1 Bioinformatics Centre and 3 Department of Biochemistry, Bose Institute,P-1/12 CIT Scheme VIIM, Calcutta 700 054, India
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Abstract |
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Keywords: accessible surface area/binding efficiency/hydrophobicity/packing of residues/residue partner number
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Introduction |
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Materials and methods |
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The solvent accessible surface area (ASA) was computed using the program ACCESS (Hubbard, 1992), which is an implementation of the Lee and Richards (1971) algorithm. The ASA for each residue (and its side chain) were calculated without considering the non-proteinous constituents of the PDB files. To represent the standard state, the ASA of residue X in both the tripeptides, GlyXGly and AlaXAla, was calculated, the models having being made in the extended conformation (
=
= 180°) using the program InsightII (Molecular Simulations, San Diego, CA). The relative accessibility of a residue is the ASA normalized by the standard ASA and in this work, for reasons discussed below, the Gly-based model tripeptide provided a more suitable standard. In addition to the observed value, an estimate of the relative accessibility was also obtained when the ASA of the residue was derived from the equation (discussed below) relating ASA to its partner number.
For a given residue, the average value of the ASA (and the standard deviation) at a given partner number were calculated. For all residues other than Gly the partners were defined for the side chain also and, consequently, there were 39 sets of data. When the average ASA values (y) were plotted against the partner numbers (x), the points could be fitted into an exponential equation of the form y = a1exp(x/a2). When the plot was extrapolated to x = 0, the value obtained was closer to that obtained for the residue in the tripeptide GlyXGly, which was thus taken as the standard state (A0) (the expected value when the protein is in the unfolded state with the minimum contact with the rest of the molecule). However, in general for the whole residue, the calculated value (at x = 0) was about 20% greater than A0 and hence it was decided to fix a1 at the value of the standard state and fit only the parameter a2 against the observed data. Though the quality of fit was slightly worse (judged from the R2 value), this set of parameters was used for further calculations as they gave the expected value of A0.
To find the optimum value of the cut-off distance, the following calculations were performed at different values (4.0, 4.5, 5.0, 6.0 and 7.0 Å). (i) The average partner numbers for all residue types (whole) in the database were determined. (ii) For each residue the average accessible surface area <ASA> at each partner number was found. Then an exponential fitting was performed to relate <ASA> to the whole range of partner numbers. Hence for each cut-off distance we had a set of 20 equations for all residue types. (iii) For a given PDB file, we took each residue in turn, calculated its partner number in the structure and from the equations (found above) calculated its ASA. We did this for all the residues in the file and summed to obtain the total calculated ASA for the molecule. This was compared with the observed ASA (obtained using ACCESS) to give the parameter RA = ASA(calc)/ASA(obs). (iv) RA values were computed for all the PDB chains (139 in total) (for which not more than 5% of the residues were rejected based on the selection criteria enumerated at the beginning) and their average, <RA>, was found. The cut-off distance giving a value (0.93) closest to 1 was 4.5 Å.
A similar experiment was carried out to decide if the bonded atoms were to be included in the calculation of partner numbers. The calculations were repeated (only at the cut-off distance of 4.5 Å) by considering even the backbone atoms of the neighbouring residues as partners. When these partner numbers were fitted to ASA, the R2 value of fitting was considerably poorer than that obtained when these atoms were excluded when calculating partner numbers. Also, when this set of equations was used, <RA> was 1.3 (±2), which differed by a greater amount from the ideal value of 1.
The codes for the PDB files used are given in the Appendix.
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Results and discussion |
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The local environment of a residue can be characterized by the number of atoms in contact with it, within a distance of 4.5 Å (the reason behind the use of this limit is elaborated in a separate section).
