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                <text>Computational approach of artificial neural network</text>
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                <text>Artificial Neural Network; Automobile Industry; Pharmaceutical Industry; Prediction; Stock Price</text>
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                <text>This paper makes an attempt to predict the movement of the stock price for the following day using Artificial Neural Network (ANN). For the purpose of this research, two companies from each industry have been chosen that is, TATA Motors and Honda Motors from the Automobile industry and Cadila Pharmaceuticals Ltd. and Glenmark Pharmaceuticals from the Pharmaceutical industry. The historical prices of these companies were collected and by using Artificial Neural Network (ANN), the movement of the stock price for the next day is predicted.  2017 IEEE.</text>
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                <text>Ravichandra T.; Thingom C.</text>
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                <text>IEEE International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2017 - Proceedings, pp. 646-649.</text>
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                <text>Ravichandra T., Department of Professional Studies, Christ University, Bangalore, India; Thingom C., Centre for Digital Innovation, Christ University, Bangalore, India</text>
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                <text>Computational Aspects of Business Management with Special Reference to Monte Carlo Simulation</text>
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                <text>Business management is concerned with organizing and efficiently utilizing resources of a business, including people, in order to achieve required goals. One of the main aspects in this process is planning, which involves deciding operations of the future and consequently generating plans for action. Computational models, both theoretical and empirical, help in understanding and providing a framework for such a scenario. Statistics and probability can play an important role in empirical research as quantitative data is amenable for analysis. In business management, analysis of risk is crucial as there is uncertainty, vagueness, irregularity, and inconsistency. An alternative and improved approach to deterministic models is stochastic models like Monte Carlo simulations. There has been a considerable increase in application of this technique to business problems as it provides a stochastic approach and simulation process. In stochastic approach, we use random sampling to solve a problem statistically and in simulation, there is a representation of a problem using probability and random numbers. Monte Carlo simulation is used by professionals in fields like finance, portfolio management, project management, project appraisal, manufacturing, insurance and so on. It equips the decision-maker by providing a wide range of likely outcomes and their respective probabilities. This technique can be used to model projects which entail substantial amounts of funds and have financial implications in the future. The proposed chapter will deal with concepts of Monte Carlo simulation as applied to Business Management scenario. A few specific case studies will demonstrate its application and interpretation.  2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Prasad S.</text>
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                <text>Modeling and Optimization in Science and Technologies, Vol-18, pp. 629-645.</text>
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                <text>Prasad S., Former Associate Professor, Department of Statistics, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Computational Chemical Property Prediction and Anticancer Simulation of Heterocyclic Molecules  </text>
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                <text>The Density Functional Theory (DFT) technique is popularly employed in establishing organic molecules' structural properties and reactivities. The B3LYP hybrid functional with the basis set 6-311G++(d,p) is utilised in the computational calculations with Gaussian 09W software. The DFT studies include energy minimisation (geometry optimisation), frontier molecular orbitals (FMO) analyses, theoretical UV spectral computation, natural bond orbital (NBO) evaluation, Topological analyses using Multiwfn 3.8 software are performed to evaluate the Pauli repulsion in atomic orbitals (as shown by ELF (Electron Localisation Function) maps), the areas of strong and weak pi-delocalisation in the molecules (as depicted in LOL (Localised Orbital Locator) maps) and the weak non-covalent intra-molecular interactions (as indicated in colour maps of RDG (Reduced Density Gradient)). Pharmacological evaluation is performed using SwissADME, ADMETLab 2.0, and PreADMET online tools. Molecular docking is performed using AutoDock Tools 1.5.6 with select anticancer target proteins to predict the bioactivity potential of the title molecules. The molecules studied in the work include a spiro