QLS guest seminar - Today at 15h00

Quantitative Life Sciences qls at ictp.it
Mon Sep 10 09:46:01 CEST 2018


Today, Monday 10 September 2018 15h00
ICTP, Central Area, 2nd floor, old SISSA building, Via Beirut 2 

Speaker:  R.P. Vivek-Ananth -- The Institute of Mathematical Sciences 
(IMSc), Chennai, India

Title: Prediction and analysis of the secretome of an opportunistic 
fungal pathogen & Exploration of the phytochemical space of Indian 
medicinal plants :


Iwill be presenting results from two of my recently published works on 
a) prediction and analysis of the secretome of an opportunistic fungal 
pathogen Aspergillus fumigatus and b) exploration of the phytochemical 
space of Indian medicinal plants using cheminformatics and network theory.
Aspergillus fumigatus and multiple other Aspergillus species cause a 
wide range of lung infections, collectively termed aspergillosis. 
Aspergilli are ubiquitous in environment with healthy immune systems 
routinely eliminating inhaled conidia, however, Aspergilli can become an 
opportunistic pathogen in immune-compromised patients. The aspergillosis 
mortality rate and emergence of drug-resistance reveals an urgent need 
to identify novel targets. Secreted and cell membrane proteins play a 
critical role in fungal-host interactions and pathogenesis. Using a 
computational pipeline integrating data from high-throughput experiments 
and bioinformatic predictions, we have identified secreted and cell 
membrane proteins in ten Aspergillus species known to cause 
aspergillosis. Small secreted and effector-like proteins similar to 
agents of fungal-plant pathogenesis were also identified within each 
secretome. A comparison with humans revealed that at least 70% of 
Aspergillus secretomes have no sequence similarity with the human 
proteome. An analysis of antigenic qualities of Aspergillus proteins 
revealed that the secretome is significantly more antigenic than cell 
membrane proteins or the complete proteome. Finally, overlaying an 
expression dataset, four A. fumigatus proteins upregulated during 
infection and with available structures, were found to be structurally 
similar to known drug target proteins in other organisms, and were able 
to dock in silico with the respective drug.

Phytochemicals of medicinal plants encompass a diverse chemical space 
for drug discovery. India is rich with a flora of indigenous medicinal 
plants that have been used for centuries in traditional Indian medicine 
to treat human maladies. A comprehensive online database on the 
phytochemistry of Indian medicinal plants will enable computational 
approaches towards natural product based drug discovery. In this 
direction, we have created IMPPAT, a manually curated database of 1742 
Indian Medicinal Plants, 9596 Phytochemicals, And 1124 Therapeutic uses 
spanning 27074 plant-phytochemical associations and 11514 
plant-therapeutic associations. Notably, the curation effort led to a 
non-redundant in silico library of 9596 phytochemicals with standard 
chemical identifiers and structure information. Using cheminformatic 
approaches, we have computed the physicochemical, ADMET (absorption, 
distribution, metabolism, excretion, toxicity) and drug-likeliness 
properties of the IMPPAT phytochemicals. We show that the stereochemical 
complexity and shape complexity of IMPPAT phytochemicals differ from 
libraries of commercial compounds or diversity-oriented synthesis 
compounds while being similar to other libraries of natural products. 
Within IMPPAT, we have filtered a subset of 960 potential druggable 
phytochemicals, of which majority have no significant similarity to 
existing FDA approved drugs, and thus, rendering them as good candidates 
for prospective drugs. IMPPAT database is openly accessible at: 

Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-2240623
e-mail: qls at ictp.it

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