Comparative void-volume analysis of psychrophilic and mesophilic enzymes: Structural bioinformatics of psychrophilic enzymes reveals sources of core flexibility
© Paredes et al; licensee BioMed Central Ltd. 2011
- Received: 9 July 2011
- Accepted: 20 October 2011
- Published: 20 October 2011
Psychrophiles, cold-adapted organisms, have adapted to live at low temperatures by using a variety of mechanisms. Their enzymes are active at cold temperatures by being structurally more flexible than mesophilic enzymes. Even though, there are some indications of the possible structural mechanisms by which psychrophilic enzymes are catalytic active at cold temperatures, there is not a generalized structural property common to all psychrophilic enzymes.
We examine twenty homologous enzyme pairs from psychrophiles and mesophiles to investigate flexibility as a key characteristic for cold adaptation. B-factors in protein X-ray structures are one way to measure flexibility. Comparing psychrophilic to mesophilic protein B-factors reveals that psychrophilic enzymes are more flexible in 5-turn and strand secondary structures. Enzyme cavities, identified using CASTp at various probe sizes, indicate that psychrophilic enzymes have larger average cavity sizes at probe radii of 1.4-1.5 Å, sufficient for water molecules. Furthermore, amino acid side chains lining these cavities show an increased frequency of acidic groups in psychrophilic enzymes.
These findings suggest that embedded water molecules may play a significant role in cavity flexibility, and therefore, overall protein flexibility. Thus, our results point to the important role enzyme flexibility plays in adaptation to cold environments.
- Cavity Volume
- Cold Adaptation
- Amino Acid Frequency
- Protein Flexibility
- Thermophilic Protein
Life exists over a wide temperature range, from as low as -15°C to as high as 122°C . On the upper end of the temperature spectrum, thermophiles and hyperthermophiles have been studied extensively by the scientific community, particularly the molecular mechanisms that support protein structure and function at high temperatures. For example, compact and strong hydrophobic packing is typically found in most cores of thermophilic proteins, which increases the energy needed to unfold the protein, making it possible for thermophilic proteins to retain native structure at high temperatures . Indeed, a strong correlation exists between high core packing density and thermostability [2–4]. We are also intrigued by the obverse - organisms that survive optimally at cold temperatures; harsh environments with restricted molecular mobility and reduced reaction kinetics that hinder myriad cellular and biomolecular processes [5–7].
Psychrophiles, "cold-loving" microorganisms, have adapted to life at low temperatures by using a variety of mechanisms. These include the production of anti-freeze and cold-shock proteins, alterations in membrane composition, and overexpression of proteins that destabilize DNA structures, among other mechanisms [8–10]. Some of the more interesting adaptations are found in psychrophilic enzymes. In particular, psychrophilic enzymes typically have a higher occurrence of nonpolar residues on their surface, which destabilizes water structure around the enzyme such that water properties are considerably distinct from bulk water, and a lower abundance of arginine and proline residues, which increases backbone flexibility. Moreover, fewer weak interactions, such as hydrogen bonds, reduce the degree of packing within the enzyme core and make psychrophilic enzymes more conformationally flexible [[11–13]; and references therein]. Increased flexibility has been proposed as a major molecular mechanism for the evolution of cold adapted enzymes, a hypothesis supported by spectroscopic analysis (e.g., nuclear magnetic resonance , dynamic fluorescence quenching  and molecular dynamics (MD) simulations ).
