The TDR Targets Database v4

This is a set of public queries intented to illustrate how to
share lists of targets and query sets.

This set contains 4 queries that return different lists of Plasmodium
genes: enzymes (genes with any EC number); genes absent in human/mouse;
genes that orthologs in Mycobacterium that are essential; and genes
that have orthologs in E. coli that are essential.

Finally, a fifth query is also included in the published set that
is the result of ranking all the genes retrieved by these 4 queries.

The UNION of queries 1-4 has been ranked according to the following
scoring scheme:
Plasmodium enzymes: 20
Plasmodium absent in human/mouse: 50
Plasmodium essential in Mycobacterium: 30
Plasmodium essential in E. coli: 30

All the scores are additive.

Feel free to use these queries for your own good.

Ranked list of Mtb genes, by weighting, containg potential targets.

P. falciparum targets generated based on weighted queries on structure, phylogeny, essentilaity and druggability. 4
queries were run with intersection and union of queries.

3 queries run for pfal...

1. pfal enzymes with any essentiality evidence
2. pfal genes with high dindex (>0.8)
3. pfal genes which have no mammalian ortholgs

qureies were weighted with 30, 20 & 10 as scores and then the UNION of the 3 queries was taken.

Enzymes from T brucei for which there is some structural info avail (actual or model), Cmpd desireability >0.5,
Druggability >0.7, and <2 Transmembrane domains

This is a list of P fal enzymes (EC any) with <2 Tm segments and are essential in some model organism with Cmpd
desireability index of >0.5 a druggability index of >0.7 and with either modeled or an actual structure.

A set of attributes potentially relevant to T. brucei drug target design, including:
- enzymes [100]
- MW <100 kDa [20]
- no TM domains [20]
- structure available in PDB [50]
- model available in ModBase [30]
- present in all TriTryps [25]
- NOT in human [25]
- essentiality evidence in some (other) organism(s) [40]
- essential in T. brucei (lethal RNAi or KO phenotype) [50]
- druggability evidence inferred from orthology (>0.6) [35]
- compound desirability inferred from orthology (>0.3) [35]
- publications in PubMed [35]

TB prioritized targets

The aim of the survey is to capture, collate and make publicly available expert knowledge on potential drug targets
against Human African Trypanosomiasis (HAT). This survey is part of the WHO-TDR Drug Targets Networks
community-wide
strategy to build a prioritise portfolio of tropical disease drug targets. The idea to survey the scientific
community
came from a workshop on Drug Discovery for Trypanosomatid Diseases, held in Dundee in February 2007.

Groups engaged in drug discovery against HAT need to access the best possible drug targets and to contact and
collaborate with experts on that target. This portal is an opportunity to (a) make the community aware of specific
molecular targets and (b) state whether or not you are engaged in, or would be interested in collaborating on, a
drug discovery project related to that target.

This survey on HAT is a pilot scheme. If is considered successful, it may be extended to many other neglected
diseases.

List of suggested targets

Currently NO experimental genetic or chemical evidence

Tb927.8.3530 Glycerol-3-phosphate dehydrogenase – NAD-dependent Paul A Michels
Tb927.1.3830 Glucose-6-phosphate isomerase Paul A Michels
Tb927.5.890 Oligosaccharyl transferase (OST) subunit Michael A Ferguson
Tb927.5.900 Oligosaccharyl transferase (OST) subunit Michael A Ferguson
Tb927.5.910 Oligosaccharyl transferase (OST) subunit Michael A Ferguson

