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In this work, we theoretically studied ten organic dyes using the DFT and TD-DFT methods, where triphenylamine was used as the donor for the D1-D5 dyes, while the 2, 6-diphenyl-4H-pyranylidene donor was used for the D6-D10 dyes. Substituents (alkyl and methoxy) were also introduced into these donor groups. These dyes also include 1, 3, 4-oxadiazole and phenyl as a bridge π and cyanoacrylic acid as acceptor. The electronic and optical properties of all dyes have been calculated as EHOMO, ELUMO, EGAP, Voc (the open-circuit photovoltage), λmax, Eex, LHE (the light-harvesting efficiency) and ΔGinj (the free injection energy) in order to compare their performance as DSSC sensitizers. The donor effect of all dyes was discussed on the one hand and on the other hand the effects of the introduction of substituents (alkyl and methoxy) to the donor before and after binding to TiO2 cluster. The results show that the performance of the dyes using 2, 6-diphenyl-4H-pyranylidene as donor has improved compared with the rest of the dyes, which may improve the power conversion efficiency. Therefore, these dyes D6-D10 are good candidates for use as DSSC sensitizers.

The new SARS-CoV-2 coronavirus is the causative agent of the COVID-19 pandemic outbreak that affected whole the world with more than 6 million confirmed cases and over 370,000 deaths. At present, there are no effective treatments or vaccine for this disease, which constitutes a serious global health crisis. As the pandemic still spreading around the globe, it is of interest to use computational methods to identify potential inhibitors for the virus. The crystallographic structures of 3CLpro (PDB: 6LU7) and RdRp (PDB 6ML7) were used in virtual screening of 50000 chemical compounds obtained from the CAS Antiviral COVID19 database using 3D-similarity search and standard molecular docking followed by ranking and selection of compounds based on their binding affinity, computational techniques for the sake of details on the binding interactions, absorption, distribution, metabolism, excretion, and toxicity prediction; we report three 4-(morpholin-4-yl)-1,3,5-triazin-2-amine derivatives; two compounds (2001083-68-5 and 2001083-69-6) with optimal binding features to the active site of the main protease and one compound (833463-19-7) with optimal binding features to the active site of the polymerase for further consideration to fight COVID-19. The structural stability and dynamics of lead compounds at the active site of 3CLpro and RdRp were examined using molecular dynamics (MD) simulation. Essential dynamics demonstrated that the three complexes remain stable during simulation of 20 ns, which may be suitable candidates for further experimental analysis. As the identified leads share the same scaffold, they may serve as promising leads in the development of dual 3CLpro and RdRp inhibitors against SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Introduction: The new species of coronaviruses (CoVs), SARS-CoV-2, was reported as responsible for an outbreak of respiratory disease. Scientists and researchers are endeavoring to develop new approaches for the effective treatment against of the COVID-19 disease. There are no finally targeted antiviral agents able to inhibit the SARS-CoV-2 at present. Therefore, it is of interest to investigate the potential uses of levamisole derivatives, which are reported to be antiviral agents targeting the influenza virus. Methods: In the present study, 12 selected levamisole derivatives containing imidazo[2,1-b]thiazole were subjected to molecular docking in order to explore the binding mechanisms between these derivatives and the SARS-CoV-2 Mpro (PDB: 7BQY). The levamisole derivatives were evaluated for in silico ADMET properties for wet-lab applicability. Further, the stability of the best-docked complex was checked using molecular dynamics (MD) simulation at 20 ns. Results: Levamisole derivatives and especially molecule N°6 showed more promising docking results, presenting favorable binding interactions as well as better docking energy compared to chloroquine and mefloquine. The results of ADMET prediction and MD simulation support the potential of the molecule N°6 to be further developed as a novel inhibitor able to stop the newly emerged SARS-CoV-2. Conclusion: This research provided an effective first line in the rapid discovery of drug leads against the novel CoV (SARS-CoV-2).

The new Corona-virus, recently called the severe acute respiratory syndrome Coronavirus (SARS-CoV-2) appears for the first time in China and more precisely in Wuhan (December 2019). This disease can be fatal. Seniors, and people with other medical conditions (diabetes, heart disease…), may be more vulnerable and become seriously ill. This is why research into drugs to treat this infection remains essential in several research laboratories. Natural herbal remedies have long been the main, if not the only, remedy in the oral tradition for treating illnesses. Modern medicine has known its success thanks to traditional medicine, the effectiveness of which derives from medicinal plants. The objective of this study is to determine if the components of natural origin have an anti-viral effect and which can prevent humans from infection by this coronavirus using the most reliable method is molecular docking, which used to find the interaction between studied molecules and the protein, in our case we based on the inhibitor of Coronavirus (nCoV-2019) main protease. The results of molecular docking showed that among 67 molecules of natural origin, three molecules (Crocin, Digitoxigenin, and β-Eudesmol) are proposed as inhibitors against the coronavirus based on the energy types of interaction between these molecules and studied protein. Communicated by Ramaswamy H. Sarma Highlights Determine natural compounds that can have an anti-viral effect and which can prevent humans from infection by this coronavirus; Molecular docking to find interaction between the molecules studied and the receptor of COVID-19; The synthesis of these molecules and the evaluation of their in vitro activity against SARS-Cov-2 could be interesting.