Psychrophilic enzymes have been shown to lose more entropy upon transition state activation than their mesophilic counterparts, suggesting that the psychrophilic proteins exist in a more disordered ground state [17, 9]. This intuitively makes sense, since in order for psychrophilic enzymes to be more active at low temperatures they must have more kinetic energy . Nonetheless, the structural basis of this flexibility remains unclear. For example, an MD simulations study of one-on-one comparisons of trypsin from Atlantic salmon and its mesophilic counterpart  found that the psychrophilic trypsin possesses higher flexibility close to the active site parts. Interestingly, the active site is where there is the most significant difference in amino acid composition between mesophilic and psychrophilic trypsins. However, other psychrophilic enzymes exhibit regions of flexibility in places distant from the active site. For example, psychrophilic uracil-DNA glycosylases  have fewer strong ion-pair interactions near the C-terminus than their mesophilic counterparts. This local difference results in increased flexibility in the psychrophilic enzymes. Psychrophilic alpha-amylases  show greater overall flexibility than the mesophilic/thermophilic counterparts. This is consistent with thermal unfolding experiments, where the psychrophilic enzymes unfold at low temperatures cooperatively without intermediates due to fewer stabilizing interactions, while thermophilic amylases show intermediates during unfolding, indicating that there are regions with greater rigidity than others. The different strategies that psychrophilic enzymes use to adapt to colder environments have resulted in a number of divergent viewpoints on the influence of local and global protein flexibility on cold adaptation.
An interesting structural property of proteins, particularly as it relates to thermostability, is cavity number and size. Protein thermostability appears to diminish when cavities are created in the protein . Such cavities represent packing defects in the protein core. In the case of psychrophilic proteins, only a few studies have addressed these cavities, and then only with a small set of proteins [11, 22]. No clear relationship was observed between psychrophily and total void-volume in the enzyme core, as might be expected from the strong hydrophobic cores present in thermophilic proteins. However, an increased number of three-dimensional structures of psychrophilic proteins have become available and offer the opportunity to revisit such a structural analysis. Here we test the hypothesis that cavity properties in psychrophilic enzymes endow these proteins with the increased conformationally flexibility necessary to function optimally at low temperatures.
In the current work we investigated differences in the average cavity volume and crystallographic waters between psychrophilic and mesophilic homologs. A non-redundant set of 20 psychrophilic enzymes was examined, with each paired to a homologous mesophilic enzyme (sequence identity above 35% to 76%), and all with high resolution crystal structures. In addition to counting cavities and calculating void volumes, we evaluated amino acid frequencies in residue positions surrounding cavities. We present evidence that the average cavity size of psychrophilic enzymes is larger, and contains more surrounding hydrophilic groups, than their mesophilic counterparts. These findings support a hypothesis that psychrophilic enzymes may have a predisposition to having more water molecules within their cavities, which consequently increases enzyme conformational dynamics, leading to greater activity under the rigidifying cold environment. The results provide a potential strategy by which optimal temperature could be altered.
List of homologous enzymes used in this study
Resolution (Å) %
Antarctic bacterium ds2-3r
Sus scrofa Acidaminococcus
1 × dw
1n × q
Vibrio sp. pa-44
Bacillus clausii ksm-k16 Chromobacterium
Colwellia psychrerythraea 34h
Psychrophilic enzymes sacrifice conformational stability to become more flexible, and with greater intrinsic flexibility they remain catalytically active at lower temperatures [11–13, 15, 17]. Nonetheless, the structural basis for this flexibility remains unclear. To investigate psychrophilic protein flexibility on a molecular level, we carried out a statistical comparison of crystallographic B-values between psychrophilic and homologous mesophilic proteins.
Following a similar methodology, Siglioccolo et al.  also analyzed B'-values of psychrophilic and mesophilic proteins grouped by common secondary structures (α-helices, β-sheets, and turns). They observed that β-sheets and turns tend to be more flexible in psychrophilic proteins, relative to helices. The results hold true for this new, larger set of homologous pairs. Because overall flexibility differences were factored out by normalization, we cannot distinguish an increased flexibility in β-sheets from a decreased flexibility in α-helices using this data; however, it is worth noting that β-sheets tend to sit in the core of a protein where lattice defects have less of an effect, leaving intrinsic flexibility as the likely cause of higher B-values.
Cavity volume and morphology
B-values suggest, but do not inform, structural differences between a psychrophilic protein and its mesophilic counterpart, which prompted us to investigate the intrinsic characteristics of the protein core. Thermophilic globular proteins are known to have a highly compact hydrophobic core . Hydrophobic packing in psychrophilic proteins has not been widely studied, but the increased presence of amino acids with smaller side-chains inside the protein, points to a weak hydrophobic core. The internal loose packing in the protein core relates to intrinsic flexibility, which has been previously noted .
