Publications

We maintain an update list of our publications below. For Philip Fowler’s citation metrics, please see his Google Scholar page, whereas for altmetrics (readers, tweets etc) please see his ImpactStory pages. If you would like a copy of any of these papers, please check out the list on his ORCID pages, departmental webpages, my ResearchGate site, or get in touch. The Group has a GitHub organisation and Philip also has his own personal GitHub pages where various pieces of code and examples can be cloned. Finally, there is a figshare page where you can find some (now old) Prelim (first year) biochemistry lecture notes.

Members of the group have their name in bold.

Preprints

Below are a list of manuscripts that are available as a preprint but have not yet been accepted in a peer-reviewed journal. Once accepted they will have their details updated.

79. Westhead J, Baker CS, Brouard M, Colpus M, Constantinides B, Hall A, Knaggs J, Lopes Alves M, Spies R, Thai H, Surrell S, Govender K, Peto TEA, Crook DW, Omar SV, Turner R, Fowler PW
Enhancement and validation of the antibiotic resistance prediction performance of a cloud-based genetics processing platform for Mycobacteria
bioRxiv preprint doi:10.1101/2024.11.08.622466

78. Lynch CI, Adlard D, Fowler PW
Predicting rifampicin resistance in M. tuberculosis using machine learning informed by protein structural and chemical features.
bioRxiv preprint doi:10.1101/2024.08.15.608097

77. Hunt M, Hinrichs AS, Anderson D, Karim L, Dearlove BL, Knaggs J, Constantinides B, Fowler PW, Rodger G, Street TL, Lumley SF, Webster H, Sanderson T, Ruis C, Maio ND, Amenga-Etego LN, Amuzu DS, Avaro M, Awandare GA, Ayivor-Djanie R, Bashton M, Batty EM, Bediako Y, Belder DD, Benedetti E, Bergthaler A, Boers SA, Campos J, Carr RAA, Cuba F, Dattero ME, Dejnirattisai W, Dilthey AT, Duedu KO, Endler L, Engelmann I, Francisco NM, Fuchs J, Z. EG, Groc S, Gyamfi J, Heemskerk D, Houwaart T, Hsiao N, Huska M, Hoelzer M, Iranzadeh A, Jarva H, Jeewandara C, Jolly B, Joseph R, Kant R, Ki KKK, Kurkela S, Lappalainen M, Lataretu M, Liu C, Malavige GN, Mashe T, Mongkolsapaya J, Montes B, Molina-Mora JA, Morang’a CM, Mvula B, Nagarajan N, Nelson A, Ngoi JM, Paixao JPd, Panning M, Poklepovich T, Quashie PK, Ranasinghe D, Russo M, San JE, Sanderson ND, Scaria V, Screaton G, Sironen T, Sisay A, Smith D, Smura T, Supasa P, Suphavilai C, Swann J, Tegally H, Tegomoh B, Vapalahti O, Walker A, Wilkinson R, Williamson C, IMSSC2 Laboratory Network Consortium, de Oliveira T, Peto TE, Crook D, Corbett-Detig R, Iqbal Z
Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny
bioRxiv preprint doi:10.1101/2024.04.29.591666

76. Amoako D, Anh NT, Brouard M, Romero CC, Ramirez AC, Constantinides B, Crook D, Cuong PM, Diagne MM, Diallo A, Dung NT, Dunn L, Duyet LV, Everatt J, Fletcher K, Fowler PW, Gail M, Gharbia S, Hospital for Tropical Diseases SARS-CoV-2 testing team, Hong NTT, Hunt M, Iqbal Z, Jeffery K, Kekana D, Kesteman T, Knaggs J, Alves ML, Man DNH, Mathers AJ, Ngoc MN, Oakley S, Parikh H, Peto T, Herrera MR, Sanderson N, Sintchenko V, Swann J, Tam NT, Tan LV, Thach PN, Top NM, Trang NT, Trang VD, Van Doorn HR, von Gottberg A, Wolter N, Young BC
SARS-CoV-2 sequencing with cloud-based analysis illustrates expedient co-ordinated surveillance of viral genomic epidemiology across six continents
medRxiv preprint doi:10.1101/2023.11.27.23298986

