A fast method for predicting amino acid mutations that lead to unfolding

J.D. Wright1 and C. Lim1,2,3

1 Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan and 2 Department of Chemistry, National Tsing-Hua University, Hsinchu 300, Taiwan


    Abstract
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 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
Amino acid mutation(s) that cause(s) partial or total unfolding of a protein can lead to disease states and failure to produce mutants. It is therefore very useful to be able to predict which mutations can retain the conformation of a wild-type protein and which mutations will lead to local or global unfolding of the protein. We have developed a fast and reasonably accurate method based on a backbone-dependent side-chain rotamer library to predict the (folded or unfolded) conformation of a protein upon mutation. This method has been tested on proteins whose wild-type 3D structures are known and whose mutant conformations have been experimentally characterized to be folded or unfolded. Furthermore, for the cases studied here, the predicted partially folded or denatured mutant conformation correlate with a decrease in the stability of the mutant relative to the wild-type protein. The key advantage of our method is that it is very fast and predicts locally or globally unfolded states fairly accurately. Hence, it may prove to be useful in designing site-directed mutagenesis, X-ray crystallography and drug design experiments as well as in free energy simulations by helping to ascertain whether a mutation will alter or retain the wild-type conformation.

Keywords: conformational change/drug design/mutagenesis/protein folding/rotamers


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
Proteins can be denatured under various conditions. These include the use of denaturants, heat, pH, as well as single or multiple amino acid mutations (Arcus et al., 1995Go). Amino acid mutation(s) that cause(s) partial or total unfolding of a protein lead to significant consequences. Such events result in failure to produce mutant proteins, wasting lots of time and money (Gromiha et al., 1999Go). Furthermore, they can also lead to disease states; e.g. single amino acid mutations and subsequent inactivation of the tumor suppressor p53 protein is believed to occur in ~60% of human cancers and up to 80% of colon cancers (see below). A point mutation that causes a significant change in the backbone conformation of a protein prevents X-ray crystallographers from using molecular replacement techniques to solve the mutant structure based on the known wild-type structure. Such point mutations can also create problems in pattern recognition (Bairoch, 1991Go; Orengo et al., 1993Go; Hofmann et al., 1999Go) and in free energy simulations (Kollman, 1993Go). It is therefore very useful to be able to predict which mutations can retain the conformation of a wild-type protein and which mutations will cause local or global unfolding.

This paper reports a fast and reliable method for predicting which mutations inside a protein will induce a significant conformational change, based on modeling mutations using a backbone-dependent side-chain rotamer library (Dunbrack and Karplus, 1993Go). The concept of rotamer libraries is based on the observation that side-chain dihedral angles tend to cluster around particular values (Ponder and Richards, 1987Go). Since a side-chain can be rotated around the dihedral to fit each position these were termed rotamers. Furthermore, since the backbone {phi} and {Psi} dihedral angles were found to be strongly correlated with the side-chain dihedral angles (Figure 1Go), a backbone-dependent rotamer library for amino acid side chains, which gives the preferred rotamer for certain {phi},{Psi} combinations of each residue type, was developed (Dunbrack and Karplus, 1993Go, 1994Go; Dunbrack and Cohen, 1997Go). Examples of the backbone-dependent rotamer libraries for isoleucine and proline are illustrated in Figure 2Go. In modeling a point mutation, the most probable rotamer from a backbone-dependent rotamer library is used to initially place the side-chain of a mutant given the backbone of the wild-type protein. Any steric clash is then resolved by systematic searches of rotamers in an order defined by the rotamer library and a modified van der Waals (VDW) interaction energy (see Materials and methods). Finally, the total energy of the mutant protein is evaluated using an empirical energy function with a united-atom forcefield.



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Fig. 1. Diagram showing the backbone {phi} and {Psi} angles (a) and side-chain {chi}1 and {chi}2 angles for isoleucine (b) and proline (c).

 


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Fig. 2. Backbone-dependent rotamer library for isoleucine (top) and proline (bottom). In the {phi}{Psi} plot, the various numbers denote the {chi}1 and {chi}2 ranges for each defined rotamer of the amino acid side-chains. For example, in the case of proline, 1 denotes a rotamer with {chi}1 from 0 to 60° and {chi}2 from -60 to 0°, while 3 denotes a rotamer with {chi}1 from -60 to 0°and {chi}2 from 0 to 60°.