Genetic AND chemical evidence

Tb10.389.1360 Glutamate-cysteine ligase Margaret A Phillips
Tb927.6.4410 S-adenosylmethionine decarboxylase Margaret A Phillips
Tb927.6.4460 S-adenosylmethionine decarboxylase Margaret A Phillips
Tb927.1.1240 cytidine triphosphate synthase Gavin A Whitlock
Tb927.1.700 Phosphoglycerate kinase (glycosomal, isoenzyme C) Paul A Michels
Tb11.01.6980 Vps34 (phosphatidylinositol 3-kinase catalytic subunit) Mark Field
Tb927.6.4280 Glyceraldehyde-3-phosphate dehydrogenase (glycosomal) Paul A Michels
Tb927.6.4300 Glyceraldehyde-3-phosphate dehydrogenase (glycosomal) Paul A Michels
Tb10.6k15.3640 Alternative oxidase Christiine E Clayton
Tb927.7.3360 farnesyl pyrophosphate synthase Roberto Docampo
Tb09.160.4300 solanesyl diphosphate synthase Roberto Docampo
Tb10.61.3140 Glycogen Synthase Kinase Frederick S Buckner
Tb11.01.0330 Aurora kinase-1 Larry Ruben
Tb11.01.5300 Ornithine decarboxylase Margaret A Phillips
Tb10.70.6220 Histone deacetylases David Horn
Tb927.2.2190 Histone deacetylases David Horn
Tb10.406.0520 Trypanothione reductase Alan H Fairlamb
Tb09.160.3590 Cyclic nucleotide specific phsphodiesterase Thomas Seebeck
Tb09.160.3630 Cyclic nucleotide specific phsphodiesterase Thomas Seebeck
Tb10.70.5820 Hexokinase 1 James C Morris
Tb10.61.2550 N-myristoyl transferase Andrew L Hopkins
Tb927.7.460 Protein farnesyltransferase beta subunit Wesley C Van Voorhis
Tb927.3.4490 protein farnesyltransferase alpha subunit Wesley C Van Voorhis
Tb11.01.3900 GlcNAc-PI de-N-acetylase Michael A Ferguson

Genetic OR chemical evidence

Tb927.4.1140 PI4 Kinase III beta Margaret A Phillips
Tb927.7.7420 ATP synthase F1, alpha subunit Achim Schnaufer
Tb927.3.1380 ATP synthase F1, beta subunit Achim Schnaufer
Tb10.70.2210 CRK3:CYC6 Jeremy C Mottram
Tb10.61.3060 GPI:protein transamidase Jeremy C Mottram
Tb927.5.800 TbCK1.2 (Caesin Kinase 1.2) Michael D Urbaniak
Tb927.5.790 TbCK1.2E (Caesin Kinase 1.2) Michael D Urbaniak
Tb10.100.0130 Peroxin 14 (PEX14) Paul A Michels
Tb927.5.1100 Peroxin 5 (PEX5) Paul A Michels
Tb10.61.2680 Pyruvate kinase Paul A Michels
Tb10.6k15.2620 Phosphoglycerate mutase Paul A Michels
Tb927.3.3270 Phosphofructokinase Paul A Michels
Tb10.70.4740 Enolase Paul A Michels
Tb10.70.1370 Fructose-1,6-bisphosphate aldolase Paul A Michels
Tb10.70.5200 Glucose-6-phosphate dehydrogenase Paul A Michels
Tb927.2.3270 Invariant surface glycoprotein Mark Carrington
Tb927.2.3280 Invariant surface glycoprotein Mark Carrington
Tb927.2.3290 Invariant surface glycoprotein Mark Carrington
Tb927.2.3300 Invariant surface glycoprotein Mark Carrington
Tb927.2.3310 Invariant surface glycoprotein Mark Carrington
Tb927.2.3320 Invariant surface glycoprotein Mark Carrington
Tb11.02.3210 Triosephosphate isomerase Paul A Michels
Tb927.7.4900 XRNA Christiine E Clayton
Tb927.1.2600 PUF9 Christiine E Clayton
Tb11.03.0580 UBP1 Christiine E Clayton
Tb11.03.0620 UBP2 Christiine E Clayton
Tb927.3.5280 DRBD1 Christiine E Clayton
Tb927.1.4650 CFB2 Christiine E Clayton
Tb927.6.600 MRNA degradation CAF1 deadenylase Christiine E Clayton
Tb927.7.6310 Polo-like kinase Tansy C Hammarton
Tb09.160.4250 TbCPX (peroxiredoxin) Shane R Wilkinson
Tb09.160.4280 TRYP1 (tryparedoxin peroxidase) Shane R Wilkinson
Tb927.7.1120 TbGPXI-A (non-selenium glutathione peroxidase) Shane R Wilkinson
Tb927.7.1130 TbGPXI-B (non-selenium glutathione peroxidase) Shane R Wilkinson
Tb927.7.1140 TbGPXI-C (non-selenium glutathione peroxidase) Shane R Wilkinson
Tb927.3.3760 TbTPNI (tryparedoxin) Shane R Wilkinson
Tb927.3.3780 TbTPNI (tryparedoxin) Shane R Wilkinson
Tb11.01.7550 TbSODB2 (Superoxide metabolism) Shane R Wilkinson
Tb11.01.6660 TbSODB2 (Superoxide metabolism) Shane R Wilkinson
Tb927.2.4370 Trypanothione synthetase Alan H Fairlamb
Tb11.01.4701 Membrane-bound histidine acid phosphatase Peter Overath
Tb927.6.4220 TbMAPK5 Isabel Roditi
Tb11.01.5220 JBP1 (targetting J biosynthesis Piet Borst
Tb927.6.940 Metacaspases Jeremy C Mottram
Tb11.02.0330 UDP-Glucose 4'-Epimerase (GalE) Michael D Urbaniak
Tb09.160.2970 RNA Editing ligase 1 Kenneth D Stuart
Tb11.02.0120 UDP-GlcNAc diphosphorylase Michael A Ferguson

