Limits...
Protein-protein docking with dynamic residue protonation states.

Kilambi KP, Reddy K, Gray JJ - PLoS Comput. Biol. (2014)

Bottom Line: On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock.Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions.The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.

ABSTRACT
Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

Show MeSH
pH-dependent binding effects in Fc–FcRn complex.(A) Interface score of the top pHDock prediction for the Fc–FcRn complex as a function of the docking pH. (B) Interface score vs Irmsd plots generated using pHDock at pH 6.25 and pH 7.50. (C) Top pHDock models at pH 6.25 (cyan) and pH 7.50 (green) showing the three critical ionic interactions responsible for the large pH-dependent binding affinity change. Note the change in the protonation states of His-435 and His-436.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4263365&req=5

pcbi-1004018-g007: pH-dependent binding effects in Fc–FcRn complex.(A) Interface score of the top pHDock prediction for the Fc–FcRn complex as a function of the docking pH. (B) Interface score vs Irmsd plots generated using pHDock at pH 6.25 and pH 7.50. (C) Top pHDock models at pH 6.25 (cyan) and pH 7.50 (green) showing the three critical ionic interactions responsible for the large pH-dependent binding affinity change. Note the change in the protonation states of His-435 and His-436.

Mentions: To test the efficacy of pHDock in predicting pH effects on binding affinities, we used the pHDock algorithm to dock the murine Fc–FcRn complex (1I1A [30]) at various environmental pH values. We tested all integral pH values between 3.0 and 11.0, and used a finer interval of 0.25 pH units for the relevant pH range of 6.0–8.0 where the striking binding affinity change is observed. We used the interface scores (I) of the top-scoring pHDock models to approximate the binding affinity at different pH values. Fc–FcRn complex shows a binding minimum at pH 6.25 (IpH6.25: −13.99 Rosetta Energy Units (REU)), and thereafter the affinity rapidly weakens as the environment pH increases to 7.50 (IpH7.50: −11.82 REU) (Fig. 7A). Converting the binding energies to equilibrium constants using the relation we estimated the ratio of equilibrium constants at pH values 6.25 and 7.50 as where KpH6.25 and KpH7.50 are the equilibrium binding constants at pH 6.25 and 7.50, respectively, and kBT is 0.59 kcal/mol at 298K. The equation yields a 40-fold drop in the binding affinity as the pH increases from 6.25 to 7.50, which is similar to the 50 to 100-fold drop from experiments [52]. Interestingly, the docking plots show successful energy funnels for both pH values (Fig. 7B). However, the energy funnel is more pronounced at pH 6.25 (discrimination score −0.96) than pH 7.50 (discrimination score −0.47), indicating a site-specific binding event at both pH values, but with markedly different affinities.


Protein-protein docking with dynamic residue protonation states.

Kilambi KP, Reddy K, Gray JJ - PLoS Comput. Biol. (2014)

pH-dependent binding effects in Fc–FcRn complex.(A) Interface score of the top pHDock prediction for the Fc–FcRn complex as a function of the docking pH. (B) Interface score vs Irmsd plots generated using pHDock at pH 6.25 and pH 7.50. (C) Top pHDock models at pH 6.25 (cyan) and pH 7.50 (green) showing the three critical ionic interactions responsible for the large pH-dependent binding affinity change. Note the change in the protonation states of His-435 and His-436.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263365&req=5

pcbi-1004018-g007: pH-dependent binding effects in Fc–FcRn complex.(A) Interface score of the top pHDock prediction for the Fc–FcRn complex as a function of the docking pH. (B) Interface score vs Irmsd plots generated using pHDock at pH 6.25 and pH 7.50. (C) Top pHDock models at pH 6.25 (cyan) and pH 7.50 (green) showing the three critical ionic interactions responsible for the large pH-dependent binding affinity change. Note the change in the protonation states of His-435 and His-436.
Mentions: To test the efficacy of pHDock in predicting pH effects on binding affinities, we used the pHDock algorithm to dock the murine Fc–FcRn complex (1I1A [30]) at various environmental pH values. We tested all integral pH values between 3.0 and 11.0, and used a finer interval of 0.25 pH units for the relevant pH range of 6.0–8.0 where the striking binding affinity change is observed. We used the interface scores (I) of the top-scoring pHDock models to approximate the binding affinity at different pH values. Fc–FcRn complex shows a binding minimum at pH 6.25 (IpH6.25: −13.99 Rosetta Energy Units (REU)), and thereafter the affinity rapidly weakens as the environment pH increases to 7.50 (IpH7.50: −11.82 REU) (Fig. 7A). Converting the binding energies to equilibrium constants using the relation we estimated the ratio of equilibrium constants at pH values 6.25 and 7.50 as where KpH6.25 and KpH7.50 are the equilibrium binding constants at pH 6.25 and 7.50, respectively, and kBT is 0.59 kcal/mol at 298K. The equation yields a 40-fold drop in the binding affinity as the pH increases from 6.25 to 7.50, which is similar to the 50 to 100-fold drop from experiments [52]. Interestingly, the docking plots show successful energy funnels for both pH values (Fig. 7B). However, the energy funnel is more pronounced at pH 6.25 (discrimination score −0.96) than pH 7.50 (discrimination score −0.47), indicating a site-specific binding event at both pH values, but with markedly different affinities.

Bottom Line: On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock.Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions.The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.

ABSTRACT
Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

Show MeSH