Brief. Bioinformatics - Calculating transcription factor binding maps for chromatin.

Tópicos

{ bind(1733) structur(1185) ligand(1036) }
{ take(945) account(800) differ(722) }
{ sequenc(1873) structur(1644) protein(1328) }
{ structur(1116) can(940) graph(676) }
{ featur(1941) imag(1645) propos(1176) }
{ spatial(1525) area(1432) region(1030) }
{ gene(2352) biolog(1181) express(1162) }
{ method(1219) similar(1157) match(930) }
{ research(1085) discuss(1038) issu(1018) }
{ algorithm(1844) comput(1787) effici(935) }
{ can(981) present(881) function(850) }
{ activ(1452) weight(1219) physic(1104) }
{ learn(2355) train(1041) set(1003) }
{ data(1714) softwar(1251) tool(1186) }
{ visual(1396) interact(850) tool(830) }
{ state(1844) use(1261) util(961) }
{ high(1669) rate(1365) level(1280) }
{ general(901) number(790) one(736) }
{ risk(3053) factor(974) diseas(938) }
{ import(1318) role(1303) understand(862) }
{ health(3367) inform(1360) care(1135) }
{ cost(1906) reduc(1198) effect(832) }
{ can(774) often(719) complex(702) }
{ problem(2511) optim(1539) algorithm(950) }
{ howev(809) still(633) remain(590) }
{ perform(1367) use(1326) method(1137) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ patient(2837) hospit(1953) medic(668) }
{ sampl(1606) size(1419) use(1276) }
{ use(1733) differ(960) four(931) }
{ survey(1388) particip(1329) question(1065) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Current high-throughput experiments already generate enough data for retrieving the DNA sequence-dependent binding affinities of transcription factors (TF) and other chromosomal proteins throughout the complete genome. However, the reverse task of calculating binding maps in a chromatin context for a given set of concentrations and TF affinities appears to be even more challenging and computationally demanding. The problem can be addressed by considering the DNA sequence as a one-dimensional lattice with units of one or more base pairs. To calculate protein occupancies in chromatin, one needs to consider the competition of TF and histone octamers for binding sites as well as the partial unwrapping of nucleosomal DNA. Here, we consider five different classes of algorithms to compute binding maps that include the binary variable, combinatorial, sequence generating function, transfer matrix and dynamic programming approaches. The calculation time of the binary variable algorithm scales exponentially with DNA length, which limits its use to the analysis of very small genomic regions. For regulatory regions with many overlapping binding sites, potentially applicable algorithms reduce either to the transfer matrix or dynamic programming approach. In addition to the recently proposed transfer matrix formalism for TF access to the nucleosomal organized DNA, we develop here a dynamic programming algorithm that accounts for this feature. In the absence of nucleosomes, dynamic programming outperforms the transfer matrix approach, but the latter is faster when nucleosome unwrapping has to be considered. Strategies are discussed that could further facilitate calculations to allow computing genome-wide TF binding maps.

Resumo Limpo

current highthroughput experi alreadi generat enough data retriev dna sequencedepend bind affin transcript factor tf chromosom protein throughout complet genom howev revers task calcul bind map chromatin context given set concentr tf affin appear even challeng comput demand problem can address consid dna sequenc onedimension lattic unit one base pair calcul protein occup chromatin one need consid competit tf histon octam bind site well partial unwrap nucleosom dna consid five differ class algorithm comput bind map includ binari variabl combinatori sequenc generat function transfer matrix dynam program approach calcul time binari variabl algorithm scale exponenti dna length limit use analysi small genom region regulatori region mani overlap bind site potenti applic algorithm reduc either transfer matrix dynam program approach addit recent propos transfer matrix formal tf access nucleosom organ dna develop dynam program algorithm account featur absenc nucleosom dynam program outperform transfer matrix approach latter faster nucleosom unwrap consid strategi discuss facilit calcul allow comput genomewid tf bind map

Resumos Similares

J Chem Inf Model - Aromatic-aromatic interactions in proteins: beyond the dimer. ( 0,801234726254643 )