A list of potential Plasmodium protease drug targets.
*NB Relies on the word "protease" or "peptidase" appearing in gene name to identify proteases - maybe also possible
with EC numbers?

The weighting is
In Plasmodium, has a name like “peptidase”: 100
In Plasmodium, has a name like “protease”: 100
has literature: 30
has modelled or solved structure: 50
druggability >0.3: 50
no orthologues in mammals: 50
essential in some organism: 30

•trna Synthetases
•some essentiality data
•druggability > 0.7
•compound desirablility > 0.1

This is simply a set of queries for genes expressed either in the top quintile (80-100%) or the 2nd quintile (60-80%)
for each of the blood-borne stages: early ring, late ring, early schizont, late schizont, early trophozoite, late
trophozoite, and merozoite. Intersections of individual queries can be performed to assess correlations among
stages.

this is a test

This published set contains a comprehensive set of queries from Pfal that have been weighted 1 against all pfal genes
weighted 0. The Query titles are descriptive of the weighting and combinations. This data set is useful for making
a spread sheet of pfal genes with ability to adjust the weighting to allow re-ranking of target genes.

This is an example of incorporating literature rankings of targets into TDRtargets.org. In PLoS Comp Biol 2: e61
(2006), S. Hasan et al. generate 3 ranked lists of M. tuberculosis genes, each based on a separate criterion:
metabolic role, whether they are specific to Actinobacteria, and expression during dormancy. My query set includes
a list of Hasan's top 400 genes (top ~10%) for each criterion as well as an intersection showing the genes that
rank in the top 400 for all 3.

Based on PLoS ONE 2: e1189, 2007. The authors first narrowed the Brugia genes down to those with essential orthologs in
E. coli but lacking close homologs in humans. They then ranked these 589 genes with an algorithm based on data on
homology, essentiality, stage-specific expression, druggability, and expressability. My list includes the top 10%
of their rankings.

Within the Validation subsection of the search page, one can search for four types of genetic experiment:
loss-of-function mutant, overexpression, knockout unrecovered, and RNAi/antisense assay. This query set includes a
search for each type, although there is nothing under overexpression or knockout unrecovered. According to the
curation, 16 genes have been studied in a "loss-of-function mutant" way and 248 have been studied by RNAi/antisense
assay. This curation was completed by Takashi Suzuki some time ago (probably by summer of 2007) and thus is
unlikely to include the latest literature findings.