 
Our approach is based on the hypothesis that if a mutated side-chain cannot be placed using a backbone-dependent rotamer library to give an energy comparable to the wild-type protein, then the backbone conformation of the mutant is likely to deviate substantially from that of the wild-type. The results are interpreted to yield either a folded state or an unfolded state that includes partially folded and fully denatured structures. Only single point mutations are considered in this study. Furthermore, mutations to alanine or glycine have been excluded since the energy potential used in the rotamer search is a simple steric clash check (see Materials and methods). Both alanine and glycine have small side-chains that would be expected to be placed in nearly all cases and in fact have been excluded in the rotamer libraries.

First, our approach was calibrated on proteins whose wild-type as well as single-point mutant three-dimensional (3D) structures have been solved. Then it was tested on the tumor suppressor protein p53, where the wild-type 3D structure, but not the mutant one, is known. However, the mutant conformation has been inferred from interactions with monoclonal antibodies and changes in 1H and 15N chemical shifts (see below). Although there are over 7500 reports of known p53 mutations, only ~10% are unique, and out of these, only 33 mutations at 13 sites in p53 have been characterized experimentally to result in either a folded or unfolded conformation (Ory et al., 1994Go; Rolley et al., 1995Go; Brandt-Rauf et al., 1996Go; Wong et al., 1999Go). These mutations involve six of the most frequently mutated residues in cancer; Arg-175, Gly-245, Arg-248, Arg-249, Arg-273 and Arg-282 (Cho et al., 1994Go).

While many mutations have been carried out for other proteins such as barnase and chymotrypsin inhibitor, the mutations were mostly to glycine or alanine, which are not amenable to our approach. Furthermore, in many cases the effects of the single site mutation on the protein conformation have not been characterized. However, the effects of point mutations on the stability of some proteins are known; i.e. the difference in the denaturation free energies between wild-type and mutant proteins in the absence of denaturants, {Delta}{Delta}Gf->u = {Delta}Gf->umut{Delta}Gf->uwt, has been determined. To evaluate the extent to which the predicted conformation (folded or unfolded) can be correlated with protein stability, the effects of mutation on the conformation for some commonly mutated proteins, p53 (Bullock et al., 2000Go), staphylococcal nuclease (Green and Shortle, 1993Go) and the src SH3 domain (Riddle et al., 1999Go), were obtained. The expectation is that if the mutant conformation is predicted to be partially or totally denatured, then the mutant protein would likely be less stable than the wild-type one.

The results show that in the case of p53, our method can predict with ~79% accuracy which amino acid mutations will lead to local or global protein unfolding and which ones will retain the wild-type conformation. Furthermore, for the cases studied here, all mutants whose conformation was predicted to be partially or totally denatured were indeed found to be less stable than the wild-type protein.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
Proteins studied

The Protein Databank (PDB) (Abola et al., 1997Go; Sussman et al., 1998Go) was searched for proteins whose wild-type and mutant 3D structures have been solved. This search provided 94 single-point mutations from 47 different proteins. The backbone atoms of each mutant structure were fitted to those of the respective wild-type structure using the Swiss PDB-viewer (Guex and Peitsch, 1997Go) to check if the conformation of the mutant is similar to that of the wild type. The PDB identification codes for the wild-type protein are listed in Table IGo. The crystal structures of the p53 core domain/DNA complex (PDB entry 1TSR), staphylococcal nuclease (PDB entry 1STG) and the SH3 domain (PDB entry 1fmk), which were solved at a resolution of 2.2, 1.7 and 1.5 Å, respectively, were obtained from the PDB archive. In the case of p53, the 1TSR structure contains three core domain molecules and one DNA duplex. The p53 molecule that binds a consensus DNA binding site was employed in this study.


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Table I. Results from mutations for which both the wild-type and mutant protein 3D structures have been solved
 
Solvent-accessible-surface-area (SASA) calculations

SASA calculations were performed on the wild-type crystal structures using the MolMol program (Koradi et al., 1996Go) and a solvent probe radius of 1.4 Å. The percentage residue accessibility is defined as the percentage ratio of the water-accessible surface area of the side-chain X in the protein to the accessible surface area of X in the tripeptide –Gly–X–Gly–.