compoun d, spiro[1H-indole-3,2-3H-1,3- benzothiazole]-2-one, a 2(3H)-furanone, 3,3,5-triphenylfuran-2(3H)-one, and a benzo[d]imidazole, 5,6-dichloro-1-cyclopentyl-2-(methylsulfinyl)-1H- benzimidazole. In addition, comparative studies are performed on the structure and reactivity of spirobrassinin derivatives, spirocyclic isatin-derivative analogues, and 3(2H)-furanones, and these three classes of molecules have already been predicted to possess anticancer properties in vitro. Interesting properties emerge in the preliminary theoretical investigations for these molecules, particularly in the FMO, the NLO and the molecular docking studies. The theoretical studies explore the reactivity, structure, and stability of the molecules under study, and biological evaluation examines their potential as lead compounds for cancer therapeutics. These studies can be further extended to include experimental validation and in vitro and in vivo tests to confirm further the efficacy of the anticancer action as well as the potential toxicity of the compounds. The theoretical investigations provide a database of information that could be useful for
experimental scientists and medicinal chemists who primarily focus on drug design and discovery in their research so that they can narrow down the number of possible lead compounds from the vast chemical space of organic compounds that possess drug-like characteristics.</text>
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                <text>Muloor K., LTIMindtree Limited and CHRIST (Deemed to be University), Bangalore, India; Sahu S.K., LTIMindtree Limited, Bangalore, India; Behera T.K., Forrester Research, Cambridge, MA, United States; Samanta D., Rochester Institute of Technology, Pristina, United States</text>
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                <text>Computational investigation into structural, topological, electronic properties, and biological evaluation of spiro[1H-indole-3,2?-3H-1,3-benzothiazole]-2-one</text>
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                <text>The current work comprises theoretical studies on spiro[1H-indole-3,2?-3H-1,3-benzothiazole]-2-one employing density functional theory (DFT). The optimized structure and molecular geometry of the title compound were calculated. Topological studies were performed using Multiwfn 3.8, these include ELF, LOL and RDG studies to identify the main bonding regions and weak interactions in the molecule. Solvation effects were studied by taking different green solvents, using IEFPCM model. Solvation effects were investigated for electronic properties (HOMO-LUMO and UV), MEP, and NLO properties and some variation is observed in the behaviour of the title compound in gas and solvent phases. Natural bond orbital (NBO) calculations are performed to study the inter- and intra-molecular charge transfer and stability. Pharmacological evaluation comprising of drug-likeness, ADME, environmental toxicity properties using online tools such as SwissADME, Pre-ADMET, and GUSAR, to determine whether the molecule can be a potential drug candidate is performed. Finally, molecular docking against anti-melanoma targets whose Ramachandran plots have been depicted to determine the stability of the target proteins, with PyMOL, AutoDock Suite and Discovery Studio Visualizer, is carried out.  2022 Elsevier B.V.</text>
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                <text>Journal of Molecular Liquids, Vol-359</text>
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                <text>Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India; Irfan A., Department of Chemistry, College of Science, King Khalid University, P.O. Box 9004, Abha, 61413, Saudi Arabia; Jeelani A., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India</text>
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                <text>Computational investigation into the solvent effect, electron distribution, reactivity profile, pharmacokinetic properties and anti-cancer action of Hemimycalin C</text>
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                <text>This work consists of DFT studies and biological evaluation of the marine alkaloid Hemimycalin C. The DFT calculations include energy minimisation, reactivity analysis of the frontier molecular orbitals, electronic transition studies (UV spectra generation), molecular electrostatic potential colour map analysis (MEP), and natural bond orbitals (NBO) studies. Non-linear optical (NLO) properties estimation is also performed to obtain the first-order hyperpolarizability, mean polarizability and dipole moment of Hemimycalin C. The solvent methanol emerges as the most interesting among the polar solvents employed in this study, as it impacts the properties of Hemimycalin C to a significant extent. Multiwfn software is used for topological analyses, which include the calculation of Reduced Density Gradient (RDG), Localised Orbital Locator (LOL) maps), and Electron Localisation Function (ELF). The computed ADMET profile indicates that the molecule is a potent lead (drug candidate) as the medicinal chemistry parameters are mostly within the optimal range. The Ramachandran plots are also computed to show the stability and quality of the target proteins, by computation of the permitted psi and phi angles. The complexes of the ligand are docked using AutoDock Tools against blood cancer receptors to obtain good binding affinity values.  2025 Elsevier B.V.</text>