In this study, the analysis of microelectronic and photonic structure in one dimension program [AMPS-1D] has been successfully used to study organic solar cells. The program was used to optimize the performance of the organic solar cells based on (Carbazole-Methylthiophene), benzothiadiazole, Thiophene [(Cbz-Mth)-B-T]2 and [6, 6] -phenyl-C61-butyric acid methyl ester (PCBM). The cells considered, consist of Carbazole-Methylthiophene-Thiophene as electron donors, and benzothiadiazole, (6,6)-phenyl-c61-butyric acid methyl ester [PCBM] as electron acceptor. [(Cbz-Mth) -BT]2-PCBM] is used as photo active material, sandwiched between a transparent indium tin oxide (ITO) and an Al backside contact. The optoelectronic properties of these dyes were investigated by using the Density Functional Theory DFT/B3LYP/6-31G (d, p) method. We studied the influence of the variation of the thickness of the active layer, the temperature and the density of the effective states of the electrons and the holes in the conduction and valence bands respectively on the performance of the solar cells. The results were compared with the experimental data, it showed that the optimum thickness of the solar cell is about 120 nm, the maximum efficiency for the studied organic solar cell is about 9.458 % and the open circuit voltage decreases with temperature.

Background: Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten patients, societies and healthcare systems around the world. There is an urgent need to search for possible medications. Objective: This article intends to use virtual screening and molecular docking methods to find potential inhibitors from existing drugs that can respond to COVID-19. Methods: To take part in the current research investigation and to define a potential target drug that may protect the world from the pandemic of corona disease, a virtual screening study of 129 approved drugs was carried out which showed that their metabolic characteristics, dosages used, potential efficacy and side effects are clear as they have been approved for treating existing infections. Especially 12 drugs against chronic hepatitis B virus, 37 against chronic hepatitis C virus, 37 against human immunodeficiency virus, 14 anti-herpesvirus, 11 anti-influenza, and 18 other drugs currently on the market were considered for this study. These drugs were then evaluated using virtual screening and molecular docking studies on the active site of the (SARS-CoV-2) main protease (6lu7). Once the efficacy of the drug is determined, it can be approved for its in vitro and in vivo activity against the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which can be beneficial for the rapid clinical treatment of patients. : These drugs were considered potentially effective against SARS-CoV-2 and those with high molecular docking scores were proposed as novel candidates for repurposing. The N3 inhibitor cocrystallized with protease (6lu7) and the anti-HIV protease inhibitor Lopinavir were used as standards for comparison. Results: The results suggest the effectiveness of Beclabuvir, Nilotinib, Tirilazad, Trametinib and Glecaprevir as potent drugs against SARS-CoV-2 since they tightly bind to its main protease. Conclusion: These promising drugs can inhibit the replication of the virus; hence, the repurposing of these compounds is suggested for the treatment of COVID-19. No toxicity measurements are required for these drugs since they were previously tested prior to their approval by the FDA. However, the assessment of these potential inhibitors as clinical drugs requires further in vivo tests of these drugs.

In order to understand the electronic contribution of the thienopyrazine building block on the electronic properties of π-conjugated systems, small molecules containing thiophene and thienopyrazine moieties are synthesized and jointly studied by theoretical (DFT) and experimental methods (UV-Vis, UPS). Taking advantages of these preliminar attractive results, four low band gap extended structures have been elaborated on the base of Donor-Acceptor-Donor sequences (DAD); these elongated π-conjugated molecules exhibit noticeable electronic and absorption properties spreading from the near UV to NIR regions.

International audience; In this study, the analysis of microelectronic and photonic structure in a one dimension program [AMPS-1D] has been successfully used to study organic solar cells. The program was used to optimize the performance of organic solar cells based on (carbazole-methylthiophene), benzothiadiazole and thiophene [(Cbz-Mth)-B-T]2 as electron donors, and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) as an electron acceptor. The optoelectronic properties of these dyes were investigated by using the Density Functional Theory DFT/B3LYP/6-31G(d,p) method. We studied the influence of the variation of the thickness of the active layer, the temperature, and the density of the effective states of the electrons and the holes in the conduction and valence bands respectively on the performance of the solar cells based on [(Cbz-Mth)-BT]2-PCBM as a photoactive material, sandwiched between a transparent indium tin oxide (ITO) and an aluminum (Al) electrode. The addition of other thiophene units in the copolymer or the deposition of a layer of PEDOT between the anode (ITO) and the active layer, improves the performances of the cell, especially resulting in a remarkable increase in the value of the power conversion efficiency (PCE

In this work, we use the DFT calculation to investigate the photophysical properties of three compound organic light-emitting diodes. These new compounds based on thiophene, oxadiazole, and TPA, whose structure is donor-π-acceptor (D-π-A). To investigate the relationship between the structures and properties optic of these electroluminescent materials we optimize the ground state and the excited state to determine the relationship between the geometrical and optical properties. The calculation of ionization potential and electronic affinity shows that the D2 molecule has the lowest value of IP. The molecule D2 has the highest value for λtotal. These results show that the electron transport capacity is less than the hole transport capacity. This calculation shows that the compounds with PA structure own interesting characteristics in terms of IP, AE and reorganization energy. Thus, that these compounds present the best performance for electroluminescence devices. The emission properties show that the compounds can be used as blue and yellow emitters electroluminescent.

Electrical and dielectric properties for bulk ethylcarbazole-terphenyl (PEcbz-Ter) have been studied over frequency range 1 kHz–2 MHz and temperature range (R.T –120°C). The copolymer PEcbz-Ter was characterised by using X-ray diffraction. The frequency dependence of the dielectric constant (εr′) and dielectric loss (εr″) has been investigated using the complex permittivity. εr′ of the copolymer decreases with increasing frequency and increases with temperature. AC conductivity (σac) data were analysed by the universal power law. The behaviour of σac increases with increasing temperature and frequency. The change of the frequency exponent (s) with temperature was analysed in terms of different conduction mechanisms, and it was found that the correlated barrier-hopping model is the predominant conduction mechanism. The electric modulus was used to analyze the relaxation phenomenon in the material.

