Sadanand Singh
University of Wisconsin-Madison
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Sadanand Singh.
Nature Chemistry | 2012
Chris T. Middleton; Peter Marek; Ping Cao; Chi Cheng Chiu; Sadanand Singh; Ann Marie Woys; Juan J. de Pablo; Daniel P. Raleigh; Martin T. Zanni
While amyloid formation has been implicated in the pathology of over twenty human diseases, the rational design of amyloid inhibitors is hampered by a lack of structural information about amyloid-inhibitor complexes. We use isotope labeling and two-dimensional infrared spectroscopy to obtain a residue-specific structure for the complex of human amylin, the peptide responsible for islet amyloid formation in type 2 diabetes, with a known inhibitor, rat amylin. Based on its sequence, rat amylin should block formation of the C-terminal β-sheet, but at 8 hours after mixing rat amylin blocks the N-terminal β-sheet instead. At 24 hours after mixing, rat amylin blocks neither β-sheet and forms its own β-sheet most likely on the outside of the human fibrils. This is striking because rat amylin is natively disordered and not previously known to form amyloid β-sheets. The results show that even seemingly intuitive inhibitors may function by unforeseen and complex structural processes.
Biophysical Journal | 2010
Allam S. Reddy; Lu Wang; Sadanand Singh; Yun L. Ling; Lauren E. Buchanan; Martin T. Zanni; J. L. Skinner; Juan J. de Pablo
Patients with type II diabetes exhibit fibrillar deposits of human amylin protein in the pancreas. It has been proposed that amylin oligomers arising along the aggregation or fibril-formation pathways are important in the genesis of the disease. In a step toward understanding these aggregation pathways, in this work we report the conformational preferences of human amylin monomer in solution using molecular simulations and infrared experiments. In particular, we identify a stable conformer that could play a key role in aggregation. We find that amylin adopts three stable conformations: one with an α-helical segment comprising residues 9-17 and a short antiparallel β-sheet comprising residues 24-28 and 31-35; one with an extended antiparallel β-hairpin with the turn region comprising residues 20-23; and one with no particular structure. Using detailed calculations, we determine the relative stability of these various conformations, finding that the β-hairpin conformation is the most stable, followed by the α-helical conformation, and then the unstructured coil. To test our predicted structure, we calculate its infrared spectrum in the amide I stretch regime, which is sensitive to secondary structure through vibrational couplings and linewidths, and compare it to experiment. We find that theoretically predicted spectra are in good agreement with the experimental line shapes presented herein. The implications of the monomer secondary structures on its aggregation pathway and on its interaction with cell membranes are discussed.
Annual Review of Chemical and Biomolecular Engineering | 2012
Sadanand Singh; Manan Chopra; Juan J. de Pablo
One of the central problems in statistical mechanics is that of finding the density of states of a system. Knowledge of the density of states of a system is equivalent to knowledge of its fundamental equation, from which all thermodynamic quantities can be obtained. Over the past several years molecular simulations have made considerable strides in their ability to determine the density of states of complex fluids and materials. In this review we discuss some of the more promising approaches proposed in the recent literature along with their advantages and limitations.
Biophysical Journal | 2013
Chi Cheng Chiu; Sadanand Singh; Juan J. de Pablo
The formation of human islet amyloid polypeptide (hIAPP) is implicated in the loss of pancreatic β-cells in type II diabetes. Rat amylin, which differs from human amylin at six residues, does not lead to formation of amyloid fibrils. Pramlintide is a synthetic analog of human amylin that shares three proline substitutions with rat amylin. Pramlintide has a much smaller propensity to form amyloid aggregates and has been widely prescribed in amylin replacement treatment. It is known that the three prolines attenuate β-sheet formation. However, the detailed effects of these proline substitutions on full-length hIAPP remain poorly understood. In this work, we use molecular simulations and bias-exchange metadynamics to investigate the effect of proline substitutions on the conformation of the hIAPP monomer. Our results demonstrate that hIAPP can adopt various β-sheet conformations, some of which have been reported in experiments. The proline substitutions perturb the formation of long β-sheets and reduce their stability. More importantly, we find that all three proline substitutions of pramlintide are required to inhibit β conformations and stabilize the α-helical conformation. Fewer substitutions do not have a significant inhibiting effect.
Journal of Chemical Physics | 2013
Sadanand Singh; Chi Cheng Chiu; Allam S. Reddy; Juan J. de Pablo
The human islet amylin polypeptide is produced along with insulin by pancreatic islets. Under some circumstances, amylin can aggregate to form amyloid fibrils, whose presence in pancreatic cells is a common pathological feature of Type II diabetes. A growing body of evidence indicates that small, early stage aggregates of amylin are cytotoxic. A better understanding of the early stages of the amylin aggregation process and, in particular, of the nucleation events leading to fibril growth could help identify therapeutic strategies. Recent studies have shown that, in dilute solution, human amylin can adopt an α-helical conformation, a β-hairpin conformation, or an unstructured coil conformation. While such states have comparable free energies, the β-hairpin state exhibits a large propensity towards aggregation. In this work, we present a detailed computational analysis of the folding pathways that arise between the various conformational states of human amylin in water. A free energy surface for amylin in explicit water is first constructed by resorting to advanced sampling techniques. Extensive transition path sampling simulations are then employed to identify the preferred folding mechanisms between distinct minima on that surface. Our results reveal that the α-helical conformer of amylin undergoes a transformation into the β-hairpin monomer through one of two mechanisms. In the first, misfolding begins through formation of specific contacts near the turn region, and proceeds via a zipping mechanism. In the second, misfolding occurs through an unstructured coil intermediate. The transition states for these processes are identified. Taken together, the findings presented in this work suggest that the inter-conversion of amylin between an α-helix and a β-hairpin is an activated process and could constitute the nucleation event for fibril growth.
Journal of Chemical Theory and Computation | 2012
Sadanand Singh; Chi Cheng Chiu; Juan J. de Pablo
Recently proposed metadynamics techniques offer an effective means for improving sampling in simulations of complex systems, including polymers and biological macromolecules. One of the drawbacks of such methods has been the absence of well-defined or effective convergence criteria. A solution to this problem is considered here in which an optimal ensemble is introduced to minimize the travel time across the entire order parameter range of interest. The usefulness of the proposed approach is illustrated in the context of two systems consisting of biological molecules dissolved in water. The results presented in this work indicate that the proposed method is considerably faster than other existing algorithms for the study of these systems, and that the corresponding free energy that emerges from the simulations converges to the exact result.
Nature Materials | 2013
Sadanand Singh; M. D. Ediger; Juan J. de Pablo
Journal of the American Chemical Society | 2011
Lu Wang; Chris T. Middleton; Sadanand Singh; Allam S. Reddy; Ann Marie Woys; David B. Strasfeld; Peter Marek; Daniel P. Raleigh; Juan J. de Pablo; Martin T. Zanni; J. L. Skinner
Journal of Chemical Physics | 2011
Sadanand Singh; Juan J. de Pablo
Journal of Statistical Physics | 2011
Sadanand Singh; Chi Cheng Chiu; Juan J. de Pablo