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                <text>Journal of Molecular Liquids, Vol-423</text>
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                <text>Coronary Artery Disease (CAD) is caused by stenosis of the coronary artery's lumen. This heart disease is one of the reasons for the highest mortality worldwide.  This illness manifests as stenosis or plaque in the coronary arteries and causes atherosclerosis. It damages or clogs the heart arteries, causing a lack of blood flow to the heart muscles and leading to a heart attack. There are different medical modalities to diagnose the heart artery disease. A standard method used by the cardiologist to diagnose the severity of this disease is coronary angiography. An X-ray machine is used to capture the angiogram image at various angles during cardiac catheterization. Experts examine the data and offers different opinions. owever, most of the angiogram videos consist of unclear images with artifacts, and because of the complex structure of the arteries, medical experts fail to get accurate information about the damages and blockages in arteries. Based on the cardiologist's suggestions, a computational model is proposed as a secondary method to detect and recognize the stenosis level from the coronary angiogram images. The proposed model is Coronary Artery Stenosis Detection Using Digital Image Processing (CASDDIP). The proposed research model/framework can identify the stenosis in the cardiogram image with good accuracy of 98.06% precision. This proposed research experimentation can be compared with existing literature methods which outperforms compared to other methods using real time dataset. A dataset, such as angiogram videos and images of patients under varying age groups, is used to train the model. These videos are acquired from the healthcare center with due consent. The proposed CASDDIP model consists of four modules:  Keyframe extraction and preprocessing  Coronary Artery Segmentation  Feature extraction and stenosis detection Initially, a novel keyframe extraction method is proposed to find the keyframe from the angiogram video. Followed by a hybrid segmentation method is presented in this research to extract the coronary artery region from the image. Further a method is proposed to detect the stenosis by extracting and fusing different features. Detected stenosis is categorized using the proposed stenosis level classification method. This CASDDIP model is a supporting tool to help the cardiologist during diagnosis.</text>
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                <text>Grid computing the job scheduling is the major issue that needs to be addressed prior to the development of a grid system or architecture. Scheduling is the users job to apropos resources in the grid environment. Grid computing has got a very wide domain in its application and thus induces various research opportunities that are generally spread over many areas of distributed computing and computer science. The cardinal point of scheduling is being attaining apex attainable performance and to satisfy the application requirements with computing resources at exposure. This paper posits techniques of using different scheduling techniques for increasing the efficacy of the grid system. This hybrid scheduler could enable the grid system to reduce the execution time. This paper also proposes an architecture which could be implemented ensuring the optimal results in the grid environment. This adaptive scheduler would possibly combine the pros of two scheduling strategies to produce a hybrid scheduling strategy which could cater the ever changing workload encountered by the gird system. The main objective of the proposed system is to reduce to overall job execution time and processor utilization time.  2020, Springer Nature Switzerland AG.</text>
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                <text>Lecture Notes on Data Engineering and Communications Technologies, Vol-33, pp. 387-394.</text>
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                <text>ISSN: 23674512</text>
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                <text>Sinha P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India; Aeishel G., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India</text>
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                <text>Computational modeling of heat transfer in magneto-non-Newtonian material in a circular tube with viscous and Joule heating</text>
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                <text>Casson fluid; DarcyForchheimer flow; heat source/sink; heat transfer; Joule heating; viscous dissipation</text>
