 7203-7208 ◽  
Author(s):  
Natalia Sizochenko ◽  
Agnieszka Gajewicz ◽  
Jerzy Leszczynski ◽  
Tomasz Puzyn
Keyword(s):  
Causal Inference ◽  
Quality Evaluation ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Validation Criteria ◽  
Qsar Models ◽  
Quantitative Structure Activity Relationships ◽  
Inference Methods

In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure–Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model.

scholarly journals Rodent Carcinogenicity Dataset

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Natalja Fjodorova ◽  
Marjana Novič
Keyword(s):  
Molecular Structure ◽  
Quantitative Structure Activity Relationship ◽  
Future Research ◽  
Qsar Modeling ◽  
Carcinogenic Potency ◽  
Dragon Descriptors ◽  
Qsar Models ◽  
Funded Project ◽  
Rodent Carcinogenicity

The rodent carcinogenicity dataset was compiled from the Carcinogenic Potency Database (CPDBAS) and was applied for the classification of quantitative structure-activity relationship (QSAR) models for the prediction of carcinogenicity based on the counter-propagation artificial neural network (CP ANN) algorithm. The models were developed within EU-funded project CAESAR for regulatory use. The dataset contains the following information: common information about chemicals (ID, chemical name, and their CASRN), molecular structure information (SDF files and SMILES), and carcinogenic (toxicological) properties information: carcinogenic potency (TD50_Rat_mg; carcinogen/noncarcinogen) and structural alert (SA) for carcinogenicity based on mechanistic data. Molecular structure information was used to get chemometrics information to calculate molecular descriptors (254 MDL and 784 Dragon descriptors), which were further used in predictive QSAR modeling. The dataset presented in the paper can be used in future research in oncology, ecology, or chemicals' risk assessment.

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