Department of Microbiology and Immunology, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA 19107, USA.E-mail: weber{at}asterix.jci.tju.edu
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Abstract |
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Keywords: drug resistance/HIV protease/indinavir/molecular mechanics/saquinavir
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Introduction |
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The HIV-1 protease is essential for the production of infectious virus particles. The protease catalyzes the hydrolysis of specific sequences in the precursor polyproteins to release itself and the other mature structural and functional viral proteins (Debouck et al., 1987; Darke et al., 1988
). The 99 residue HIV-1 protease is a member of the aspartic protease family and is enzymatically active as a homodimer. Crystal structures of the uninhibited HIV-1 protease and of the protease in complex with numerous inhibitors have been determined (for a review, see Wlodawer and Erickson, 1993
). The binding of inhibitors to wild-type HIV-1 protease has been analyzed by molecular mechanics calculations. These calculations provide a simple and rapid method to estimate the trends in the free energy of binding different ligands to a protein of known structure (reviewed in Weber and Harrison, 1998
). Generally, the contributions of entropy and solvation are neglected in these calculations. However, several successful calculations have been reported. Holloway et al. (1995) obtained correlation coefficients R = 7688.5% between the proteaseinhibitor interaction energies and the differences in free energy derived from inhibition constants using the MM2X force field in OPTIMOL. A combination of molecular mechanics estimation of the interaction energy and heuristic estimation of entropy gave a correlation coefficient of 75.5% for 13 inhibitors of HIV protease (Head et al., 1996
). In addition, we have shown that molecular mechanics calculations with AMMP (Harrison, 1993
) can evaluate the trends in catalytic efficiency for peptide substrates of HIV-1 protease. Calculations on HIV protease with the tetrahedral intermediate of 21 peptide substrates related by single amino acid substitutions in positions P4P3' gave a correlation coefficient of 0.64 between the interaction energies and the differences in free energy derived from kinetic measurements (Weber and Harrison, 1996
). The calculations on 14 substrates with changes in the P2P2' positions gave a highly significant correlation of 0.86. The calculations also gave a significant correlation with kinetic measurements for the related protease from Rous sarcoma virus with similar peptide substrates (Weber and Harrison, 1997
). Here, this method is extended to drug-resistant mutants of HIV-1 protease with two clinical inhibitors. The molecular mechanics calculations are shown to be capable of predicting the relative inhibition of protease mutants by saquinavir and indinavir.
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Materials and methods |
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The minimization and molecular dynamics were run using the program AMMP (Harrison, 1993) that incorporates an algorithm to increase the speed and allow the calculation of non-bonded and electrostatic terms without the use of a cut-off radius. AMMP is available from http://asterix.jci.tju.edu. The calculations were run on a DEC AlphaStation 233. The molecular mechanics calculations used the UFF potential set (Rappe et al., 1992
) with parameters modified as described in Weber and Harrison (1996, 1997) (parameter set sp4). In addition, the force constants for the planarity terms of the carbonyl and aromatic carbon atoms were increased from 6 to 150 and 100 kcal/mol.Å, respectively. This change significantly improved the agreement between the calculated normal mode frequencies and observed infrared absorptions for formaldehyde and benzene. Charges for the non-standard groups were generated as described previously (Weber and Harrison, 1996
). The positions for the non-hydrogen atoms were initially fixed in order to calculate and minimize the hydrogen atom positions. No screening dielectric term or bulk solvent correction was included. A constant dielectric of one was used. No cut-off was applied for non-bonded and electrostatic terms. These terms were calculated with an algorithm that amortizes or spreads the cost of calculation over many simpler calculations which results in lower average cost, as described in Harrison and Weber (1994). This algorithm, when used in conjunction with the fast multipole method as implemented in AMMP, brings the cost of the calculation without cut-offs below the cost of using a cut-off of 810 Å with standard approaches.