Amino acid frequency surrounding psychrophilic cavities
This study reveals that cavities in psychrophilic enzymes found at probe size 1.4 to 1.5 Å: (1) are statistically significantly different than in homologous mesophilic enzymes; and (2) their cavity surfaces contain a higher proportion of acidic amino acids. Several studies have found that cavities with these specific characteristics allow water molecules to exist stably within them [27–30]. Two key characteristics, in particular, are high polarity and excess space for movement. For example, Park and Saven  analyzed 6,718 buried water molecules contained in 842 different high resolution protein structures, revealing that these water molecules formed hydrogen bonds with polar atoms, predominantly near residues that compose turns or coils. Chen and Stites  obtained a similar result both experimentally and computationally with staphylococcal nuclease, wherein a water molecule stabilized Glu-66. These authors concluded that water molecules in polar cavities make more stable hydrogen bonds with the cavity walls and have longer residence times than in hydrophobic cavities. However, the presence of water and its function in protein cavities remains unclear.
It is well established that overall hydration increases the flexibility of the protein [26–30]. For example, Armstrong et al. , using electron paramagnetic resonance (EPR) spectroscopy, showed the importance of water hydration in the core of apomyoglobin and its role in protein transition between several structural conformational states, presumably by acting as a lubricant. The dynamics of water inside the protein core affects protein thermostability . Another methodology used to understand the role of water in enzymes, specifically the role of water in catalysis, involves nonaqueous systems. Specifically, adding water to a final concentration of 1% (v/v) in tetrahydrofuran resulted in a significant increase in the proteolytic activity of subtilisin Carlsberg, concomitant with an increase in active site mobility as determined by EPR . Using molecular dynamics simulations, Tarek and Tobias  demonstrated that higher levels of hydration contribute to increased in protein motion. Similarly, Rupley et al. , showed that a specific level of hydration is required by proteins to be active (0.4 g H2O per g dry protein). These findings point to an important correlation between hydration, protein flexibility, and enzymatic activity.
Many studies have proposed the importance of cavity hydration and its relation to higher protein flexibility. Fischer et al.  theoretically calculated the vibration entropy of bovine pancreatic trypsin inhibitor with bound and unbound water-122 (a buried water molecule). Bound water molecules increase the vibrational entropy of the protein, which could also be thought of as an increase in protein flexibility . Garcia and Hummer  used MD simulations to observe that water molecules inside proteins slowly exchange with the solvent, and when the molecules escape or penetrate the protein, they cause dynamic fluctuations.
Counting crystallographic waters
The observation that cavities in psychrophiles favor water-sized objects should imply that more waters are bound to the cold-adapted enzymes. To verify this, we isolated the buried crystallographic waters in all 38 enzymes (excluding the 1a59/1k3p pair because 1a59 contains no waters) by removing the surface-exposed waters and any waters that were buried by surface exposed waters, and then counting them. A correlation was observed (R2 = 0.73) in the number of buried waters between psychrophilic and mesophilic homologs, showing a consistency across crystals and crystallographers in modeling ordered solvent (see Additional file 1, Figure S3). There is a visible trend towards more water molecules in psychrophilic enzymes; however, the significance is marginal (p = 0.05). Interestingly, counter examples in this set appear to possess large numbers of buried waters. In addition to 1a59, if we remove the five pairs of psychrophilic-mesophilic homologs with > 25 buried waters (i.e., those with a high overall water density that could skew the analysis), then 11 out of the remaining 14 pairs fit the trend of higher water content in psychrophilic enzymes than in mesophilic enzymes. Nonetheless, ignoring such data pruning, the difference is significant using either the binomial test (p = 0.03) or the paired t-test (p < 0.01). Moreover, we may not be counting all cavity water molecules because of possible experimental errors or water in cavities being highly mobile (especially in nonpolar cavities) . Therefore, a more sensitive approach, e.g., MD simulations, should be considered to test the hypothesis that psychrophilic enzymes bind more water than their mesophilic counterparts.
