QLS guest seminar - Today at 15h00
Quantitative Life Sciences
qls at ictp.it
Mon Sep 10 09:46:01 CEST 2018
QLS GUEST SEMINAR
Today, Monday 10 September 2018 15h00
ICTP, Central Area, 2nd floor, old SISSA building, Via Beirut 2
https://goo.gl/maps/qotEd4RyXGJ2
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 :
Abstract:
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:
https://cb.imsc.res.in/imppat.
--
Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste, Italy
Tel. +39-040-2240623
www.ictp.it/research/qls.aspx
e-mail: qls at ictp.it
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