The models were based on the starting crystal structures of wild-type HIV-1 protease with saquinavir (Krohn et al., 1991) and indinavir (Protein Database entry 1HSG; Chen et al., 1994
). The hydrogen atoms were generated by minimization for the wild-type protease, inhibitor and the water molecules observed in the crystal structures. Saquinavir was given an overall charge of zero. For indinavir, different protonation states were considered with an overall charge of 0, +1 and +2. The partial charges for the inhibitor atoms were generated by a method of moments calculation, as described for the tetrahedral reaction intermediate of HIV protease (Weber and Harrison, 1996
). Each mutation was made by stripping the two residues in each dimer down to the Cß atom, except for the mutant R8Q where the C
atoms were also kept, since this side chain is long and on the protein surface. The new atoms for each substituted residue were created by minimizing on the bond, angle, hybrid and torsion geometrical terms. Each of the side chain torsion angles for the mutated residues was rotated through 360° in steps of 15° to search for alternative conformations. This torsion search finds the angle(s) that have a minimum in the non-bonded and electrostatic energy terms. Finally, the modeled proteaseinhibitor complex was optimized by a longer minimization using 100 steps of conjugate gradients followed by 16 cycles of alternating 30 steps of conjugate gradients and short runs of molecular dynamics (20 steps of 1 fs at 300 K). The proteaseinhibitor interaction energy was calculated using the standard non-bonded and electrostatic terms and also using the screen correction described below.
Screen correction
One potential defect in the standard point charge model for atomic interactions is the inability of a point charge to account correctly for the spread of the electron cloud. While the typical distribution of electrons is highly peaked at the nucleus, the electrostatic potential of a set of orbitals can be significantly different from a point charge model at short distances (<56 Å). The difference is readily visible when the electrostatic potential from a 1s orbital is compared with the potential around a point charge. The electrostatic potential between 1s orbitals is shallower than the potential of point charges at short interatomic distances. Therefore, a new term was introduced to correct for the electron distribution in atoms which are represented as point charges in the standard terms. The atomic partial charge was represented as a delocalized charge distribution. As a first approximation, the charge was assumed to be distributed approximately as a 1s hydrogen orbital with an arbitrary radial scale. A major reason for using a 1s hydrogen orbital was the availability of an analytical expression for the electrostatic potential. The coulomb interaction between atoms i and j (Vij) is given by (Wallace, 1984)
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Results |
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The molecular mechanics interaction energy is an estimate of the internal energy difference between separate and bound states and does not include the entropic contribution or solvation terms. Therefore, the calculated interaction energy will only show correlation with the relative binding free energy derived from inhibition constants, G = RTln(Kimu/Kiwt), where subscript mu refers to mutant and wt to wild-type protease, if the differences in entropy and solvation are similar for all the tested protease mutants. In addition, there will be no correlation if the wild-type and mutant proteases have different conformational changes on binding the same inhibitor. In fact, conformational differences near the site of mutation were observed in the crystal structure of the V82A mutant protease with inhibitor (Baldwin et al., 1995
).
The complexes were built starting from the crystal structures of wild-type HIV-1 protease with the inhibitors, saquinavir (Krohn et al., 1991) or indinavir (Chen et al., 1994
). The chemical structures of the inhibitors are shown in Figure 1
. The minimized complexes included the protease dimer, bound inhibitor and water molecules from the crystal structures. The positions of the non-hydrogen protease atoms in the minimized complexes were compared with those in the crystal structures of wild-type protease. The minimized complex with saquinavir had root mean square (r.m.s.) differences compared with the crystal structure of 0.36 Å for C
atoms, 0.46 Å for main chain atoms, 0.69 Å for side chain atoms and 0.58 Å for all atoms. Similarly, the minimized complex of HIV-1 protease with indinavir gave r.m.s. differences of 0.34 Å for C
atoms, 0.41 Å for main chain atoms, 0.61 Å for side chain atoms and 0.52 Å for all atoms compared with the 1HSG crystal structure. These values are well within the range of 0.160.79 Å for r.m.s. differences observed between main chain atoms in different crystal forms of the same protein (Zegers et al., 1994
) and close to the average value of 0.40 Å for C
atoms (Flores et al., 1993
). There are no crystal structures available for mutant proteases with saquinavir or indinavir. When the crystal structures of all HIV protease mutants in the Protein Database (Bernstein et al., 1977
) were compared with the wild-type structure, the average r.m.s. deviation was 0.56 Å for C
atoms. A similar variation (0.6 Å) has been reported for the structures of wild-type protease with different inhibitors (Wlodawer and Erickson, 1993
). Therefore, the differences due to minimization with AMMP are within the range of experimental differences in HIV protease crystal structures and in other protein structures and indicate the accuracy of the potentials and minimization procedure.