In this study we explored a variety of structural bioinformatic metrics to seek a structural explanation for cold adaptation in enzymes. The most significant structural differences are an increase in the size of the water-sized cavities and a trend in amino acid composition towards carboxylic acids in these cavities. Through an additional consensus of measures, including a significant increase in crystallographic B-values in β-sheets and turns, and a marginally significant increase in the number of buried crystallographic waters, we can conclude that psychrophilic enzymes tend to be more solvated in the core as compared to mesophilic enzymes. In particular, the evidence that psychrophilic cavities are well characterized by a water-sized probe suggests that mutations that reshaped internal cavities to fit water may have led to more bound water, which in turn led to an increased flexibility in the core, consistent with water-protein literature.
Statistical metrics suffer from small data sets, crystallographic variability, and the fact that multiple mechanisms for cold adaptation exist. Nonetheless, our results point to a common hypothesis that can now be tested by protein design experiments (e.g., increasing the number of acidic residues that comprise cavities). Cavities are not necessarily the only element of a protein that endows psychrophilic proteins with cold adaptation, but structure-based differences in cavities may reveal themselves to be critical to cold adaptation and might help to design enzymes capable of functioning at low temperatures. Similar results may be obtained in other rigidifying environments, such as organic solvents, polymeric materials [37, 38], or protein-nanomaterial conjugate materials [39, 40].
The proteins used in this study were collected from the Protein Data Bank (PDB). The first set consisted of PDB structures of cold adapted enzymes proposed by Siddiqui et al.  as well as additional enzymes selected from the National Center of Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov). To be considered, each protein was required to have at least 150 amino acids and a crystal structure with resolution better than 2.5 Å. To obtain valid mesophilic-psychrophilic homolog pairs, a series of steps were followed. First, DaliLite  (comparison of 3D structures) was used to obtain a set of homologous mesophilic proteins valid for comparison to their psychrophilic counterparts, using a requirement of at least 30% sequence identity. Proteins with resolution poorer than 2.5 Å were discarded. The Pfam  was used to confirm that each pair was homologous. Lastly, the Prokaryotic Growth Temperature Database (PGTdb)  was used to classify proteins by the growth temperature of the organism (psychrophiles 0-20°C, mesophiles 20-45°C, and thermophiles 45-100°C). Note that all eukaryotic organisms were mesophilic, with few exceptions.
B'(psy)i is the normalized B-value of the psychrophile enzyme at the ith position in a pairwise sequence alignment. Larger ΔB'-values imply a higher level of flexibility. Therefore, ΔB'i > 0 indicates that the psychrophilic protein is more flexible at that amino acid position than its homologous mesophilic protein.
The Computed Atlas of Surface Topography of proteins (CASTp)  was used to test for the presence of cavities and the associated void volume. The program uses Delaunay triangulation and the alpha shapes algorithm to determine cavities and pockets. CASTp also outputs the set of amino acids surrounding each cavity/pocket, the cavity/pocket surface volume through solvent accessible surface calculation, and the number of exits from the pocket. A cavity is defined as a pocket with zero exits.
CASTp calculations were performed with the following probe radii: 0.6, 0.8, 1.0, 1.2, 1.4, 1.6 and 1.8 Å. In all cases, the goal was to identify cavities that were fully contained in the protein subunit and not at the interface between subunits. Crystallographic water molecules were ignored. For each protein pair the total number of cavities (Cav), total volume inside the cavities (using accessible surface) (Vol), and total volume in cavities divided by total number of cavities (Vol/Cav) were determined. A paired t-test was used to account for the correlation between the proteins pairs because they shared the same environment. The null hypothesis tested was that no differences were observed between the mean values of each population (psychrophilic and mesophilic proteins) with respect to the aforementioned measures.