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                <text>Numerous industrial and engineering systems, like, heat exchangers, chemical action reactors, geothermic systems, geological setups, and many others, involve convective heat transfer through a porous medium. The diffusion rate, drag force, and mechanical phenomenon are dealt with in the DarcyForchheimer model, and hence this model is vital to study the fluid flow and heat transport analysis. Therefore, numerical simulation of the DarcyForchheimer dynamics of a Casson material in a circular tube subjected to the energy losses due to the viscous heating and Joule dissipation mechanisms is performed. The novelty of the present investigation is to scrutinize the convective heat transport characteristics in a circular tube saturated with DarcyForchheimer porous matrix by utilizing the non-Newtonian Casson fluid. The flow occurs due to the elongation of the surface of a tube with a uniform heat-based source/sink. The similarity solution of the nonlinear problem was obtained using dimensionless similarity variables. The effects of operating parameters related to the flow phenomena are analyzed. Further, the friction factor and Nusselt number are also analyzed in detail. The present flow model ensures no flow reversal and acts as a coolant of the heated cylindrical surface; the existence of the magnetic field, as well as an inertial coefficient,acts as the momentum-breaking forces, whereas Casson fluidity buildsit. The Joule heating phenomenon enhances the magnitude of temperature. The thermal field of the Casson fluid is higher at the surface of the circular pipe due to convective thermal conditions.  2021 Wiley Periodicals LLC.</text>
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                <text>Mahanthesh B.; Al-Kouz W.; Swain K.; Rout P.K.</text>
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                <text>Heat Transfer, Vol-50, No. 7, pp. 6703-6718.</text>
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                <text>Mahanthesh B., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Al-Kouz W., Mechanical and Maintenance Engineering Department, German Jordanian University, Amman, Jordan; Swain K., Department of Mathematics, Gandhi Institute for Technology, Bhubaneswar, Odisha, India; Rout P.K., Department of Mathematics, Gandhi Institute for Technology, Bhubaneswar, Odisha, India</text>
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                <text>Computational Modelling of Complex Systems for Democratizing Higher Education: A Tutorial on SAR Simulation</text>
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              <elementText elementTextId="174903">
                <text>Colaboratory; Jupyter; Python; Reproducible research; SAR</text>
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                <text>Engineering systems like Synthetic Aperture Radar (SAR) are complex systems and require multi-domain knowledge to understand. Teaching and learning SAR processing is intensive in terms of time and resources. It also requires software tools and computational power for preprocessing and image analysis. Extensive literature exists on computational models of SAR in MATLAB and other commercial platforms. Availability of computational models in open-source reproducible platforms like Python kernel in Jupyter notebooks running on Google Colaboratory democratizes such difficult topics and facilitates student learning. The model, discussed here, generates SAR data for a point scatterer using SAR geometry, antenna pattern, and range equation and processes the data in range and azimuth with an aim to generate SAR image. The model demonstrates the generation of synthetic aperture and the echo signal qualities as also how the pulse-to-pulse fluctuating range of a target requires resampling to align the energy with a regular grid. The model allows for changing parameters to alter for resolution, squint, geometry, radar elements such as antenna dimensions, and other factors. A successful learning outcome would be to understand where parameters need to be changed, to affect the model in a specific way. Factors affecting Range Doppler processing are demonstrated. Use of the discussed model nullifies use of commercial software and democratizes SAR topic in higher education.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Govind P.J.; Kumar N.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 723-734.</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-19-9379-4_52" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-9379-4_52&lt;/a&gt;
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                <text>ISSN: 23673370; ISBN: 978-981199378-7</text>
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                <text>Govind P.J., CHRIST (Deemed to be University), Kengeri, Bangalore, India; Kumar N., CHRIST (Deemed to be University), Kengeri, Bangalore, India</text>
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                <text>Computational screening of natural compounds from Salvia plebeia R. Br. for inhibition of SARS-CoV-2 main protease</text>
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                <text>ADMET; Main protease; Molecular docking; Molecular dynamic simulation; PASS; Plebeiosides B; Rutin; Salvia plebeia R. Br</text>