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Discussion |
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The calculations for the R8Q mutant did not show agreement with the relative inhibition constant for any of the tested models of indinavir. The lack of agreement may arise from a different or larger conformational change on binding indinavir to R8Q, a different charged state for the R8Qindinavir complex or larger changes in the ignored entropic and solvent contributions. The most likely possibility is the existence of a different charged state and solvent structure in the R8Qindinavir complex compared with the complexes with the other mutants. However, the calculations gave significant agreement for the R8Qsaquinavir complex in which the inhibitor was uncharged. Moreover, the calculations apparently were able to accommodate the effect of the conformational change that was observed in the crystal structure of the V82A mutant (Baldwin et al., 1995) and the effects of double mutants. The agreement of the trends in predicted compared with calculated energies suggested that drug resistance is due to small changes in the internal energy of the proteaseinhibitor complex including both van der Waals and electrostatic changes. Similar conclusions were reached by other groups from analysis of crystal structures (Pazhanisamy et al., 1996
; Ala et al., 1997
). One caveat is that the tested mutants all alter residues in the inhibitor binding site, whereas some common drug-resistant mutations, such as L90M and N88D, alter residues that are not in direct contact with inhibitor (Schinazi et al., 1997
). Their mode of action is not understood.
Prolonged exposure to saquinavir results in the resistant mutants L90M and G48V (Boucher, 1996), although these particular mutants were not included in the available kinetic measurements. This pattern of resistance differs from those arising with other protease inhibitors. Exposure to indinavir results in the mutation of V82, followed by changes at M46, V84 and other positions (Condra et al., 1995
; Schinazi et al., 1997
). The calculations predict that saquinavir will be most effective on mutants V32I, V82F and M46I and least effective on the three mutants containing I84V. Similarly, indinavir is predicted to be most effective on V82I and M46I mutants and least effective on V82A and M46I/I84V. However, the relative effectiveness of the two drugs cannot be predicted for a particular mutant, since the calculations do not give absolute values for the binding free energies.
The physical and chemical properties of the mutants of HIV-1 protease have been reproduced in the molecular mechanics calculations for 19 out of 20 complexes. The inclusion of the new screen correction has allowed the extension of molecular mechanics calculations from predicting the effects of changes in the ligand (Xu et al., 1995; Weber and Harrison, 1996
, 1997
) to predicting the effects of mutations in the protein. The current calculations only include the ordered water molecules that are observed in the crystal structures of the wild-type protease. In the future, the molecular mechanics calculations will be improved by reparameterization, particularly of charged atom types, and better treatment of solvent. The calculations were best for changes involving neutral groups. However, the majority of drug-resistant mutations involve conservative substitutions of hydrophobic residues and alterations in charge are relatively rare (13% of all substitutions) (Schinazi et al.,1997). Therefore, the calculations can be applied to select the best protease inhibitor to use for particular drug-resistant variants found in AIDS patients. The same technique is also applicable to design modifications of the inhibitors to improve their effectiveness for resistant variants of HIV-1 protease.
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Acknowledgments |
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Notes |
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References |
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Baldwin,W.T., Bhat,T.N., Liu,B., Pattabiraman,N. and Erickson,J.W. (1995). Nature Struct. Biol., 2, 244249.[ISI][Medline]
Bernstein,F.C., Koetzle,T.F., Williams,G., Meyer,E.F., Brice,M.D., Rodgers,J.R., Kennard,O., Shimanouchi,T., Tasumi,M. (1977) J. Mol. Biol., 112, 535542.[ISI][Medline]
Boucher,C. (1996). AIDS 10 (Suppl 1), S15S19.[ISI][Medline]
Chen,Z., Li,Y., Chen,E., Hall,D.L., Darke,P.L., Culberson,C., Shafer,J.A. and Kuo,L.C. (1994) J. Biol. Chem., 269, 26344.
