scholarly journals 3D-QSAR study of adenosine 5’-phosphosulfate (APS) analouges as ligands for APS reductase

2021 ◽  
pp. 15-15
Author(s):  
Slavica Eric ◽  
Ilija Cvijetic ◽  
Mire Zloh
Keyword(s):  
Rational Design ◽  
3D Qsar ◽  
Qsar Model ◽  
Qsar Study ◽  
Molecular Interaction Fields ◽  
Key Characteristics ◽  
Aps Reductase ◽  
High Degree ◽  
Key Pathways ◽  
Important Enzyme

Metabolism of sulfur (sulfur assimilation pathway, SAP) is one of the key pathways for the pathogenesis and survival of persistant bacterias, such as Mycobacterium tuberculosis (Mtb), in the latent period. Adenosine 5?-phospho-sulfate reductase (APSR) is an important enzyme involved in the SAP, absent from the human body, so it might represents a valid target for development of new antituberculosis drugs. This work aimed to develop 3D QSAR model based on the crystal structure of APSR from Pseudomonas aeruginosa, which shows high degree of homology with APSR from Mtb, in complex with its substrate, adenosine 5?-phosphosulfate (APS). 3D QSAR model was built from a set of 16 nucleotide analogues of APS using alignment-independent descriptors derived from molecular interaction fields (MIF). The model improves the understanding of the key characteristics of molecules necessary for the interaction with target, and enables the rational design of novel small molecule inhibitors of Mtb APSR.

A new, fully validated and interpreted quantitative structure-activity relationship model of p-aminosalicylic acid derivatives as neuraminidase inhibitors

2013 ◽  
Vol 67 (5) ◽  
Author(s):  
Ana Hartmman ◽  
Daniela Jornada ◽  
Eduardo Melo
Keyword(s):  
Predictive Ability ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Neuraminidase Inhibitors ◽  
Aminosalicylic Acid ◽  
Randomization Tests ◽  
Qsar Study ◽  
Relationship Model ◽  
Mechanism Of Interaction

AbstractA multivariate QSAR study with a set of 34 p-aminosalicylic acid derivatives, described as neuraminidase inhibitors of the H1N1 viruses, is presented in this work. The variable selection was performed with the Ordered Predictors Selection (OPS) algorithm and the model was built with the Partial Least Squares (PLS) regression method. Leave-N-out cross-validation and y-randomization tests showed that the model was robust and free from chance correlation. The external predictive ability was superior to the 3D-QSAR model previously published. Moreover, it was possible to perform a mechanistic interpretation, where the descriptors referred directly to the mechanism of interaction with the neuraminidase.

scholarly journals Molecular Modeling of Antimalarial Agents by 3D-QSAR Study and Molecular Docking of Two Hybrids 4-Aminoquinoline-1,3,5-triazine and 4-Aminoquinoline-oxalamide Derivatives with the Receptor Protein in Its Both Wild and Mutant Types

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hanine Hadni ◽  
Mohamed Mazigh ◽  
El’mbarki Charif ◽  
Asmae Bouayad ◽  
Menana Elhallaoui
Keyword(s):  
Molecular Docking ◽  
3D Qsar ◽  
Qsar Model ◽  
Molecular Structures ◽  
Basis Set ◽  
Receptor Protein ◽  
Quantum Chemical Descriptors ◽  
Qsar Study ◽  
Antimalarial Agents ◽  
Quadruple Mutant

Modeling studies using 3D-QSAR and molecular docking methods were performed on a set of 34 hybrids of 4-aminoquinoline derivatives previously studied as effective antimalarial agents of wild type and quadruple mutant Plasmodium falciparum dihydrofolate reductase (DHFR). So, the famous mathematical method multiple linear regression (MLR) was explored to build the QSAR model. The DFT-B3LYP method with the basis set 6-31G was used to calculate the quantum chemical descriptors, chosen to represent the electronic descriptors of molecular structures. On the contrary, the MM2 method was used to calculate lipophilic, geometrical, physicochemical, and steric descriptors. The QSAR model tested with artificial neural network (ANN) method shows high performance towards its predictability. The predicted model was confirmed by three validation methods: leave-one-out (LOO) cross validation, Y-randomization, and validation external. The molecular docking study of three compounds 9, 11, and 26 on both wild and quadruple mutant types of pf-DHFR-TS as the protein target helps to understand more and then predict the binding modes with the binding sites.