J Chem Inf Model - Modeling anesthetic binding sites within the glycine alpha one receptor based on prokaryotic ion channel templates: the problem with TM4. ( 0,777134730628879 )
J Chem Inf Model - Molecular mechanism of selective binding of peptides to silicon surface. ( 0,743702854799031 )
Comput Biol Chem - A new protein graph model for function prediction. ( 0,729980936152398 )
Comput Biol Chem - Protein function prediction using neighbor relativity in protein-protein interaction network. ( 0,728840580996195 )
J Chem Inf Model - A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins. ( 0,723058012837135 )
J Chem Inf Model - Comprehensive classification and diversity assessment of atomic contacts in protein-small ligand interactions. ( 0,722809236506714 )
Comput. Biol. Med. - A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach. ( 0,718456736139447 )
Comput Biol Chem - Analysis and recognition of the GAGA transcription factor binding sites in Drosophila genes. ( 0,716196561834075 )
J Chem Inf Model - Energetic and dynamic aspects of the affinity maturation process: characterizing improved variants from the bevacizumab antibody with molecular simulations. ( 0,712547234969795 )
J Chem Inf Model - 3D matched pairs: integrating ligand- and structure-based knowledge for ligand design and receptor annotation. ( 0,711931761158515 )
J Chem Inf Model - In silico mutagenesis and docking study of Ralstonia solanacearum RSL lectin: performance of docking software to predict saccharide binding. ( 0,711519563811213 )
J Chem Inf Model - Structurally conserved binding sites of hemagglutinin as targets for influenza drug and vaccine development. ( 0,711417464887817 )
Comput Biol Chem - Consensus in silico computational modelling of the p22phox subunit of the NADPH oxidase. ( 0,707326269751066 )
Comput Biol Chem - Computational simulation of ligand docking to L-type pyruvate kinase subunit. ( 0,705268558960413 )
J Chem Inf Model - Ligand aligning method for molecular docking: alignment of property-weighted vectors. ( 0,704257104539799 )
J Chem Inf Model - Matching cavities in g protein-coupled receptors to infer ligand-binding sites. ( 0,703935514909768 )
Comput. Biol. Med. - Cyclin-dependent kinases 5 template: useful for virtual screening. ( 0,699056690513914 )
J Chem Inf Model - Insights into the conformational switching mechanism of the human vascular endothelial growth factor receptor type 2 kinase domain. ( 0,698720808451548 )
J Chem Inf Model - GalaxyDock: protein-ligand docking with flexible protein side-chains. ( 0,698203664743606 )
J Chem Inf Model - Multiple interaction regions in the orthosteric ligand binding domain of the a7 neuronal nicotinic acetylcholine receptor. ( 0,69456158835562 )
J Chem Inf Model - Numerical errors in minimization based binding energy calculations. ( 0,694165582651834 )
Wiley Interdiscip Rev Syst Biol Med - Functional protein microarray technology. ( 0,693310013893754 )
J Chem Inf Model - Incorporating backbone flexibility in MedusaDock improves ligand-binding pose prediction in the CSAR2011 docking benchmark. ( 0,692956060263939 )
J Chem Inf Model - AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors. ( 0,692942327358717 )
J Chem Inf Model - Computational rationale for the selective inhibition of the herpes simplex virus type 1 uracil-DNA glycosylase enzyme. ( 0,691650642795441 )
J Chem Inf Model - Elucidation of allosteric inhibition mechanism of 2-Cys human peroxiredoxin by molecular modeling. ( 0,69092797213223 )
J Chem Inf Model - Ligand-induced structural changes in TEM-1 probed by molecular dynamics and relative binding free energy calculations. ( 0,689894604351616 )
J Chem Inf Model - Profiling the structural determinants for the selectivity of representative factor-Xa and thrombin inhibitors using combined ligand-based and structure-based approaches. ( 0,689438816498084 )
J Chem Inf Model - Scoring by intermolecular pairwise propensities of exposed residues (SIPPER): a new efficient potential for protein-protein docking. ( 0,689114512497647 )
J Chem Inf Model - Computational comparison of imidazoline association with the I2 binding site in human monoamine oxidases. ( 0,688885429003352 )
J Chem Inf Model - TRAPP: a tool for analysis of transient binding pockets in proteins. ( 0,688581198692932 )
J Chem Inf Model - Interference of boswellic acids with the ligand binding domain of the glucocorticoid receptor. ( 0,688430442793274 )
J Chem Inf Model - Elucidation of conformational states, dynamics, and mechanism of binding in human -opioid receptor complexes. ( 0,687484255873754 )