Condra,J.H. et al. (1995) Nature, 374, 569571.[ISI][Medline]
Darke,P.L. et al. (1988) Biochem. Biophys. Res. Commun., 156, 297303.[ISI][Medline]
DeBouck,C., Gomiak,J.G., Strickler,J.E., Meek,T.D., Metcalf,B.W. and Rosenberg,M. (1987) Proc. Natl Acad. Sci. USA, 84, 89038907.[Abstract]
Flores,T.P., Orengo,C.A., Moss,D.S. and Thornton,J.M. (1993) Protein Sci., 2, 18111826.
Gulnik,S.V., Suvorov,L.I., Liu,B., Yu,B. anderson,B., Mitsuya,H. and Erickson,J.W. (1995) Biochemistry, 34, 92829287.[ISI][Medline]
Harrison, R.W. (1993) J. Comput. Chem., 14, 11121122.[ISI]
Harrison,R.W. (1998) J. Comput. Chem., submitted.
Harrison,R.W. and Weber,I.T. (1994) Protein Engng, 7, 13531363.[Abstract]
Head,R.D., Smythe,M.L., Oprea,T.I., Waller,C.L., Green,S.M. and Marshall,G.R. (1996) J. Am. Chem. Soc., 118, 39593969.[ISI]
Holloway,M.K. et al. (1995) J. Med. Chem., 38, 305317.[ISI][Medline]
Kageyama,S. et al. (1993) Antimicrob. Agents Chemother., 37, 810817.[Abstract]
Krohn,A., Redshaw,S., Ritchie,J.C., Graves,B.J. and Hatada,M. (1991) J. Med. Chem., 34, 33403342.[ISI][Medline]
Maschera,B., Darby,G., Palu,G., Wright,L.L., Tisdale,M., Myers,R., Blair,E.D. and Furfine,E.S. (1996) J. Biol. Chem., 271, 3323133235.
Pazhanisamy,S., Stuver,C.M., Cullinan,A.B., Margolin,N., Rao,B.G. and Livingston,D.J. (1996) J. Biol. Chem., 271, 1797917985.
Press,W.H., Teukolsky,S.A., Vettering,W.T. and Flannery,B.R. (1992) Numerical Recipes in C. 2nd edn. Cambridge University Press, Cambridge, pp. 636639.
Rappe,A.K., Casewit,C.J., Colwell,K.S., Goddard,W.A.,III and Skiff,W.M. (1992) J. Am. Chem. Soc., 114, 1002410035.[ISI]
Schinazi,R.F., Larder,B.A. and Mellors,J.W. (1997) Int. Antiviral News, 5, 129142.
Wallace,P.R. (1984) Mathematical Analysis of Physical Problems. Dover, New York, pp. 180181.
Weber,I.T. and Harrison,R.W. (1996) Protein Engng, 9, 679690.[Abstract]
Weber,I.T. and Harrison,R.W. (1997) Protein Sci., 6, 23652374.
Weber,I.T. and Harrison,R.W. (1998) In Kubinyi,H., Folkers,G. and Martin,Y.C. (eds), 3D QSAR in Drug Design, Vol. 2. Kluwer Adademic, Dordrecht, pp. 115127.
Wlodawer,A. and Erickson,J.W. (1993) Annu. Rev. Biochem., 62, 543585.[ISI][Medline]
Xu,L.Z., Weber,I.T., Harrison,R.W., Gidh-Jain,M. and Pilkis,S.J. (1995) Biochemistry, 34, 60836092.[ISI][Medline]
Zegers,I., Maes,D., Dao-Thi,M.-H., Poortmans,F., Palmer,R. and Wyns,L. (1994) Protein Sci., 3, 23222339.
Received July 10, 1998; revised October 10, 1998; accepted February 25, 1999.