Using the genome comparison software Genlight, two separate in silico workflows were implemented to derive a set of
parasite proteins for which gene disruption of the orthologs in both C. elegans and D. melanogaster yielded
deleterious phenotypes (e.g., lethal, impairment of motility), i.e., are essential genes/proteins. 71 genes were
identified that were expressed in the relevant developmental stages of the parasite infecting humans. Subsequent in
depth manual curation of the combined workflow output revealed 57 candidate proteins.
[Smp_122390 ||29042.m003538|notchless-related| could not be found in TDR database and is therefore excluded.]

I have run a number of queries using different criteria to
retrieve T. cruzi genes.

Each query filters genes based on a single criteria.

These are:
* gene does not have orthologs in human/mouse [50]
* gene has orthologs in T. brucei [40]
* gene has orthologs in Yeast that are essential [50]
* gene has orthologs in Bacteria (E. coli, M. tuberculosis)
that are essential [40]
* gene has 3D Model(s) [30]
* gene has 3D structure(s) [40]
* gene has a druggability index > 0.6 (0-1 scale) [40]

A ranked list of genes was produced by asking for the UNION
of the above queries and assigning a weight (score) to each query
(in square brackets above).

Feel free to use this set, add/remove queries, revise my scoring scheme,
etc. And do share back your revised sets!

This query-set consist of 8 (sub)queries that look for genes in the T.cruzi genome having different desirable
properties
such as absence in human, enzyme activity, ortholog gene(s) in T. brucei, essentiality evidence in any species
(that could
be further refined asking for orthologs to essential genes in a particular model specie), significant druggability
evidence
inferred from orthology, single-copy number (1 or 2 copies because of the pseudodiploid nature of the T.cruzi
genome), availability of
structural models (PDB or Modbase) and assayablity; plus a composite query or ranked list which comes from the
weighted UNION of the others.
You can import this queries to your session, redo the score strategy of the ranked list, or build a new one
combining this queries with others.

transporters with phylogenetic distribution: not in hsa but in pfa they all have expression ranking 80-100%

This is an update to a previously published multi-query ranking. The criteria used are the same, but performing these
queries in the new version 3 of the database allows other users to easily reweight the queries.

This is an update of a previously published query set, done mostly to take advantage of the reweighting feature option
in the new database (version 3). The criteria remain the same as before, i.e., enzymes (100), MW < 100 kDa (20), no
TM domains (20), PDB structure (50), Modbase model (30), present in all TriTryps (25), not in humans (25),
essential in at least one model organism (40), genetic validation in Leishmania (50), druggability > 0.6 (35),
compound desirability > 0.3 (35), and PubMed publications (35).

This is the description for the query set(s) you are about to
publish.

Replace this text with your own description. Remember that this
description is the only thing another user will know about
this set before deciding on browsing/using it.

It's a good idea to briefly describe each query and maybe say
something about the scoring/weighting scheme (if appropriate).

Targets suggested in a 2006 review of chemotherapeutic agents.

This is the description for the query set(s) you are about to
publish.

Replace this text with your own description. Remember that this
description is the only thing another user will know about
this set before deciding on browsing/using it.

It's a good idea to briefly describe each query and maybe say
something about the scoring/weighting scheme (if appropriate).

referring to previously posted "BP6 plasmodium",
i think there is an error - "druggability" has been missed out...
i have tried to do a new search again, and maybe you all could have a look at this...

S. Anishetty et al. (2005) identified ~190 enzymes from M. tuberculosis with low or no sequence homology to human
proteins. This is their list of Mtu enzymes, taken from Tables 1 and 2 of their paper. A few errors from their
paper (e.g., missing "c" at the end of gene identifiers) have been corrected.

A.G. Tsolaki et al. (PNAS 2004) studied 100 clinical strains of M. tuberculosis and identified over 220 genes that were
deleted from at least one strain (supplementary Table 2 of their paper). This list of genes has been added here for
possible use in prioritizing TB drug targets. Genes on this list should perhaps be given a negative weight, since
the pathogen can survive without them.