75. Constantinides B, Webster H, Gentry J, Bastable J, Dunn L, Oakley S, Swann J, Sanderson N, Fowler PW, Peto TEA, Stoesser N, Street T, Crook DW
Rapid turnaround multiplex sequencing of SARS-CoV-2: comparing tiling amplicon protocol performance
medRxiv preprint doi:10.1101/2021.12.28.21268461

2024

74. Farrar A, Feehily C, Turner P, Zagajewski A, Chatzimichail S, Crook D, Andersson M, Oakley S, Barrett L, El Sayyed H, Fowler PW, Nellåker C, Kapanidis AN, Stoesser N
Infection Inspection: Using the power of citizen science to help with image-based prediction of antibiotic resistance in Escherichia coli treated with ciprofloxacin.
Sci Rep 14:19543 doi:10.1038/s41598-024-69341-3
medRxiv preprint doi:10.1101/2023.12.11.23299807

73. The CRyPTIC Consortium
Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning
PLoS Comp Biol doi: 10.1371/journal.pcbi.1012260
bioRxiv preprint. doi: 10.1101/2021.09.14.458035

72. Carter JJ, Walker TM, Waker AS, Whitfield M, Morlock GP, Lynch CI, Adlard D, Peto TEA, Posey JE, Crook DW, Fowler PW.
Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine learning approaches.
JAC AMR 6:dlae037 doi:10.1093/jacamr/dlae037
bioRxiv preprint doi:10.1101/518142

71. Brunner V, Fowler PW
Compensatory mutations are associated with increased in vitro growth in resistant clinical samples of Mycobacterium tuberculosis.
mGen 10:001187 doi:10.1099/mgen.0.001187
bioRxiv preprint doi:10.1101/2023.06.21.545231

70. The CRyPTIC Consortium
Quantitative measurement of antibiotic resistance in M. tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach.
Nature Comms 15:488 doi:10.1038/s41467-023-44325-5
bioRxiv preprint doi:10.1101/2021.09.14.460353

 

2023

69. Davies TJ, Swann J, Sheppard AE, Pickford H, Lipworth S, AbuOun M, Ellington M, Fowler PW, Hopkins S, Hopkins KL, Crook DW, Peto TEA, Anjum MF, Walker AS, Stoesser N
Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli
mGen 9:001151 & bioRxiv preprint doi:10.1101/2021.11.03.467004

 

68. The CRyPTIC Consortium
Reply: “Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis.”
Eur Resp J 61:2300426 doi:10.1183/13993003.00426-2023

 

67. Brankin AE, Fowler PW
Inclusion of minor alleles improves catalogue-based prediction of fluoroquinolone resistance in M. tuberculosis
J Antimicrob Chemother AMR 5:dlad039 doi:10.1093/jacamr/dlad039 
bioRxiv preprint doi:10.1101/2022.11.09.515757

 

66. Dreyer V, Mandal A, Dev P, Merker M, Barilar I, Utpatel C, Nilgiriwala K, Rodrigues K, Crook DW, The CRyPTIC Consortium, Rasigade JP, Wirth T, Mistry N, Niemann S
High fluoroquinolone resistance proportions among multidrug-resistant tuberculosis driven by dominant L2 Mycobacterium tuberculosis clones in the Mumbai Metropolitan Region
Genome Med 22:14 doi:10.1186/s13073-022-01076-0

65. Sonnenkalb L, Carter JJ, Spitaleri A, Iqbal Z, Hunt M, Malone K, Utpatel C, Cirrillo DM, Rodrigues C, Nilgiriwala KS, the CRyPTIC Consortium, Fowler PW, Merker M, Niemann S.
Deciphering Bedaquiline and Clofazimine Resistance in Tuberculosis: An Evolutionary Medicine Approach
Lancet Microbe 54:e358 doi:10.1016/S2666-5247(23)00002-2 
bioRxiv preprint doi:10.1101/2021.03.19.436148.