J. Comput. Biol. - Topology of RNA-RNA interaction structures. ( 0,686943871323405 )
J Chem Inf Model - Perturbation of fluid dynamics properties of water molecules during G protein-coupled receptor-ligand recognition: the human A2A adenosine receptor as a key study. ( 0,686339864343239 )
J Chem Inf Model - Molecular dynamics simulations of CXCL-8 and its interactions with a receptor peptide, heparin fragments, and sulfated linked cyclitols. ( 0,686062970957638 )
J Chem Inf Model - Computational method to identify druggable binding sites that target protein-protein interactions. ( 0,685427370682889 )
J Chem Inf Model - Dynamics of noncovalent interactions in all-a and all-? class proteins: implications for the stability of amyloid aggregates. ( 0,685020893538215 )
J Chem Inf Model - Docking challenge: protein sampling and molecular docking performance. ( 0,684930768218049 )
J Chem Inf Model - Thermodynamics of fragment binding. ( 0,684772414046381 )
J Chem Inf Model - Molecular determinants of Bim(BH3) peptide binding to pro-survival proteins. ( 0,6839593201216 )
J Chem Inf Model - Experimentally guided structural modeling and dynamics analysis of Hsp90-p53 interactions: allosteric regulation of the Hsp90 chaperone by a client protein. ( 0,683404221751529 )
J Chem Inf Model - 3D-QSAR based on quantum-chemical molecular fields: toward an improved description of halogen interactions. ( 0,681636464502843 )
J Chem Inf Model - Structural basis of specific binding between Aurora A and TPX2 by molecular dynamics simulations. ( 0,68159791355612 )
J Chem Inf Model - Molecular dynamic behavior and binding affinity of flavonoid analogues to the cyclin dependent kinase 6/cyclin D complex. ( 0,68123119546379 )
Comput Biol Chem - Molecular simulation investigation on the interaction between barrier-to-autointegration factor dimer or its Gly25Glu mutant and LEM domain of emerin. ( 0,681090374300515 )
J Chem Inf Model - Functional prediction of binding pockets. ( 0,68017546223665 )
J Chem Inf Model - Application of the docking program SOL for CSAR benchmark. ( 0,680054427118431 )
Wiley Interdiscip Rev Syst Biol Med - Protein-membrane interactions: the virtue of minimal systems in systems biology. ( 0,680015467405776 )
J Chem Inf Model - Flexibility and explicit solvent in molecular-dynamics-based docking of protein-glycosaminoglycan systems. ( 0,679364390763396 )
J Chem Inf Model - Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules. ( 0,678700848987057 )
J Chem Inf Model - Transplant-insert-constrain-relax-assemble (TICRA): protein-ligand complex structure modeling and application to kinases. ( 0,677873057400108 )
J. Comput. Biol. - Adjustable chain trees for proteins. ( 0,676315781820764 )
J Chem Inf Model - Including explicit water molecules as part of the protein structure in MM/PBSA calculations. ( 0,675216854950527 )
J Chem Inf Model - Elements of nucleotide specificity in the Trypanosoma brucei mitochondrial RNA editing enzyme RET2. ( 0,675077854900672 )
Comput Biol Chem - Communication between the active site and the allosteric site in class A beta-lactamases. ( 0,674310058266662 )
Comput Biol Chem - Interactions of iron-sulfur clusters with small peptides: insights into early evolution. ( 0,673402444321326 )
J Chem Inf Model - Ligand binding site identification by higher dimension molecular dynamics. ( 0,673327095892372 )
J Chem Inf Model - Strategies to calculate water binding free energies in protein-ligand complexes. ( 0,672023205577694 )
J Chem Inf Model - Docking server for the identification of heparin binding sites on proteins. ( 0,671176376187487 )
J Chem Inf Model - Insights into AT1 receptor activation through AngII binding studies. ( 0,670957443705855 )
Comput Math Methods Med - The effect of edge definition of complex networks on protein structure identification. ( 0,67014829898767 )
J Chem Inf Model - Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity? ( 0,670139893156833 )
J Chem Inf Model - Global free energy scoring functions based on distance-dependent atom-type pair descriptors. ( 0,66960874600767 )
Comput Biol Chem - Halogen bonding in complexes of proteins and non-natural amino acids. ( 0,669174794580329 )
J Chem Inf Model - Analyzing the topology of active sites: on the prediction of pockets and subpockets. ( 0,66879654358017 )
J Chem Inf Model - Correlating protein hot spot surface analysis using ProBiS with simulated free energies of protein-protein interfacial residues. ( 0,668693825921942 )