Amino acid frequency
Amino acid frequencies were calculated for inward-facing side chains surrounding the cavities in psychrophilic proteins, and were compared to those in mesophilic proteins. The amino acids were classified into four types: 1) hydrophobic (Ala, Cys, Ile, Met, Pro, Val, Leu, Phe, Trp); 2) polar (Asn, Gln, Gly, Ser, Thr); 3) basic (Arg, His, Lys); and 4) acidic (Glu, Asp), for analysis. Probability distributions over the four amino acid types were summed separately for psychrophiles and homologous mesophiles over cavity wall position. A paired two-sample t-test was used to assess the differences between each psychrophilic and mesophilic distribution. The p-value obtained from the paired two samples test is considered statistically significant when p-value < 0.01
The number of buried crystallographically ordered waters was determined by iteratively removing all waters with non-zero solvent exposed surface area, as determined by MASKER  until no further waters could be removed. A paired two-sample t-test and a binomial test were used to assess the differences between each psychrophilic and mesophilic distribution. The p-value obtained from the paired two samples test is considered statistically significant when p-value < 0.01. Approximately 20-30% of all cavities are unoccupied by water in both mesophiles and psychrophiles. This information suggests that at worst, there is an undercounting of the number of waters in cavities in both the psychrophiles and their homologous mesophiles, which should not significantly affect the statistics.
These investigations were supported by grants from the National Institute Health No.: GM088838 (CB and JSD) and ES018022 (JSD). Furthermore, we wish to thank Dr. Joe Dundas for help in running batch mode CASTp software.
- D'Amico S, Collins T, Marx J, Feller G, Gerday C: Psychrophilic microorganisms: challenges for life. EMBO Rep 2006, 7: 385–389.PubMed CentralView ArticlePubMedGoogle Scholar
- Vogt G, Argos P: Protein thermal stability: hydrogen bonds or internal packing. J Mol Biol 1997, 269: 631–643.View ArticlePubMedGoogle Scholar
- Vijayabaskar MS, Vishveshwara S: Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks. BMC Bioinformatics 2010, 11(Suppl 1):S49.PubMed CentralView ArticlePubMedGoogle Scholar
- Chen J, Stites WE: Replacement of staphylococcal nuclease hydrophobic core residues with those from thermophilic homologues indicates packing is improved in some thermostable proteins. J Mol Biol 2004, 344: 271–280.View ArticlePubMedGoogle Scholar
- Cavicchioli R, Siddiqui KS, Andrews D, Sowers KR: Low-temperature extremophiles and their applications. Current Opinion in Biotechnology 2002, 13: 253–261.View ArticlePubMedGoogle Scholar
- Smalås AO, Leiros HK, Os V, Willassen NP: Cold adapted enzymes. Biotechnology Annu Rev 2000, 6: 57.Google Scholar
- Russell R, Gerike U, Danson M, Hough D, Taylor G: Structural adaptations of the cold-active citrate synthase from an Antarctic bacterium. Structure 1998, 6: 351–362.View ArticlePubMedGoogle Scholar
- Gerday C, Aittaleb M, Chessa JP, Feller G: Cold-adapted enzymes: from fundamentals to biotechnology. Trends in Biotechnology 2000, 18: 103–107.View ArticlePubMedGoogle Scholar
- Davail S, Feller G, Narinx E, Gerday C: Cold adaptation of proteins. J Biol Chem 1999, 269: 17448–17453.Google Scholar
- Aghajari N, Petegem F, Villeret V, Chessa JP, Gerday C, Haser R, Beeumen J: Crystal structures of a psychrophilic metalloprotease reveal new insights into catalysis by cold-adapted proteases. Proteins: Structure, Function, and Genetics 2002, 50: 636–647.View ArticleGoogle Scholar
