In this work, we combine the strengths of mixed-integer linear optimization (MILP) and logistic regression for predicting the in vivo toxicity of chemicals using only their measured in vitro assay data. The proposed approach utilizes a biclustering method based on iterative optimal reordering (DiMaggio, P. A., McAllister, S. R., Floudas, C. A., Feng, X. J., Rabinowitz, J. D., and Rabitz, H. A. (2008). Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies. BMC Bioinformatics 9, 458-474.; DiMaggio, P. A., McAllister, S. R., Floudas, C. A., Feng, X. J., Rabinowitz, J. D., and Rabitz, H. A. (2010b). A network flow model for biclustering via optimal re-ordering of data matrices. J. Global. Optim. 47, 343-354.) to identify biclusters corresponding to subsets of chemicals that have similar responses over distinct subsets of the in vitro assays. The biclustering of the in vitro assays is shown to result in significant clustering based on assay target (e.g., cytochrome P450 [CYP] and nuclear receptors) and type (e.g., downregulated BioMAP and biochemical high-throughput screening protein kinase activity assays). An optimal method based on mixed-integer linear optimization for reordering sparse data matrices (DiMaggio, P. A., McAllister, S. R., Floudas, C. A., Feng, X. J., Li, G. Y., Rabinowitz, J. D., and Rabitz, H. A. (2010a). Enhancing molecular discovery using descriptor-free rearrangement clustering techniques for sparse data sets. AIChE J. 56, 405-418.; McAllister, S. R., DiMaggio, P. A., and Floudas, C. A. (2009). Mathematical modeling and efficient optimization methods for the distance-dependent rearrangement clustering problem. J. Global. Optim. 45, 111-129) is then applied to the in vivo data set (21.7% sparse) in order to cluster end points that have similar lowest effect level (LEL) values, where it is observed that the end points are effectively clustered according to (1) animal species (i.e., the chronic mouse and chronic rat end points were clearly separated) and (2) similar physiological attributes (i.e., liver- and reproductive-related end points were found to separately cluster together). As the liver and reproductive end points exhibited the largest degree of correlation, we further analyzed them using regularized logistic regression in a rank-and-drop framework to identify which subset of in vitro features could be utilized for in vivo toxicity prediction. It was observed that the in vivo end points that had similar LEL responses over the 309 chemicals (as determined by the sparse clustering results) also shared a significant subset of selected in vitro descriptors. Comparing the significant descriptors between the two different categories of end points revealed a specificity of the CYP assays for the liver end points and preferential selection of the estrogen/androgen nuclear receptors by the reproductive end points.

PURPOSE. To characterize visual loss across the full visual field in idiopathic intracranial hypertension (IIH) patients with mild central visual loss. METHODS. We tested the full visual field (508 nasal, 808 temporal, 308 superior, 458 inferior) of 1 eye of 39 IIH patients by using static perimetry (size V) with the Open Perimetry Interface. Participants met the Dandy criteria for IIH and had at least Frisén grade 1 papilledema with better than À5 dB mean deviation (MD) centrally. Two observers (MW and AS) evaluated the visual field defects, adjudicated any differences, and reviewed optical coherence tomography data. RESULTS. We found a greater MD loss peripherally than centrally (central 268). The median MD (and corresponding median absolute deviations) was À1.37 dB (1.61 dB) for the periphery and À0.77 dB (0.87 dB) for the central 268, P < 0.001. There were about 30% more abnormal test locations identified in the periphery (P ¼ 0.12), and the mean defect depth increased with eccentricity (P < 0.001). The most frequent defect found was a temporal wedge (23% of cases) in the periphery with another 23% that included this sector with inferior temporal loss. Although the presence of papilledema limited correlation, 55% of the temporal wedge defects had optical coherence tomography retinal nerve fiber layer deficits in the corresponding superonasal location. Other common visual field defects were inferonasal loss, superonasal loss, and superior and inferior arcuate defects. Seven patients (18%) had visual field defects in the periphery with normal central visual field testing. CONCLUSION. In IIH patients, we found substantial visual loss both outside 308 of the visual field and inside 308 with the depth of the defect increasing linearly with eccentricity. Temporal wedge defects were the most common visual field defect in the periphery. Static threshold perimetry of the full visual field appears to be clinically useful in IIH patients.

The prediction of loop structures is considered one of the main challenges in the protein folding problem. Regardless of the dependence of the overall algorithm on the protein data bank, the flexibility of loop regions dictates the need for special attention to their structures. In this article, we present algorithms for loop structure prediction with fixed stem and flexible stem geometry. In the flexible stem geometry problem, only the secondary structure of three stem residues on either side of the loop is known. In the fixed stem geometry problem, the structure of the three stem residues on either side of the loop is also known. Initial loop structures are generated using a probability database for the flexible stem geometry problem, and using torsion angle dynamics for the fixed stem geometry problem. Three rotamer optimization algorithms are introduced to alleviate steric clashes between the generated backbone structures and the side chain rotamers. The structures are optimized by energy minimization using an all atom force field. The optimized structures are clustered using a traveling salesman problem based clustering algorithm. The structures in the densest clusters are then utilized to refine dihedral angle bounds on all amino acids in the loop. The entire procedure is carried out for a number of iterations, leading to improved structure prediction and refined dihedral angle bounds. The algorithms presented in this article has been tested on 3190 loops from the PDBSelect25 data set and on targets from the recently concluded CASP9 community-wide experiment.

The three-dimensional (3-D) structure prediction of proteins, given their amino acid sequence, is addressed using the first principles–based approach ASTRO-FOLD 2.0. The key features presented are: (1) Secondary structure prediction using a novel optimization-based consensus approach, (2) β-sheet topology prediction using mixed-integer linear optimization (MILP), (3) Residue-to-residue contact prediction using a high-resolution distance-dependent force field and MILP formulation, (4) Tight dihedral angle and distance bound generation for loop residues using dihedral angle clustering and non-linear optimization (NLP), (5) 3-D structure prediction using deterministic global optimization, stochastic conformational space annealing, and the full-atomistic ECEPP/3 potential, (6) Near-native structure selection using a traveling salesman problem-based clustering approach, ICON, and (7) Improved bound generation using chemical shifts of subsets of heavy atoms, generated by SPARTA and CS23D. Computational results of ASTRO-FOLD 2.0 on 47 blind targets of the recently concluded CASP9 experiment are presented.