For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity relationship) to study their anticancer activities against HTC116 (human colon cancer), relying on the 3-dimensional descriptors: steric and electrostatic descriptors for the CoMFA (comparative molecular field analysis) method and steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor descriptors for the CoMSIA method. CoMFA as well as the CoMSIA model have encouraging values of the cross-validation coefficient (Q2) of 0.608 and 0.806 and conventional correlation coefficient (R2) of 0.960 and 0.934, respectively. Furthermore, values of R2test have been obtained as 0.75 and 0.90, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. Based on these satisfactory results, ten new compounds have been designed and predicted by in silico ADMET method. This study could expand the understanding of chalcone derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.

The α-amylase is regarded as a promising drug target for diabetes mellitus-type II. Hence, inhibiting α-amylase activity is a potential drug discovery approach for treating this chronic metabolic disorder. The present study explores the structural requirements and understands the inhibition mechanism of the novel developed indole-based derivatives as α-amylase inhibitors through 3D-QSAR, molecular docking, ADMET, and molecular dynamics (MD) simulation. The 3D-QSAR study showed good statistical reliability for two developed predictive models; CoMFA and CoMSIA. Through a deep investigation of docking analysis, detailed interactions with α-amylase of the most active compound 7 were explored. Four new indole derivatives were designed based on the contour maps and docking analysis, with significantly higher inhibitory activity than the molecules in the dataset. The selected molecules were evaluated for pharmacokinetic properties, showing a reasonably good ADMET profile. Furthermore, a 20-ns MD simulation of selected compounds bound to α-amylase was performed to ensure stability during simulation further. Greater stability of the designed molecule-protein complex A1 was found. The present findings shed light on the binding mode and the interactions between newly designed compounds, especially compound A1 and α-amylase and may be beneficial for drug development efforts targeting type-II diabetes.

This work aims to investigate the chemical composition of essential oils extracted from the seeds of six wild Moroccan Apiaceae species (Ammodaucus leucotrichus Coss & Dur, Carum carvi L., Coriandrum sativum L., Cuminum cyminum L., Foeniculum vulgare Mill., and Petroselinum crispum (Mill.) Fuss.,), and study the potential of the main compounds of the obtained essential oils as Acetylcholinesterase inhibitors. The essential oils thus obtained were analyzed and identified by the GC-Ms. To determine the similarities and dissimilarities between the chemical composition of the essential oils of the six species, we performed the Principal component analysis (PCA) and Agglomerative Hierarchical Clustering (AHC). The main compounds of the selected plants were studied for their docking behavior against acetylcholinesterase using surflex-docking. The GC-Ms results showed that the major components present in the A.leucotrichus Coss, C.carvi, C.sativum, C.cyminum, F.vulgare, and P.crispum were respectively Perrillaldehyde, Carvone, Linalool, Cuminaldehyde, Estragole, and Apiol. Regarding the in silico study of the main compounds, Cuminaldehyde as the major component of C. cyminum L., essential oil indicated a strong Acetylcholinesterase inhibitory activity. These presented findings suggest that the essential oil of C. cyminum may be a novel alternative source of acetylcholinesterase inhibitor.

The 3D QSAR analysis using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques is performed on novel nalidixic acid based 1,2,4-triazole derivatives suggested earlier as antibacterial agents. The CoMFA and CoMSIA models employed for a training set of 28 compounds gives reliable values of Q2 (0.53 and 0.52, respectively) and R2 (0.79 and 0.85, respectively). The contour maps produced by the CoMFA and CoMSIA models are used to determine a three-dimensional quantitative structure-activity relationship. Based on the 3D QSAR contours new molecules with high predicted activities are designed. In addition, surflex-docking is performed to confirm the stability of predicted molecules in the receptor.

Copper-catalyzed azide–alkyne cycloaddition (CuAAC) is a straightforward way for making covalent connections between building blocks containing various functional groups. It is widely used in organic synthesis, medicinal chemistry, polymer chemistry, and bioconjugation applications. Using copper acetonitrile as catalyst for click reactions (CuAAC) lead to a non-concerted reaction, and affect Parr functions indices to determine the polar sites, therefore predict the favorable regioisomer (1,4-regioisomer) and explain the contradiction obtained to the experimental results. The huge difference of activation barriers between catalyzed and uncatalyzed reaction indicate that is a selective reaction.

Eight novel organic compounds with donor–π–acceptor (D–π–A) structure were designed for use as donors in organic bulk heterojunction (BHJ) solar cells. The molecules have thieno[2,3-b]indole as donor, methylene malononitrile as electron acceptor group, and a π-spacer bridge based on thiophene and benzene or its derivatives. The designed compounds were studied using density functional theory (DFT) and time-dependent DFT approaches, to shed light on how the π-conjugation order influences the performance of corresponding photovoltaic solar cells. The study includes prediction of the energy of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) levels, the energy gap, Voc (the open-circuit voltage), the λmax of absorption, and other quantum-chemical parameters. The results show that, the greater the number of thiophenes present in the bridge, the better the compound as a donor for BHJ solar cells. The theoretical power conversion efficiency calculated for the designed products reaches 6%.

To search for newer and potent antileishmanial drugs, a series of 36 compounds of 5-(5-nitroheteroaryl-2-yl)-1,3,4-thiadiazole derivatives were subjected to a quantitative structure-activity relationship (QSAR) analysis for studying, interpreting, and predicting activities and designing new compounds using several statistical tools. The multiple linear regression (MLR), nonlinear regression (RNLM), and artificial neural network (ANN) models were developed using 30 molecules having pIC50 ranging from 3.155 to 5.046. The best generated MLR, RNLM, and ANN models show conventional correlation coefficients R of 0.750, 0.782, and 0.967 as well as their leave-one-out cross-validation correlation coefficients RCV of 0.722, 0.744, and 0.720, respectively. The predictive ability of those models was evaluated by the external validation using a test set of 6 molecules with predicted correlation coefficients Rtest of 0.840, 0.850, and 0.802, respectively. The applicability domains of MLR and MNLR transparent models were investigated using William’s plot to detect outliers and outsides compounds. We expect that this study would be of great help in lead optimization for early drug discovery of new similar compounds.