scholarly journals 4D-QSAR Analyses for EGFR Inhibitors Based on CDDA-OPS-GA Method

2021 ◽  
Author(s):  
Daogang Qin ◽  
Xiaoqi Zeng ◽  
Tiansheng Zhao ◽  
Biying Cai ◽  
Bowen Yang ◽  
...  
Keyword(s):  
Rational Design ◽  
Growth Factor Receptor ◽  
3D Qsar ◽  
Qsar Model ◽  
Detection Algorithm ◽  
Egfr Inhibitors ◽  
Conformational Ensemble ◽  
Good Potential ◽  
Epidermal Growth ◽  
External Prediction

Abstract Epidermal growth factor receptor is a preferred target for treating cancer. Compared to 3D-QSAR, 4D-QSAR has the feature of conformational flexibility and free alignment for individual ligands. In present studies, the 4D-QSAR of 131 analogs of 4-anilino quinazoline for EGFR inhibitors was built. The GROMACS package was employed to yield the conformational ensemble profile. The field descriptors of Coulomb and Lennard−Jones potentials were calculated by LQTA-QSAR. The filter descriptors and variable selection is very important, which was performed by means of comparative distribution detection algorithm (CDDA), ordered predictors selection (OPS) and genetic algorithm (GA) method. Best 4D-QSAR model yielded satisfactory statistics (R2 = 0.71), good performance in internal (Q2LOO = 0.60) and external prediction (R2pred = 0.69, k = 0.97, k′ = 1.01). The 4D-QSAR was shown to be robust (Q2LMO = 0.59) and was not built by chance (R2YS = 0.17, Q2YS = −0.25). The model has a good potential for rational design new EGFR inhibitors.

CoMFA, CoMSIA and HQSAR Analysis of 3-aryl-3-ethoxypropanoic Acid Derivatives as GPR40 Modulators

2020 ◽  
Vol 17 (1) ◽  
pp. 100-118
Author(s):  
Krishna A. Gajjar ◽  
Anuradha K. Gajjar
Keyword(s):  
Biological Activity ◽  
Structural Information ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Statistical Parameters ◽  
Qsar Study ◽  
Negative Contribution

Background: Human GPR40 receptor, also known as free fatty-acid receptor 1, is a Gprotein- coupled receptor that binds long chain free fatty acids to enhance glucose-dependent insulin secretion. In order to improve the resistance and efficacy, computational tools were applied to a series of 3-aryl-3-ethoxypropanoic acid derivatives. A relationship between the structure and biological activity of these compounds, was derived using a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using CoMFA, CoMSIA and two-dimensional QSAR study using HQSAR methods. Methods: Building the 3D-QSAR models, CoMFA, CoMSIA and HQSAR were performed using Sybyl-X software. The ratio of training to test set was kept 70:30. For the generation of 3D-QSAR model three different alignments were used namely, distill, pharmacophore and docking based alignments. Molecular docking studies were carried out on designed molecules using the same software. Results: Among all the three methods used, Distill alignment was found to be reliable and predictive with good statistical results. The results obtained from CoMFA analysis q2, r2cv and r2 pred were 0.693, 0.69 and 0.992 respectively and in CoMSIA analysis q2, r2cv and r2pred were 0.668, 0.648 and 0.990. Contour maps of CoMFA (lipophilic and electrostatic), CoMSIA (lipophilic, electrostatic, hydrophobic, and donor) and HQSAR (positive & negative contribution) provided significant insights i.e. favoured and disfavoured regions or positive & negative contributing fragments with R1 and R2 substitutions, which gave hints for the modifications required to design new molecules with improved biological activity. Conclusion: 3D-QSAR techniques were applied for the first time on the series 3-aryl-3- ethoxypropanoic acids. All the models (CoMFA, CoMSIA and HQSAR) were found to be satisfactory according to the statistical parameters. Therefore such a methodology, whereby maximum structural information (from ligand and biological target) is explored, gives maximum insights into the plausible protein-ligand interactions and is more likely to provide potential lead candidates has been exemplified from this study.