Mutation calculations

Single-site mutations were modeled with a locally modified version of the SCWRL (Bower et al., 1997Go) program using a backbone-dependent side-chain rotamer library. The program identifies the most common side-chain {chi}1 and {chi}2 angles for the mutant residue corresponding to the backbone {phi} and {Psi} angles of the wild-type protein at that position. Once the {chi} angles have been identified, the side-chain without hydrogen atoms is built using bond lengths and angles from the Amber forcefield (Cornell et al., 1995Go). Subsequently, the side chain is checked for steric clashes against the backbone using a simple distance-dependent potential, which approximates the VDW potential:

(1)
In Equation (1)Go, R is the distance between the atoms and R0 is the sum of the atomic radii, which have been reduced by ~15% from their VDW radii. If there are unfavorable interactions with the backbone the rotamer is rejected and the next most common rotamer is used. This is repeated until there are no clashes or no more rotamers left. The built rotamer is then checked for side-chain to side-chain interactions using the same modified VDW potential (Equation 1Go). If there are side-chain to side-chain clashes then the rotamers corresponding to the cluster of interacting residues are searched. The first combination of rotamers with no steric clashes or the combination with the lowest steric clash score is taken as the final solution. Since there may already be some close contacts in the crystal structure an initial calculation was performed on the wild-type protein to obtain a background steric energy.


    Energy calculations
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 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
Since the energy term in Equation (1)Go is based on a modified VDW potential, the total energy of the protein was also computed using the united Amber forcefield (Weiner et al., 1984Go, 1986Go) using a distance-dependent dielectric constant. The full interaction energies of the wild-type (Ewt) and mutant (Emut) proteins were calculated using Sybyl version 6.3 (Tripos, 1996Go). The relative strain, S, in the mutant protein was computed as:

(2)
where Nwt and Nmut are the number of atoms in the wild-type and mutant proteins, respectively. Note that as Nwt and Nmut for the proteins studied here are large (>500), while their difference is small (<10), Equation (2)Go is nearly equal to the ratio between the mutant and wild-type energies relative to one; i.e. (Emut /Ewt) - 1.


    Results
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 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
For each wild-type protein, the background steric energy, ESCWRLwt, and the total energy, EAMBERwt, were computed (see Materials and methods). The mutant side-chain was then placed using a backbone-dependent side-chain rotamer library, which yields four possible outcomes. First, the most common rotamer for the mutant residue corresponding to the backbone {phi} and {Psi} angles of the wild-type residue resulted in no steric clashes or minor clashes; hence, the initial rotamer was placed. Second, the initial rotamer of the mutant side-chain clashed with the backbone, so other rotamers of the mutant side-chain were tested and the most common one that did not clash with the backbone was placed. Both of these results are indicated by a score of <=10 units relative to the background steric energy; i.e. ESCWRLmut - ESCWRLwt = {Delta}ESCWRL <=10. Third, all rotamers of the mutant side-chain clashed with the backbone. Fourth, the placement of the mutant rotamer clashed with other side chains and the local conformational space had to be searched. Therefore, to place the mutant, other side-chains have to adopt non-native rotamers to make space for it.

The results for wild-type and mutant proteins of known 3D structures as well as for p53, staphylococcal nuclease, and the src SH3 domain are presented in Tables I to IIIGoGo. The tables give the percentage SASA for the wild-type residue. A residue is considered to be buried if its SASA is <20%, partially buried if its SASA is between 20 and 50%, and solvent exposed if its SASA is >50% (Gromiha et al., 1999Go). The tables indicate if the mutant side-chain clashed with the backbone (denoted by BB) or with other side-chains (denoted by SC) resulting in non-native rotamers for the other side-chain(s). They also give the steric energy difference between the mutant and wild-type protein from Equation (1)Go ({Delta}ESCWRL = ESCWRLmut - ESCWRLwt) as well as the strain in the mutant protein relative to the wild-type from Equation (2)Go (S = Emut/Ewt - 1; see Materials and methods). The results are interpreted so that the mutant protein is considered to retain the wild-type fold (denoted by F) if S is <0.10, but to result in local or global unfolding of the wild-type structure (denoted by U) if S is >=0.10. Since S is close to the ratio between the mutant and wild-type energies relative to one, i.e. (EmutEwt)/Ewt, a value of S >= 0.10 indicates a `hot-spot' with an energy (EmutEwt) that is >10% of the total energy of the wild-type protein. The threshold of 0.10 was determined empirically by calibrating the results for proteins of known 3D structures in Table IGo (see below).


