Combining First-Principles and Data Modeling for the Accurate Prediction of the Refractive Index of Organic Polymers

2017 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
First Principles ◽  
Data Modeling ◽  
Accurate Prediction ◽  
Index Of Refraction ◽  
Structure Theory ◽  
Organic Polymers ◽  
Number Density ◽  
Lorenz Equation ◽  
In Silico Studies ◽  
Wide Range

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3–1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that an guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and highly economical path to determining the RI values for a wide range of organic polymers.

Combining First-Principles and Data Modeling for the Accurate Prediction of the Refractive Index of Organic Polymers

2017 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
First Principles ◽  
Data Modeling ◽  
Accurate Prediction ◽  
Index Of Refraction ◽  
Structure Theory ◽  
Organic Polymers ◽  
Number Density ◽  
Lorenz Equation ◽  
In Silico Studies ◽  
Wide Range

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3–1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that an guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and highly economical path to determining the RI values for a wide range of organic polymers.

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2018 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

Therapeutic Properties of Several Chemical Compounds from Salvia officinalis L. in Alzheimer’s Disease

2020 ◽  
Vol 21 ◽  
Author(s):  
Georgiana Uță ◽  
Denisa Ștefania Manolescu ◽  
Speranța Avram
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Side Effects ◽  
Chemical Compounds ◽  
Natural Compounds ◽  
Salvia Officinalis ◽  
Chemical Structures ◽  
In Silico Studies ◽  
Wide Range ◽  
Salvia Officinalis L

Background.: Currently, the pharmacological management in Alzheimer's disease is based on several chemical structures, represented by acetylcholinesterase and N-methyl-D-aspartate (NMDA) receptor ligands, with still unclear molecular mechanisms, but severe side effects. For this reason, a challenge for Alzheimer's disease treatment remains to identify new drugs with reduced side effects. Recently, the natural compounds, in particular certain chemical compounds identified in the essential oil of peppermint, sage, grapes, sea buckthorn, have increased interest as possible therapeutics. Objectives.: In this paper, we have summarized data from the recent literature, on several chemical compounds extracted from Salvia officinalis L., with therapeutic potential in Alzheimer's disease. Methods.: In addition to the wide range of experimental methods performed in vivo and in vitro, also we presented some in silico studies of medicinal compounds. Results. Through this mini-review, we present the latest information regarding the therapeutic characteristics of natural compounds isolated from Salvia officinalis L. in Alzheimer's disease. Conclusion.: Thus, based on the information presented, we can say that phytotherapy is a reliable therapeutic method in a neurodegenerative disease.

Chalcones: As potent α-amylase enzyme inhibitors; synthesis, in vitro, and in silico studies

2020 ◽  
Vol 16 ◽  
Author(s):  
Mahboob Ali ◽  
Momin Khan ◽  
Khair Zaman ◽  
Abdul Wadood ◽  
Maryam Iqbal ◽  
...  
Keyword(s):  
In Silico ◽  
Enzyme Inhibitors ◽  
Biological Activities ◽  
Condensation Reaction ◽  
Type Ii Diabetes Mellitus ◽  
Spectroscopic Techniques ◽  
Chalcone Derivatives ◽  
In Silico Studies ◽  
Wide Range

: Background: The inhibition of α-amylase enzyme is one of the best therapeutic approach for the management of type II diabetes mellitus. Chalcone possesses a wide range of biological activities. Objective: In the current study chalcone derivatives (1-17) were synthesized and evaluated their inhibitory potential against α-amylase enzyme. Method: For that purpose, a library of substituted (E)-1-(naphthalene-2-yl)-3-phenylprop-2-en-1-ones was synthesized by ClaisenSchmidt condensation reaction of 2-acetonaphthanone and substituted aryl benzaldehyde in the presence of base and characterized via different spectroscopic techniques such as EI-MS, HREI-MS, 1H-, and 13C-NMR. Results: Sixteen synthetic chalcones were evaluated for in vitro porcine pancreatic α-amylase inhibition. All the chalcones demonstrated good inhibitory activities in the range of IC50 = 1.25 ± 1.05 to 2.40 ± 0.09 μM as compared to the standard commercial drug acarbose (IC50 = 1.34 ± 0.3 μM). Conclusion: Chalcone derivatives (1-17) were synthesized, characterized, and evaluated for their α-amylase inhibition. SAR revealed that electron donating groups in the phenyl ring have more influence on enzyme inhibition. However, to insight the participation of different substituents in the chalcones on the binding interactions with the α-amylase enzyme, in silico (computer simulation) molecular modeling analyses were carried out.