Consider the following scenario: you're interested in the glycolytic pathway, which has been validated as a target in
T. brucei (e.g., PMID 15955817). Which enzyme(s) should you investigate further? Could do a prioritization of
glycolytic/gluconeogenic enzymes with the following criteria:
* KEGG glycolysis/gluconeogenesis
* weighted union including
- PDB structures - 20
- Modbase models - 10
- assayability - 20
- literature references - 20
- druggability > 0.4 - 20
- compound desirability > 0.2 - 10
- number of paralogs = 1 - 10
* additional points awarded in proportion to flux control according to PMID 15955817:
- GAPDH (1.2.1.12) – 40
- glycerol-3-P DH (1.1.1.8) – 30
- glycerol-3-phosphate oxidase (1.1.99.5) – 30
- PGAM (5.4.2.1) – 30
- aldolase (4.1.2.13) – 10
- enolase (4.2.1.11) – 10
- PGK (2.7.2.3) – 10
- pyruvate kinase (2.7.1.40) – 10

Based on PMID 18000556. Kumar et al.'s genome-wide analysis identified 580+ possible Brugia drug targets. They are
given here along with the weights reported in the paper's supplementary information, except for a few genes not in
TDRtargets.org due to changes in the Brugia genome since the publication of the paper.

A prioritization session mainly based on phenotypes observed in C. elegans,
absence in human and mouse and druggability (inferred by sequence similarity against known druggable targets,
uploaded list)
Initial Criteria:

Score for genes in query #10 (Sterility in C. elegans): 20
Score for genes in query #11 (3D model available): 2
Score for genes in query #12 (enzyme): 10
Score for genes in query #13 (bibliographic reference): 2
Score for genes in query #2 (in human): -40
Score for genes in query #3 (in mouse): -20
Score for genes in query #4 (in C. elegans): 10
Score for genes in query #5 (any essentiality evidence): 5
Score for genes in query #6 (Embryonic Lethal/Arrest in C. elegans): 30
Score for genes in query #7 (Growth Defect in C. elegans): 20
Score for genes in query #8 (Larval/Adult Lethal/Arrest in C. elegans): 40
Score for genes in query #9 (Morphology Defect in C. elegans): 20
Score for genes in query #19 (druggable genes inferred by sequence simiarity): 30

For this genome prioritization we considered several filters independently and
calculated the weighted (ranked) UNION of these, so we don`t exclude targets
that miss some of the criteria. We considered lethal and some non-lethal mutant
phenotypes in C. elegans and D. melanogaster or in ANY species (although
non-lethals have a lower weight); expression data from ESTs obtained from
SchistoDB (expressed in ANY relevant stage, but also giving a higher weight if
expressed in more than one relevant stage); druggability inferred by sequence
similarity against known druggable targets; availability of structural models
in Modbase; and gave a negative weight to the presence of orthologous genes in
human.

D. melanogaster knock-out phenotypes were downloaded from FlyBase, and mapped
to Schistosoma mansoni genes through OrthoMCL clusters. EST data was obtained
from SchistoDB.

I have also included the top targets list from Caffrey et al.: the top 35
targets (with orthologs in D.melanogaster AND C.elegans, with deleterious
mutant phenotypes in these model organisms, expressed in relevant stages, and
orthologs to known druggable genes described in literature), and top 18 targets
(which are also homologous to proteins with 3d structures including
co-crystallized ligands).

These two lists have not been given a weight so: i) they don't affect our prioritization but ii) they appear in the
final list so we can see where they rank in our list.

Genomic scale ranking of L. major genes demonstrating that combining a wide range of criteria can be quiet useful in
target prioritization work. Using this set of queries two different lists were generated - one without including
essentiality data and another including essentiality data.