The distributions of the numbers of atoms surrounding each residue and just the side chain are presented in Figure 1, where the residues are ordered according to increasing volume as given by Chothia (Chothia, 1975
). The largest residue, Trp, has the highest average number (38) of contacts and the smallest, Gly, the least (19). For all non-Gly residues, the difference in numbers for the whole residue and the side chain (i.e. the number due to the main-chain atoms) is
13. Pro, with a pyrrolidine ring encompassing both the side chain and the main chain, has a smaller number of partners than suggested by its size; Pro and Gly have similar values. Pro residues are generally restricted to loop regions which are more frequently on the surface of a protein, thus leading to a lower than expected atom neighbour count. Of the three hydrophobic residues having nearly identical volumes, Leu, Ile and Met, the last residue has a slightly higher number of contacts, possibly indicating a greater inclination of the Met S, as compared with an aliphatic carbon atom, to interact with other groups (Pal and Chakrabarti, 2001
). Between two residues, Met and Lys, which are also of comparable volume, the latter has a smaller number of contacts, indicating that a hydrophilic residue has a smaller number of protein atoms around it than a hydrophobic residue of equal size. However, although more hydrophilic than Leu and Ile, which follow it, His has about the same number of contacts. This, together with the large values observed for Phe and Tyr, may suggest that the aromatic residues are better packed than the aliphatic residues.
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The number of partner atoms delineated here is similar to the number of ligand atoms in the first coordination sphere of a metal ion in inorganic chemistry. Starting with Nishikawa and Ooi (Nishikawa and Ooi, 1980), many workers have analysed spatial neighbours in terms of contact numbers (Panjikar et al., 1997
; Karlin et al., 1999
; Zhang and Kim, 2000
). These have also been used in deriving potentials of mean force for interactions among residues, for application in threading sequences into the correct fold (Miyazawa and Jernigan, 1996
; Bahar and Jernigan, 1997
). Correlation coefficients between mean partner numbers and some of these earlier publications are given in Table I
. As could be expected, the two sets of values calculated by us are highly correlated between themselves, as well as with the values of Karlin et al. (Karlin et al., 1999
), who also considered all surrounding atoms around a residue, but at a slightly longer distance of 5 Å. The correlation is rather poor (and inverse) with the values of Bahar and Jernigan (Bahar and Jernigan, 1997
) and Zhang and Kim (Zhang and Kim, 2000
), who employed a low-resolution model in which a residue is represented by a single interaction site located at the C
position. Irrespective of the type of residue, on average about six non-bonded residues are found within a sphere of radius 6.5 Å centred on it and, as such, these values are less discriminating. An all-atom model, on the other hand, using a cut-off length larger than the van der Waals contact distance, provides coordination numbers which reflect the nature of the residue in a much more realistic manner.
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The mean values of the accessible surface areas (ASAs) of the residues (considering either the whole residue or only the side chain) at different values of the partner number are plotted for two representative residues in Figure 2. It is seen that the standard deviations of the mean values decrease with increasing number of partners and the variation of ASA can be adequately represented by an exponential form (Table II
). In the majority of cases, extrapolation to x = 0 (i.e. no partner) leads to a value which is close to the value for the residue (X) obtained in the fragment GlyXGly in an extended conformation. As a result, the ASA value of the residue flanked by Gly residues (and not Ala) on either side can be taken as the standard state (A0) for the residue. This is also justified by the fact that in our methodology the side-chain atoms (starting at Cß) of the flanking residues are legitimate contenders to be counted as partners for the central residue X.
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Estimates of average relative accessibilities of residues
Using the equation relating ASA and partner number, it is possible to calculate the ASA (<A>calc) corresponding to the average number of partners for the whole residue and the side chain. These estimates of average ASA compare very well with the means of the observed values (<A>obs) obtained using the standard algorithm of Lee and Richards (Lee and Richards, 1971) (Table III
); the hydrophobic residues show better agreement than the hydrophilic residues and the whole residue compared with the side chain. On dividing <A>calc by the standard value (taken as the ASA of the residue X in the peptide GlyXGly, as discussed earlier) one obtains an estimate of the average relative accessibility for the residue in a protein structure. Comparison of the values for the whole residue with those for the side chain reveals an interesting feature. For polar residues the side chain shows higher accessibility than the whole residue (with Lys being the most prominent). This is along the expected line, as for these residues the more hydrophilic part is in the side chain, which is thus more exposed than the rest of the residue. For hydrophobic residues the values are nearly identical, with the side chain in some cases having a slightly lower value than that for the corresponding residue taken as the whole. (However, this trend becomes much clearer if one does a similar calculation with a smaller cut-off distance of 4.0 Å; data not shown.)
