01786nas a2200157 4500008004100000245006900041210006700110260000800177300001400185490000600199520128500205100001501490700002101505700001701526856008501543 2019 eng d00aInsights into the origin of life: did it begin from HCN and H2O?0 aInsights into the origin of life did it begin from HCN and H2O cSEP a1532-15400 v53 a

The seminal Urey-Miller experiments showed that molecules crucial to life such as HCN could have formed in the reducing atmosphere of the Hadean Earth and then dissolved in the oceans. Subsequent proponents of the "RNA World" hypothesis have shown aqueous HCN to be the starting point for the formation of the precursors of RNA and proteins. However, the conditions of early Earth suggest that aqueous HCN would have had to react under a significant number of constraints. Therefore, given the limiting conditions, could RNA and protein precursors still have formed from aqueous HCN? If so, what mechanistic routes would have been followed? The current computational study, with the aid of the ab initio nanoreactor (AINR), a powerful new tool in computational chemistry, addresses these crucial questions. Gratifyingly, not only do the results from the AINR approach show that aqueous HCN could indeed have been the source of RNA and protein precursors, but they also indicate that just the interaction of HCN with water would have sufficed to begin a series of reactions leading to the precursors. The current work therefore provides important missing links in the story of prebiotic chemistry and charts the road from aqueous HCN to the precursors of RNA and proteins.

1 aDas, Tamal1 aGhule, Siddharth1 aVanka, Kumar uhttps://library.ncl.res.in/content/insights-origin-life-did-it-begin-hcn-and-h2o01752nas a2200181 4500008004100000022001400041245008300055210006900138260000900207300001400216490000800230520115100238100002101389700002101410700002701431700001701458856009501475 2020 eng d a1089-563900aUnraveling the hidden role of the counteranion in ``cation in a cage'' systems0 aUnraveling the hidden role of the counteranion in cation in a ca cOCT  a8040-80490 v1243 a

The current work showcases general principles at play in systems consisting of cations present inside molecular cages. Such systems, relevant to chemistry and biology, have been carefully investigated by computational methods. The important Ge(II)-encapsulating cage systems have been studied first. The very fact that such compounds exist appears highly unlikely, given the highly reactive nature of the Ge(II) dication. Our studies reveal what really occurs in solution when such complexes are formed: the Ge(II) dications are actually present as [Ge-X](+) (where X is the ``non-coordinating'' counterion employed in such systems) during entry and subsequent existence at the center of the cage. Hence, what is actually present is a ``pseudomonocation''. Interestingly, such pseudomonocation-encapsulated cages are seen to be equally relevant in systems of biological importance, such as for dicationic s block-based ionophores. In explaining such cases, the concept of ``isoionicity'' is introduced, demonstrating that the counterion-coordinated dications are isoionic with a monocation, such as Li(I), isolated in the same ionophore.

1 aMukherjee, Anagh1 aGhule, Siddharth1 aTiwari, Mrityunjay, K.1 aVanka, Kumar uhttps://library.ncl.res.in/content/unraveling-hidden-role-counteranion-cation-cage-systems02326nas a2200229 4500008004100000022001400041245012600055210006900181260000800250300001400258490000700272520151300279653001901792653003601811653001901847653002001866653002401886100002101910700002101931700001701952856012701969 2021 eng d a1439-423500aComputational insights into the role of external and local electric fields in macrocyclic chemical and biological systems0 aComputational insights into the role of external and local elect cDEC a2484-24920 v223 aThe investigation of the role of the electric field in systems of widespread interest employing computational techniques is an emerging area of research. The outcome of applying an oriented external electric field (OEEF) on the geometric and electronic properties of the chemically unique pi-conjugated cyclic carbon ring compounds has been explored with density functional theory (DFT). Distinct changes in the structural and electronic features of such ring compounds are observed upon the application of OEEFs. Importantly, the calculations indicate that a mixed aliphatic-aromatic conjugated ring converts from a singlet to a triplet after the application of an OEEF, suggesting potential applications in optoelectronics for such molecules, without the need for photochemically induced change in the spin state. Furthermore, the influence of built-in local electric fields (LEFs) present in naturally occurring macrocyclic systems such as valinomycin has also been explored. Static and ab initio molecular dynamics (AIMD) calculations indicate that LEFs are the primary driving factor in determining the energetically favoured position of counter anions such as chloride (Cl-) in the potassium (K+) and sodium (Na+) coordinated valinomycin macrocycle structures: they exist inside the cage in the case of K+ sequestration by valinomycin and outside for Na+. This divergence has been proposed to be the determining factor for the selectivity of the valinomycin macrocycle for binding a K+ cation over Na+.10acounter anions10aDensity functional calculations10aelectric field10aion selectivity10amacrocyclic systems1 aMukherjee, Anagh1 aGhule, Siddharth1 aVanka, Kumar uhttps://library.ncl.res.in/content/computational-insights-role-external-and-local-electric-fields-macrocyclic-chemical-and02230nas a2200193 4500008004100000022001400041245009700055210006900152260000900221300001600230490000600246520156000252100002101812700002501833700001801858700001801876700001701894856012501911 2022 eng d a2470-134300aPredicting the redox potentials of phenazine derivatives using DFT-assisted machine learning0 aPredicting the redox potentials of phenazine derivatives using D cAPR  a11742-117550 v73 a

This study investigates four machine-learning (ML) models to predict the redox potentials of phenazine derivatives in dimethoxyethane using density functional theory (DFT). A small data set of 151 phenazine derivatives having only one type of functional group per molecule (20 unique groups) was used for the training. Prediction accuracy was improved by a combined strategy of feature selection and hyperparameter optimization, using the external validation set. Models were evaluated on the external test set containing new functional groups and diverse molecular structures. High prediction accuracies of R2 > 0.74 were obtained on the external test set. Despite being trained on the molecules with a single type of functional group, models were able to predict the redox potentials of derivatives containing multiple and different types of functional groups with good accuracies (R2 > 0.7). This type of performance for predicting redox potential from such a small and simple data set of phenazine derivatives has never been reported before. Redox flow batteries (RFBs) are emerging as promising candidates for energy storage systems. However, new green and efficient materials are required for their widespread usage. We believe that the hybrid DFT-ML approach demonstrated in this report would help in accelerating the virtual screening of phenazine derivatives, thus saving computational and experimental costs. Using this approach, we have identified promising phenazine derivatives for green energy storage systems such as RFBs.

1 aGhule, Siddharth1 aDash, Soumya, Ranjan1 aBagchi, Sayan1 aJoshi, Kavita1 aVanka, Kumar uhttps://library.ncl.res.in/content/predicting-redox-potentials-phenazine-derivatives-using-dft-assisted-machine-learning