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                <text>The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to ? 8.0kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of ? 9.1kcal/mol and ? 8.9kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected proteinligand complexes to confirm their stability at 300ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Graphic abstract: [Figure not available: see fulltext.]  2021, Society for Plant Research.</text>
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                <text>Zackria A.A.; Pattabiraman R.; Murthy T.P.K.; Kumar S.B.; Mathew B.B.; Biju V.G.</text>
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                <text>Vegetos, Vol-35, No. 2, pp. 345-359.</text>
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                <text>&lt;a href="https://doi.org/10.1007/s42535-021-00304-z" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s42535-021-00304-z&lt;/a&gt;
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              <elementText elementTextId="107497">
                <text>All Open Access; Green Open Access; Hybrid Gold Open Access</text>
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                <text>ISSN: 9704078</text>
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                <text>Zackria A.A., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Pattabiraman R., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Murthy T.P.K., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Kumar S.B., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Mathew B.B., Department of Biotechnology, Dayananda Sagar College of Engineering, Karnataka, Bengaluru, 560078, India; Biju V.G., Department of Computer Science and Engineering, Christ (Deemed-to-be University), Karnataka, Bengaluru, 560060, India</text>
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              <elementText elementTextId="105934">
                <text>Computational simulation of surface tension and gravitation-induced convective flow of a nanoliquid with cross-diffusion: An optimization procedure</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
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              <elementText elementTextId="105935">
                <text>Boundary layer flow; Inclined magnetic field; Marangoni convection; Nanoliquid; RSM; Sensitivity analysis; Thermal radiation</text>
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                <text>The control of heat transfer in the hydromagnetic semiconductor crystal involves Marangoni convection with buoyancy forces. In this study, the conventional thermo-solutal Marangoni mixed flow model is modified by incorporating the solutal buoyancy effects that are significant in the flow phenomenon. The heat and mass transfer (HMT) characteristics of the Marangoni convective flow of a Cu ? H2O nanofluid subjected to the assisting/resisting buoyancy forces and cross-diffusion are numerically studied. The homogeneous single-phase nanoliquid model is used in conjunction with experimental data of dynamic viscosity and thermal conductivity. The Dufour and Soret effects are considered. Governing equations are solved using the finite difference-based algorithm. The problem is analyzed in a unified way considering the cases of buoyancy-assisted flow and buoyancy-opposed flow. The response surface methodology (RSM) based on the face-centered composite design (CCD) is used to optimize the heat and mass transfer rates. A multivariate regression model is proposed and authenticated prior to optimization. Additionally, sensitivity analysis is performed using the full quadratic regression model. The increase in the temperature profile is more significant due to the radiative heat flux than the inclined magnetic field. Heat transfer has a high sensitivity to the appearance of thermal radiation, while mass transfer has a high sensitivity to the Soret effect. Simultaneous optimization of HMT rates is achieved with the high level of thermal radiation and low levels of the cross-diffusion aspects.  2022</text>
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              <elementText elementTextId="105937">
                <text>Mackolil J.; Mahanthesh B.</text>
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              <elementText elementTextId="105938">
                <text>Applied Mathematics and Computation, Vol-425</text>
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              <elementText elementTextId="105939">
                <text>Elsevier Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.amc.2022.127108" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.amc.2022.127108&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127209052&amp;amp;doi=10.1016%2Fj.amc.2022.127108&amp;amp;partnerID=40&amp;amp;md5=e78a60c498645bd33e5ebbfa752128dc" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127209052&amp;amp;doi=10.1016%2fj.amc.2022.127108&amp;amp;partnerID=40&amp;amp;md5=e78a60c498645bd33e5ebbfa752128dc&lt;/a&gt;</text>
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                <text>Restricted Access</text>
              </elementText>
