2 research outputs found
PhID: An Open-Access Integrated Pharmacology Interactions Database for Drugs, Targets, Diseases, Genes, Side-Effects, and Pathways
The current network pharmacology
study encountered a bottleneck
with a lot of public data scattered in different databases. There
is a lack of an open-access and consolidated platform that integrates
this information for systemic research. To address this issue, we
have developed PhID, an integrated pharmacology database which integrates
>400 000 pharmacology elements (drug, target, disease, gene,
side-effect, and pathway) and >200 000 element interactions
in branches of public databases. PhID has three major applications:
(1) assisting scientists searching through the overwhelming amount
of pharmacology element interaction data by names, public IDs, molecule
structures, or molecular substructures; (2) helping visualizing pharmacology
elements and their interactions with a web-based network graph; and
(3) providing prediction of drug–target interactions through
two modules: PreDPI-ki and FIM, by which users can predict drug–target
interactions of PhID entities or some drug–target pairs of
their own interest. To get a systems-level understanding of drug action
and disease complexity, PhID as a network pharmacology tool was established
from the perspective of data layer, visualization layer, and prediction
model layer to present information untapped by current databases
EcoSynther: A Customized Platform To Explore the Biosynthetic Potential in <i>E. coli</i>
Developing computational
tools for a chassis-centered biosynthetic
pathway design is very important for a productive heterologous biosynthesis
system by considering enormous foreign biosynthetic reactions. For
many cases, a pathway to produce a target molecule consists of both
native and heterologous reactions when utilizing a microbial organism
as the host organism. Due to tens of thousands of biosynthetic reactions
existing in nature, it is not trivial to identify which could be served
as heterologous ones to produce the target molecule in a specific
organism. In the present work, we integrate more than 10,000 <i>E. coli</i> non-native reactions and utilize a probability-based
algorithm to search pathways. Moreover, we built a user-friendly Web
server named EcoSynther. It is able to explore the precursors and
heterologous reactions needed to produce a target molecule in <i>Escherichia coli K12 MG1655</i> and then applies flux balance
analysis to calculate theoretical yields of each candidate pathway.
Compared with other chassis-centered biosynthetic pathway design tools,
EcoSynther has two unique features: (1) allow for automatic search
without knowing a precursor in <i>E. coli</i> and (2) evaluate
the candidate pathways under constraints from <i>E. coli</i> physiological states and growth conditions. EcoSynther is available
at http://www.rxnfinder.org/ecosynther/