Score for genes in query #100 (Lma modbase): 30
Score for genes in query #101 (Lma not in humans): 25
Score for genes in query #102 (Lma any genetic validation): 50
Score for genes in query #103 (Lma any essentiality evidence): 50
Score for genes in query #104 (Lma dindex >=0.6): 35
Score for genes in query #105 (Lma Compd desirability >0.3): 35
Score for genes in query #106 (Lma assayable): 35
Score for genes in query #107 (Lma all proteins): 1
Score for genes in query #110 (Lma in Tbr and Tcr): 25
Score for genes in query #95 (Lma enz (EC + func. Categ.)): 100
Score for genes in query #96 (Lma Pubmed): 35
Score for genes in query #97 (Lma mwt <100kDa): 20
Score for genes in query #98 (Lma no TM domain): 20
Score for genes in query #99 (Lma PDB): 50

Genomic scale ranking of M. tuberculosis genes emphasizing gene essentiality and expression during persistence. The
data for gene attenuation and expression was uploaded into TDRtargets DB along with the original scores provided in
the respective publications.


Score for genes in query #10 (Mtb weighted list for persistence expression score as in Murphy-Brown data): 22 to
-18 (variable weight values)
Score for genes in query #2 (Hasan 2006 persistence, revised):597 to -2119 (variable weight values)
Score for genes in query #5 (Mtu PDB structures): 20
Score for genes in query #8 (Mtu all proteins): 1
Score for genes in query #9 (Mtb weighted list for gene attenuation score as in Murphy-Brown data): 10 to 0
(variable weight values)

Genomic scale ranking of P. falciparum genes using the same set of queries that were used for the L. major list. This
demonstrates that the same set of queries may be used to rank targets in various pathogens.

Score for genes in query #78 (Pfa enz (EC + func. Categ.)): 100
Score for genes in query #79 (Pfa Pubmed): 35
Score for genes in query #80 (Pfa mwt <100kDa): 20
Score for genes in query #81 (Pfa no TM domain): 20
Score for genes in query #82 (Pfa PDB): 50
Score for genes in query #83 (Pfa modbase): 30
Score for genes in query #84 (Pfa not in humans): 25
Score for genes in query #85 (Pfa any genetic validation): 50
Score for genes in query #86 (Pfa any essentiality evidence): 50
Score for genes in query #87 (Pfa dindex >=0.6): 35
Score for genes in query #88 (Pfa Compd desirability >0.3): 35
Score for genes in query #89 (Pfa assayable): 35
Score for genes in query #90 (Pfa all proteins): 1
Score for genes in query #93 (Pfa in Pvi): 25

Genomic scale ranking of M. tuberculosis genes using the same set of queries that were used for the L. major list. This
demonstrates that the same set of queries may be used to rank targets in various pathogens.

Score for genes in query #60 (Mtb enz (EC + func. Categ.)): 100
Score for genes in query #61 (Mtb Pubmed): 35
Score for genes in query #62 (Mtb mwt <100kDa): 20
Score for genes in query #63 (Mtb no TM domain): 20
Score for genes in query #64 (Mtb PDB): 50
Score for genes in query #65 (Mtb modbase): 30
Score for genes in query #66 (Mtb not in humans): 25
Score for genes in query #67 (Mtb in Mle): 25
Score for genes in query #68 (Mtb any genetic validation): 50
Score for genes in query #69 (Mtb any essentiality evidence): 50
Score for genes in query #70 (Mtb dindex >=0.6): 35
Score for genes in query #71 (Mtb Compd desirability >0.3): 35
Score for genes in query #72 (Mtb assayable): 35
Score for genes in query #74 (Mtb all proteins): 1

This ranked list of P. falciparum genes was made up to prioritize targets that are associated with the apicoplast. The
list of apicoplast targeted genes were obtained by manual curation.