scholarly journals 3D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2,3-Dioxygenase (IDO) Inhibitors

2012 ◽  
Vol 9 (4) ◽  
pp. 1753-1759 ◽  
Author(s):  
Kamlendra S. Bhadoriya ◽  
Shailesh V. Jain ◽  
Sanjaykumar B. Bari ◽  
Manish L. Chavhan ◽  
Kuldeep R. Vispute
Keyword(s):  
Nearest Neighbor ◽  
External Validation ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Study ◽  
Internal Validation ◽  
Contour Maps ◽  
Model Classification ◽  
Ido Inhibitors

3D-QSAR approach usingkNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report herek-nearest neighbor molecular field analysis (kNN-MFA)-based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q2= 0.7627, representing internal validation) in training set and 79.35% (pred_r2= 0.7935, representing external validation) in test set using sphere exclusion and forward as a method of data selection and variable selection, respectively. Contour maps using this approach showed that hydrophobic and steric effects dominantly determine binding affinities. The information rendered by 3D-QSAR model may lead to a better understanding of structural requirements of IDO inhibitors and can help in the design of novel potent molecules.

scholarly journals Computational Approaches for the Design of Novel Anticancer Compounds Based on Pyrazolo[3,4-d]pyrimidine Derivatives as TRAP1 Inhibitor

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5932
Author(s):  
Amena Ali ◽  
Magda H. Abdellattif ◽  
Abuzer Ali ◽  
Ola AbuAli ◽  
Mohd Shahbaaz ◽  
...  
Keyword(s):  
3D Qsar ◽  
Md Simulations ◽  
Docking Study ◽  
Qsar Model ◽  
Computational Techniques ◽  
Amino Acid Residues ◽  
Molecular Docking Study ◽  
Qsar Study ◽  
Screening Study ◽  
Leave One Out

In the present in-silico study, various computational techniques were applied to determine potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of important features required for activity. The 3D QSAR study showed a statistically significant model with R2 = 0.96 and Q2 = 0.57. Leave one out (LOO) cross-validation (R2 CV = 0.58) was used to validate the QSAR model. The molecular docking study showed maximum XP docking scores (−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56, 43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583, SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were validated using the 100 ns MD simulations performed for the selected five docked complexes. The selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules present in the literature. The ZINC database was used for a virtual screening study that screened ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis showed noticeable results. The results of the study may be helpful for the further development of potent TRAP1 inhibitors

scholarly journals Insights into the Structural Requirements of 2(S)-Amino-6-Boronohexanoic Acid Derivatives as Arginase I Inhibitors: 3D-QSAR, Docking, and Interaction Fingerprint Studies

2018 ◽  
Vol 19 (10) ◽  
pp. 2956 ◽  
Author(s):  
José Velázquez-Libera ◽  
Carlos Navarro-Retamal ◽  
Julio Caballero
Keyword(s):  
Binding Site ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Cerebrovascular Diseases ◽  
Binding Modes ◽  
Structure Activity ◽  
Arginase I ◽  
Important Enzyme

Human arginase I (hARGI) is an important enzyme involved in the urea cycle; its overexpression has been associated to cardiovascular and cerebrovascular diseases. In the last years, several congeneric sets of hARGI inhibitors have been reported with possible beneficial roles for the cardiovascular system. At the same time, crystallographic data have been reported including hARGI–inhibitor complexes, which can be considered for the design of novel inhibitors. In this work, the structure–activity relationship (SAR) of Cα substituted 2(S)-amino-6-boronohexanoic acid (ABH) derivatives as hARGI inhibitors was studied by using a three-dimensional quantitative structure–activity relationships (3D-QSAR) method. The predictivity of the obtained 3D-QSAR model was demonstrated by using internal and external validation experiments. The best model revealed that the differential hARGI inhibitory activities of the ABH derivatives can be described by using steric and electrostatic fields; the local effects of these fields in the activity are presented. In addition, binding modes of the above-mentioned compounds inside the hARGI binding site were obtained by using molecular docking. It was found that ABH derivatives adopted the same orientation reported for ABH within the hARGI active site, with the substituents at Cα exposed to the solvent with interactions with residues at the entrance of the binding site. The hARGI residues involved in chemical interactions with inhibitors were identified by using an interaction fingerprints (IFPs) analysis.

