Dataset Information

Rational design of a novel calcium-binding site adjacent to the ligand-binding site on CD2 increases its CD48 affinity.

ABSTRACT: Electrostatic interactions are important for molecular recognition processes including Ca2+-binding and cell adhesion. To understand these processes, we have successfully introduced a novel Ca2+-binding site into the non-Ca2+-dependent cell adhesion protein CD2 using our criteria that are specifically tailored to the structural and functional properties of the protein environment and charged adhesion surface. This designed site with ligand residues exclusively from the beta-sheets selectively binds to Ca2+ and Ln3+ over other mono- and divalent cations. While Ca2+ and Ln3+ binding specifically alters the local environment of the designed Ca2+-binding site, the designed protein undergoes a significantly smaller conformation change compared with those observed in naturally occurring Ca2+-binding sites that are composed of at least part of the flexible loop and helical regions. In addition, the CD2-CD48-binding affinity increased approximately threefold after protein engineering, suggesting that the cell adhesion of CD2 can be modulated by altering the local electrostatic environment. The study provides site-specific information for regulating cell adhesion within CD2 and gives insight into the structural factors required for Ca2+-modulated biological processes.

SUBMITTER: Jones LM

PROVIDER: S-EPMC2248323 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature

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Rational design of a novel calcium-binding site adjacent to the ligand-binding site on CD2 increases its CD48 affinity.

Jones Lisa M LM Yang Wei W Maniccia Anna W AW Harrison Alice A van der Merwe P Anton PA Yang Jenny J JJ

Protein science : a publication of the Protein Society 20080301 3

Electrostatic interactions are important for molecular recognition processes including Ca2+-binding and cell adhesion. To understand these processes, we have successfully introduced a novel Ca2+-binding site into the non-Ca2+-dependent cell adhesion protein CD2 using our criteria that are specifically tailored to the structural and functional properties of the protein environment and charged adhesion surface. This designed site with ligand residues exclusively from the beta-sheets selectively bi ...[more]

PMID: 18287277

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Project description:Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding affinity and thus impact the drug's efficacy and side effects. Unfortunately, large-scale experimental screening of ligand-binding against protein variants is still time-consuming and expensive. Alternatively, in silico approaches can play a role in guiding those experiments. Methods ranging from computationally cheaper machine learning (ML) to the more expensive molecular dynamics have been applied to accurately predict the mutation effects. However, these effects have been mostly studied on limited and small datasets, while ideally a large dataset of binding affinity changes due to binding site mutations is needed. In this work, we used the PSnpBind database with six hundred thousand docking experiments to train a machine learning model predicting protein-ligand binding affinity for both wild-type proteins and their variants with a single-point mutation in the binding site. A numerical representation of the protein, binding site, mutation, and ligand information was encoded using 256 features, half of them were manually selected based on domain knowledge. A machine learning approach composed of two regression models is proposed, the first predicting wild-type protein-ligand binding affinity while the second predicting the mutated protein-ligand binding affinity. The best performing models reported an RMSE value within 0.5 [Formula: see text] 0.6 kcal/mol-1 on an independent test set with an R2 value of 0.87 [Formula: see text] 0.90. We report an improvement in the prediction performance compared to several reported models developed for protein-ligand binding affinity prediction. The obtained models can be used as a complementary method in early-stage drug discovery. They can be applied to rapidly obtain a better overview of the ligand binding affinity changes across protein variants carried by people in the population and narrow down the search space where more time-demanding methods can be used to identify potential leads that achieve a better affinity for all protein variants.

Dataset Information

Rational design of a novel calcium-binding site adjacent to the ligand-binding site on CD2 increases its CD48 affinity.

Publications

Rational design of a novel calcium-binding site adjacent to the ligand-binding site on CD2 increases its CD48 affinity.

Similar Datasets

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