The various parameters used are ...
Score for genes in query #181 (Curated list of apicoplast located genes): 1000
Score for genes in query #182 (Pfa Enzymes (EC + functional category)): 100
Score for genes in query #188 (Pfa any essentiality): 50
Score for genes in query #190 (Pfa all proteins): 1
Score for genes in query #193 (Pfa expression in any RBC stage (80-100%)): 25
Score for genes in query #194 (Pfa uploaded weighted list for Isoelectric point): 90 - 0 (variable weights)
Score for genes in query #195 (Pfa uploaded weighted list for molecular weight): 50 - 0 (variable weights)
Score for genes in query #196 (Pfa compound desirability >0.2): 10
Score for genes in query #199 (Pfa Pubmed): -20
Score for genes in query #200 (Pfa PDB structures): -100
Score for genes in query #201 (Pfa Modbase structure models): 10
Score for genes in query #202 (Pfa NOT in humans): 50
Score for genes in query #203 (Pfa ortholog in taxon (Pvi)): 50
Score for genes in query #204 (Pfa any genetic validation): -50
Score for genes in query #205 (Pfa Dindex >=0.4): 20
Score for genes in query #206 (Pfa assayable): 20

Genomic scale ranking of B. malayi genes emphasizing phenotype, expression, curation and druggable data.

Score for genes in query #208 (Sma EC numbers - uploaded list): 10
Score for genes in query #209 (Orthologs of D. melanogaster genes with mutant phenotype lethal): 10
Score for genes in query #210 (Orthologs of D. melanogaster genes with mutant phenotype neurophysiological defect):
10
Score for genes in query #211 (Embryonic Lethal/Arrest in C. elegans): 10
Score for genes in query #212 (Growth Defect in C. elegans): 3
Score for genes in query #213 (Larval/Adult Lethal/Arrest in C. elegans): 10
Score for genes in query #214 (Morphology Defect in C. elegans): 3
Score for genes in query #215 (Sterility in C. elegans): 3
Score for genes in query #216 (any essentiality evidence): 3
Score for genes in query #217 (structural model available): 10
Score for genes in query #218 (druggable genes inferred by sequence simiarity): 10
Score for genes in query #219 (expressed in adult worm (ESTs)): 3
Score for genes in query #220 ( expressed in egg stage (ESTs)): 3
Score for genes in query #221 ( expressed in schistosomula stage (ESTs)): 3
Score for genes in query #222 (expressed in any relevant stage (ESTs)): 10
Score for genes in query #223 (Sma all proteins): 1
Score for genes in query #225 (Sma in Cel): 10
Score for genes in query #226 (Sma uploaded list of metabolic chokepoint enzymes (Berriman et al, 2009)): 10
Score for genes in query #227 (Sma uploaded list of targets identified by STARlite search (Berriman et al, 2009)):
10
Score for genes in query #228 (Sma uploaded list of targets similar to known human targets (Berriman et al, 2009)):
10

Genomic scale ranking of T. brucei genes focusing on the glycolytic pathway. Published data on glycolytic flux was used
to upload a weighted list of genes which was then combined with other internal datasets in TDRtargets DB.


Score for genes in query #118 (Tbr all proteins): 1
Score for genes in query #119 (Tbr in Pubmed): 20
Score for genes in query #120 (Tbr PDB structure): 20
Score for genes in query #121 (Tbr modbase structures): 10
Score for genes in query #122 (Tbr Dindex >=0.4): 20
Score for genes in query #123 (Tbr Compound desirability > 0.2): 10
Score for genes in query #124 (Tbr assayable): 20
Score for genes in query #125 (Tbr Glycolysis from KEGG): 1000
Score for genes in query #128 (uploaded weighted list of enzymes influencing glycolytic flux in Tbr): 40 to 10
(variable weight values)

I have run a number of queries using different criteria to
retrieve T. cruzi genes.

Each query filters genes based on a single criteria.

