scholarly journals A combined experimental and computational study of the substituent effect on the photodynamic efficacy of amphiphilic Zn(ii)phthalocyanines

2016 ◽  
Vol 4 (34) ◽  
pp. 5683-5691 ◽  
Author(s):  
Anzhela Galstyan ◽  
Kristina Riehemann ◽  
Michael Schäfers ◽  
Andreas Faust
Keyword(s):  
Substituent Effect ◽  
Computational Study ◽  
Structural Features

The interplay between structural features, photophysical characteristics and photodynamic efficacy of carbohydrate substituted amphiphilic Zn(ii)phthalocyanines is presented.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

STRUCTURAL FEATURES, COMPUTATIONAL STUDIES AND BIOLOGICAL ANALYSIS: SCHIFF’S BASE LIGAND AND ITS COORDINATION COMPOUNDS

INDIAN DRUGS ◽  
2021 ◽  
Vol 58 (07) ◽  
pp. 22-31
Author(s):  
Seema Gautam ◽  
Sulekh Chandra ◽  
Jugmendra Singh ◽  
Navneet Manav ◽  
Vinod K Paliwal ◽  
...  
Keyword(s):  
Metal Ions ◽  
Coordination Compounds ◽  
Computational Study ◽  
Inhibition Zone ◽  
Antibacterial Activities ◽  
Structural Features ◽  
Schiff’S Base ◽  
H Nmr ◽  
Diffusion Technique ◽  
Elemental Analyses

Structure and biological application based analysis has been carried out for Schiff’s base ligand containing nitrogen and sulphur donor atoms and also for a series of its coordination compounds. Ligand benzil-bis(5-amino-1,3,4-thiadiazole-2-thiol) (L) has been prepared and structural features of ligand investigated by elemental analyses, IR, 1 H-NMR, mass spectra and molecular modeling studies. The chemical reaction of the prepared ligand with metal ions afforded mononuclear coordination compounds of Mn(II) and Co(II) metal ions. The characterization of the coordination compounds is being based on the techniques i.e. elemental analysis, infra-red, UV-visible as well as melting point, molar conductivity and magnetic moment measurement. A computational study has been done to understand the miscellaneous coordination modes of ligand to metal ions. Characterization result shows that coordination compounds exhibit a six coordinated geometrical arrangement i.e. octahedral geometry. The biological inhibition zone (antifungal and antibacterial activities) of synthesized compounds, i.e. ligand and its coordination compounds, has been monitored using well diffusion technique

Computational Study for Molecular Properties of Some of the Isolated Chemicals from Leaves Extract of Guiera Senegalensis as Aluminium Corrosion Inhibitor

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
A. M. Ayuba ◽  
◽  
M. Abubakar ◽  
Keyword(s):  
Molecular Dynamics ◽  
Quantum Chemical ◽  
Energy Gap ◽  
Computational Study ◽  
Physical Adsorption ◽  
Chemical Constituents ◽  
Molecular Size ◽  
Structural Features ◽  
Inhibitor Molecule ◽  
Fukui Indices

The present work describes the computational methods for the corrosion inhibition of aluminium using three selected chemical constituents (5-methyldihydroflavasperone, 5-methylflavasperone and methoxylated naphthyl butanone) reportedly obtained from the leaves extract of Guirea senegalensis. Quantum chemical calculations including EHOMO, ELUMO, energy gap (ΔE), electronegativity (χ), global hardness (η) and fraction of electrons transfer from the inhibitor molecule to the aluminium surface (ΔN) were calculated. The local reactive sites through Fukui indices which explain the effect of structural features of these components in relation to electrophilic and nucleophilic point of attack were evaluated. The similarities in quantum chemical parameters for the compounds obtained revealed that the adsorption strengths of the molecules will be mostly determined by molecular size rather than electronic structure parameters. Fukui indices showed that the point of interaction of inhibitor molecule with the Al(l10) surface were through aromatic carbon atom rich in pi-electrons and oxygen atom of the alkanone functional group in the inhibitor molecules. Molecular dynamics simulations describing the adsorption behavior of the inhibitor molecule on Al(110) surface through Forcite quench molecular dynamics were carried out. The compounds were found to all obey the mechanism of physical adsorption because of their relatively low adsorption energies.

scholarly journals Benzamide Derivatives Targeting the Cell Division Protein FtsZ: Modifications of the Linker and the Benzodioxane Scaffold and Their Effects on Antimicrobial Activity

Antibiotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 160 ◽  
Author(s):  
Valentina Straniero ◽  
Lorenzo Suigo ◽  
Andrea Casiraghi ◽  
Victor Sebastián-Pérez ◽  
Martina Hrast ◽  
...  
Keyword(s):  
Antimicrobial Activity ◽  
Cell Division ◽  
Single Molecule ◽  
Efflux Pump ◽  
Computational Study ◽  
Structural Features ◽  
Temperature Sensitive ◽  
Bacterial Cell Division ◽  
Gram Positive ◽  
Prokaryotic Protein

Filamentous temperature-sensitive Z (FtsZ) is a prokaryotic protein with an essential role in the bacterial cell division process. It is widely conserved and expressed in both Gram-positive and Gram-negative strains. In the last decade, several research groups have pointed out molecules able to target FtsZ in Staphylococcus aureus, Bacillus subtilis and other Gram-positive strains, with sub-micromolar Minimum Inhibitory Concentrations (MICs). Conversely, no promising derivatives active on Gram-negatives have been found up to now. Here, we report our results on a class of benzamide compounds, which showed comparable inhibitory activities on both S. aureus and Escherichia coli FtsZ, even though they proved to be substrates of E. coli efflux pump AcrAB, thus affecting the antimicrobial activity. These surprising results confirmed how a single molecule can target both species while maintaining potent antimicrobial activity. A further computational study helped us decipher the structural features necessary for broad spectrum activity and assess the drug-like profile and the on-target activity of this family of compounds.

Computational Study Reveals PARP1 and P2Y1 Receptors as Prospective Targets of Withaferin-A for Cardiovascular Diseases

2021 ◽  
Vol 19 ◽  
Author(s):  
Rekha Ravindran ◽  
Praveen Kumar PK ◽  
Sriram Kumar ◽  
Sujata Roy ◽  
Sakthi Abirami Gowthaman ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Cardiovascular Diseases ◽  
Target Genes ◽  
Computational Study ◽  
Structural Features ◽  
Pharmacophore Modeling ◽  
Withaferin A ◽  
Network Pharmacology ◽  
Stable Complex ◽  
Approved Drugs

Background: Cardiovascular Diseases (CVDs) remain the leading cause of death worldwide, which urges for effective strategies of prevention and treatment. Withaferin-A (WFA), the key metabolite identified in Withania somnifera, has been known for its cardioprotective properties. Although it has been traditionally employed to treat cardiovascular ailments for several decades, its exact mechanism of action still remains unexplained Objective: The current study modelled and scored the interactions of WFA with nine prospective protein-targets associated with cardiovascular diseases through molecular docking and DSX-scoring. Methods: Molecular docking was carried out using Autodock and DSX-scoring was carried out using DSX standalone software. WFA was observed to favorably interact with six targets before DSX-based rescoring, but only with Poly (ADP-Ribose) Polymerase-1 and P2Y Purinoceptor-1 after DSX-based rescoring. The spatial orientation, physicochemical properties and structural features of Withaferin-A were compared with that of these approved drugs by pharmacophore modeling and hierarchical clustering Results: The results of molecular docking, DSX-based rescoring and complete pharmacophore modeling together revealed that PARP1 and P2Y1 receptor could be prospective targets of WFA for the treatment of CVD. Conclusion: Simulation using GROMACS has revealed that WFA forms a more stable complex with PARP1 and will be useful in developing the broad-spectrum drugs against cardiovascular diseases. Further computational studies through machine learning and network pharmacology methods can be carried out to improve Withaferin-A compound features by incorporating additional functional groups necessary for molecular recognition of the target genes in network responsible for cardiovascular diseases.

scholarly journals Computational Study of Estrogen Receptor-Alpha Antagonist with Three-Dimensional Quantitative Structure-Activity Relationship, Support Vector Regression, and Linear Regression Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Ying-Hsin Chang ◽  
Jun-Yan Chen ◽  
Chiou-Yi Hor ◽  
Yu-Chung Chuang ◽  
Chang-Biau Yang ◽  
...  
Keyword(s):  
Estrogen Receptor ◽  
Inhibitory Activity ◽  
Estrogen Receptor Alpha ◽  
Computational Study ◽  
Three Dimensional ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Support Vector ◽  
Human Estrogen Receptor ◽  
Qsar Models

Human estrogen receptor (ER) isoforms, ERα and ERβ, have long been an important focus in the field of biology. To better understand the structural features associated with the binding of ERα ligands to ERα and modulate their function, several QSAR models, including CoMFA, CoMSIA, SVR, and LR methods, have been employed to predict the inhibitory activity of 68 raloxifene derivatives. In the SVR and LR modeling, 11 descriptors were selected through feature ranking and sequential feature addition/deletion to generate equations to predict the inhibitory activity toward ERα. Among four descriptors that constantly appear in various generated equations, two agree with CoMFA and CoMSIA steric fields and another two can be correlated to a calculated electrostatic potential of ERα.

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