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Items: 1 to 50 of 139

1.

Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0.

Shin WH, Kihara D.

J Comput Aided Mol Des. 2019 Sep 10. doi: 10.1007/s10822-019-00222-y. [Epub ahead of print]

PMID:
31506789
2.

Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.

Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D.

Nat Methods. 2019 Sep;16(9):911-917. doi: 10.1038/s41592-019-0500-1. Epub 2019 Jul 29.

PMID:
31358979
3.

Improving 3-Hour Sepsis Bundled Care Outcomes: Implementation of a Nurse-Driven Sepsis Protocol in the Emergency Department.

Moore WR, Vermuelen A, Taylor R, Kihara D, Wahome E.

J Emerg Nurs. 2019 Jun 21. pii: S0099-1767(18)30293-9. doi: 10.1016/j.jen.2019.05.005. [Epub ahead of print]

PMID:
31235077
4.

Computational identification of protein-protein interactions in model plant proteomes.

Ding Z, Kihara D.

Sci Rep. 2019 Jun 19;9(1):8740. doi: 10.1038/s41598-019-45072-8.

5.

Lactose derivatives as potential inhibitors of pectin methylesterases.

L'Enfant M, Kutudila P, Rayon C, Domon JM, Shin WH, Kihara D, Wadouachi A, Pelloux J, Pourceau G, Pau-Roblot C.

Int J Biol Macromol. 2019 Jul 1;132:1140-1146. doi: 10.1016/j.ijbiomac.2019.04.049. Epub 2019 Apr 10.

PMID:
30978419
6.

A global map of the protein shape universe.

Han X, Sit A, Christoffer C, Chen S, Kihara D.

PLoS Comput Biol. 2019 Apr 12;15(4):e1006969. doi: 10.1371/journal.pcbi.1006969. eCollection 2019 Apr.

7.

55 Years of the Rossmann Fold.

Shin WH, Kihara D.

Methods Mol Biol. 2019;1958:1-13. doi: 10.1007/978-1-4939-9161-7_1.

PMID:
30945211
8.

The Balancing Act of Intrinsically Disordered Proteins: Enabling Functional Diversity while Minimizing Promiscuity.

Macossay-Castillo M, Marvelli G, Guharoy M, Jain A, Kihara D, Tompa P, Wodak SJ.

J Mol Biol. 2019 Apr 5;431(8):1650-1670. doi: 10.1016/j.jmb.2019.03.008. Epub 2019 Mar 13.

9.

Survey of Machine Learning Techniques for Prediction of the Isoform Specificity of Cytochrome P450 Substrates.

Xiong Y, Qiao Y, Kihara D, Zhang HY, Zhu X, Wei DQ.

Curr Drug Metab. 2019 May 22;20(3):229-235. doi: 10.2174/1389200219666181019094526.

PMID:
30338736
10.

Identification of Moonlighting Proteins in Genomes Using Text Mining Techniques.

Jain A, Gali H, Kihara D.

Proteomics. 2018 Nov;18(21-22):e1800083. doi: 10.1002/pmic.201800083. Epub 2018 Oct 10.

PMID:
30260564
11.

Analysis of Protein Complexes in the Unicellular Cyanobacterium Cyanothece ATCC 51142.

Aryal UK, Ding Z, Hedrick V, Sobreira TJP, Kihara D, Sherman LA.

J Proteome Res. 2018 Nov 2;17(11):3628-3643. doi: 10.1021/acs.jproteome.8b00170. Epub 2018 Oct 3.

PMID:
30216071
12.

Prediction of protein group function by iterative classification on functional relevance network.

Khan IK, Jain A, Rawi R, Bensmail H, Kihara D.

Bioinformatics. 2019 Apr 15;35(8):1388-1394. doi: 10.1093/bioinformatics/bty787.

PMID:
30192921
13.

Phylo-PFP: improved automated protein function prediction using phylogenetic distance of distantly related sequences.

Jain A, Kihara D.

Bioinformatics. 2019 Mar 1;35(5):753-759. doi: 10.1093/bioinformatics/bty704.

PMID:
30165572
14.

De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge.

Terashi G, Kihara D.

J Struct Biol. 2018 Nov;204(2):351-359. doi: 10.1016/j.jsb.2018.07.013. Epub 2018 Jul 31.

15.

Computing and Visualizing Gene Function Similarity and Coherence with NaviGO.

Ding Z, Wei Q, Kihara D.

Methods Mol Biol. 2018;1807:113-130. doi: 10.1007/978-1-4939-8561-6_9.

PMID:
30030807
16.

Computational Methods for Predicting Protein-Protein Interactions Using Various Protein Features.

Ding Z, Kihara D.

