@article {43253,
	title = {TDR Targets: a chemogenomics resource for neglected diseases},
	journal = {Nucleic Acids Research},
	volume = {40},
	year = {2012},
	month = {JAN},
	pages = {D1118-D1127},
	abstract = {The TDR Targets Database (http://tdrtargets.org) has been designed and developed as an online resource to facilitate the rapid identification and prioritization of molecular targets for drug development, focusing on pathogens responsible for neglected human diseases. The database integrates pathogen specific genomic information with functional data (e.g. expression, phylogeny, essentiality) for genes collected from various sources, including literature curation. This information can be browsed and queried using an extensive web interface with functionalities for combining, saving, exporting and sharing the query results. Target genes can be ranked and prioritized using numerical weights assigned to the criteria used for querying. In this report we describe recent updates to the TDR Targets database, including the addition of new genomes (specifically helminths), and integration of chemical structure, property and bioactivity information for biological ligands, drugs and inhibitors and cheminformatic tools for querying and visualizing these chemical data. These changes greatly facilitate exploration of linkages (both known and predicted) between genes and small molecules, yielding insight into whether particular proteins may be druggable, effectively allowing the navigation of chemical space in a genomics context.},
	doi = {10.1093/nar/gkr1053},
	author = {Magarinos, Maria P. and Carmona, Santiago J. and Crowther, Gregory J. and Ralph, Stuart A. and Roos, David S. and Shanmugam, Dhanasekaran and Van Voorhis, Wesley C.}
}
@article {44494,
	title = {Targeted phenotypic screening in plasmodium falciparum and toxoplasma gondii reveals novel modes of action of medicines for malaria venture malaria box molecules},
	journal = {mSphere},
	volume = {3},
	year = {2018},
	month = {JAN},
	pages = { e00534-17},
	type = {Journal Article},
	abstract = {The Malaria Box collection includes 400 chemically diverse small molecules with documented potency against malaria parasite growth, but the underlying modes of action are largely unknown. Using complementary phenotypic screens against Plasmodium falciparum and Toxoplasma gondii, we report phenotype-specific hits based on inhibition of overall parasite growth, apicoplast segregation, and egress or host invasion, providing hitherto unavailable insights into the possible mechanisms affected. First, the Malaria Box library was screened against tachyzoite stage T. gondii and the half-maximal effective concentrations (EC50s) of molecules showing >=80\% growth inhibition at 10 {\textmu}M were determined. Comparison of the EC50s for T. gondii and P. falciparum identified a subset of 24 molecules with nanomolar potency against both parasites. Thirty molecules that failed to induce acute growth inhibition in T. gondii tachyzoites in a 2-day assay caused delayed parasite death upon extended exposure, with at least three molecules interfering with apicoplast segregation during daughter cell formation. Using flow cytometry and microscopy-based examinations, we prioritized 26 molecules with the potential to inhibit host cell egress/invasion during asexual developmental stages of P. falciparum. None of the inhibitors affected digestive vacuole integrity, ruling out a mechanism mediated by broadly specific protease inhibitor activity. Interestingly, five of the plasmodial egress inhibitors inhibited ionophore-induced egress of T. gondii tachyzoites. These findings highlight the advantage of comparative and targeted phenotypic screens in related species as a means to identify lead molecules with a conserved mode of action. Further work on target identification and mechanism analysis will facilitate the development of antiparasitic compounds with cross-species efficacy.},
	issn = {23795042},
	doi = {10.1128/mSphere.00534-17},
	author = {Subramanian, Gowtham},
	editor = {Belekar, Meenakshi A.}
}
@article {46175,
	title = {Targeted phenotypic screening in plasmodium falciparum and toxoplasma gondii reveals novel modes of action of medicines for malaria venture malaria box molecules (vol 3, e00534-17, 2018)},
	journal = {MSphere},
	volume = {4},
	year = {2019},
	month = {APR},
	pages = {e00159-19},
	type = {Correction},
	issn = {2379-5042},
	doi = {10.1128/mSphere.00159-19},
	author = {Subramanian, Gowtham and Belekar, Meenakshi A. and Shukla, Anurag and Tong, Jie Xin and Sinha, Ameya and Chu, Trang T. T. and Kulkarni, Akshay S. and Preiser, Peter R. and Reddy, D. Srinivasa and Tan, Kevin S. W. and Shanmugam, Dhanasekaran and Chandramohanadas, Rajesh}
}
@article {47004,
	title = {TDR Targets 6: driving drug discovery for human pathogens through intensive chemogenomic data integration},
	journal = {Nucleic Acids Research},
	volume = {48},
	year = {2020},
	month = {JAN },
	pages = {D992-D1005},
	type = {Article},
	abstract = {<p>The volume of biological, chemical and functional data deposited in the public domain is growing rapidly, thanks to next generation sequencing and highly-automated screening technologies. These datasets represent invaluable resources for drug discovery, particularly for less studied neglected disease pathogens. To leverage these datasets, smart and intensive data integration is required to guide computational inferences across diverse organisms. The TDR Targets chemogenomics resource integrates genomic data from human pathogens and model organisms along with information on bioactive compounds and their annotated activities. This report highlights the latest updates on the available data and functionality in TDR Targets 6. Based on chemogenomic network models providing links between inhibitors and targets, the database now incorporates network-driven target prioritizations, and novel visualizations of network subgraphs displaying chemical- and target-similarity neighborhoods along with associated target-compound bioactivity links. Available data can be browsed and queried through a new user interface, that allow users to perform prioritizations of protein targets and chemical inhibitors. As such, TDR Targets now facilitates the investigation of drug repurposing against pathogen targets, which can potentially help in identifying candidate targets for bioactive compounds with previously unknown targets. TDR Targets is available at https://tdrtargets.org.</p>
},
	issn = {0305-1048},
	doi = {10.1093/nar/gkz999},
	author = {Landaburu, Lionel Uran and Berenstein, Ariel J. and Videla, Santiago and Maru, Parag and Shanmugam, Dhanasekaran and Chernomoretz, Ariel and Aguero, Fernan}
}
@article {48819,
	title = {Tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India},
	journal = {Journal of Infection and Public Health},
	volume = {16},
	year = {2023},
	month = {AUG},
	pages = {1290-1300},
	type = {Article},
	abstract = {<p>
	Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.Methods: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a {\textquoteleft}{\textquoteleft}band of five{\textquoteright}{\textquoteright} outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implica-tions for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.\&amp; COPY; 2023 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).</p>
},
	keywords = {COVID-19, Delta, Omicron, SARS-CoV-2 genomic surveillance, Variant of concern, Whole Genome Sequencing (WGS)},
	issn = {1876-0341},
	doi = {10.1016/j.jiph.2023.06.004},
	author = {Niveditha, Divya and Khan, Soumen and Khilari, Ajinkya and Nadkarni, Sanica and Bhalerao, Unnati and Kadam, Pradnya and Yadav, Ritu and Kanekar, Jugal B. and Shah, Nikita and Likhitkar, Bhagyashree and Sawant, Rutuja and Thakur, Shikha and Tupekar, Manisha and Nagar, Dhriti and Rao, Anjani G. and Jagtap, Rutuja and Jogi, Shraddha and Belekar, Madhuri and Pathak, Maitreyee and Shah, Priyanki and Ranade, Shatakshi and Phadke, Nikhil and Das, Rashmita and Joshi, Suvarna and Karyakarte, Rajesh and Ghose, Aurnab and Kadoo, Narendra and Shashidhara, L. S. and Monteiro, Joy Merwin and Shanmugam, Dhanasekaran and Raghunathan, Anu and Karmodiya, Krishanpal}
}