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Reduction of surface area on folding and correlation with hydrophobicity
The accessible area of a fully extended polypeptide chain is reduced by a factor of about three on folding into the native structure (Chothia, 1975). Considering individual residues (Table III
), it is found that in general the estimates of the relative accessibilities of hydrophilic residues are
30 (Lys being the most exposed), whereas for hydrophobic residues the values are in the range 1020. This clear demarcation between the two types of residues led us to examine whether there is any relationship between relative accessibility and a few hydrophobicity scales taken from the literature (Cornette et al., 1987
). Indeed, it was found that there is an inverse correlation (Table IV
). Thus the fraction of a residue that is buried on folding is directly proportional to its hydrophobicity. Of the hydrophobicity scales that were tried, the match is poor for the one due to Wolfenden et al. (Wolfenden et al., 1981
), which measures the distribution of amino acid side chains between dilute aqueous solutions and the vapour phase. However, the correlation improves on the exclusion of Gly, Ala and Arg. The other experimental scale of Fauchère and Pliska (Fauchère and Pliska, 1983
) using octanolwater distribution measurements is in excellent agreement (Figure 3
), as also is the statistical scale of Miller et al. (Miller et al., 1987
) based on the distribution of residues between the surface and interior of proteins; the match with the latter scale shows further improvement on exclusion of Arg and Gly, two residues almost from the two ends of the size spectrum.
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Two factors went into consideration in the choice of the cut-off distance. First, we wanted to include those atoms which have van der Waals and other specific non-covalent interactions with a given residue. For delineating hydrogen bonds a distance of <3.9 Å is generally used (McDonald and Thornton, 1994) and weak interactions (such as the CH···O hydrogen bond) are known to extend to about 4.0 Å (Desiraju, 1996
). When the closest contact distance between any two atoms of a pair of aromatic rings is within 4.5 Å, there is a binding interaction between the rings (McGaughey et al., 1998
). As such, a limiting distance of 4.5 Å was deemed to be reasonable. On the other hand, as we were attempting to correlate the partner number with the accessible surface area and the latter can be affected owing to the screening of solvent by other atoms not in immediate contact (i.e., at a longer distance), we tried a number of distances (4.0, 4.5, 5.0, 6.0 and 7.0 Å). As discussed in Materials and methods, the optimum value was selected by finding out the partner numbers (at different limiting ranges) of all the residues in a polypeptide chain and then converting these to the corresponding ASA values (using the appropriate exponential equations); the distance which provided the best match (the perfect match would give a value of 1) of the calculated ASA of the molecule to its observed ASA was found to be 4.5 Å (Table V
). An <RA> of 0.93 suggests that we have an alternative procedure to compute the ASA of a protein molecule that is within 7% the true value.
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Implications and summary |
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The average (or expected, based on the equation derived here) ASA of a residue corresponding to a given number of partners provides a means to assess the efficiency of packing of a residue. If the observed ASA is more than the expected value, it suggests that the partners have been less efficient in covering the surface of the residue, whereas a smaller observed value indicates a tighter packing by the surrounding atoms. It is conceivable that the number of partners will depend on, in addition to the size and type of the residue, the location in the tertiary fold and as the ASA depends on this number it is likely that not all residues can be packed equally well in a given location. Hence the residue-specific exponential relationship between the partner number and ASA may offer a new algorithm for a threading procedure (to identify the possible fold for a given sequence) that is conceptually different from other methods of protein-fold recognition (Torda, 1997) and we are working on its development. Quantifying the steric fit of a ligand to a macromolecule is equivalent to quantifying the internal packing in protein and the aforementioned equations can be used to assess the importance of different residues in the binding site of a ligand, as has been attempted in the case of Trp (Samanta and Chakrabarti, 2001
). Finally, we have developed a procedure for estimating the ASA of a protein chain, which is within 7% of the value obtained using the protocol of Lee and Richards (Lee and Richards 1971
) (Table V
).
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Appendix |
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The subunit identifier, if present, is given as the fifth letter.