Curr Protoc Protein Sci. 2018 Aug;93(1):e62. doi: 10.1002/cpps.62. Epub 2018 Jun 21.

17.

De novo main-chain modeling for EM maps using MAINMAST.

Terashi G, Kihara D.

Nat Commun. 2018 Apr 24;9(1):1618. doi: 10.1038/s41467-018-04053-7.

18.

Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein-Ligand Docking Method.

Shin WH, Kihara D.

Methods Mol Biol. 2018;1762:105-121. doi: 10.1007/978-1-4939-7756-7_7.

PMID:
29594770
19.

Modeling the assembly order of multimeric heteroprotein complexes.

Peterson LX, Togawa Y, Esquivel-Rodriguez J, Terashi G, Christoffer C, Roy A, Shin WH, Kihara D.

PLoS Comput Biol. 2018 Jan 12;14(1):e1005937. doi: 10.1371/journal.pcbi.1005937. eCollection 2018 Jan.

20.

Protein 3D Structure and Electron Microscopy Map Retrieval Using 3D-SURFER2.0 and EM-SURFER.

Han X, Wei Q, Kihara D.

Curr Protoc Bioinformatics. 2017 Dec 8;60:3.14.1-3.14.15. doi: 10.1002/cpbi.37.

21.

A Study of the Boltzmann Sequence-Structure Channel.

Magner A, Kihara D, Szpankowski W.

Proc IEEE Inst Electr Electron Eng. 2017 Feb;105(2):286-305. doi: 10.1109/JPROC.2016.2608797. Epub 2016 Oct 20.

22.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes.

Chiba S, Ishida T, Ikeda K, Mochizuki M, Teramoto R, Taguchi YH, Iwadate M, Umeyama H, Ramakrishnan C, Thangakani AM, Velmurugan D, Gromiha MM, Okuno T, Kato K, Minami S, Chikenji G, Suzuki SD, Yanagisawa K, Shin WH, Kihara D, Yamamoto KZ, Moriwaki Y, Yasuo N, Yoshino R, Zozulya S, Borysko P, Stavniichuk R, Honma T, Hirokawa T, Akiyama Y, Sekijima M.

Sci Rep. 2017 Sep 20;7(1):12038. doi: 10.1038/s41598-017-10275-4.

23.

DextMP: deep dive into text for predicting moonlighting proteins.

Khan IK, Bhuiyan M, Kihara D.

Bioinformatics. 2017 Jul 15;33(14):i83-i91. doi: 10.1093/bioinformatics/btx231.

24.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

Peterson LX, Shin WH, Kim H, Kihara D.

Proteins. 2018 Mar;86 Suppl 1:311-320. doi: 10.1002/prot.25376. Epub 2017 Sep 11.

25.

Protein structure model refinement in CASP12 using short and long molecular dynamics simulations in implicit solvent.

Terashi G, Kihara D.

Proteins. 2018 Mar;86 Suppl 1:189-201. doi: 10.1002/prot.25373. Epub 2017 Sep 1.

26.

In silico structure-based approaches to discover protein-protein interaction-targeting drugs.

Shin WH, Christoffer CW, Kihara D.

Methods. 2017 Dec 1;131:22-32. doi: 10.1016/j.ymeth.2017.08.006. Epub 2017 Aug 9. Review.

27.

MPFit: Computational Tool for Predicting Moonlighting Proteins.

Khan I, McGraw J, Kihara D.

Methods Mol Biol. 2017;1611:45-57. doi: 10.1007/978-1-4939-7015-5_5.

PMID:
28451971
28.

Using PFP and ESG Protein Function Prediction Web Servers.

Wei Q, McGraw J, Khan I, Kihara D.

Methods Mol Biol. 2017;1611:1-14. doi: 10.1007/978-1-4939-7015-5_1.

PMID:
28451967
29.

Modeling disordered protein interactions from biophysical principles.

Peterson LX, Roy A, Christoffer C, Terashi G, Kihara D.

PLoS Comput Biol. 2017 Apr 10;13(4):e1005485. doi: 10.1371/journal.pcbi.1005485. eCollection 2017 Apr.

30.

Prenatal nicotine exposure decreases the release of dopamine in the medial frontal cortex and induces atomoxetine-responsive neurobehavioral deficits in mice.

Alkam T, Mamiya T, Kimura N, Yoshida A, Kihara D, Tsunoda Y, Aoyama Y, Hiramatsu M, Kim HC, Nabeshima T.

Psychopharmacology (Berl). 2017 Jun;234(12):1853-1869. doi: 10.1007/s00213-017-4591-z. Epub 2017 Mar 23.

PMID:
28332006
31.