Accurate prediction of 195Pt NMR chemical shifts for a series of Pt(ii) and Pt(iv) antitumor agents by a non-relativistic DFT computational protocol

2014 ◽  
Vol 43 (14) ◽  
pp. 5409-5426 ◽  
Author(s):  
Athanassios C. Tsipis ◽  
Ioannis N. Karapetsas
Keyword(s):  
Dft Calculations ◽  
Anticancer Agents ◽  
Antitumor Agents ◽  
Chemical Shifts ◽  
Accurate Prediction ◽  
Nmr Chemical Shifts ◽  
Relativistic Dft ◽  
Square Planar ◽  
Wide Range ◽  
Computational Protocol

Exhaustive benchmark DFT calculations reveal that the non-relativistic GIAO-PBE0/SARC-ZORA(Pt)∪6-31+G(d)(E) computational protocol predicts accurate 195Pt NMR chemical shifts for a wide range of square planar Pt(ii) and octahedral Pt(iv) anticancer agents.

scholarly journals Insights into the Antioxidant Mechanism of Newly Synthesized Benzoxazinic Nitrones: In Vitro and In Silico Studies with DPPH Model Radical

Antioxidants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1224
Author(s):  
Stefania Marano ◽  
Cristina Minnelli ◽  
Lorenzo Ripani ◽  
Massimo Marcaccio ◽  
Emiliano Laudadio ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Epr Spectroscopy ◽  
Point Of View ◽  
Uv Spectrophotometry ◽  
Design And Synthesis ◽  
Antioxidant Mechanism ◽  
Primary Mechanism ◽  
In Silico Studies ◽  
Wide Range

Synthetic nitrone spin-traps are being explored as therapeutic agents for the treatment of a wide range of oxidative stress-related pathologies, including but not limited to stroke, cancer, cardiovascular, and neurodegenerative diseases. In this context, increasing efforts are currently being made to the design and synthesis of new nitrone-based compounds with enhanced efficacy. The most researched nitrones are surely the ones related to α-phenyl-tert-butylnitrone (PBN) and 5,5-dimethyl-1-pyrroline N-oxide (DMPO) derivatives, which have shown to possess potent biological activity in many experimental animal models. However, more recently, nitrones with a benzoxazinic structure (3-aryl-2H-benzo[1,4]oxazin-N-oxides) have been demonstrated to have superior antioxidant activity compared to PBN. In this study, two new benzoxazinic nitrones bearing an electron-withdrawing methoxycarbonyl group on the benzo moiety (in para and meta positions respect to the nitronyl function) were synthesized. Their in vitro antioxidant activity was evaluated by two cellular-based assays (inhibition of AAPH-induced human erythrocyte hemolysis and cell death in human retinal pigmented epithelium (ARPE-19) cells) and a chemical approach by means of the α,α-diphenyl-β-picrylhydrazyl (DPPH) scavenging assay, using both electron paramagnetic resonance (EPR) spectroscopy and UV spectrophotometry. A computational approach was also used to investigate their potential primary mechanism of antioxidant action, as well as to rationalize the effect of functionalization on the nitrones reactivity toward DPPH, chosen as model radical in this study. Further insights were also gathered by exploring the nitrone electrochemical properties via cyclic voltammetry and by studying their kinetic behavior by means of EPR spectroscopy. Results showed that the introduction of an electron-withdrawing group in the phenyl moiety in the para position significantly increased the antioxidant capacity of benzoxazinic nitrones both in cell and cell-free systems. From the mechanistic point of view, the calculated results closely matched the experimental findings, strongly suggesting that the H-atom transfer (HAT) is likely to be the primary mechanism in the DPPH quenching.

scholarly journals Revealing biophysical properties of KfrA-type proteins as a novel class of cytoskeletal, coiled-coil plasmid-encoded proteins

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. Adamczyk ◽  
E. Lewicka ◽  
R. Szatkowska ◽  
H. Nieznanska ◽  
J. Ludwiczak ◽  
...  
Keyword(s):  
Dna Binding ◽  
Host Range ◽  
Coiled Coil ◽  
Amino Acid Sequences ◽  
Broad Host Range ◽  
Biophysical Properties ◽  
Dna Binding Sites ◽  
In Silico Studies ◽  
Wide Range

Abstract Background DNA binding KfrA-type proteins of broad-host-range bacterial plasmids belonging to IncP-1 and IncU incompatibility groups are characterized by globular N-terminal head domains and long alpha-helical coiled-coil tails. They have been shown to act as transcriptional auto-regulators. Results This study was focused on two members of the growing family of KfrA-type proteins encoded by the broad-host-range plasmids, R751 of IncP-1β and RA3 of IncU groups. Comparative in vitro and in silico studies on KfrAR751 and KfrARA3 confirmed their similar biophysical properties despite low conservation of the amino acid sequences. They form a wide range of oligomeric forms in vitro and, in the presence of their cognate DNA binding sites, they polymerize into the higher order filaments visualized as “threads” by negative staining electron microscopy. The studies revealed also temperature-dependent changes in the coiled-coil segment of KfrA proteins that is involved in the stabilization of dimers required for DNA interactions. Conclusion KfrAR751 and KfrARA3 are structural homologues. We postulate that KfrA type proteins have moonlighting activity. They not only act as transcriptional auto-regulators but form cytoskeletal structures, which might facilitate plasmid DNA delivery and positioning in the cells before cell division, involving thermal energy.

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