1A1IA, 1A1YI, 1A28B, 1A2PA, 1A2ZA, 1A34A, 1A3C_, 1A48_, 1A4IB, 1A6M_, 1A7S_, 1A8D_, 1A8E_, 1A9XB, 1ABA_, 1ADOA, 1ADS_, 1AE9B, 1AFWA, 1AGQA, 1AHO_, 1AIE_, 1ALVA, 1AMF_, 1AMM_, 1AMX_, 1AOCA, 1AOHB, 1APYA, 1AQB_, 1ARV_, 1ATLA, 1AUN_, 1AVWB, 1AXN_, 1AY7B, 1AYFA, 1AYL_, 1AYOA, 1AZO_, 1B0NA, 1B0NB, 1B0UA, 1B0YA, 1B16A, 1B2VA, 1B3AA, 1B4KB, 1B5EA, 1B65A, 1B67A, 1B6A_, 1B6G_, 1B7CA, 1B8OA, 1B93A, 1BA8A, 1BABB, 1BBHA, 1BBPA, 1BDO_, 1BE9A, 1BEA_, 1BEC_, 1BENB, 1BF6A, 1BFG_, 1BFTA, 1BG6_, 1BGF_, 1BI5A, 1BJ7_, 1BK0_, 1BK7A, 1BKRA, 1BQCA, 1BRT_, 1BS4A, 1BS9_, 1BSMA, 1BTN_, 1BU7A, 1BX4A, 1BX7_, 1BXAA, 1BXOA, 1BY2_, 1BYI_, 1BYQA, 1BYRA, 1C24A, 1C2AA, 1C3D_, 1C3MA, 1C3WA, 1C52_, 1CBN_, 1CC8A, 1CCZA, 1CEQA, 1CEWI, 1CEX_, 1CF9A, 1CFB_, 1CG6A, 1CKAA, 1CLEA, 1CMBA, 1CNV_, 1COZA, 1CPO_, 1CPQ_, 1CQYA, 1CS1A, 1CTJ_, 1CTQA, 1CV8_, 1CVL_, 1CXQA, 1CXYA, 1CY5A, 1CYDA, 1CYO_, 1CZFA, 1CZPA, 1D3VA, 1D7PM, 1D9CB, 1DBWB, 1DCIA, 1DCS_, 1DF4A, 1DFNA, 1DG9A, 1DGWY, 1DHN_, 1DI6A, 1DIN_, 1DLFH, 1DLFL, 1DOKA, 1DOSA, 1DOZA, 1DPSD, 1DPTA, 1DUN_, 1DXGA, 1ECD_, 1ECPA, 1EDG_, 1EDMB, 1EGPA, 1EUS_, 1EXTB, 1EZM_, 1FCE_, 1FIPA, 1FIT_, 1FLEI, 1FLTV, 1FLTY, 1FNA_, 1FRPA, 1FUS_, 1FVKA, 1G3P_, 1GCI_, 1GDOB, 1GOF_, 1GP1A, 1GPEA, 1GSA_, 1GUQA, 1HFC_, 1HFES, 1HKA_, 1HLEB, 1HOE_, 1HTRP, 1HUUA, 1HXN_, 1IAB_, 1ICFI, 1IDAA, 1IFC_, 1IIBA, 1ISUA, 1IXH_, 1JDW_, 1JER_, 1JHGA, 1KNB_, 1KOE_, 1KP6A, 1KPTA, 1KVEA, 1KVEB, 1LAM_, 1LATA, 1LBU_, 1LCL_, 1LKFA, 1LKKA, 1LOUA, 1LTSA, 1LTSC, 1LUCA, 1MAI_, 1MDC_, 1MFMA, 1MGTA, 1MKAA, 1MLA_, 1MML_, 1MOF_, 1MOLA, 1MOQ_, 1MPGA, 1MRJ_, 1MROA, 1MROB, 1MROC, 1MSI_, 1MSK_, 1MTYB, 1MTYG, 1MUGA, 1MUN_, 1NAR_, 1NBCA, 1NCOA, 1NIF_, 1NKD_, 1NKR_, 1NLS_, 1NOX_, 1NP4A, 1NPK_, 1NULB, 1OAA_, 1OBWA, 1OPD_, 1OPY_, 1ORC_, 1OTFA, 1PBE_, 1PCFA, 1PDO_, 1PGS_, 1PHF_, 1PLC_, 1PNE_, 1POA_, 1POC_, 1PPN_, 1PSRA, 1PTQ_, 1PTY_, 1PYMB, 1QB7A, 1QCXA, 1QCZA, 1QD1A, 1QDDA, 1QFMA, 1QFOA, 1QGIA, 1QGWB, 1QGWD, 1QH4A, 1QH5A, 1QH8A, 1QH8B, 1QHFA, 1QJ4A, 1QJ8A, 1QKSA, 