In this paper, we present a quantum chemical analysis of geometries and optoelectronic properties of a series of flavonoids and derivatives with the aim to research new molecules for applications in the fields of chemical physics and materials science. The calculations are based on the functional density theory (DFT) level of the B3LYP with 6-31G (d, p). This method was used to calculate the energy of HOMO and LUMO level, the Egap (gap energy), the Voc open circuit voltage). The DFT (TD-B3LYP /6-31G (d, p)) was used to calculate (λmax maximum of absorption) as well as other quantum parameters. The study of organic solar cells cannot be effective unless accompanied by a thorough understanding electronic distribution on the HOMO and LUMO energy levels of the components, so the researchers calculated and discussed the HOMO, LUMO, energy gap, and Voc of the test compounds. The result shows that these studied molecules are good candidates for application in the fields of optoelectronic devices such as OLED, conducting devices and organic solar cells.

Kinase-related apoptosis-inducing kinase 2 (DRAK2) is a serine/threonine kinase and belongs to the death-associated protein kinase DPAK family, which is responsible for induction of apoptosis in many cell types. Thus, DRAK2 is regarded as a promising target for treatment of autoimmune diseases. To investigate the binding between DRAK2 and indirubin inhibitors and design potent inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking were performed. Comparative Molecular Similarity Indices Analysis (CoMSIA) was developed using 33 molecules having pIC50 ranging from 8.523 to 5.000 (IC50 in nM). The best CoMSIA model gave a significant coefficient of determination (R2 = 0.93), as well as a (leave-one-out cross-validation coefficient Q2 of 0.81. The predictive ability of this model was evaluated by external validation using a test set of eight compounds and yielded a predicted coefficient of determination R2test of 0.94. The contour maps could provide structural features to improve inhibitory activity. Good consistency between contour maps and molecular docking strongly suggests that the molecular modeling is reliable. Based on these satisfactory results, we designed several new DRAK2 inhibitors and their inhibitory activities were predicted using different models, which are developed on different training and test sets. Additionally, these newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations compared to the best inhibitor from the studied dataset. This study could be useful in lead identification and optimization for early drug discovery of DRAK2 inhibitors.

Proviral Integration site for Moloney murine leukemia virus-1 (PIM1) belongs to the serine/threonine kinase family of Ca2+-calmodulin-dependent protein kinase (CAMK) group, which is involved in cell survival and proliferation as well as a number of other signal transduction pathways. Thus, PIM1 is regarded as a promising target for treatment of cancers. In the present paper, a three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking were performed to investigate the binding between PIM1 and thiazolidine inhibitors in order to design potent inhibitors. The comparative molecular similarity indices analysis (CoMSIA) was developed using twenty-six molecules having pIC50 ranging from 8.854 to 6.011 (IC50 in nM). The best CoMSIA model gave significant statistical quality. The determination coefficient (R2) and Leave-One-Out cross-validation coefficient (Q2) are 0.85 and 0.58, respectively. Furthermore, the predictive ability of this model was evaluated by external validation((n = 11, R2test = 0.72, and MAE = 0.170 log units). The graphical contour maps could provide structural features to improve inhibitory activity. Furthermore, a good consistency between contour maps and molecular docking strongly demonstrates that the molecular modeling is reliable. Based on these satisfactory results, we designed several new potent PIM1 inhibitors and their inhibitory activities were predicted by the molecular models. Additionally, those newly designed inhibitors, showed promising results in the preliminary in silico ADMET evaluations, compared to the best inhibitor from the studied dataset. The results expand our understanding of thiazolidines as inhibitors of PIM1 and could be of great help in lead optimization for early drug discovery of highly potent inhibitors.

Ca2+/calmodulin-dependent protein kinase II (CAMKIIδ) belongs to the serine/threonine kinase family, which is involved in a broad range of cellular events in cell survival and proliferation as well as a number of other signal transduction pathways. Thus, it is regarded a promising target for treatment of cancers. In the present paper, a three-dimensional quantitative structure–activity relationship and molecular docking were applied to investigate a series of new CAMKIIδ inhibitors of pyrazolopyrimidine derivatives. The determination coefficient (R2) and leave-one-out cross-validation coefficient (Q2) of CoMSIA model are 0.676 and 0.956, respectively. The predictive ability of this model was evaluated by the external validation using a test set of eight compounds with a predicted determination coefficient $$R^{ 2}_{\text{test}}$$ of 0.80, besides the mean absolute error of the test set was 0.328 log units. Docking results are in concordance with CoMSIA contour maps, gave the information for interactive mode exploration. Based on those satisfactory results, newly designed molecules were predicted with highly potent CAMKIIδ inhibitory activity, additionally, they have showed promising results in the preliminary in silico ADMET evaluations. This study could expand our understanding of pyrazolopyrimidine derivatives as inhibitors of CAMKIIδ and would be of great help in lead optimization for early drug discovery of highly potent CAMKIIδ inhibitors.