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                <text>ISSN: 963003; CODEN: AMHCB</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="105944">
                <text>Online</text>
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              <elementText elementTextId="105945">
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              <elementText elementTextId="105947">
                <text>Mackolil J., Department of Mathematics, Centre for Mathematical Needs, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mahanthesh B., Department of Mathematics, Centre for Mathematical Needs, CHRIST (Deemed to be University), Bengaluru, 560029, India</text>
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          <element elementId="50">
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                <text>Computational statistics of data science for secured software engineering</text>
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            <description>An account of the resource</description>
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                <text>The chapter focuses on exploring the work done for applying data science for software engineering, focusing on secured software systems development. With requirements management being the first stage of the life cycle, all the approaches that can help security mindset right at the beginning are explored. By exploring the work done in this area, various key themes of security and its data sources are explored, which will mark the setup of base for advanced exploration of the better approaches to make software systems mature. Based on the assessments of some of the work done in this area, possible prospects are explored. This exploration also helps to emphasize the key challenges that are causing trouble for the software development community. The work also explores the possible collaboration across machine learning, deep learning, and natural language processing approaches. The work helps to throw light on critical dimensions of software development where security plays a key role.  2021, IGI Global.</text>
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              <elementText elementTextId="157981">
                <text>Althar R.R.; Samanta D.</text>
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              <elementText elementTextId="157982">
                <text>Methodologies and Applications of Computational Statistics for Machine Intelligence, pp. 81-96.</text>
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                <text>&lt;a href="https://doi.org/10.4018/978-1-7998-7701-1.ch005" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/978-1-7998-7701-1.ch005&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124797202&amp;amp;doi=10.4018%2F978-1-7998-7701-1.ch005&amp;amp;partnerID=40&amp;amp;md5=08fd2433a75779442f4ae6c963cf1eed" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124797202&amp;amp;doi=10.4018%2f978-1-7998-7701-1.ch005&amp;amp;partnerID=40&amp;amp;md5=08fd2433a75779442f4ae6c963cf1eed&lt;/a&gt;</text>
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="157986">
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                <text>ISBN: 978-179987703-5; 978-179987701-1</text>
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              <elementText elementTextId="157989">
                <text>English</text>
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                <text>Althar R.R., Christ (Deemed to be University), QMS, First American India, Bangalore, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India</text>
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              <elementText elementTextId="91161">
                <text>Computational studies into the chemical nature, thermal behaviour, solvent role, reactivity and biological evaluation of Rigidin E  A marine alkaloid with potent liver cancer inhibition</text>
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                <text>ADMET; Anti-cancer; DFT; Docking; Marine alkaloid</text>
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                <text>The current work includes theoretical studies of Rigidin E (marine alkaloid) molecule with the DFT technique and evaluation of its biological properties in silico. DFT calculations in different media were performed for the title molecule. Gradual changes were noticed in the properties of the title compound when subjected to solvation in polar solvents. Electron density distribution, interaction and excitation were demonstrated using topological studies (ELF, LOL, RDG, and charge transfer) done using Multiwfn software. From FMO analysis, methanol is the solvent in which the title compound has the highest band gap value (3.8972 eV) compared to other solvents, and in the gas phase it has a band gap value of 3.6886 eV. Theoretical UV studies show that n -&amp;gt;?* and n -&amp;gt;?* electronic transitions are significant in Rigidin E. In water, the title molecule has a first-order hyperpolarizability about 100 times that of the reference substance urea, indicating its powerful NLO potential in aqueous medium. ADMET profile was generated using online tools (ADMET lab 2.0, PreADMET, and SwissADME). For the title molecule, docking was done against select liver cancer targets using AutoDock Tools and the lowest binding affinity was obtained ?4.62 kcal/mol against 4H6J protein.  2023 Elsevier B.V.</text>