NaviGO: interactive tool for visualization and functional similarity and coherence analysis with gene ontology.

Wei Q, Khan IK, Ding Z, Yerneni S, Kihara D.

BMC Bioinformatics. 2017 Mar 20;18(1):177. doi: 10.1186/s12859-017-1600-5.

32.

Variability of Protein Structure Models from Electron Microscopy.

Monroe L, Terashi G, Kihara D.

Structure. 2017 Apr 4;25(4):592-602.e2. doi: 10.1016/j.str.2017.02.004. Epub 2017 Mar 2.

33.

Discovery of Nicotinamide Adenine Dinucleotide Binding Proteins in the Escherichia coli Proteome Using a Combined Energetic- and Structural-Bioinformatics-Based Approach.

Zeng L, Shin WH, Zhu X, Park SH, Park C, Tao WA, Kihara D.

J Proteome Res. 2017 Feb 3;16(2):470-480. doi: 10.1021/acs.jproteome.6b00624. Epub 2016 Dec 5.

34.

Prediction of Local Quality of Protein Structure Models Considering Spatial Neighbors in Graphical Models.

Shin WH, Kang X, Zhang J, Kihara D.

Sci Rep. 2017 Jan 11;7:40629. doi: 10.1038/srep40629.

35.
36.

Predicting Real-Valued Protein Residue Fluctuation Using FlexPred.

Peterson L, Jamroz M, Kolinski A, Kihara D.

Methods Mol Biol. 2017;1484:175-186. doi: 10.1007/978-1-4939-6406-2_13.

PMID:
27787827
37.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

Peterson LX, Kim H, Esquivel-Rodriguez J, Roy A, Han X, Shin WH, Zhang J, Terashi G, Lee M, Kihara D.

Proteins. 2017 Mar;85(3):513-527. doi: 10.1002/prot.25165. Epub 2016 Oct 14.

38.

An expanded evaluation of protein function prediction methods shows an improvement in accuracy.

Jiang Y, Oron TR, Clark WT, Bankapur AR, D'Andrea D, Lepore R, Funk CS, Kahanda I, Verspoor KM, Ben-Hur A, Koo da CE, Penfold-Brown D, Shasha D, Youngs N, Bonneau R, Lin A, Sahraeian SM, Martelli PL, Profiti G, Casadio R, Cao R, Zhong Z, Cheng J, Altenhoff A, Skunca N, Dessimoz C, Dogan T, Hakala K, Kaewphan S, Mehryary F, Salakoski T, Ginter F, Fang H, Smithers B, Oates M, Gough J, Törönen P, Koskinen P, Holm L, Chen CT, Hsu WL, Bryson K, Cozzetto D, Minneci F, Jones DT, Chapman S, Bkc D, Khan IK, Kihara D, Ofer D, Rappoport N, Stern A, Cibrian-Uhalte E, Denny P, Foulger RE, Hieta R, Legge D, Lovering RC, Magrane M, Melidoni AN, Mutowo-Meullenet P, Pichler K, Shypitsyna A, Li B, Zakeri P, ElShal S, Tranchevent LC, Das S, Dawson NL, Lee D, Lees JG, Sillitoe I, Bhat P, Nepusz T, Romero AE, Sasidharan R, Yang H, Paccanaro A, Gillis J, Sedeño-Cortés AE, Pavlidis P, Feng S, Cejuela JM, Goldberg T, Hamp T, Richter L, Salamov A, Gabaldon T, Marcet-Houben M, Supek F, Gong Q, Ning W, Zhou Y, Tian W, Falda M, Fontana P, Lavezzo E, Toppo S, Ferrari C, Giollo M, Piovesan D, Tosatto SC, Del Pozo A, Fernández JM, Maietta P, Valencia A, Tress ML, Benso A, Di Carlo S, Politano G, Savino A, Rehman HU, Re M, Mesiti M, Valentini G, Bargsten JW, van Dijk AD, Gemovic B, Glisic S, Perovic V, Veljkovic V, Veljkovic N, Almeida-E-Silva DC, Vencio RZ, Sharan M, Vogel J, Kansakar L, Zhang S, Vucetic S, Wang Z, Sternberg MJ, Wass MN, Huntley RP, Martin MJ, O'Donovan C, Robinson PN, Moreau Y, Tramontano A, Babbitt PC, Brenner SE, Linial M, Orengo CA, Rost B, Greene CS, Mooney SD, Friedberg I, Radivojac P.

Genome Biol. 2016 Sep 7;17(1):184. doi: 10.1186/s13059-016-1037-6.

39.

Missing gene identification using functional coherence scores.

Chitale M, Khan IK, Kihara D.

Sci Rep. 2016 Aug 24;6:31725. doi: 10.1038/srep31725.