 

2022

64. Hunt M, Letcher B, Malone KM, Nguyen G, Hall MB, Colquhoun RM, Lima L, Schatz M, Ramakr- 2022 ishnan S, The CRyPTIC Consortium, Iqbal Z
Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes
Genome Biology 23:147
doi:10.1186/s13059-022-02714-x
bioRxiv preprint: doi:10.1101/2021.09.15.460475

 

63. The CRyPTIC Consortium
A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics
PLoS Biology 20(8):e3001721 doi:10.1371/journal.pbio.3001721
bioRxiv preprint doi:10.1101/2021.09.14.460274

 

62. The CRyPTIC Consortium
Genome-wide association studies of global Mycobacterium tuberculosis resistance to thirteen antimicrobials in 10,228 genomes
PLoS Biology 20(8):e3001755 doi:10.1371/journal.pbio.3001755
bioRxiv preprint doi:10.1101/2021.09.14.460272

 

61. Brankin AE, Fowler PW
Predicting antibiotic resistance in complex protein targets using alchemical free energy methods
J Comp Chem 43:1771 doi:10.1002/jcc.26979 
chemRxiv preprint doi:10.26434/chemrxiv-2021-shfgp

 

60. Fowler PW, Wright C, Spiers H, Zhu T, Baeten EML, Hoosdally SW, Gibertoni Cruz AL, Roohi A, Kouchaki S, Walker TM, Peto TEA, Miller G, Lintott C, Clifton D, Crook DW, Walker AS, The CRyPTIC Consortium
BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates
eLife 11:e75046 doi:10.7554/eLife.75046
bioRxiv preprint doi:10.1101/2021.07.20.453060

 

59. Hunt M, Swann J, Constantinides B, Fowler PW, Iqbal Z
ReadItAndKeep: rapid decontamination of SARS-CoV-2 sequencing reads
Bioinformatics 38:3291 doi:10.1093/bioinformatics/btac311
bioRxiv preprint doi:10.1101/2022.01.21.477194

 

58. World Health Organization
Optimized broth microdilution plate methodology for drug susceptibility testing of Mycobacterium tuberculosis complex
ISBN: 9789240047419

 

57. The CRyPTIC Consortium
Epidemiological cutoff values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing of M. tuberculosis.
Eur Resp J 60:2200239 doi:10.1183/13993003.00239-2022
medRxiv preprint doi:10.1101/2021.02.24.21252386.

 

56. Walker TM, Miotto P, Köser CU, Fowler PW, Knaggs J, Iqbal Z, Hunt M, Chindelevitch L, Farhat M, Cirillo DM, Comas I, Posey JE, Omar SV, Peto TEA, Suresh A, Uplekar S, Laurent S, Colman
R, Nathanson CM, Zignol M, Walker AS, the CRyPTIC Consortium, the Seq&Treat Consortium,
Crook DW, Ismail N, Rodwell TC
The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A new global standard for molecular diagnostics
Lancet Microbe 3:E265
doi:10.1016/S2666-5247(21)00301-3

 

2021

55. Adams O, Deme JC, Parker JL, the CRyPTIC Consortium, Fowler PW, Lea SM, Newstead S
Cryo-EM Structure and Resistance Landscape of M. tuberculosis MmpL3: An Emergent Therapeutic Target
Structure 29:1182
doi:10.1016/j.str.2021.06.013

 

54. Ismail NA, Nathanson CM, Korobitsyn A, Zignol M, Kasaeva T, Rodwell T, Miotto P, Walker TM, 2021 66 Fowler PW, Knaggs J, Iqbal Z, Hunt M, Chindelevitch L, Farhat M, Cirillo D, Crook DW, Comas I, Posey J, Vally Omar S, Peto TEA, Walker AS, Suresh A, Uplekar S, Laurent S, Colman R
Catalogue of mutations in M. tuberculosis complex and their association with drug resistance.
World Health Organization ISBN: 9789240028173

53. Lumley SF, Rodger G, Constantinides B, Sanderson N, Chau KK, Street TL, O’Donnell D, Howarth A, Hatch SB, Marsden BD, Cox S, James T, Warren F, Peck LJ, Ritter TG, de Toledo Z, Warren L, Axten D, Cornall RJ, Jones EY, Stuart DI, Screaton G, Ebner D, Hoosdally S, Chand M,
Oxford University Hospitals Staff Testing Group, Crook DW, O’Donnell A, Conlon CP, Pouwels KB, Walker AS, Peto TEA, Hopkins S, Walker TM, Stoesser NE, Matthews PC, Jeffery K, Eyre DW
An observational cohort study on the incidence of SARS-CoV-2 infection and B.1.1.7 variant infection in healthcare workers by antibody and vaccination status
accepted by Clin Infec Dis doi: 10.1093/cid/ciab608
medRxiv preprint doi: 10.1101/2021.03.09.21253218

