Background: Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimer's and Parkinson's diseases. On the biotechnological side, protein production is often hampered by the accumulation of recombinant proteins into aggregates. Thus, the development of methods to anticipate the aggregation properties of polypeptides is receiving increasing attention. AGGRESCAN is a web-based software for the prediction of aggregation-prone segments in protein sequences, the analysis of the effect of mutations on protein aggregation propensities and the comparison of the aggregation properties of different proteins or protein sets. Results: AGGRESCAN is based on an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies. Conclusion: By identifying aggregation-prone segments in proteins, AGGRESCAN http://bioinf.uab.es/aggrescan/ shall facilitate (i) the identification of possible therapeutic targets for anti-depositional strategies in conformational diseases and (ii) the anticipation of aggregation phenomena during storage or recombinant production of bioactive polypeptides or polypeptide sets.

Different approaches to improve the simple point charge model for liquid water (SPC) were investigated. This led to a whole series of new water models with additional van der Waals interaction sites at the hydrogen atoms, modified partial charges and modified geometries. The properties of these models are analyzed and discussed. Particular emphasis has been put on the study of the dependence and sensitivity of water properties on the model parameters. We found that a simultaneous improvement of the dielectric permittivity and the diffusion coefficient is difficult to attain for a rigid, nonpolarizable three interaction site model. Nevertheless, two of the models presented here, SPC/A and SPC/L, show good agreement with experimental data on water and have been characterized in more detail. We conclude that SPC/L represents the overall properties of water better than SPC. Especially, it shows excellent dielectric properties, an improved shear viscosity and a slightly lower diffusion coefficient.