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The role of entropy and polarity in intermolecular contacts in protein crystals.

ABSTRACT: The integrity and X-ray diffraction quality of protein crystals depend on the three-dimensional order of relatively weak but reproducible intermolecular contacts. Despite their importance, relatively little attention has been paid to the chemical and physical nature of these contacts, which are often regarded as stochastic and thus not different from randomly selected protein surface patches. Here, logistic regression was used to analyze crystal contacts in a database of 821 unambiguously monomeric proteins with structures determined to 2.5 A resolution or better. It is shown that the propensity of a surface residue for incorporation into a crystal contact is not a linear function of its solvent-accessible surface area and that amino acids with low exposed surfaces, which are typically small and hydrophobic, have been underestimated with respect to their contact-forming potential by earlier area-based calculations. For any given solvent-exposed surface, small and hydrophobic residues are more likely to be involved in crystal contacts than large and charged amino acids. Side-chain entropy is the single physicochemical property that is most negatively correlated with the involvement of amino acids in crystal contacts. It is also shown that crystal contacts with larger buried surfaces containing eight or more amino acids have cores that are depleted of polar amino acids.

SUBMITTER: Cieslik M

PROVIDER: S-EPMC2672819 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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The role of entropy and polarity in intermolecular contacts in protein crystals.

Cieślik Marcin M Derewenda Zygmunt S ZS

Acta crystallographica. Section D, Biological crystallography 20090418 Pt 5

The integrity and X-ray diffraction quality of protein crystals depend on the three-dimensional order of relatively weak but reproducible intermolecular contacts. Despite their importance, relatively little attention has been paid to the chemical and physical nature of these contacts, which are often regarded as stochastic and thus not different from randomly selected protein surface patches. Here, logistic regression was used to analyze crystal contacts in a database of 821 unambiguously monome ...[more]

PMID: 19390155

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Project description:BackgroundStudy of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems.ResultsIn this work, we are providing new insights into the differences between biological and crystallographic complexes by focusing on "pair-properties" of interfaces that have not yet been fully investigated. We investigated properties such intermolecular residue-residue contacts (already successfully applied to the prediction of binding affinities) and interaction energies (electrostatic, Van der Waals and desolvation). By using the XtalMany and BioMany interface datasets, we show that interfacial residue contacts, classified as a function of their physico-chemical properties, can distinguish between biological and crystallographic interfaces. The energetic terms show, on average, higher values for crystal interfaces, reflecting a less stable interface due to crystal packing compared to biological interfaces. By using a variety of machine learning approaches, we trained a new interface classification predictor based on contacts and interaction energetic features. Our predictor reaches an accuracy in classifying biological vs crystal interfaces of 0.92, compared to 0.88 for EPPIC (one of the main state-of-the-art classifiers reporting same performance as PISA).ConclusionIn this work we have gained insights into the nature of intermolecular contacts and energetics terms distinguishing biological from crystallographic interfaces. Our findings might have a broader applicability in structural biology, for example for the identification of near native poses in docking. We implemented our classification approach into an easy-to-use and fast software, freely available to the scientific community from http://github.com/haddocking/interface-classifier .

Dataset Information

The role of entropy and polarity in intermolecular contacts in protein crystals.

Publications

The role of entropy and polarity in intermolecular contacts in protein crystals.

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