These are:
* gene does not have orthologs in human/mouse [50]
* gene has orthologs in T. brucei [40]
* gene has orthologs in Yeast that are essential [50]
* gene has orthologs in Bacteria (E. coli, M. tuberculosis) that are essential [40]
* gene has 3D Model(s) [30]
* gene has 3D structure(s) [40]
* gene has a druggability index > 0.6 (0-1 scale) [60]
* gene has evidence of expression in amastigotes (at least 1 mass spec/peptide) [3]
* gene has evidence of expression in amastigotes (at least 2 mass spec/peptides) [6]
* gene has evidence of expression in trypomastigotes (at least 1 mass spec/peptide) [2]
* gene has evidence of expression in trypomastigotes (at least 2 mass spec/peptides) [4]

A ranked list of genes was produced by asking for the UNION
of the above queries and assigning a weight (score) to each query
(in square brackets above).

Feel free to use this set, add/remove queries, revise my scoring scheme,
etc. And do share back your revised sets!

We use the TDR Targets database to classify coding sequences from the Trypanosoma cruzi genome according to their
nucleotide diversity and properties of interest in a target.

T. cruzi targets that are also present in Leishmania, but that are absent in T. brucei.

The prioritization strategy includes some other general (basic) attributes, apart from the phylogenetic ones, as
described below:

Query #1 (amastigote expression >= 2 spectra / 2 peptides): 20
Query #10 (tcruzi all genes): 1
Query #11 (tcruzi not in humans): 80
Query #12 (tcruzi in leish): 90
Query #13 (tcruzi not in tbrucei): 150
Query #14 (tcruzi reagent availability): 30
Query #15 (tcruzi assay available): 30
Query #2 (is enzyme): 20
Query #3 (3D structure): 10
Query #4 (3D model): 10
Query #5 (any evidence of essentiality): 50
Query #6 (> 3 paralogs): -30
Query #7 (druggability > .5): 60
Query #8 (bibrefs): 25
Query #9 (low molecular weight (< 100 kDa)): 25

Genomic scale ranking of B. malayi genes emphasizing phenotype and druggable data (mapped by orthology)

Score for genes in query #1 (Bma - sterile in Cel): 20
Score for genes in query #10 (Bma - morphology defect in Cel): 20
Score for genes in query #11 (Bma any essentiality): 5
Score for genes in query #12 (Bma precedence for being druggalable): 30
Score for genes in query #14 (Bma any EC): 10
Score for genes in query #15 (Bma in PDB): 5
Score for genes in query #16 (Bma assayable): 5
Score for genes in query #17 (Bma all proteins): 1
Score for genes in query #2 (Bma modbase): 2
Score for genes in query #4 (Bma pubmed): 2
Score for genes in query #5 (Bma in Cel): 10
Score for genes in query #7 (Bma - embryonic lethal/arrest in Cel): 30
Score for genes in query #8 (Bma - growth defect in Cel): 20
Score for genes in query #9 (Bma - larval/adult lethal/arrest in Cel): 40

There seems to be no overlap between these two which needs to be verified

Included in this set are 10 queries associated with a manuscript being submitted to PLoS Neglected Tropical Diseases.
They are numbered 2 through 11 to correspond to the numbers of the tables in that manuscript. These queries offer
examples of genome-wide prioritzation of drug targets in the pathogens B. malayi, L. major, M. tuberculosis, P.
falciparum, S. mansoni, T. brucei, and T. cruzi.

L. major queries being "published" so Fernan can access them in revising Fig. 1 for PLoS NTD.

A copy of the rankings reported by S. Hasan et al. (PLoS Comput Biol 2006), with emphasis on importance during
persistent infections. A few genes are missing because their identifiers have changed since the study was conducted
or because they were mis-entered at the time.

This data set is obtained from the supplementary data for of the concerned article. Here genes were scored for 2
parameters - 1) expression (+ve for UP and -ve for down). We combined these 2 scores to get a single value; and 2)
attenuation. The final combination of the the scores for these 2 parameters was obtained (see the union result). As
the intention was to combine this data with the ranking provided by Hasan et al (2006) and the dynamic range of the
scores associated with these 2 scores was very different (597 to -2119 in case of Hasan data and 23 to -17 in case
of Murphy & Brown), the M&B data was multiplied by a factor of 10 to generate score values ranging between 234 to
-172 (see uploaded Query 4)