Protein aggregation: in silico algorithms and applications

Protein aggregation is a topic of immense interest to the scientific community due to its role in several neurodegenerative diseases/disorders and industrial importance. Several in silico techniques, tools, and algorithms have been developed to predict aggregation in proteins and understand the aggregation mechanisms. This review attempts to provide an essence of the vast developments in in silico approaches, resources available, and future perspectives. It reviews aggregation-related databases, mechanistic models (aggregation-prone region and aggregation propensity prediction), kinetic models (aggregation rate prediction), and molecular dynamics studies related to aggregation. With a multitude of prediction models related to aggregation already available to the scientific community, the field of protein aggregation is rapidly maturing to tackle new applications.     

Frequency and significance of fungal isolations from conjunctival sac and their role in ocular infections

Five hundred conjunctival swabs, from 150 males and 100 females with no history of ocular infections, were collected and cultured for the isolations of fungi. Eighty (16 %) of the total specimens yielded positive fungal isolations. The isolation rate was more from the males than the females subjects. Mycelial fungi were predominant than the yeast organisms. Aspergillus species were the commonest isolates with A. flavus taking the lead in the isolations being positive 16 of the total 24 Aspergillus species isolated. A variable rate of fungal isolations was observed in different months of the year. The percentage of the isolations increases after the local use of Efcorlin-N. Nineteen of the 20 eyes studied did not yield the same fungal species in the repeated samples.Presented at the Second All India Congress of Medical Microbiologists at Hydrabad from December 22–24, 1978.