74 research outputs found
A coarse graining approach to determine nucleic acid structures from small angle neutron scattering profiles in solution
We present a theoretical method to calculate the small angle neutron scattering profile of nucleic acid structures in solution. Our approach is sensitive to the sequence and the structure of the nucleic acid. In order to test our approach, we apply this method to the calculation of the experimental scattered intensity of the decamer d(CCAACGTTGG)(2) in H(2)O. This sequence was specifically chosen for this study as it is believed to adopt a canonical B-form structure in 0.3 M NaCl. We find that not only will our methodology reproduce the experimental scattered intensity for this sequence, but our method will also discriminate between B-, A- and Z-form DNA. By studying the scattering profile of this structure in 0.5 and 1.0 M NaCl, we are also able to identify tetraplex and other similar oligomers formation and to model the complex using the experimental scattering data in conjunction with our methodology
Quantum and classical vibrational relaxation dynamics of N-methylacetamide on ab initio potential energy surfaces
Employing extensive quantum-chemical calculations at the DFT/B3LYP and MP2
level, a quartic force field of isolated N-methylacetamide is constructed.
Taking into account 24 vibrational degrees of freedom, the model is employed to
perform numerically exact vibrational configuration interaction calculations of
the vibrational energy relaxation of the amide I mode. It is found that the
energy transfer pathways may sensitively depend on details of the theoretical
description. Moreover, the exact reference calculations were used to study the
applicability and accuracy of (i) the quasiclassical trajectory method, (ii)
time-dependent second-order perturbation theory, and (iii) the instantaneous
normal mode description of frequency fluctuations. Based on the results,
several strategies to describe vibrational energy relaxation in biomolecular
systems are discussed.Comment: 18 pages, 6 figures, submitted to J. Phys. Chem.
Unbiased Global Optimization of Lennard-Jones Clusters for N <= 201 by Conformational Space Annealing Method
We apply the conformational space annealing (CSA) method to the Lennard-Jones
clusters and find all known lowest energy configurations up to 201 atoms,
without using extra information of the problem such as the structures of the
known global energy minima. In addition, the robustness of the algorithm with
respect to the randomness of initial conditions of the problem is demonstrated
by ten successful independent runs up to 183 atoms. Our results indicate that
the CSA method is a general and yet efficient global optimization algorithm
applicable to many systems.Comment: revtex, 4 pages, 2 figures. Physical Review Letters, in pres
Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms
We describe a global optimization technique using `basin-hopping' in which
the potential energy surface is transformed into a collection of
interpenetrating staircases. This method has been designed to exploit the
features which recent work suggests must be present in an energy landscape for
efficient relaxation to the global minimum. The transformation associates any
point in configuration space with the local minimum obtained by a geometry
optimization started from that point, effectively removing transition state
regions from the problem. However, unlike other methods based upon hypersurface
deformation, this transformation does not change the global minimum. The lowest
known structures are located for all Lennard-Jones clusters up to 110 atoms,
including a number that have never been found before in unbiased searches.Comment: 8 pages, 3 figures, revte
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AB Initio Protein Tertiary Structure Prediction: Comparative-Genetic Algorithm with Graph Theoretical Methods
During the period from September 1, 1998 until September 1, 2000 I was awarded a Sloan/DOE postdoctoral fellowship to work in collaboration with Professor John Moult at the Center for Advanced Research in Biotechnology (CARB). Our research project, ''Ab Initio Protein Tertiary Structure Prediction and a Comparative Genetic algorithm'', yielded promising initial results. In short, the project is designed to predict the native fold, or native tertiary structure, of a given protein by inputting only the primary sequence of the protein (one or three letter code). The algorithm is based on a general learning, or evolutionary algorithm and is called Genetic Algorithm (GAS). In our particular application of GAS, we search for native folds, or lowest energy structures, using two different descriptions for the interactions of the atoms and residues in a given protein sequence. One potential energy function is based on a free energy description, while the other function is a threading potential derived by Moult and Samudrala. This modified genetic algorithm was loosely termed a Comparative Genetic Algorithm and was designed to search for native folded structures on both potential energy surfaces, simultaneously. We tested the algorithm on a series of peptides ranging from 11 to 15 residues in length, which are thought to be independent folding units and thereby will fold to native structures independent of the larger protein environment. Our initial results indicated a modest increase in accuracy, as compared to a standard Genetic Algorithm. We are now in the process of improving the algorithm to increase the sensitivity to other inputs, such as secondary structure requirements. The project did not involve additional students and as of yet, the work has not been published
Information and Data Sharing Policy, Genomic Science Program, DOE
The Office of Biological and Environmental Research (OBER) will require that all publishable information resulting from GTL funded research must conform to community recognized standard formats when they exist, be clearly attributable, and be deposited within a community recognized public database(s) appropriate for the research conducted. Furthermore, all experimental data obtained as a result of GTL funded research must be kept in an archive maintained by the Principal Investigator (PI) for the duration of the funded project. Any publications resulting from the use of shared experimental data must accurately acknowledge the original source or provider of the attributable data. The publication of information resulting from GTL funded research must be consistent with the Intellectual Property provisions of the contract under which the publishable information was produced
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