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                <text>Hammad W.; Parakkal S.C.; Datta R.; Muthu S.; Alharbi N.S.; Abbas G.</text>
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                <text>Journal of Molecular Liquids, Vol-392</text>
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                <text>Elsevier B.V.</text>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.molliq.2023.123514" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.molliq.2023.123514&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175848353&amp;amp;doi=10.1016%2Fj.molliq.2023.123514&amp;amp;partnerID=40&amp;amp;md5=b252379d86a472b43f8b02701b9a8145" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175848353&amp;amp;doi=10.1016%2fj.molliq.2023.123514&amp;amp;partnerID=40&amp;amp;md5=b252379d86a472b43f8b02701b9a8145&lt;/a&gt;</text>
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                <text>ISSN: 1677322; CODEN: JMLID</text>
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                <text>Hammad W., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Abbas G., Institute of Inorganic Chemistry, Karlsruhe Institute of Technology, Engesserstr 15, Karlsruhe, 76131, Germany</text>
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                <text>Computational study of charge transfer iso-surface in first three excited states, electron-hole transition effects, chemical nature and bond order analysis investigations of chrysogine</text>
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                <text>ADMET; DFT; Docking; Lung cancer; Topology</text>
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                <text>This work presents the theoretical DFT (Density Functional Theory) studies and the biological application of chrysogine, a marine alkaloid. Energy minimisation and additional DFT evaluations were performed for vacuum and solvent media. It has been observed that solvation with polar solvents has resulted in a slight variation in the molecule's properties. The Multiwfn software was employed to carry out various topological analyses. Among these, the charge transfer studies show that the second and third excited states are the most significant. From the reactivity analysis, the least energy gap (4.9624 eV) is obtained in water, indicating that chrysogine is most reactive in aqueous media. Theoretical UV studies show that the trends in ?max values correspond to n &amp;gt;?* and n &amp;gt;?* electronic transitions within the molecule. An increase in medium polarity has demonstrated in the MEP (Molecular Electrostatic Potential) maps an increase in the potential range from ?6.619 10?2 a.u. to 6.619 10?2 a.u. in the gas phase, to a sharp rise to ?8.036 10?2 a.u. to 8.036 10?2 a.u. in ethanol, ?8.098 10?2 a.u. to 8.098 10?2 a.u. in methanol, ?8.130 10?2 a.u. to 8.130 10?2 a.u. in DMSO, and ?8.127 10-2 a.u. to 8.127 10?2 a.u. in water. The most significant transition contributing to molecular stability from NBO (Natural Bond Orbital) analysis is: (O2-C9) ?* ? ?* (C7-C8) with the energy of 258.13 kcal mol?1. The ADMET profile for the molecule was assimilated with the help of online servers. The molecule was docked against lung cancer target proteins (PDB ID: 1NTK, 3QFB) using software such as AutoDock Tools and PyMOL. The respective illustrations and data were visualised using Discovery Studio Visualizer. Good binding affinities (?5.69 kcal mol?1 for 1NTK and ?6.64 kcal mol?1 for 3QFB proteins) and interactions were achieved with the selected targets.  2024 Elsevier B.V.</text>
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              <elementText elementTextId="79794">
                <text>Bhargiri J.J.; Parakkal S.C.; Datta R.; Alharbi N.S.; Kadaikunnan S.; Muthu S.</text>
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                <text>Computational and Theoretical Chemistry, Vol-1237</text>
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                <text>Elsevier B.V.</text>
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                <text>2024-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.comptc.2024.114649" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.comptc.2024.114649&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193487312&amp;amp;doi=10.1016%2Fj.comptc.2024.114649&amp;amp;partnerID=40&amp;amp;md5=aaaf9ab39fb482adfb5437b8b0eb6b6b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193487312&amp;amp;doi=10.1016%2fj.comptc.2024.114649&amp;amp;partnerID=40&amp;amp;md5=aaaf9ab39fb482adfb5437b8b0eb6b6b&lt;/a&gt;</text>
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                <text>ISSN: 2210271X</text>
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                <text>Bhargiri J.J., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Kadaikunnan S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India</text>
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