Dioxygen and nitric oxide pathways and affinity to the catalytic site of rubredoxin:oxygen oxidoreductase from Desulfovibrio gigas
- 163 Downloads
Rubredoxin:oxygen oxidoreductase (ROO) is the terminal oxidase of a soluble electron transfer chain found in Desulfovibrio gigas. This protein belongs to the flavodiiron family and was initially described as an oxygen reductase, converting this substrate to water and acting as an oxygen-detoxifying system. However, more recent studies evidenced also the ability for this protein to act as a nitric oxide reductase, suggesting an alternative physiological role. To clarify the apparent bifunctional nature of this protein, we performed molecular dynamics simulations of the protein, in different redox states, together with O2 and NO molecules in aqueous solution. The two small molecules were parameterized using free-energy calculations of the hydration process. With these simulations we were able to identify specific protein paths that allow the diffusion of both these molecules through the protein towards the catalytic centers. Also, we have tried to characterize the preference of ROO towards the presence of O2 and/or NO at the active site. By using free-energy simulations, we did not find any significant preference for ROO to accommodate both O2 and NO. Also, from our molecular dynamics simulations we were able to identify similar diffusion profiles for both O2 and NO molecules. These two conclusions are in good agreement with previous experimental works stating that ROO is able to catalyze both O2 and NO.
KeywordsRubredoxin:oxygen oxidoreductase Diffusion Oxygen Nitric oxide Molecular dynamics
We thank João Vicente and Miguel Teixeira for fruitful discussions about FDPs. This work was supported by grants 36560/1999/FCT-Sapiens and by fellowship SFRH/BD/10622/2002 from Fundação para a Ciência ea Tecnologia, Portugal.
- 2.Vicente JB, Carrondo MA, Teixeira M, Frazão C (2007) In: Messerschmidt A (ed) Handbook of metalloproteins. Wiley, New York, pp 1–19Google Scholar
- 6.Dilling W, Cypionka H (1990) FEMS Microbiol Lett 71:123–128Google Scholar
- 8.Gardner A, Helmick R, Gardner P (2002) J Biol Chem 277:8172–8177Google Scholar
- 9.Gomes CM, Giuffrè A, Forte H, Vicente JB, Saraiva L, Brunori M, Teixeira M (2002) J Biol Chem 277:25273–25276Google Scholar
- 16.Saraiva LM, Vicente JB, Teixeira M (2004) Adv Microb Physiol 49:77–129Google Scholar
- 17.DeLano WL (2003) PyMOL. DeLano Scientific, San CarlosGoogle Scholar
- 22.Lancaster JR (1994) Proc Natl Acad Sci USA 91:8137–8141Google Scholar
- 26.Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Zakrzewski VG, Montgomery JA Jr, Stratmann RE, Burant JC, Dapprich S, Millam JM, Daniels AD, Kudin KN, Strain MC, Farkas O, Tomasi J, Barone V, Cossi M, Cammi R, Mennucci B, Pomelli C, Adamo C, Clifford S, Ochterski J, Petersson GA, Ayala PY, Cuik Q, Morokuma K, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Cioslowski J, Ortiz JV, Baboul AG, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Gomperts R, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Gonzalez C, Challacombe M, Gill PMW, Johnson B, Chen W, Wong MW, Andres JL, Head-Gordon M, Replogle ES, Pople JA (1998) Gaussian 98. Gaussian, PittsburghGoogle Scholar
- 31.Lin ST, Hsu HW (1969) J Chem Eng Data 14:328–332Google Scholar
- 44.Ben-Naim A (1992) Statistical thermodynamics for chemists and biochemists. Plenum Press, New YorkGoogle Scholar
- 48.Lindahl E, Hess B, van der Spoel D (2001) J Mol Model 7:306–317Google Scholar