1QMPD, 1QQ4A, 1QQ5A, 1QQP1, 1QQP2, 1QQP4, 1QREA, 1QRRA, 1QSGA, 1QTSA, 1QTWA, 1QU9A, 1RB9_, 1RCF_, 1REC_, 1REGY, 1RGEA, 1RHS_, 1RIE_, 1RZL_, 1SCJB, 1SFP_, 1SGPI, 1SLUA, 1SMD_, 1SMLA, 1SRA_, 1SUR_, 1SVFA, 1SVFB, 1SVPA, 1SVY_, 1SWUB, 1TAFA, 1TAXA, 1TC1A, 1TEN_, 1TGXA, 1TIB_, 1TIF_, 1TL2A, 1TML_, 1TOAA, 1TTBA, 1TVXB, 1U9AA, 1UBPA, 1UBPB, 1UNKA, 1UOX_, 1VCAA, 1VFRA, 1VFYA, 1VHH_, 1VID_, 1VIE_, 1VLS_, 1VNS_, 1VSRA, 1WAB_, 1WAPB, 1WDCA, 1WHI_, 1WHO_, 1WWCA, 1XNB_, 1YACA, 1YAGG, 1YCC_, 1YGE_, 1YTBA, 2A0B_, 2ABK_, 2ACY_, 2AHJC, 2ARCB, 2AYH_, 2BC2A, 2BOPA, 2BOSA, 2CBP_, 2CCYA, 2CHSA, 2CPGA, 2CTC_, 2DRI_, 2DTR_, 2EBN_, 2EBOA, 2END_, 2ERL_, 2FDN_, 2GAR_, 2GDM_, 2HBG_, 2HDDB, 2HFT_, 2HMZA, 2IGD_, 2ILK_, 2KNT_, 2LISA, 2MSBB, 2MYR_, 2NLRA, 2PII_, 2PSPA, 2PTH_, 2PVBA, 2QWC_, 2RN2_, 2SAK_, 2SICI, 2SN3_, 2SNS_, 2SPCA, 2TNFA, 2TPSA, 2TRXA, 2TYSB, 2UBPC, 3CHBD, 3CHY_, 3CLA_, 3CYR_, 3ENG_, 3EZMA, 3GRS_, 3LZT_, 3PTE_, 3PVIA, 3PYP_, 3SDHA, 3SEB_, 3SIL_, 3STDA, 3TDT_, 3TSS_, 3VUB_, 4EUGA, 4MT2_, 5HPGA, 5PTI_, 6CEL_, 6GSVA, 7A3HA, 7RSA_, 8ABP_, 8PRKA, 9WGAA, 16PK_, 19HCA, 153L_, 256BA, 451C_.
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Note added in proof |
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FAUPL KYTDO MILLER PONNU WOLF EISEN
(w) 0.61 0.79 0.76 0.61 0.84 0.77
(sc) 0.40 0.75 0.71 0.50 0.81 0.63
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Notes |
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4 To whom correspondence should be addressed. E-mail: pinak{at}boseinst.ernet.in
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Acknowledgments |
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References |
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Bahar,I. and Jernigan,R.L. (1997) J. Mol. Biol., 266, 195214.[CrossRef][ISI][Medline]
Berman,H.M., Westbrook,J., Feng,Z., Gilliland,G., Bhat,T.N., Weissig,H., Shindyalov,I.N. and Bourne,P.E. (2000) Nucleic Acids Res., 28, 235242.