 

52. Lumley SF, O’Donnell D, Stoesser NE, Matthews PC, Howarth A, Hatch, SB, Marsden BD, et al. and the Oxford University Hospitals Staff Testing Group
Antibody Status and Incidence of SARS-CoV-2 Infection in Health Care Workers
N Eng J Med 384:533
doi:10.1056/NEJMoa2034545

 

51. Lumley SF, Wei J, O’Donnell D, Stoesser NE, Matthews PC, Howarth A, Hatch SB, Marsden BD, Cox S, James T, Peck LJ, Ritter TG, de Toledo Z, Cornall RJ, Jones EY, Stuart DI, Screaton G,
Ebner D, Hoosdally S, Crook DW, Conlon CP, Pouwels KB, Walker AS, Peto TEA, Walker TM,
Jeffery K, Eyre DW, Oxford University Hospitals Staff Testing Group
The Duration, Dynamics, and Determinants of SARS-CoV-2 Antibody Responses in Individual Healthcare Workers
Clin Infec Dis 73:e699
doi: 10.1093/cid/ciab004
and medRxiv preprint doi: 10.1101/2020.11.02.20224824

 

2020

50. Fowler PW
How quickly can we predict trimethoprim resistance using alchemical free energy methods?
Interface Focus 10:20190141
doi: 10.1098/rsfs.2019.0141 and bioRxiv preprint doi:10.1101/2020.01.13.904664

 
 

49. Eyre DW, Lumley SF, Donnell DO, Campbell M, Sims E, Lawson E, Warren F, James T, Cox S, Howarth A, Doherty G, Hatch SB, Kavanagh J, Chau KK, Fowler PW, Swann J, Volk D, Yang-Turner F, Stoesser NE, Matthews PC, Dudareva M, Davies T, Shaw RH, Peto L, et al.
Differential occupational risks to healthcare workers from SARS-CoV-2 observed during a prospective observational study
eLife 9:e60675
doi: 10.7554/eLife.60675 and medRxiv preprint
doi:10.1101/2020.06.24.20135038

 
 

48. Davies TJ, Stoesser N, Sheppard AE, Abuoun M, Fowler PW, Swann J, Quan P, Griffiths D, Vaughan A, Morgan M, Phan HTT, Jeffery KJM, Andersson M, Eillington M, Ekelund O, Mathers A, Bonomo R, Woodford N, Crook DW, Peto TEA, Anjum M, Walker AS
Reconciling the potentially irreconcilable? Genotypic and phenotypic amoxicillin-clavulanate resistance in E. coli.
Antimicrobial Agent Chemo 64:e02026
doi: 10.1128/AAC.02026-19 and preprint doi:10.1101/511402

 

47. Wilson DJ, CRyPTIC Consortium
GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes.
Mol Biol Evol msaa0699
doi: 10.1093/molbev/msaa069 and biorXiv preprint doi: 10.1101/523316

 

46. Merker M, Kohl TA, Barilar I, Andres S, Fowler PW, Chryssanthou E, Ängeby K, Jureen P, Moradigaravand D, Parkhill J, Peacock SJ, Schön T, Maurer F, Walker TM, Köser C, Niemann S.
Phylogenetically informative mutations in genes implicated in antibiotic resistance in Mycobacterium tuberculosis complex.
Genome Medicine 12:27
doi: 10.1186/s13073-020-00726-5

 

2019

45. Hunt M, Bradley P, Lapierre SG, Heys S, Thomsit M, Hall MB, Malone KM, Wintringer P, Walker TM, Cirillo DM, Comas I, Farhat MR, Fowler PW, Gardy J, Ismail N, Kohl TA, Mathys V, Merker M, Niemann S, Omar SV, Sintchenko V, Smith G, van Soolingen D, Supply P, Tahseen S, Wilcox M, Arandjelovic I, Peto TEA, Crook DW, Iqbal Z.
Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe
Wellcome Open Research 4:191
doi:10.12688/wellcomeopenres.15603.1

 