We used density functional theory at B3LYP level with 6-31G(d,p) basis set for all atoms to study the electrochemical, photovoltaic, and absorption properties of four new organic π-conjugated donor–π–acceptor structures based on diketo-pyrrolo-pyrrole for use in dye-sensitized solar cells (DSSCs). Meanwhile, the cyanocarboxylic acid function of these compounds was used as electron acceptor to attract electrons from the donor unit via the π-spacer and also to attach the dye to a TiO2 surface. This study focuses on the effect of the π-spacer on structural, electronic, and photovoltaic properties including the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), energy gap, density of states (DOS), ultraviolet–visible (UV–Vis) absorption spectrum, free energy change of electron injection ∆Ginject, light harvesting efficiency, intramolecular charge transfer, and electrochemical properties (chemical potential μ, electronegativity χ, and global hardness η). Moreover, the structure–properties correlation for all dyes is discussed. Our quantum calculations reveal that the dye based on furan as π-spacer (Dye-Fu) may represent a potential electron donor for use in DSSCs.

New donor-acceptor based copolymer incorporating carbazole as electron donor molecule and benzothiazole as electron withdrawing one has been designed and synthesized for organic solar cells applications. The synthesis procedure was achieved via a chemical oxydation pathway. Structural modifications were examined using infrared spectroscopy. Then, optical properties were investigated by the means of UV-VIS and photoluminescence measurements. A large red shift was observed in both optical absorption and emission spectra, showing an extension of the conjugation length going from the pristine PVK to the PVK-based copolymer. The experimental analyses were completed by theoretical calculations based on density functional theory (DFT) and time-dependant density functional theory (TD-DFT) methods. Then, Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) levels have been calculated in order to elucidate the intramolecular charge transfer (ICT) between the electron acceptor and the electron donor moieties and to establish the energetic diagrams of PVK and the PVK-based copolymer. All results showed that this copolymer exhibit interesting photophysical properties and shows promising photovoltaic trends.

Cell division cycle 7 (CDC7) is a serine/threonine kinase, which plays a vital role in the replication initiation of DNA synthesis. Overexpression of the CDC7 in various tumor growths and in cell proliferation makes it a promising target for treatment of cancers. To investigate the binding between the CDC7 and furanone inhibitors, and in order to design highly potent inhibitors, a three-dimensional quantitative structure activity relationship (3D-QSAR) with molecular docking was performed. The optimum CoMSIA model showed significant statistical quality on all validation methods with a determination coefficient (R2 = 0.945), bootstrapping R2 mean (BS-R2 = 0.960), and leave-one-out cross-validation (Q2) coefficient of 0.545. The predictability of this model was evaluated by external validation using a test set of nine compounds with a predicted determination coefficient R2test of 0.96, besides the mean absolute error (MAE) of the test set was 0.258 log units. The extracted contour maps were used to identify the important regions, where the modification was necessary to design a new molecule with improved activity. Furthermore, a good consistency between the molecular docking and contour maps strongly demonstrates that the molecular modeling is reliable. Based on those obtained results, we designed several new potent CDC7 inhibitors, and their inhibitory activities were validated by the molecular models. Additionally, those newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations.

DFT and TD-DFT calculations using ten various functionals contain 0 to 100% of HF exchange amount (BLYP, B3LYP, PBE0, M06, BHandH, BHandHLYP, M06-2X, CAM-B3LYP, LC-ωPBE and M06HF), in combination with ten double-ζ and triple-ζ basis sets of Poples, have been performed in order to explore their effects on the geometrical and electronic properties, and evaluate their accuracies to predict the visible spectra of C213, C214 and C215 triphenylamine-based (TPA) dyes for Dye-sensitized solar cells (DSSCs) applications. The calculation of the bond lengths and dihedral angle values for C213 dye ground state geometry showed a sensitive dependence to the percentage of HF exchange amount contribution in xc-functional, while the contributions of augmentation of the basis sets size has no remarkable effect from the 6-31G(d) basis set. Regarding the energies of the HOMO and LUMO levels, their calculation values were dependent on functional nature. The great accuracy to predict the ground state maximum absorption wavelength was showed by the functional approaches having HF exchange amount around 50%. The best prediction was recorded by BHandH functional using 6-31+G(d) basis set for both geometry optimization and TDDFT calculations within CPCM/THF solvent model. Using the lowest computational cost and accurate method, the light harvesting efficiency (LHE) was enhanced from C213 to C215 dye. Additionally, the injection driving force (ΔGinject.) to TiO2 semiconductor and the driving force for regeneration (ΔGreg) by I−/I3− electrolyte were evaluated and suggest that the intermolecular charge-transfer mechanism is operative in the studied dyes when applied to DSSC.

In this study, the anticancer activity of a series of 32 molecules based on anthra[1,9-cd]pyrazol-6(2H)-one was studied by three-dimensional quantitative structure-activity relationship (QSAR) analyses: multiple linear regression (MLR), partial least squares (PLS), multiple nonlinear regression (MNLR), cross-validation analyses, and Y-randomization. A theoretical study of series was firstly studied using density functional theory (DFT) calculations at B3LYP/6-31 level of theory for employing to determine the structural parameters and electronic properties. Then the topological descriptors were computed using ACD/ChemSketch and ChemDraw 8.0 programs. The RNLM, given the descriptors obtained from the MLR and PLS, exhibited a correlation coefficient close to 0.91. The prediction models collected were confirmed by two methods of cross-validation and scrambling (or Y-randomization). The strong correlation between experimental and predicted activity values was observed, indicating the validation and good quality of the derived QSAR model.

