Examinando por Materia "Molecular modeling"

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    A Comparative Assessment of Emerging Solvents and Adsorbents for Mitigating CO2 Emissions From the Industrial Sector by Using Molecular Modeling Tools
    (Frontiers Media S.A., 2020-01-01) Bahamon D.; Alkhatib I.I.I.; Alkhatib N.; Builes S.; Sinnokrot M.; Vega L.F.; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de Procesos
    The possibilities offered by molecular modeling tools to obtain relevant data at process conditions, while also gaining molecular insights on the techniques used for CO2 capture and separation, are presented here using selected case studies. Two different technologies, absorption with amine-based systems and adsorption on porous materials, were explored, using the molecular-based equation of state, soft-Statistical Associating Fluid Theory (SAFT), and Grand Canonical Monte Carlo simulations, respectively. The aqueous monoethanolamine (MEA) system was set as the benchmark for absorption and compared to the performance of 8 alternative amine-based systems, while 16 adsorbents belonging to different families (zeolites, metal–organic frameworks, amorphous silicas, and activated carbons), bare or functionalized with alkylamines, were investigated for the separation of CO2 by adsorption. In addition to obtaining molecular information on the CO2 capture process, the models were further used to examine the CO2 capture performance in terms of cyclic working capacity and energy index as key performance indicators, allowing the identification of promising systems that can improve the current ones to be further evaluated for separation in non-power industries. Results show that for the same total amine mass concentration, non-aqueous amine solvents have a 5–10% reduction in cyclic working capacity, and a 10–30% decrease in the energy index compared to their aqueous counterparts due to their lower heat of vaporization and specific heat capacity. In addition, M-MOF-74, NaX, and NaY structures present the best results for adsorption in temperature swing adsorption (TSA) processes. Similar values of energy requirements to those of amine-based systems (2–2.5 MJ kg CO2–1) were obtained for some of the adsorbent; however, the disadvantage of the TSA process versus absorption should be considered. These results confirm the reliability of molecular modeling as an attractive and valuable screening tool for CO2 capture and separation processes. © Copyright © 2020 Bahamon, Alkhatib, Alkhatib, Builes, Sinnokrot and Vega.
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    Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands
    (Springer International Publishing, 2016-05-01) Pérez, G.M.; Salomón, L.A.; Montero-Cabrera, L.A.; de la Vega, J.M.G.; Mascini, M.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
    A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.