44. Brankin AE, Fowler PW
Predicting Resistance is (Not) Futile.
ACS Cent Sci. 5:1312
doi: 10.1021/acscentsci.9b00791

 

43. Collins JJ, Brown E, Baym M, Wright GD, Dantas G, Burrows L, Liu GY, Fowler PW, Whitchurch CB, Skelly AN, Honda K, Strathdee SA, Patterson TL.
Overcoming Antibiotic Resistance.
Cell Host Microbe 26:8.
doi: 10.1016/j.chom.2019.06.007

 

42. Yang-Turner F, Volk D, Fowler PW, Hoosdally S, Peto TEA, Crook DW
Scalable Pathogen Pipeline Platform (SP3) Enabling Unified Genomic Data Analysis with Elastic Cloud Computing
IEEE Cloud 2019 478
doi: 10.1109/CLOUD.2019.00083

 

41. Yang Y, Walker TM, Walker AS, Wilson DJ, Peto TEA, Crook DW, Shamout F, CRyPTIC Consortium, Zhu T, Clifton DA
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
Bioinformatics 35:3240
doi: 10.1093/bioinformatics/btz067

 

40. Kouchaki S, Yang Y, Walker TM, Walker AS, Wilson DJ, Peto TEA, Crook DW, CRyPTIC Consortium, Clifton DA
Application of machine learning techniques to tuberculosis drug resistance analysis
Bioinformatics 35:2276
doi: 10.1093/bioinformatics/bty949

 

2018

39. Fowler PW, Gibertoni-Cruz AL, Hoosdally S, Jarrett L, Borroni E, Chiacchiaretta M, Rathod P, Lehmann S, Molodtsov N, Grazian C, Walker TM, Robinson E, Hoffmann H, Peto TEA, Cirillo DM, Smith EG, Crook DW
Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis
Microbiology 164:1522
doi: 10.1099/mic.0.000733 and biorXiv preprint doi: 10.1101/229427

 

38. The CRyPTIC Consortium and the 100,000 Genomes Project
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing
N Eng J Med 379:1403
doi: 10.1056/NEJMoa1800474

 

37. Rancoita PMV, Cugnata F, Gibertoni-Cruz AL, Borroni E, Hoosdally SJ, Walker TM, Grazian C, 2018 12 Davies TJ, Peto TEA, Crook DW, Fowler PW, Cirillo DM and the CRyPTIC consortium
Validating a 14-Drug Microtiter Plate Containing Bedaquiline and Delamanid for Large-Scale Re-
search Susceptibility Testing of Mycobacterium tuberculosis
Antimicrob Agent Chemo 62:e00344
doi: 10.1128/AAC.00344-18 and biorXiv preprint doi: 10.1101/244731

 

36. Fowler PW, Coles K, Gordon NC, Kearns AM, Llewelyn MJ, Peto TEA, Crook DW, Walker AS
Robust prediction of resistance to trimethoprim in S. aureus
Cell Chem Biol 25:339
doi: 10.1016/j.chembiol.2017.12.009

 

2017

35. Duncan A, Reddy T, Koldsø H, Helie J, Fowler PW, Chavent M, Sansom MSP Protein crowding and lipid complexity influence the nanoscale dynamic organization of ion channels in cell membranes
Sci. Rep. 7:16647
doi: 10.1038/s41598-017-16865-6

 

34. Fowler PW, Sansom MSP, Reithmeier RAF
Effect of the Southeast Asian Ovalocytosis Deletion on the Conformational Dynamics of the Signal-Anchor Transmembrane Segment 1 of the Red Cell Anion Exchanger 1 (AE1, Band 3).
Biochemistry56:712
doi: 10.1021/acs.biochem.6b00966

 

2016

33. Fowler PW, Helie J, Duncan AL,Chavent M, Koldsø H, Sansom MSP
Membrane stiffness is modified by integral membrane proteins.
Soft Matter 12:7792
doi: 10.1039/c6sm01186a

 

32. Fowler PW, Williamson JJ, Sansom MSP, Olmsted PD
Roles of interleaflet coupling and hydrophobic mismatch in lipid membrane phase-separation kinetics.
J Am Chem Soc 138:11633
doi: 10.1021/jacs.6b04880

 

