GQSAR modeling and combinatorial library generation of 4-phenylquinazoline-2-carboxamide derivatives as antiproliferative agents in human Glioblastoma tumors

Goswami, Debolina; Goyal, Sukriti; Jamal, Salma; Jain, Ritu; Wahi, Divya; Grover, Abhinav

doi:10.1016/j.compbiolchem.2017.03.017

Cited by 5 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For external validation of the model, the pIC50 values of the test set molecules were predicted and the pred r2 value that provides the statistical correlation between predicted and actual activities of the test set compounds was calculated as follows All these statistical parameters were used to evaluate the quality of the model. Correlation coe cient (r2) described the tness of training set data whereas predictive correlation coe cient (pred-r2) was used to evaluate the tness of the test set [17,28]. The cross-validation coe cient (q2) and F-test (Fischer's value) showed the statistical signi cance of the regression model and the standard errors (pred r2 se, q2 se, and r2 se) gave an idea of the quality and tness of the model.…”

Section: Fragmentation Of Molecules and Gqsar Model Buildingmentioning

confidence: 99%

“…This study makes use of fragment-based quantitative structure-activity relationship (GQSAR) modelling. A lot of research already found potential using the GQSAR approach [16,17]. Here the GQSAR is used to correlate the biological activity of indole substituted compounds.…”

Section: Introductionmentioning

confidence: 99%

“…Group-based QSAR or GQSAR is a method that investigates the structure-activity relationship based on molecular fragments of the set of molecules. GQSAR is an advantageous and more informative approach than other conventional 2D and 3D QSAR methods [16,17]. Conventional QSAR methods do not make clear exactly which part of the molecules should be substituted or modi ed to increase the activity.…”

Section: Introductionmentioning

confidence: 99%

“…The biological activity of molecular fragments and their descriptors are correlated, leading to the QSAR model(s) which focuses on important substitution sites with their chemical nature and interactions. The information derived from the developed model helps in suggesting signi cant molecular fragments that can be utilized as the building blocks while designing novel molecules [17].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

WITHDRAWN: In-silico discovery of novel microtubule inhibitors targeting colchicine binding site; A combined Group-based QSAR approach

Sahu

Ojha

2022

Preprint

View full text Add to dashboard Cite

Microtubules are a potential target for the design and development of novel anti-mitotic drugs for cancer therapy Focusing on their mechanisms of action, Microtubuletargeting agents are classified into stabilizers and destabilizers, among them destabilizers binding to colchicine binding site domain is an important source of research in recent years. A number of molecules containing indole scaffold have been described as tubulin polymerization inhibitors with the potential to interact with the colchicine binding site. The research is focused on the search for new indole-based colchicine binding site inhibitors, for that fragment-based QSAR utilized for the important interacting site for potent fragment attachment and the designed fragment library screened for the finding of the potent molecule and finally, three molecules screened and validated for their reactivity using DFT and stability using Molecular dynamics simulation, among them m16 showing the potential result with high interaction energy, high molecular reactivity and confirms high stability as compared to others.

show abstract

Section: Fragmentation Of Molecules and Gqsar Model Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

WITHDRAWN: In-silico discovery of novel microtubule inhibitors targeting colchicine binding site; A combined Group-based QSAR approach

Sahu

Ojha

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The current methods for generating QSAR using fragment descriptors include the Free-Wilson approach, HQSAR, and two-dimension topological QSAR [76][77][78] . The recommended novel approach G-QSAR, on the other hand, varies from it in two ideas: I In the G-QSAR method, every molecule in the database has fragmented using a group of predetermined criteria prior to the fragmentation descriptors being calculated.…”

Section: Methodology Of Gqsarmentioning

confidence: 99%

Untitled

2023

IJPSR

View full text Add to dashboard Cite

Structure-Activity relationship (SAR) only identifies the chemical group responsible for producing the target biological effect in the organism. It was first present in 1865, structural activity relationship was refined dates back to the nineteenth century and now it has advanced from QSAR to 3D QSAR. Quantitative Structure-Activity Relationships (QSAR) are attempted to correlate the structural and biological properties of compounds or molecules. QSAR is used in drug design and medicinal chemistry. By using QSAR, scientists predefined toxicity related to organic molecules and determined the perfect potential biological activity that helps produce drug moiety. Group Based-Quantitative Structure-Activity Relationship (G-QSAR) is fragment dependent method which bases on molecule descriptors. Statistical parameters validate the GQSAR method. The cross-term fragment descriptor is used in GQSAR to study the relation of molecular fragments and variation in biological-based response. It provides a clue for designing new molecules and predicting their activity. In this article, we mainly concentrate on the various QSAR model such as Hansch Analysis, Free Wilson Analysis, various physicochemical properties, QSAR development process, QSAR model, and methodology of the GQSAR model, implementation and working as well as some general aspects in QSAR and GQSAR study.

show abstract

Identification of anti-cancer natural compounds against colchicine binding site of tubulin: a combined structure and QSAR-based approach

Sahu

Kumar

Singh

et al. 2023

Molecular Simulation

View full text Add to dashboard Cite

GQSAR modeling and combinatorial library generation of 4-phenylquinazoline-2-carboxamide derivatives as antiproliferative agents in human Glioblastoma tumors

Cited by 5 publications

References 16 publications

WITHDRAWN: In-silico discovery of novel microtubule inhibitors targeting colchicine binding site; A combined Group-based QSAR approach

WITHDRAWN: In-silico discovery of novel microtubule inhibitors targeting colchicine binding site; A combined Group-based QSAR approach

Untitled

Identification of anti-cancer natural compounds against colchicine binding site of tubulin: a combined structure and QSAR-based approach

Contact Info

Product

Resources

About