Design, synthesis, antifungal activity and 3D-QSAR study of novel pyrazole carboxamide and niacinamide derivatives containing benzimidazole moiety

2019 ◽  
Vol 43 (7) ◽  
pp. 3000-3010 ◽  
Author(s):  
Wei-Jie Si ◽  
Xiao-Bin Wang ◽  
Min Chen ◽  
Meng-Qi Wang ◽  
Ai-Min Lu ◽  
...  
Keyword(s):  
Antifungal Activity ◽  
Predictive Ability ◽  
3D Qsar ◽  
Qsar Model ◽  
Qsar Study ◽  
Design Synthesis ◽  
Effective Inhibition

The synthesized pyrazole carboxamide and niacinamide derivatives containing a benzimidazole moiety showed effective inhibition of the fungus B. cinereal growth. The 3D-QSAR model was built and revealed fine predictive ability.

scholarly journals Synthesis, Antifungal Activity, and 3D-QSAR Study of Novel Nopol-Derived 1,3,4-Thiadiazole-Thiourea Compounds

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1708
Author(s):  
Ming Chen ◽  
Wen-Gui Duan ◽  
Gui-Shan Lin ◽  
Zhong-Tian Fan ◽  
Xiu Wang
Keyword(s):  
Antifungal Activity ◽  
Alternaria Solani ◽  
3D Qsar ◽  
Qsar Model ◽  
Gibberella Zeae ◽  
Cercospora Arachidicola ◽  
Qsar Study ◽  
Structure Activity ◽  
Better Than

A series of novel nopol derivatives bearing the 1,3,4-thiadiazole-thiourea moiety were designed and synthesized by multi-step reactions in search of potent natural product-based antifungal agents. Their structures were confirmed by FT-IR, NMR, ESI-MS, and elemental analysis. Antifungal activity of the target compounds was preliminarily evaluated by in vitro methods against Fusarium oxysporum f. sp. cucumerinum, Cercospora arachidicola, Physalospora piricola, Alternaria solani, Gibberella zeae, Rhizoeotnia solani, Bipolaris maydis, and Colleterichum orbicalare at 50 µg/mL. All the target compounds exhibited better antifungal activity against P. piricola, C. arachidicola, and A. solani. Compound 6j (R = m, p-Cl Ph) showed the best broad-spectrum antifungal activity against all the tested fungi. Compounds 6c (R = m-Me Ph), 6q (R = i-Pr), and 6i (R = p-Cl Ph) had inhibition rates of 86.1%, 86.1%, and 80.2%, respectively, against P. piricola, much better than that of the positive control chlorothalonil. Moreover, compounds 6h (R = m-Cl Ph) and 6n (R = o-CF3 Ph) held inhibition rates of 80.6% and 79.0% against C. arachidicola and G. zeae, respectively, much better than that of the commercial fungicide chlorothalonil. In order to design more effective antifungal compounds against A. solani, analysis of the three-dimensional quantitative structure–activity relationship (3D-QSAR) was carried out using the CoMFA method, and a reasonable and effective 3D-QSAR model (r2 = 0.992, q2 = 0.753) has been established. Furthermore, some intriguing structure–activity relationships were found and are discussed by theoretical calculation.

scholarly journals Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer’s Disease

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5773
Author(s):  
Rosa Purgatorio ◽  
Nicola Gambacorta ◽  
Marco Catto ◽  
Modesto de Candia ◽  
Leonardo Pisani ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Qsar Study ◽  
Active Compounds ◽  
Wide Range ◽  
Ic50 Values ◽  
Isatin Derivatives

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer’s disease. The newly synthesized molecules spanned their IC50 values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the ‘active’ compounds from the ‘inactive’ (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of ‘active’ compounds, i.e., those achieving finite IC50 values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q2 = 0.596) and in the external test set (n = 14, r2ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein.

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