31. Koldsø H, Reddy T, Fowler PW, Duncan AL, Sansom MSP
Membrane compartmentalization reduces the mobility of lipids and proteins within a model plasma membrane.
J Phys Chem B 120:8873
doi: 10.1021/acs.jpcb.6b05846

 

30. Samsudin F, Parker JL, Sansom MSP, Newstead and Fowler PW
Accurate prediction of ligand affinities for a peptide transporter.
Cell Chem Biol 23:299
doi: 10.1016/j.chembiol.2015.11.015

 

2015

29. Beale JH, Parker JL, Samsudin F, Barret AL, Senan A, Bird LE, Scott D, Owens RJ, Sansom MSP, 2015 23 Tucker SJ, Meredith D, Fowler PW and Newstead S
Crystal structures of the extracellular domain from PepT1 and PepT2 provide novel insights into mammalian peptide transport.
Structure 23:1889.
doi: 10.1016/j.str.2015.07.016

 

28. Jefferys E, Sands Z, Shi J, Sansom MSP and Fowler PW
Alchembed: A computational method for incorporating proteins into complex lipid geometries.
J Chem Theo Comp. 11:2743
doi: 10.1021/ct501111d

 

27. Reddy T, Shorthouse D, Parton D, Jefferys E, Fowler PW, Chavent M, Baaden M, Sansom MSP (2015)
Nothing to sneeze at: a dynamic and integrative computational model of an influenza A virion.
Structure. 23:584.
doi: 10.1016/j.str.2014.12.019

 

26. Fowler PW, Orwick-Rydmark M, Radestock S, Solcan N, Dijkman P, Lyons JA, Kwok J, Caffery M, Watts A, Forrest LR and Newstead S (2015)
Gating topology of the proton coupled oligopeptide symporters.
Structure 23:290.
doi: 10.1016/j.str.2014.12.012

 

2014

25. Fowler PW, Bollepalli MK, Rapedius M, Shang L, Nematian E, Sansom MSP, Tucker SJ, Baukrowitz T (2014)
Insights into the structural nature of the transition state in the Kir channel gating pathway.
Channels 8:551
doi: 10.4161/19336950.2014.962371

 

24. Bollepalli MK, Fowler PW, Rapedius M, Shang L, Sansom MSP, Tucker SJ, Baukrowitz T (2014)
State dependent network connectivity determines gating in a K+ channel.
Structure 22:1037

 

23. Jefferys E, Sansom MSP and Fowler PW (2014)
NRas slows the rate at which a model lipid bilayer phase separates.
RSC Faraday Discussion 169:209
doi: 10.1039/c3fd00131h

 

22. Stelzl L, Fowler PW, Sansom MSP and Beckstein O (2014)
Flexible gates generate occluded intermediates in the transport cycle of LacY.
J Mol Biol 426:735
doi: 10.1016/j.jmb.2013.10.024

 

2013

21. Fowler PW, Beckstein O, Abad E and Sansom MSP (2013)
Detailed examination of a single conduction event in a potassium channel.
 J Phys Chem Lett 4:3104
doi: 10.1021/jz4014079

 

20. Fowler PW, Abad E, Beckstein O and Sansom MSP (2013)
Energetics of multi-ion conduction pathways in potassium ion channels.
J Chem Theo Comp 9:5176
doi: 10.1021/ct4005933

 

19. Fowler PW and Sansom MSP (2013)
The pore of voltage-gated potassium ion channels is strained when closed.
Nature Communications 4:1872
doi: 10.1038/ncomms2858

 

2012

18. Solcan N, Kwok J, Fowler PW, Cameron AD, Drew D, Iwata S and Newstead S (2012)
Alternating access mechanism in the POT family of oligopeptide transporters.
EMBO J 31:3411
doi: 10.1038/emboj.2012.157

 

2011

17. Newstead S, Drew D, Cameron AD, Postis VLG, Xia X, Fowler PW, Carpenter EP, Sansom MSP, McPheron MJ, Baldwin SA and Iwata S (2011)
Crystal structure of a prokaryotic homologue of the mammalian oligopeptide-proton symporters, PepT1 and PepT2.
EMBO J 30:417
doi: 10.1038/emboj.2010.309

 

