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Shiv Nadar University

Center for Informatics

Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or equivalently, glucose-binding pockets. In this work, we combine molecular dynamics simulations of HSA and the state-of-art machine learning method Support Vector Machine (SVM) to predict glucose-binding pockets in HSA. SVM uses the three dimensional arrangement of atoms and their chemical properties to predict glucose-binding ability of a pocket. Feature selection reveals that the arrangement of atoms and their chemical properties within the first 4Å from the centroid of the pocket play an important role in the binding of glucose. With a 10-fold cross validation accuracy of 84 percent, our SVM model reveals seven new potential glucose-binding sites in HSA of which two are exposed only during the dynamics of HSA. The predictions are further corroborated using docking studies. These findings can complement studies directed towards the development of HSA as an alternate biomarker for glycemic monitoring. © 2016 IEEE.

World University root node

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations

The atomic and electronic structure of both neutral and negatively charged ZrGen (n=1-21) clusters have been studied using ab initio calculations. The atomic structures have been identified by comparing the calculated results of the electronic spectra of the anion clusters with the available photoelectron spectroscopy data. We find that the atomic structure of ZrGen cluster can be derived by adding one or more Ge atoms on smaller clusters. Our results show that in some cases a higher energy isomer of ZrGen anion cluster may be present in experiments, but the neutral of such an anion is often the lowest energy isomer. This shows the importance of the lowest energy isomer of neutral clusters in experiment. In some cases, it is found that two different isomers of the anion of a cluster converge to the identical isomer of the neutral. A large value of the highest occupied molecular orbital-lowest unoccupied molecular orbital gap as well as binding energy per atom has been calculated for ZrGe16 neutral cluster and hence, it is more stable and less reactive as compared to other clusters. This agrees with the high abundance of ZrGe16 cluster in experiments. The Zr atom is encapsulated in a cage-like structure at a size of thirteen or more Ge atoms. This also agrees with the experiments. Further, we have calculated vertical and adiabatic detachment energies and obtained a low value for ZrGe16 also in agreement with experiments. The addition of an electron to a neutral ZrGe11 cluster, however, changes its atomic structure drastically and thus, the calculated adiabatic and vertical detachment energies for ZrGe11 anion differ very significantly. © 2015 Elsevier B.V.

Computational and Theoretical Chemistry

Growth behavior and electronic structure of neutral and anion ZrGen (n=1-21) clusters

In this paper, we develop a first principles atomistic model of single atom substitutions within boron suboxide to predict the effect of potential sintering aides (Al, Mg, Si, and Lu) and processing contaminants (C, N, F, S, P, Li, and Ti) on its cohesive energies and local bonding reconstruction. Our results indicate that metallic dopants strongly destabilize the B6O crystal structure. However, non-metallic dopants, particularly C and N, only slightly weaken the cohesive energy of the crystal. We then performed a more detailed study of multi-atom carbon substitution within B6O. The energetic cost (2.81 eV) associated with doping two carbon atoms was highest when the carbon substituted for two polar boron sites from adjacent icosahedra and lowest when the carbon replaces both an equatorial boron and its neighboring oxygen, forming a Q-Co dimer. When a C-B-C chain replaced an 0-0 chain within the B6O unit cell, the product state was lower in energy than pristine B6O. As more carbon substituted within the icosahedra neighboring the C-B-C chain, the product structure became increasingly lower in energy. This suggested an exothermic reaction pathway for the precipitation of a local boron carbide-like structure from B6O. These results partially explain the driving force behind the formation of B4C that is often encountered during B6O processing. © 2016 by The American Ceramic Society.

Ceramic Engineering and Science Proceedings

First principles calculations of dopant effects in boron suboxide

ARMY RESEARCH LAB ABERDEEN PROVING GROUND MD WEAPONS AND MATERIALS RESEARCH {\ldots}

Effect of Carbon Doping on the Electronic Structure and Elastic Properties of Boron Suboxide

We report results of the atomic structure, alloying behavior, and magnetism in FemPtn(m+n=2-10) clusters using projector augmented wave (PAW) pseudopotential method and spin-polarized generalized gradient approximation (GGA) for the exchange-correlation energy. These results are compared with those obtained by using HCTH exchange-correlation functional and LANL2DZ basis set in the Gaussian program and the overall trends are found to be similar. As in bulk Fe-Pt alloys, clusters with equal composition of Fe and Pt have the largest binding energy and the largest heat of nanoalloy formation for a given number of atoms in the cluster. There are some deviations due to the different symmetries in clusters and in cases where the total number of atoms is odd. The lowest energy isomers tend to maximize bonds between unlike atoms with Fe (Pt) atoms occupying high (low) coordination sites in the core (surface) of the cluster. The binding energy, heat of formation, and the second order difference of the total energy show Fe2Pt2, Fe4Pt4, and Fe4Pt6 clusters to be the most stable ones among the different clusters we have studied. The magnetic moments on Fe atoms are high in Pt-rich clusters as well as in small Fe-rich clusters and decrease as the aggregation of Fe atoms and the cluster size increases. The maximum value of the magnetic moments on Fe atoms is ∼3.8μB, whereas for Pt atoms it is 1 μB. These are quite high compared with the values for bulk Fe as well as bulk FePt and Fe3Pt phases while bulk Pt is nonmagnetic. There is significant charge transfer from those Fe atoms that interact directly with Pt atoms. We discuss the hybridization between the electronic states of Pt and Fe atoms as well as the variation in the magnetic moments on Fe and Pt atoms. Our results provide insight into the understanding of the nanoalloy behavior of Fe-Pt and we hope that this would help to design Fe based nanoalloys and their assemblies with high magnetic moments for strong magnets without rare earths as well as Pt alloy catalysts. © 2015 American Physical Society. ©2015 American Physical Society.