- Gianese G, Bossa F, Pascarella S: Comparative structural analysis of psychrophiic and meso and thermophilic enzymes. Proteins 2002, 47: 236–249.View ArticlePubMedGoogle Scholar
- Siddiqui KS, Cavicchioli R: Cold-adapted enzymes. Annu Rev Biochem 2006, 75: 403–433.View ArticlePubMedGoogle Scholar
- Chiuri R, Maiorano G, Rizzello A, del Mercato LL, Cingolani R, Rinaldi R, Maffia M, Pompa PP: Exploring Local Flexibility/Rigidity in Psychrophilic and Mesophilic Carbonic anhydrases. Biophys J 2009, 96: 1586–1596.PubMed CentralView ArticlePubMedGoogle Scholar
- Alimenti C, Vallesi A, Pedrini B, Wuthrich K, Luporini P: Molecular cold-adaptation: Comparative analysis of two homologous families of psychrophilic and mesophilic signal proteins of the protozoan ciliate. Euplotes IUBMB Life 2009, 61: 838–845.View ArticlePubMedGoogle Scholar
- Georlette D, Blaise V, Collins T, Gerday C: Some like it cold: biocatalysis at low temperatures. FEMS Microbiology 2004, 28: 25–42.View ArticleGoogle Scholar
- Papaleo E, Riccardi L, Fantucci P, Villa C, De Gioia L: Flexibility and enzymatic cold-adaptation: a comparative molecular dynamics investigation of the elastase family. Biochimica Biophys Acta 2006, 1764: 1397–1406.View ArticleGoogle Scholar
- Lonhienne T, Gerday C, Feller G: Psychrophilic enzymes: revisiting the thermodynamic parmeters. Biochimica Biophys Acta 2000, 1543: 1–10.View ArticleGoogle Scholar
- Papaleo E, Pasi M, Riccardi L, Sambi I, Fantucci P, Gioia L: Protein flexibility in psychrophilic and mesophilic trypsins. Evidence of evolutionary conservation of protein dynamics in trypsin-like serine-proteases. FEBS Letters 2008, 582: 1008–1018.View ArticlePubMedGoogle Scholar
- Olufsen M, Smals A, Moe E, Brandsdal B: Increased flexibility as a strategy for cold adaptation a comparative molecular dynamics study of cold- and warm-active uracil dna glycosylase. J Biol Chem 2005, 280: 18042–18048.View ArticlePubMedGoogle Scholar
- Aghajari N, Feller G, Gerday C, Haser R: Structures of the psychrophilic Alteromonas haloplanctis [alpha]-amylase give insights into cold adaptation at a molecular level. Structure 1998, 6: 1503–1516.View ArticlePubMedGoogle Scholar
- Ohmura T, Ueda T, Ootsuka K, Saito M, Imoto T: Stabilization of hen egg white lysozyme by a cavity-filling mutation. Protein Science 2001, 10: 313–320.PubMed CentralView ArticlePubMedGoogle Scholar
- Tronelli D, Maugini E, Bossa F, Pascarella S: Structural adaptation to low temperatures-analysis of the subunit interface of oligomeric psychrophilic enzymes. FEBS Journal 2007, 274: 4595–4608.View ArticlePubMedGoogle Scholar
- Karplus PA, Schulz GE: Prediction of chain flexibility in proteins. Naturwissenschaften 1985, 72: 212–213.View ArticleGoogle Scholar
- Smith D, Radivojac P, Obradovic Z, Dunker K, Zhu G: Improved amino acid flexibility parameters. Protein Science 2003, 12: 1060–1072.PubMed CentralView ArticlePubMedGoogle Scholar
- Siglioccolo A, Gerace R, Pascarella S: "Cold spots" in protein cold adaptation: Insights from normalized atomic displacement parameters (B'-factors). Biophys Chem 2010, 153: 104–14.View ArticlePubMedGoogle Scholar
- Armstrong BD, Choi J, López C, Wesener DA, Hubbell W, Cavagnero S, Han S: Site-Specific Hydration Dynamics in the Nonpolar Core of a Molten Globule by Dynamic Nuclear Polarization of Water. J Am Chem Soc 2011, 133: 5987–5995.PubMed CentralView ArticlePubMedGoogle Scholar