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Table III. Correlation between conformational change and protein stabilitya
 
Calibration against known mutant 3D structures

Table IGo summarizes the results for the wild-type proteins and their respective mutants from the PDB survey. In each of the 94 mutations, the 3D structure of the mutant protein was found to match the wild-type configuration after it was overlaid with the wild-type one, and 90% of the mutant residues retained {phi} and {Psi} angles within 20° of the wild-type residue. Hence, all the mutants in Table IGo adopt their wild-type fold. Out of the 94 mutations, 88 (or 94%) of the cases were predicted successfully to retain the wild-type conformation, as evidenced by S < 0.10. In particular, the mutation of a short, neutral, Ser-214 in anionic trypsin (PDB entry 1ane) to a longer, negatively charged glutamic acid or positively charged lysine was correctly predicted to retain the wild-type conformation even though the mutation occurred in a buried site. Another non-trivial correct prediction is the mutation of partially buried Gly-120 in human growth hormone (PDB entry 1hgu) to a positively charged arginine.

For the remaining six mutations (see bold italic entries in Table IGo), the X-ray structures show that the protein can accommodate the mutant side-chain without having to distort its main-chain conformation significantly, but the current methodology fails to predict this. All six incorrectly predicted cases in Table IGo correspond to buried or partially buried mutation sites. Hence, taking into consideration the SASA term in predicting the mutant conformation, by assuming that the strain can be relieved in solvent-exposed loop regions, would not improve the agreement with experiment.

In three of the incorrectly predicted cases in Table IGo, PDB entries 1bmz (human transthyretin, Leu-55->Pro), 1rdg (rubredoxin, Gly-10->Val) and 2alp ({alpha}-lytic protease, Gly-216->Leu), there were no rotamers for the mutant residue corresponding to the backbone dihedral angles for the wild-type residue. For example, no proline can be found in the rotamer library with {phi} and {Psi} equal to those (-126° and 112°) of wild-type Leu-55 in 1bmz (see Figure 2Go). Furthermore, the non-rotameric mutant side-chain clashed either with the backbone (Leu-55->Pro in 1bmz) or with other side-chains (Gly-216->Leu in 2alp), creating strain in the predicted mutant structure. This strain can apparently be alleviated by local backbone changes in the mutant residue, as is evident from the X-ray structure of the mutant protein.

In contrast, the backbone {phi} and {Psi} dihedral angles for the mutant and wild-type residues are similar in the other three incorrectly predicted cases in Table IGo; PDB entries 1a27 (17-ß-hydroxysteriod-dehydrogenase, His->Leu), 2amg (1,4-{alpha} maltotetrahydrolase, Glu->Gln) and 6gst (glutathione transferase, Tyr->Phe). In the latter two cases, the mutant side-chain was placed in a rotameric state that occurred with low probability and clashed with other side-chains, whereas in the X-ray structure it is found in a more common rotameric state. However, in the former case, the leucine is placed by the SCWRL algorithm in its most favored rotamer ({chi}1 = -73°; {chi}2 =175°), but in the X-ray structure it is found in an uncommon rotamer ({chi}1 = -140°; {chi}2 = -73°).

Tests on p53 mutants

The p53 results in Table IIGo show that out of the 33 mutations, 26 (or 79%) of the cases were predicted successfully to either retain the wild-type conformation or result in partial or total unfolding of the wild-type backbone. In particular, the conformations of all aromatic and aliphatic mutants in Table IIGo were correctly predicted. Also of note is the side by side mutation of Arg-248 and Arg-249, both to tryptophan. Our method correctly predicts that the mutation of solvent-exposed Arg-248 to tryptophan can be accommodated by the wild-type conformation (S = 0.01), while mutation of the buried Arg-249 to tryptophan cannot (S = 0.12). Since the relatively buried Trp-249 has steric clashes with other side chains in its proximity, it is likely to require a deformation of the backbone conformation in order to accommodate the mutant side chain. The mutations of Arg-273 to cysteine, histidine and leucine are interesting since they appear to lower the total energy in each case (-0.04 for Cys-273, -0.02 for His-273 and -0.02 for Leu-273) as well as the steric energy (-2.6 in all cases).


