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The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Zheng X, Wang J - PLoS Comput. Biol. (2015)

Bottom Line: The results of the analytical studies are confirmed by the microscopic flexible docking simulations.Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors.The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, ChangChun, Jilin, P.R. China.

ABSTRACT
We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

No MeSH data available.


The distribution of the predicted kinetic specificity.(A) The distribution of the logarithm of the predicted Timeon with 720 compounds binding to the Cox2; (B) The distribution of the logarithm of the predicted Timeoff with 720 compounds binding to the Cox2. gaussian curve: in the center; exponential curve: near the tail. The parameter values for these distributions are presented. The analytical function consisting of a Gaussian and two exponential functions is highlighted with red line.
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pcbi.1004212.g009: The distribution of the predicted kinetic specificity.(A) The distribution of the logarithm of the predicted Timeon with 720 compounds binding to the Cox2; (B) The distribution of the logarithm of the predicted Timeoff with 720 compounds binding to the Cox2. gaussian curve: in the center; exponential curve: near the tail. The parameter values for these distributions are presented. The analytical function consisting of a Gaussian and two exponential functions is highlighted with red line.

Mentions: As described in Fig 9, we found that the distribution of kinetics can be fitted quite well with log-normal distribution near the mean and power law distribution at the tail. This is consistent with our analytical models above.


The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Zheng X, Wang J - PLoS Comput. Biol. (2015)

The distribution of the predicted kinetic specificity.(A) The distribution of the logarithm of the predicted Timeon with 720 compounds binding to the Cox2; (B) The distribution of the logarithm of the predicted Timeoff with 720 compounds binding to the Cox2. gaussian curve: in the center; exponential curve: near the tail. The parameter values for these distributions are presented. The analytical function consisting of a Gaussian and two exponential functions is highlighted with red line.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401658&req=5

pcbi.1004212.g009: The distribution of the predicted kinetic specificity.(A) The distribution of the logarithm of the predicted Timeon with 720 compounds binding to the Cox2; (B) The distribution of the logarithm of the predicted Timeoff with 720 compounds binding to the Cox2. gaussian curve: in the center; exponential curve: near the tail. The parameter values for these distributions are presented. The analytical function consisting of a Gaussian and two exponential functions is highlighted with red line.
Mentions: As described in Fig 9, we found that the distribution of kinetics can be fitted quite well with log-normal distribution near the mean and power law distribution at the tail. This is consistent with our analytical models above.

Bottom Line: The results of the analytical studies are confirmed by the microscopic flexible docking simulations.Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors.The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, ChangChun, Jilin, P.R. China.

ABSTRACT
We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

No MeSH data available.