The essential oils of Artemisia ifranensis J. Didier (Asteraceae), collected from Timahdite (Moroccan Middle-Atlas) in April and June (2012) (vegetative and early bloom stages, respectively), were obtained by hydrodistillation and then analysed by gas chromatography-flame ionization detector (GC/FID) and GC-mass spectrometry (GC/MS). Moreover, antibacterial activity essential oil was evaluated against pathogen germs isolated from hospital. Disc-diffusion method in solid medium and macrodilution method in liquid medium were, respectively, used to determine inhibition diameters and the antibacterial parameters to knowing, minimal inhibitory and bactericide concentrations (MIC and MBC). Essential oil yields were 0.58 ± 0.1% and 1.11 ± 0.3% (ml/100 g), respectively, in vegetative and blooming stages. For these periods, essential oil analyses revealed that β-Thujone was the most abundant compound in the plant with 50.0 and 41.1%, respectively. Oxygenated monoterpenes and sesquiterpenes are the most important groups among identified compounds. For antibacterial activity, the results proved that essential oil was highly active against the Staphylococcus aureus.

A new series of 4- methyl quinazoline derivatives was synthesized and its anti-cancer activity was assessed. It was revealed that its compounds have potent inhibition on related phosphoinositide 3-kinases alpha (PI3Kα). In this study, the three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking approaches were performed on a series of 4-methyl quinazoline derivatives with PI3Kα inhibitors. The 3D-QSAR study was applied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods, which gave the cross-validation coefficient (Q2) values of 0.850 and 0.92, the determination coefficient (R2) values of 0.998 and 0.987, and the standard error of the estimate (SEE) values of 0.017 and 0.105, respectively. The acceptable values of determination coefficient (R2 test) to CoMFA and CoMSIA respectively corresponding to values of 0.793 and 0.804 utilizing a test set of seven molecules prove the high predictive ability of this model. Using AutoDock tools, Molecular docking analysis was utilized to validate 3D-QSAR methods and to explain the binding site interactions and energy between the most active ligands and the PI3Kα (PDB ID: 4JPS ) receptor. Based on these results, a novel series of 4- methyl quinazoline derivatives was predicted.

Covid-19 is an emerging infectious disease caused by coronavirus SARS-CoV-2. Due to the rapid rise in deaths resulted from this infection all around the world, the identification of drugs against this new coronavirus is an important requirement. Among the drugs that can fight this type of infection; natural products are substances that serve as sources of beneficial chemical molecules for the development of effective therapies. In this study, Camphor, Artemisinin and 14 Sumac phytochemicals were docked in the active site of SARS-CoV-2 main protease (PDB code: 6LU7). We have also performed molecular dynamic simulation at 100 ns with MM-GBSA/PBSA analysis for the structures with the best affinity in the binding site of the studied enzyme (Hinokiflavone and Myricetin) after docking calculations to consider parameters like RMSD, covariance, PCA, radius of gyration, potential energy, temperature and pressure. The result indicates that Hinokiflavone and Myricetin are the structures with best affinity and stability in the binding site of the studied enzyme and they respect the conditions mentioned in Lipinski's rule and have acceptable ADMET proprieties; so, these compounds have important pharmacokinetic properties and bioavailability, and they could have more potent antiviral treatment of COVID-19 than the other studied compounds.

In this paper, we report a theoretical study using density functional theory (DFT) and time-dependent (TD-DFT) for R-D-π-A systems with various alkyl chains (R). Results show that the LUMO of the dye lies above the semiconductor conduction band, promoting the injection of electrons; the lower HOMO level promotes dye regeneration. The incorporation of methyl chain (CH3) has a significant reduction in the gap energy, improved red-shift absorption spectrum and increase the molar extinction coefficient at the maximum absorption wavelength compared to D. While, the increase in alkyl chain length from C2H5 to C6H13 present a relatively reduce of gap energies, low effect on the wavelength (438 nm) and converged excitation energies. DOI: http://dx.doi.org/10.17807/orbital.v9i5.1003

The ACD/ChemSketch, MarvinSketch, and ChemOffice programmes were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters). The best descriptors were selected to establish the Quantitative Structure-Property Relationship (QSPR) of the retention/release property of odorant molecules in pectin gels using Principal Components Analysis (PCA), Multiple Linear Regression (MLR), Multiple Non-linear Regression (MNLR) and Artificial Neural Network (ANN) methods We propose a quantitative model based on these analyses. PCA has been used to select descriptors that exhibit high correlation with the retention/release property. The MLR method yielded correlation coefficients of 0.960 and 0.958 for PG-0.4 (pectin concentration: 0.4% w/w) and PG-0.8 (pectin concentration: 0.8% w/w) media, respectively. Internal and external validations were used to determine the statistical quality of the QSPR of the two MLR models. The MNLR method, considering the relevant descriptors obtained from the MLR, yielded correlation coefficients of 0.978 and 0.975 for PG-0.4 and PG-0.8 media, respectively. The applicability domain of MLR models was investigated using simple and leverage approaches to detect outliers and outside compounds. The effects of different descriptors on the retention/release property are described, and these descriptors were used to study and design new compounds with higher and lower values of the property than the existing ones. Keywords: Odorant Molecules, Retention/Release, Pectin Gels, Quantitative Structure Property Relationship, Multiple Linear Regression, Artificial Neural Network

In order to initiate the process of determining how the molecular level receptor-odorant interactions are related to odor perception, we used the SWISS-MODEL modeling server to predict the three dimensional (3D) structure of the human olfactory receptor (hOR1G1). The model was refined using minimization and side-chain optimization using SCWRL. We then used the Autodockvina and Autodock tools to predict the binding site and binding energy for the library of 13 odorants characterized by different retention/release property values to hOR1G1 receptor, to investigate the relationship between this property and the ligand-hOR1G1 interactions. We find that when the retention property increases, hydrogen bond interactions between ligands and olfactory receptor (hOR1G1) become favorable.