Betz,S.F., Raleigh,D.P. and Degrado,W.F. (1993) Curr. Opin. Struct. Biol., 3, 601610.[CrossRef][ISI]
Chothia,C. (1974) Nature, 248, 338339.[ISI][Medline]
Chothia,C. (1975) Nature, 254, 304308.[ISI][Medline]
Cornette,J.L., Cease,K.B., Margalit,H., Spouge,J.L., Berzsofsky,J.A. and DeLisi,C. (1987) J. Mol. Biol., 195, 659685.[ISI][Medline]
Desiraju,G.R. (1996) Acc. Chem. Res., 29, 441449.[CrossRef][ISI]
Dill,K.A. (1990) Biochemistry, 29, 71337155.[ISI][Medline]
Eisenberg,D., Weiss,R.M., Terwilliger,T.C. and Wilcox,W. (1982) Faraday Symp. Chem. Soc., 17, 109120.
Fauchère,J. and Pliska,V. (1983) Eur. J. Med. Chem., 18, 369375.[ISI]
Finney,J.L. (1975). J. Mol. Biol., 96, 721732.[ISI][Medline]
Hobohm,U. and Sander,C. (1994) Protein Sci., 3, 522524.
Hubbard,S. (1992) ACCESS: a Program for Calculating Accessibilities. Department of Biochemistry and Molecular Biology, University College London, London.
Karlin,S., Zhu,Z.-Y. and Baud,F. (1999) Proc. Natl Acad. Sci. USA, 96, 1250012505.
Kauzmann,W. (1959) Adv. Protein Chem., 14, 163.[ISI]
Kyte,J. and Doolittle,R.F. (1982) J. Mol. Biol., 157, 105132.[ISI][Medline]
Lee,B. and Richards,F.M. (1971) J. Mol. Biol., 55, 379400.[ISI][Medline]
McDonald,I.K. and Thornton,J.M. (1994) J. Mol. Biol., 238, 777793.[CrossRef][ISI][Medline]
McGaughey,G.B., Gagne,M. and Rappe,A.K. (1998) J. Biol. Chem., 273, 1545815463.
Miller,S., Janin J., Lesk,A.M. and Chothia,C. (1987) J. Mol. Biol., 196, 641656.[ISI][Medline]
Miyazawa,S. and Jernigan,R.L. (1996) J. Mol. Biol., 256, 623644.[CrossRef][ISI][Medline]
Nishikawa,K. and Ooi,T. (1980) Int. J. Pept. Protein Res., 16, 1932.[ISI][Medline]
Pal,D. and Chakrabarti,P. (2001) J. Biomol. Struct. Dyn. 19, 115128.[ISI][Medline]
Panjikar,S.K., Biswas,M. and Vishveshwara,S. (1997) Acta Crystallogr., D53, 627637.
Ponnuswamy,P.K., Prabhakaran,M. and Manavalan,P. (1980) Biochim. Biophys. Acta, 623, 301316.[ISI][Medline]
Richards,F.M. (1974) J. Mol. Biol., 82, 114.[ISI][Medline]
Richards,F.M. (1977) Annu. Rev. Biophys. Bioeng., 6, 151176.[CrossRef][ISI][Medline]
Rose,G.D., Geselowitz,A.R., Lesser,G.J., Lee,R.H. and Zehfus,M.H. (1985) Science, 229, 834838.[ISI][Medline]
Samanta,U. and Chakrabarti,P. (2001) Protein Eng., 14, 715.
Samanta,U., Pal,D. and Chakrabarti,P. (2000) Proteins: Struct. Funct. Genet., 38, 288300.[CrossRef][ISI][Medline]
Torda,A.E. (1997) Curr. Opin. Struct. Biol., 7, 200205.[CrossRef][ISI][Medline]
Sharp,K.A., Nicholls,A., Friedman,R. and Honig,B. (1991) Biochemistry, 30, 96869697.[ISI][Medline]
Wolfenden,R., Andersson,L., Cullis,P.M. and Southgate,C.C.B. (1981) Biochemistry, 20, 849855.[ISI][Medline]
Word,J.M., Lovell,S.C., LaBean,T.H., Taylor,H.C., Zalis,M.E., Presley,B.K., Richardson,J.S. and Richardson,D.C. (1999) J. Mol. Biol., 285, 17111733.[CrossRef][ISI][Medline]
Zhang,C. and Kim,S.-H. (2000) Proc. Natl Acad. Sci. USA, 97, 25502555.
Received May 22, 2001; revised April 26, 2002; accepted May 21, 2002.