2010

16. Paynter JJ, Andres-Enguix I, Fowler PW, Tottey S, Cheng W, Enkvetchakul D, Bavro VN, Kusakabe Y, Sansom MSP, Robinson NJ, Nichols CG and Tucker SJ (2010)
Functional complementation and genetic deletion studies of KirBac channels.
J Biol Chem 285:40754
doi: 10.1074/jbc.M110.175687

 

2009

15. Newstead S, Fowler PW, Bilton P, Carpenter E, Sadler P, Campopiano D, Sansom M, Iwata S (2009)
Insights into how nucleotide-binding domains power ABC transport.
Structure 17:1213
doi: 10.1016/j.str.2009.07.009

 

14. Abad E, Reingruber J, Fowler PW and Sansom MSP (2009)
A novel rate theory approach to transport in ion channels.
TACC 1102:236
doi: 10.1063/1.3108380

 

2008

13. Tai K, Fowler PW, Mokrab Y, Stansfield P and Sansom MSP (2008)
Molecular modeling and simulation studies of ion channel structures, dynamics & mechanisms.
Methods Nano Cell Biol 90:233
doi: 10.1016/S0091-679X(08)00812-1

 

12. Psachoulia E, Fowler PW, Bond PJ and Sansom MSP (2008)
Helix-helix interactions in membrane proteins: Coarse grained simulations of Glycophorin helix dimerization.
Biochemistry. 47:10503
doi: 10.1021/bi800678t

 

11. Fowler PW, Tai K and Sansom MSP (2008)
The selectivity of K+ ion channels: testing the hypotheses.
Biophys J 95:5062
doi: 10.1529/biophysj.108.132035

 

2007

10. Rapedius M, Paynter J, Fowler PW, Shang L, Sansom MSP, Tucker SJ and Baukrowitz T (2007)
Control of pH and PIP2 gating in heteromeric Kir4.1/Kir5.1 channels by h-bonding at the helix bundle crossing.
Channels. 1:327
doi: 10.4161/chan.5176

 

9. Rapedius M, Fowler PW, Shang L, Sansom MSP, Tucker SJ and Baukrowitz T (2007)
H-Bonding at the helix-bundle crossing controls gating in Kir potassium channels.
Neuron 55:602
doi: 10.1016/j.neuron.2007.07.026

 

8. Fowler PW, Geroult S, Jha S, Waksman G and Coveney PV (2007)
Rapid, accurate and precise calculation of relative binding affinities for the SH2 domain using a computational grid.
J Comp Theo Chem 3:1193
doi: 10.1021/ct6003017

 

7. Fowler PW , Balali-Mood K , Deol SS, Coveney PV and Sansom MSP (2007)
Monotopic proteins and lipid bilayers: a comparative study.
Biochemistry. 46:3108
doi: 10.1021/bi602455n

 

2006

6. Fowler PW and Coveney PV (2006)
A computational protocol for the integration of the monotopic protein PGHS into a bilayer. Biophys J 91:401
doi: 10.1529/biophysj.105.077784

 

2005

5. Coveney PV and Fowler PW (2006)
Modelling biological complexity: a physical scientist’s perspective.
J R Soc Interface 2:267
doi: 10.1098/rsif.2005.0045

 

4. Fowler PW, Jha S and Coveney PV (2005)
Grid-based steered thermodynamic integration accelerates the calculation of binding affinities. Phil Trans R Soc Lond A 363(1833):1999
doi: 10.1098/rsta.2005.1625

 

3. Giordanetto F, Fowler PW, Saqi M, and Coveney PV (2005)
Large scale molecular dynamics simulation of native and mutant DHPS complexes suggests the molecular basis for dihydropteroate synthase drug resistance.
Phil Trans R Soc Lond A 363:(1833):2055
doi: 10.1098/rsta.2005.1629

 

2004

2. Fowler PW, Coveney PV, Jha S and Wan S (2004)
Exact calculation of peptide-protein binding energies by steered thermodynamic integration using high performance computing grids.
Proceedings of the UK e-Science All Hands Meeting

 

1998

1. Al-Mushadani O, Boghosian BM, Coveney PV, Fowler PW, Maillet JB and Wilson JL (1998)
Lattice-Gas Simulations of Ternary Amphiphilic Fluid Flow in Porous Media.
Int J Mod Phys C 9:1479
doi: 10.1142/S0129183198001345