A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having pIC50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R1 and R2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules.

cited By 2; International audience; In this work, a theoretical study on five organic π-conjugated molecules based on thieno[3,2-b][1]benzothiophene using together quantum methods, density functional theory (DFT) and its derivative time dependent-density functional theory (TD-DFT) is reported. Different electron side groups were introduced as a bridge to investigate their effects on the electronic structure; The HOMO, LUMO, chemical hardness (η), chemical potential (μ), electronegativity (χ), electrophilicity power (ω), reorganization energy total (λtotal), open circuit voltage (Voc), the gap energy and NBO analysis of these compounds have been reported and discussed in this paper. Thus, our aim is to explore their electronic and spectroscopic properties on the basis of the DFT quantum chemical calculations, and at the same time, we are interested to make an idea on the parameters influencing the photovoltaic efficiency toward a better understanding of the structure–property relationships. The calculated results of these compounds reveal that C4, C5, with thiophene and thienopyrazine as a bridge group respectively, can be used as a potential donor of electron in organic Bulk Heterojunction solar cells (BHJ), due to its best electronic and optical properties and good photovoltaic parameters. The study of electronic, optical and structural properties of these compounds could help to design more efficient functional photovoltaic organic materials. © 2017 King Saud University

To understand the effect of the substitution by several strong electron-withdrawing groups ([1,2,5]thiadiazolo[3,4-g]quinoxaline; benzo[c][1,2,5]thiadiazole and quinoxaline) and end-capped donor groups (thiophene and phenyl) on the structural and optoelectronic properties of six conjugated compounds C1–C6 based on 2,7-silafluorene and 4,7-di (2′-thienyl) used for organic solar cells application such as bulk heterojunction (BHJ) solar cell. We have done a theoretical study to calculate and predict these properties. The electronic structures and optical absorption spectra of donors were calculated using density functional theory, and the Zerner’s intermediate neglect of differential overlap functional theory level is employed to investigate the excited singlet states, respectively, and to shed light on how the substitution and the pi-conjugation order influence the performance of these compounds in the BHJ cell. Moreover, the theoretical results including optoelectronic and photovoltaic properties of the compound C1 are in good agreement with the available experimental data extracted from bibliography. The calculated results of these molecules reveal that the compounds C3 and C6, with the [1,2,5]thiadiazolo[3,4-g]quinoxaline as electron acceptor seem to be good candidates materials for photovoltaic applications due to their best optoelectronic and photovoltaic properties.

Novel donor-π-acceptor (D-π-A) dyes composed of Triphenylamine having (3,4-etylenedioxythiophene) (EDOT), Oligothiophene and Benzothiadiazole were designed and studied. The optimized structures and optoelectronic properties of these dyes were investigated by using the Density Functional Theory DFT/B3LYP/ 6-31G (d,p) method and Time Dependant Density Functional Theory (TD/DFT) calculations. These dyes consist of electron-donor (Triphenylamine-3,4-Ethylenedioxythiophene-Oligothiophene) and acceptors/anchoring (Benzothiadiazole and Cyanoacrylic) : PTEBT3A, PTEBT2A, PTEBTA, PTET3A, PTET2A, PTETA, PEBTA and PBTA. The calculated geometries indicate that these dyes have coplanar structures. The LUMO and HOMO energy levels of these dyes can ensure a positive effect on the process of electron injection and dye regeneration. In order to predict the band gaps for guiding the synthesis of novel materials with low band gaps, we apply quantum-chemical techniques to calculate the band gaps in several oligomers. The introduction of EDOT and Benzothiadiazole units in the copolymers and the elongation of π-conjugation length of oligothiophenes led to a red-shift of absorption bands of the D-π-A dyes. The calculated HOMO-LUMO (E gap ) gaps and the wavelength of absorption spectrum (λ max ) were compared with the experimental data. It was found that a D-π-A dyes having EDOT-containing the Thiophene repeating units exhibited the low band gap and the excellent light-harvesting ability up to 795 nm. Furthermore, several quantum chemical properties, such as ionization potential (IP), electronaffinity (EA), electrophilicity index (ω), hardness (η) and chemical potential (μ) were also calculated and thoroughly discussed in the paper. The calculated results of these dyes demonstrate that these compounds can be used as potential sensitizers for TiO 2 nanocrystalline solar cells.

In this work, we report five novel organic dyes with donor–π–acceptor (D–π–A) structure, their conjugated bridge is based on phenylenevinylene and thiophene/furan, the acid 2-cyanoacrylic was used as an electron acceptor (anchoring) group and triphenylamine was used as an electron donor group for all compounds. These dyes were studied by Density Functional Theory (DFT) and Time-Dependent DFT (TD-DFT) methods using Becke's three-parameter functional and Lee–Yang–Parr functional (B3LYP) level with 6-31G(d) basis set to investigate their molecular structures, frontier molecular orbitals, optoelectronic properties and absorption spectra as implemented in the Gaussian 09 program. The HOMO (highest occupied molecular orbital), LUMO (lowest unoccupied molecular orbital) levels, gap energy (E HOMO – E LUMO ) and V oc (open-circuit voltage) of the studied compounds are calculated and discussed. These properties suggest that these compounds as good candidates for use in organic dye-sensitized solar cells.

To establish a quantitative structure-activity relationship model of the binding affinity constants (−log Ki) of 41 flavonoid derivatives towards the GABA (A) receptor, the DFT-B3LYP method with basis set 6-31G (d) was performed to gain insights into the chemical structure and property information for the studied compounds. The best topological and electronic descriptors were selected. This work was conducted with principal component analysis (PCA), multiple linear regression (MLR), multiple non-linear regression (MNLR) and artificial neural network (ANN). According to these analyses, we propose quantitative models and interpret the activity of the compounds based on multivariate statistical analysis. The statistical results of the MLR, MNLR and ANN indicate that the determination coefficients R2 were 0.896, 0.925 and 0.916, respectively. The results show that the three modelling methods can predict the studied activity well and may be useful for predicting the biological activity of new compounds. The statistical results indicate that the models are statistically significant and stable with data variation in the external validation.