40.

PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation.

Shin WH, Christoffer CW, Wang J, Kihara D.

J Chem Inf Model. 2016 Sep 26;56(9):1676-91. doi: 10.1021/acs.jcim.6b00163. Epub 2016 Aug 19.

41.

Ensemble-based evaluation for protein structure models.

Jamroz M, Kolinski A, Kihara D.

Bioinformatics. 2016 Jun 15;32(12):i314-i321. doi: 10.1093/bioinformatics/btw262.

42.

Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations.

Kingsley LJ, Esquivel-Rodríguez J, Yang Y, Kihara D, Lill MA.

J Comput Chem. 2016 Jul;37(20):1861-5. doi: 10.1002/jcc.24412. Epub 2016 May 27.

43.

Genome-scale prediction of moonlighting proteins using diverse protein association information.

Khan IK, Kihara D.

Bioinformatics. 2016 Aug 1;32(15):2281-8. doi: 10.1093/bioinformatics/btw166. Epub 2016 Mar 26.

44.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

Lensink MF, Velankar S, Kryshtafovych A, Huang SY, Schneidman-Duhovny D, Sali A, Segura J, Fernandez-Fuentes N, Viswanath S, Elber R, Grudinin S, Popov P, Neveu E, Lee H, Baek M, Park S, Heo L, Rie Lee G, Seok C, Qin S, Zhou HX, Ritchie DW, Maigret B, Devignes MD, Ghoorah A, Torchala M, Chaleil RA, Bates PA, Ben-Zeev E, Eisenstein M, Negi SS, Weng Z, Vreven T, Pierce BG, Borrman TM, Yu J, Ochsenbein F, Guerois R, Vangone A, Rodrigues JP, van Zundert G, Nellen M, Xue L, Karaca E, Melquiond AS, Visscher K, Kastritis PL, Bonvin AM, Xu X, Qiu L, Yan C, Li J, Ma Z, Cheng J, Zou X, Shen Y, Peterson LX, Kim HR, Roy A, Han X, Esquivel-Rodriguez J, Kihara D, Yu X, Bruce NJ, Fuller JC, Wade RC, Anishchenko I, Kundrotas PJ, Vakser IA, Imai K, Yamada K, Oda T, Nakamura T, Tomii K, Pallara C, Romero-Durana M, Jiménez-García B, Moal IH, Férnandez-Recio J, Joung JY, Kim JY, Joo K, Lee J, Kozakov D, Vajda S, Mottarella S, Hall DR, Beglov D, Mamonov A, Xia B, Bohnuud T, Del Carpio CA, Ichiishi E, Marze N, Kuroda D, Roy Burman SS, Gray JJ, Chermak E, Cavallo L, Oliva R, Tovchigrechko A, Wodak SJ.

Proteins. 2016 Sep;84 Suppl 1:323-48. doi: 10.1002/prot.25007. Epub 2016 Jun 1.

45.

Energetic Coupling between Ligand Binding and Dimerization in Escherichia coli Phosphoglycerate Mutase.

Gardner NW, Monroe LK, Kihara D, Park C.

Biochemistry. 2016 Mar 29;55(12):1711-23. doi: 10.1021/acs.biochem.5b00980. Epub 2016 Mar 10.

46.

Computational protein function predictions.

Kihara D.

Methods. 2016 Jan 15;93:1-2. doi: 10.1016/j.ymeth.2016.01.001. No abstract available.

PMID:
26778120
47.

Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.

Zhu X, Shin WH, Kim H, Kihara D.

J Chem Inf Model. 2016 Jun 27;56(6):1088-99. doi: 10.1021/acs.jcim.5b00625. Epub 2015 Dec 30.

48.

PatchSurfers: Two methods for local molecular property-based binding ligand prediction.

Shin WH, Bures MG, Kihara D.

Methods. 2016 Jan 15;93:41-50. doi: 10.1016/j.ymeth.2015.09.026. Epub 2015 Sep 30.

49.

IAS: Interaction Specific GO Term Associations for Predicting Protein-Protein Interaction Networks.

Yerneni S, Khan IK, Wei Q, Kihara D.

IEEE/ACM Trans Comput Biol Bioinform. 2018 Jul-Aug;15(4):1247-1258. doi: 10.1109/TCBB.2015.2476809. Epub 2015 Sep 25.

PMID:
26415209
50.

The PFP and ESG protein function prediction methods in 2014: effect of database updates and ensemble approaches.

Khan IK, Wei Q, Chapman S, Kc DB, Kihara D.

Gigascience. 2015 Sep 14;4:43. doi: 10.1186/s13742-015-0083-4. eCollection 2015.

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