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Table II. Results from the p53 mutationsa
 
Of the seven mutations whose effects on the wild-type conformation were incorrectly predicted (see bold italic entries in Table IIGo), four involved mutation to proline. Pro-175 and Pro-248 were predicted to result in unfolding, whereas Pro-159 and Pro-273 were predicted to retain the native fold. The distinctive feature of proline is its five-membered ring that connects its side-chain C{delta} atom to its backbone amide nitrogen. This restricts the {phi} angle of proline more than that of other amino acids. Hence, for proline the mean {phi} angle is -63° (±15°), whereas its {Psi} angle is usually clustered around either -35° or 150° (Macarthur and Thornton, 1991Go). Since the {phi} and {Psi} angles of Arg-175 in the crystal structure are -65° and 147°, respectively, they are already optimal for the mutation to proline. However, part of the proline ring is close to Gln-192 (the Pro-175 C{delta} to Gln-192 O distance is only 1.6 Å), causing the mutant Pro-175 to be highly strained (S = 0.51). Given the optimal proline backbone angles, only a slight movement would be necessary to relieve this strain. Thus our method, which does not allow for either main-chain or side-chain relaxation, incorrectly predicts that mutation of Arg-175 to proline results in a non-native conformation.

For the Arg-248 to proline mutation, there is no proline in the rotamer library with the {phi} (86°) and {Psi} (7°) dihedral angles of Arg-248, so the non-rotameric Pro-248 clashed with other side-chains causing steric strain in the mutant structure (S = 5.06). However, since the strain occurs in a solvent-exposed turn region (SASA = 51.9%), the backbone may undergo a local conformational change to relieve the strain without unfolding of the native backbone. This may explain why the Pro-248 mutant is experimentally found to retain the wild-type conformation.

In analogy to the Arg-248 to proline mutation, there were no rotamers for Pro-159 and Pro-273 corresponding to the wild-type {phi} (-120° for Ala-159; -126° for Arg-273) and {Psi} (147° for Ala-159; 110° for Arg-273) dihedral angles at that position (see Figure 2Go). Furthermore, the non-rotameric Pro-159 and Pro-273 clashed with other side-chains. This is reflected by the high {Delta}ESCWRL energies (see Table IIGo) and {Delta}EVDW energies computed by AMBER (132 kcal/mol for Pro-159 and 338 kcal/mol for Pro-273). However, the steric strain is partially offset by a gain in the electrostatic energy (-24 kcal/mol for Pro-159 and -67 kcal/mol for Pro-273), resulting in a S value that is lower than the threshold of 0.10. Hence both Pro-159 and Pro-273 are predicted to retain the wild-type conformation, contrary to experimental observations. In the p53 crystal structure, the Ala-159 backbone amide hydrogen interacts with the Val-216 backbone carbonyl oxygen. On the other hand, the Arg-273 backbone amide hydrogen interacts with the Met-133 backbone carbonyl oxygen, while its side-chain amino proton makes a salt-bridge with Asp-281 side-chain carboxylate oxygen, which, in turn, hydrogen bonds with the Arg-280 side-chain (Cho et al., 1994Go). If these interactions play a key role in maintaining the protein structure, then their loss upon mutation to proline, which lacks an amide proton and strong hydrogen-bonding donors, may partly contribute to local or global unfolding of the native structure.

The remaining three incorrectly predicted p53 mutant conformations all involve mutation of a larger residue to a smaller one in a buried region; Pro-151 to serine, Arg-175 to aspartic acid and Phe-270 to cysteine. Each of these residues has been identified to play an important role in stabilizing the structure of the p53 hydrophobic core. Pro-151 appears to be important for the structure of the loop connecting strands 3 and 4, while Phe-270 is one of the residues comprising the hydrophobic core (Cho et al., 1994Go). Arg-175 is involved in interactions bridging loop 2 and 3. The side-chain imino and amino protons of Arg-175 are hydrogen bonded to the backbone oxygen atoms of Pro-191 on loop 2 and Met-237 on loop 3 as well as the side-chain oxygen of Ser-183 on loop 2 (Cho et al., 1994Go). Although the relatively small mutant side-chain of Ser-151 or Asp-175 or Cys-270 can be placed on the wild-type backbone without creating steric strain in the mutant protein, it cannot provide the required interactions needed to stabilize the structure. This may explain the discrepancy between the predicted (folded) and experimental (unfolded) conformation.

Correlation between mutant conformation and protein stability

Table IIIGo summarizes the results for p53, staphylococcal nuclease and the src-SH3 domain. The predicted conformation is correlated against the stability of the mutant protein relative to that of the wild-type; i.e. {Delta}{Delta}Gu->f = {Delta}Gu->fmut - {Delta}Gu->fwt, where {Delta}Gu->f is the free energy difference between the folded and unfolded states. Since a point mutation can affect the native or denatured state or both (Shortle, 1996Go), a correlation is expected only if the mutation affects primarily the folded state rather than the partially folded or unfolded one. Table IIIGo shows that in all cases where the experimentally determined stability of the mutant protein is similar to that of the wild type ({Delta}{Delta}Gu->f < 0.5), the protein stability correlates with the predicted (native) conformation.