J Chem Inf Model - Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38a MAP kinase. ( 0,668529833906263 )
J Chem Inf Model - Rationalizing tight ligand binding through cooperative interaction networks. ( 0,668276975300617 )
J Chem Inf Model - Current assessment of docking into GPCR crystal structures and homology models: successes, challenges, and guidelines. ( 0,667945664883859 )
Comput Biol Chem - Mutually exclusive binding of APPL(PH) to BAR domain and Reptin regulates ?-catenin dependent transcriptional events. ( 0,667799753446424 )
J Chem Inf Model - Computational studies of darunavir into HIV-1 protease and DMPC bilayer: necessary conditions for effective binding and the role of the flaps. ( 0,667607162850703 )
J Chem Inf Model - Pharmacophore fingerprint-based approach to binding site subpocket similarity and its application to bioisostere replacement. ( 0,667458607276991 )
J Chem Inf Model - Numerical errors and chaotic behavior in docking simulations. ( 0,667449704681278 )
J Chem Inf Model - Protein-ligand docking using hamiltonian replica exchange simulations with soft core potentials. ( 0,667051313831729 )
Comput Biol Chem - Computer modeling of the dynamic properties of the cAMP-dependent protein kinase catalytic subunit. ( 0,666417834856472 )
J Chem Inf Model - Computational insight into small molecule inhibition of cyclophilins. ( 0,666070897589754 )
J Chem Inf Model - AcquaAlta: a directional approach to the solvation of ligand-protein complexes. ( 0,665890885465435 )
J Chem Inf Model - Understanding the impact of the P-loop conformation on kinase selectivity. ( 0,665675646069319 )
J Chem Inf Model - Lipoic acid and dihydrolipoic acid. A comprehensive theoretical study of their antioxidant activity supported by available experimental kinetic data. ( 0,665512868495695 )
J. Comput. Biol. - HarmonyDOCK: the structural analysis of poses in protein-ligand docking. ( 0,665470047665642 )
J Chem Inf Model - A cooperative mechanism of clotrimazoles in P450 revealed by the dissociation picture of clotrimazole from P450. ( 0,665447620993766 )
Comput Biol Chem - Normal mode analysis based on an elastic network model for biomolecules in the Protein Data Bank, which uses dihedral angles as independent variables. ( 0,665289935757638 )
J Chem Inf Model - Elucidating a key component of cancer metastasis: CXCL12 (SDF-1a) binding to CXCR4. ( 0,664837550541383 )
J Chem Inf Model - Ligand Identification Scoring Algorithm (LISA). ( 0,664784441472409 )
J Chem Inf Model - Prediction of ligand-induced structural polymorphism of receptor interaction sites using machine learning. ( 0,664739823645392 )
Comput Biol Chem - Docking assay of small molecule antivirals to p7 of HCV. ( 0,664318949662137 )
J. Comput. Biol. - Discovery of protein complexes with core-attachment structures from Tandem Affinity Purification (TAP) data. ( 0,664262345952936 )
Wiley Interdiscip Rev Syst Biol Med - Cell-specific integration of nuclear receptor function at the genome. ( 0,66388708708515 )
J Chem Inf Model - Searching the biologically relevantconformation of dopamine: a computational approach. ( 0,66373133220186 )
J Chem Inf Model - A computational approach to enzyme design: predicting -aminotransferase catalytic activity using docking and MM-GBSA scoring. ( 0,663626213551637 )
Comput Biol Chem - Structural evaluation of BTK and PKCd mediated phosphorylation of MAL at positions Tyr86 and Tyr106. ( 0,663266398734854 )
J Chem Inf Model - Impact of resistance mutations on inhibitor binding to HIV-1 integrase. ( 0,662841041380598 )
J Chem Inf Model - Truncated variants of the GCN4 transcription activator protein bind DNA with dramatically different dynamical motifs. ( 0,662750859230993 )
J Chem Inf Model - Improving docking results via reranking of ensembles of ligand poses in multiple X-ray protein conformations with MM-GBSA. ( 0,662422884552994 )
J Chem Inf Model - Importance of receptor flexibility in binding of cyclam compounds to the chemokine receptor CXCR4. ( 0,662255037064216 )
J Chem Inf Model - Hydration properties of ligands and drugs in protein binding sites: tightly-bound, bridging water molecules and their effects and consequences on molecular design strategies. ( 0,66221533354496 )
J Chem Inf Model - Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study. ( 0,662123396587628 )
J Chem Inf Model - Improved docking of polypeptides with Glide. ( 0,661799403016629 )