- Damjanovic A, Garcıa-Moreno B, Lattman E, Garcıa A: Molecular Dynamics Study of Water Penetration in Staphylococcal Nuclease. Proteins 2005, 60: 433–449.View ArticlePubMedGoogle Scholar
- Fischer S, Verma C, Hubbard RE: Rotation of Structural Water inside a Protein: Calculation of the Rate and Vibrational Entropy of Activation. J Phys Chem B 1998, 102: 1797–1805.View ArticleGoogle Scholar
- Fischer S, Verma CS: Binding of buried structural water increases the flexibility of proteins. Proceedings of the National Academy of Sciences of the United States of America 1999, 96: 9613.PubMed CentralView ArticlePubMedGoogle Scholar
- Smith JC, Merzel F, Bondar A, Tournier A, Fischer S: Structure, dynamics and reactions of protein hydration water. Trans R Soc Lond B 2004, 359: 1181–1190.View ArticleGoogle Scholar
- Park S, Saven JG: Statistical and Molecular Dynamics Studies of Buried Waters in Globular Proteins. Proteins 2005, 60: 450–463.View ArticlePubMedGoogle Scholar
- Affleck R, Xu Z, Suzawa V, Focht K, Clark DS, Dordick JS: Enzymatic catalysis and dynamics in low-water environments. Proceedings of the National Academy of Sciences of the United States of America 1992, 89: 1100.PubMed CentralView ArticlePubMedGoogle Scholar
- Tarek M, Tobias DJ: The dynamics of protein hydration water: a quantitative comparison of molecular dynamics simulations and neutron-scattering experiments. Biophys J 2000, 79: 3244–3257.PubMed CentralView ArticlePubMedGoogle Scholar
- Rupley JA, Gratton E, Careri G: Water and globular proteins. Trends in Biochemical Sciences 1983, 8: 18–22.View ArticleGoogle Scholar
- García AE, Hummer G: Water penetration and escape in proteins. Proteins: Structure, Function, and Bioinformatics 2000, 38: 261–272.View ArticleGoogle Scholar
- Matthews BW, Liu L: A review about nothing: Are apolar cavities in proteins really empty? Protein Science 2009, 18: 494–502.PubMed CentralView ArticlePubMedGoogle Scholar
- Wang P, Sergeeva MV, Lim L, Dordick JS: Biocatalytic plastics as active and stable materials for biotransformations. Nature Biotechnology 1997, 15: 789–793.View ArticlePubMedGoogle Scholar
- Wang Q, Dordick JS, Linhardt RJ: Synthesis and application of carbohydrate-containing polymers. Chemistry of Materials 2002, 14: 3232–3244.View ArticleGoogle Scholar
- Asuri P, Karajanagi SS, Yang H, Yim TJ, Kane RS, Dordick JS: Increasing protein stability through control of the nanoscale environment. Langmuir 2006, 22: 5833–5836.View ArticlePubMedGoogle Scholar
- Shang W, Nuffer JH, Dordick JS, Siegel RW: Unfolding of ribonuclease A on silica nanoparticle surfaces. Nano Letters 2007, 7: 1991–1995.View ArticlePubMedGoogle Scholar
- Holm L, Kaariainen S, Rosenstrom P, Schenkel A: Searching protein structure databases with DaliLite v.3. Bioinformatics 2008, 24: 2780–2795.PubMed CentralView ArticlePubMedGoogle Scholar
- Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer EL, Bateman : The Pfam protein families database. Nucleic Acids Res 2008, 36: 281–288.View ArticleGoogle Scholar
- Huang L, Wu LC, Laing HK, Pan KT, Horng JT: PGTdb: a database providing growth temperatures of prokaryotes. Bioinformatics 2004, 20: 276–278.View ArticlePubMedGoogle Scholar
- Dundas J, Ouyang Z, Tseng J, Binkowski A, Turpaz Y, Liang J: Castp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated resiudes. Nucleic Acids Res 2006, 34: 116–118.View ArticleGoogle Scholar
- Bystroff C: MASKER: Improved solvent-excluded molecular surface area estimations using Boolean masks. Protein Engineering 2002, 15: 959.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.