Physical Review B - Condensed Matter and Materials Physics

Atomic structure, alloying behavior, and magnetism in small Fe-Pt clusters

We report the finding of a bowl-shaped quasi-planar structure of a B84 cluster with four hexagonal holes and a three-chain ring all around the edges using ab initio calculations. A large number of other isomers including those explored earlier such as an empty cage, a filled cage, and a disordered structure, have been found to lie in a significantly higher energy band. A tubular structure, however, is only about 0.45 eV higher in energy. Calculations of the infrared and Raman spectra show that the quasi-planar structure is dynamically stable. These results suggest that quasi-planar structures may be among the low energy structures for larger clusters as well. Accordingly we have calculated the optimal quasi-planar structures stabilized with 2, 3, 5, 6, and 7 hexagonal holes also. The stability of quasi-planar structures is discussed in terms of multi-center two-electron bonding and it is shown that with increasing size their binding energy tends to approach the value for an α-boron sheet. This journal is © The Royal Society of Chemistry.

Fulltext

Nanoscale

B84: A quasi-planar boron cluster stabilized with hexagonal holes

In this paper, we propose a hybrid filter-wrapper algorithm, GSO-Infogain, for simultaneous feature selection for improved classification accuracy. GSO-Infogain employs Glowworm-Swarm Optimization(GSO) algorithm with Support Vector Machine(SVM) as its internal learning algorithm and utilizes feature ranking based on information gain as a heuristic. The GSO algorithm randomly generates a population of worms, each of which is a candidate subset of features. The fitness of each candidate solution, which is evaluated using Support Vector Machine, is encoded within its luciferin value. Each worm probabilistically moves towards the worm with the highest luciferin value in its neighbourhood. In the process, they explore the feature space and eventually converge to the global optimum. We have evaluated the performance of the hybrid algorithm for feature selection on a set of cancer datasets. We obtain a classification accuracy in the range 94-98\% for these datasets, which is comparable to the best results from other classification algorithms. We further tested the robustness of GSO-Infogain by evaluating its performance on the CoEPrA training and test datasets. GSO-Infogain performs well in this experiment too by giving similar prediction accuracies on the training and test datasets thus indicating its robustness. © Springer International Publishing Switzerland 2015.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Glowworm swarm based informative attribute selection using support vector machines for simultaneous feature selection and classification

Using ab initio calculations, we demonstrate the strong influence of valence electron concentration (VEC) on the local atomic structure and electronic properties of Mo6S9-xIx (x = 0-9) nanowires (NWs). We find new atomic models of the NWs with unique decoration of S/I atoms that are more stable than reported earlier. The electronic and mechanical properties of these NWs are in good agreement with experiments. Further we tuned VEC by either varying the number of I atoms or adding S/Li atoms to obtain semiconducting Mo6S3I6, Mo6S2I8, Li6Mo6S9, and Li3Mo6S6I3 NWs, all of which have VEC of 24 and isolated Mo6 octahedral units, as observed in bulk cluster compounds. These results suggest that VEC is the thumb rule to design and tune the atomic structure and electronic properties of Mo-S-I cluster based nanostructures. © 2015 American Chemical Society.

Journal of Physical Chemistry C

The role of valence electron concentration in tuning the structure, stability, and electronic properties of Mo6S9-xIx nanowires

We report results of a systematic study on atomic and electronic structure of 55-atom and 147-atom Fe-Pt nanoparticles with different compositions using ab initio calculations. Our results on 55-atom nanoparticles suggest icosahedral structure and segregation of Pt on the surface to be favorable. Also, there is a tendency for Fe-Pt ordering on the surface and maximization of the unlike bonds similar to the bulk, while the core is made of pure Fe13, giving it a core-shell structure. Using these considerations, we designed a unique 147-atom icosahedral Fe75Pt72 nanoparticle in which a 55-atom core is made of Fe atoms and 72 Pt atoms are on the outer shell of the icosahedron. Twenty Fe atoms are on the centers of the Pt hexagons on the faces of the icosahedron. This nanoparticle has 260 μB magnetic moments, and the local magnetic moments on Fe and Pt atoms are higher compared with the values in bulk FePt. The free Fe55 cluster has a distorted icosahedral structure to be most favorable, with large magnetic moments (∼3 μB/atom), which we also find in the core of the nanoalloy particle, but the surface Fe atoms have higher magnetic moments of about 3.4 μB/atom. All the Pt atoms are on the surface with Fe-Pt ordering in a nearly symmetric icosahedral structure, and the heat of formation is the highest, which makes it an optimal nanoparticle. The overall composition of this nanoparticle is FePt-like, but it decomposes to Fe core and Fe-Pt shell. © 2015 American Chemical Society.