Quantitative structure activity relationship was carried out to study a series of PIM1 and PIM2 inhibitors. The present study was performed on twenty-five substituted 5-(1H-indol-5-yl)-1,3,4-thiadiazols as PIM1 and PIM2 inhibitors having pIC50 ranging from 5.55 to 9 µM and from 4.66 to 8.22 µM, respectively, using genetic function algorithm for variable selection and multiple linear regression analysis (MLR) to establish unambiguous and simple QSAR models based on topological molecular descriptors. Results showed that the MLR predict activity in a satisfactory manner for both activities. Consequently, the aim of the current study is twofold, first, a simple linear QSAR model was developed, which could be easily handled by chemist to screen chemical databases, or design for new potent PIM1 and PIM2 inhibitors. Second, the outcomes extracted from the current study were exploited to predict the PIM inhibitory activity of some studied compound analogues. The goal of this study is to develop easy and convenient QSAR model could be handled by everyone to screen chemical databases or to design newly PIM1 and PIM2 inhibitors derived from 5-(1H-indol-5-yl)-1,3,4-thiadiazol. Graphical abstract Flow chart of the methodology used in this work.

(E)-N-Aryl-2-ethene-sulfonamide and its derivatives are potent anticancer agents; these compounds inhibit cancer cells proliferation. A study of quantitative structure-activity relationship (QSAR) has been applied on 40 compounds based on (E)-N-Aryl-2-ethene-sulfonamide, in order to predict their anticancer biological activity. The principal components analysis is used for minimizing the base matrix and the multiple linear regression (MLR) and multiple nonlinear regression have been used to design the relationships between the molecular descriptor and anticancer properties of the sulfonamide derivatives. The validation of the models MLR and MNLR has been done by dividing the dataset into training and test set, the external validation of multiple correlation coefficients was RpIC50 = 0.81 for MLR and RpIC50 = 0.91 for MNLR. The artificial neural network (ANN) showed a correlation coefficient close to 0.96, which concluded that this latter model is more effective and much better than the other models. This obtained model (ANN) has been confirmed by two methods of LOO cross-validation and scrambling (or Y-randomization). The high correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR model.

This study gives a quantitative structure–activity relationship (QSAR) analysis of toxicity of phenols and thiophenols to Photobacterium phosphoreum, which is an important indicator for water quality. The chemical structures of 51 phenols and thiophenols have been characterized by electronic and physic-chemical descriptors. The present study was performed using principal components analysis (PCA), multiple regression analysis (MLR) and artificial neural network (ANN). The quantitative model was accordingly proposed and the toxicity of the compounds was interpreted based on the multivariate statistical analysis. This study shows that the results obtained by MLR were suitable and have served to predict toxicity, but compared to the results of the ANN model, we conclude that the prediction achieved by the latter is more effective and better than MLR model. The statistical results of the predictive performance indicate that the ANN model is statistically significant than the previous reported model based on CART-LS-SVR. Following to the obtained results, our proposed model may be useful to predict of toxicity and risk assessment of chemicals.

Many studies have focused on indole derivatives mainly their antiproliferative effect. The therapeutic effect of this group of molecule is very important. Quantitative structure–activity relationships (QSAR) have been applied for development relationships between physicochemical properties and their biological activities. A series of 30 molecules derived from indole is based on the quantitative structure-activity relationship (QSAR). This study was carried out using the principal component analysis (PCA) method, the multiple linear regression method (MLR), non-linear regression (RNLM), the artificial neural network (ANN) and it was validated using cross validation analysis (CV). We accordingly propose a quantitative model and we try to interpret the activity of the compounds relying on the multivariate statistical analyses. A theoretical study of series was studied using density functional theory (DFT) calculations at B3LYP/6-31G(d) level of theory for employing to calculate electronic descriptors when, the topological descriptors were computed with ACD/ChemSketch and ChemDraw 8.0 programs. The best QSAR model was found in agreement with the experimental by ANN (R = 0,99).

In this paper, six symmetrical compounds with a donor–acceptor–donor (D–A–D) structure based on triphenylamine as a core and bridged with various spacer fragments with electron-acceptor character, such as quinoxaline, phenazine, benzo[g]quinoxaline, benzo[b]phenazine, thieno[3,4-b]pyrazine and thieno[3,4-b]quinoxaline, have been studied theoretically using two quantum methods, DFT and TD-DFT, together by considering their use in organic BHJ solar cells as potential donors of electron. Intramolecular charge transfer (ICT) interactions have been found for all of the compounds due to the electron withdrawing properties caused by the two imine nitrogen atoms in the pyrazine and the electron-donating properties of the other two amine nitrogen atoms in the two triphenylamines that compose the bridge. The ICT interactions are strengthened when the benzene or thiophene ring are fused on the pyrazine acceptor unit, which leads to a bathochromic shift of the ICT band. Moreover, our quantum calculations show that thiophene is a more appropriate ring than the benzene ring for enlarging the ICT interactions and expanding the absorption spectrum. We remark also that when a thiophene ring is fused on the quinoxaline unit in the D6 compound, a significant shift towards the near-infrared is realized, and it exhibits a maximum absorption wavelength at 690 nm compared to the other studied compounds with a threshold that is over 800 nm. This is attributed to the enhanced charge density on the acceptor spacer and narrow band gap of this compound, as revealed by our theoretical calculations. Finally, these results show that extending the conjugation of a compound based on pyrazine as an acceptor in a D–A–D structured compound can be realized by incorporating the thiophene unit in the bridge and then strengthening the ICT interactions.