In contrast, only 10 out of the 30 mutations (i.e. 33%) that leave the mutant less stable than the wild type correlate with the predicted locally or globally unfolded conformation. The remaining 20 mutations were predicted not to affect the wild-type conformation, even though the mutant was found to be less stable than the wild type. This poor correlation is not unexpected. On the one hand, the discrepancy could be an artifact of the present method; i.e. the mutant conformation is wrongly predicted to retain the wild-type conformation, as in the case of Pro-151 to serine or Phe-270 to cysteine (see above and Table IIGo). On the other hand, it could result from mutational effects in the unfolded (in addition to the folded) state of the mutant; e.g. Gly-245 to serine or Arg-248 to glutamine in p53, where the predicted folded conformation of the mutant is in accord with experimental findings (see Table IIGo).


    Discussion
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 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
The results in Tables I and IIGoGo show that our method for predicting the effects of amino acid mutations on the native conformation gives results in reasonable agreement with those obtained experimentally. Of the 94 single-point mutations on 47 different proteins with known wild-type and respective mutant X-ray structures, our method successfully predicted that the mutant retained the wild-type conformation in 94% of the cases based on a cutoff of S = 0.1 (see above). In the case of p53, it was able to predict with an accuracy of ~79% which mutations lead to a folded or unfolded conformation. In particular, out of the 11 p53 mutations in Table IIGo that were predicted to result in an unfolded conformation, nine were indeed observed in an unfolded conformation. A corollary of this finding is that the predicted partially folded or denatured mutant conformation can be correlated with a decrease in the stability of the mutant relative to the wild type. All 10 mutations in Table IIIGo that were predicted to result in a non-wild-type conformation were experimentally found to lead to a decrease in protein stability.

Analyses of the incorrectly predicted cases indicate situations when the method will likely fail to predict the correct mutant conformation. The method may fail to predict that the mutant is favorable in the wild-type conformation if it places the mutant residue in a non-rotameric state or a rarely populated state so that the mutant side-chain clashes with the backbone and/or nearby side-chains (e.g. 2alp Gly-216->Leu or 2amg Glu-219->Gln in Table IGo). However, such strain in the mutant structure is expected to be relieved if it occurs in a solvent-exposed loop region (e.g. p53 Arg-248->Pro in Table IIGo). On the other hand, the method may fail to predict that the mutant is unfavorable in the wild-type conformation when a big residue is mutated to a smaller one, resulting in no steric clash, but a loss in stabilizing interactions (e.g. p53 Arg-175->Asp in Table IIGo).

The key advantage of our method is that it is very fast: over 10 mutations a minute can be screened for each wild-type protein structure. On the other hand, one of the limitations in our method is that it does not allow for either main-chain or side-chain relaxation. Although this may be accounted in part by performing molecular dynamics simulations, this would slow the method dramatically, especially if slow time-scale processes are involved in relaxing the strain induced by placing the mutant side-chain (Philippopoulous and Lim, 1999Go). Furthermore, in molecular dynamics simulations the forces are derived from an empirical energy function, whose accuracy depends on the forcefield parameters, as well as the treatment of boundary and electrostatic interactions with bulk solvent.

Biological implications

Our method has potential applications in several areas; site-directed mutagenesis, X-ray crystallography, drug design, free energy simulations and pattern recognition. One of the reasons why residues are often mutated to glycine and alanine is because the latter are assumed not to perturb the wild-type conformation in most cases. Our method will free experimentalists from this restriction by allowing them to test which larger amino acids can be used as replacements instead of having to rely on the smallest ones. It may prove useful in X-ray crystallography, structure-based drug design and free energy simulations by helping to ascertain whether a mutation will alter or retain the wild-type conformation. It may be employed to improve the accuracy of function prediction from long sequence motifs (Lin et al., 2000Go). It could also be used to predict second site mutations that could restore the native conformation.


    Notes
 
3 To whom correspondence should be addressedE-mail: carmay{at}gate.sinica.edu.tw Back


    Acknowledgments
 
We thank K.-Y.Lin for helpful discussions. This work is supported by the Institute of Biomedical Sciences at Academia Sinica, the National Center for High Performance Computing, and the National Science Council, Taiwan (NSC contract 89-2311-B001-215).


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Energy calculations
 Results
 Discussion
 References
 
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Received September 19, 2000; revised March 17, 2001; accepted May 11, 2001.