Russian version English version
Volume 10   Issue 2   Year 2015
Kashyn I.A., Tuzikov A.V., Andrianov A.M.

Identification of Novel Potential Inhibitors of the HIV-1 gp41 Protein by Virtual Screening and Molecular Modeling Methods

Mathematical Biology & Bioinformatics. 2015;10(2):325-343.

doi: 10.17537/2015.10.325.

References

  1. De Clercq E. New approaches toward anti-HIV chemotherapy. J. Med. Chem. 2005;48:1297-1313. doi: 10.1021/jm040158k
  2. Este J.A., Telenti A. HIV entry inhibitors. Lancet. 2007;370:81-88. doi: 10.1016/S0140-6736(07)61052-6
  3. Rusconi S., Scozzafava A., Mastrolorenzo A., Supuran C.T. An update in the development of HIV entry inhibitors. Curr. Topics in Med. Chem. 2007;7:1273-1289. doi: 10.2174/156802607781212239
  4. Ryser H.J.P., Fluckiger R. Progress in targeting HIV-1 entry. Drug Discov. Today. 2005;10:1085-1094. doi: 10.1016/S1359-6446(05)03550-6
  5. Adamson C.S., Freed E.O. Novel approaches to inhibiting HIV-1 replication. Antiviral. Res. 2010;85:119-141. doi: 10.1016/j.antiviral.2009.09.009
  6. Tilton J.C., Doms R.W. Entry inhibitors in the treatment of HIV-1 infection. Antiviral Res. 2010;85:91-100. doi: 10.1016/j.antiviral.2009.07.022
  7. Arts E.J., Hazuda D.J. HIV-1 antiretroviral drug therapy. Cold Spring Harb. Perspect. Med. 2012;2(4).  doi: 10.1101/cshperspect.a007161
  8. Orsega S. Treatment of adult HIV infection: antiretroviral update and overview. JNP. 2007;10:612-624. doi: 10.1016/j.nurpra.2007.08.022
  9. Hartley O., Klasse P. J., Sattentau Q.J., Moore J.P. V3: HIVs switch-hitter. AIDS Res Hum Retroviruses. 2005;21:171-189. doi: 10.1089/aid.2005.21.171
  10. Sirois S., Sing T., Chou K.C. HIV-1 gp120 V3 loop for structure-based drug design. Curr. Protein Pept. Sci. 2005;6:413-422. doi: 10.2174/138920305774329359
  11. Andrianov A.M. HIV-1 gp120 V3 loop for anti-AIDS drug discovery: computer-aided approaches to the problem solving. Expert Opin. Drug Discov. 2011;6:419-435. doi: 10.1517/17460441.2011.560603
  12. Hoxie J.A. Toward an antibody-based HIV-1 vaccine. Annu. Rev. Med. 2010;61:135-152. doi: 10.1146/annurev.med.60.042507.164323
  13. Walker L.M., Burton D.R. Rational antibody-based HIV-1 vaccine design: current approaches and future directions. Curr. Opin. Immunol. 2010;22:358-366. doi: 10.1016/j.coi.2010.02.012
  14. Kwong P.D., Mascola J.R., Nabel G.J. Rational design of vaccines to elicit broadly neutralizing antibodies to HIV-1. Cold Spring Harb. Perspect. Med. 2011;1(1). doi: 10.1101/cshperspect.a007278
  15. McCoy L.E., Weiss R.A. Neutralizing antibodies to HIV-1 induced by immunization. J. Exp. Med. 2013;210:209-223. doi: 10.1084/jem.20121827
  16. Huang J., Ofek G., Laub L., Louder M.K., Doria-Rose N.A., Longo N.S., Imamichi H., Bailer R.T., Chakrabarti B., Sharma S.K., Munir Alam S., Wang T., Yang Y., Zhang B., Migueles S.A., Wyatt R., Haynes B.F., Kwong P.D., Mascola J.R., Connors M. Broad and potent neutralization of HIV-1 by a gp41-specific human antibody. Nature. 2012;491:406-414. doi: 10.1038/nature11544
  17. Andrianov A.M., Kashyn I.A., Tuzikov A.V Computer-aided search for novel anti-HIV-1 agents presenting peptidomimetics of neutralizing antibodies and evaluation of their potential inhibitory activity by molecular modeling. Mathematical Biology and Bioinformatics. 2013;8(1):119-134 (in Russ.). doi: 10.17537/2013.8.119
  18. Kashyn I.A., Tuzikov A.V., Andrianov A.M. Virtual screening of novel HIV-1 entry inhibitors blocking Cd4-binding site of the virus envelope Gp120 protein. Mathematical Biology and Bioinformatics. 2014;9(2):359-372 (in Russ.). doi: 10.17537/2014.9.359
  19. Floris M., Masciocchi J., Fanton M., Moro S. Swimming into peptidomimetic chemical space using pepMMsMIMIC. Nucl. Acids Res. 2011;39:261-269. doi: 10.1093/nar/gkr287
  20. Bernstein F.C., Koetzle T.F., Williams G.J.B., Meyer E.F., Brice M.D., Rodgers J.R., Kennard O., Shimanouchi T., Tasumi M. The protein data bank. A computer-based archival file for macromolecular structures. J. Mol. Biol. 1977;112:535-542. doi: 10.1016/S0022-2836(77)80200-3
  21. Berman H.M., Westbrook J., Feng Z., Gilliland G., Bhat T.N., Weissig H., Shindyalov I.N., Bourne P.E. The Protein Data Bank. Nucl. Acids Res. 2000;28:235-242. doi: 10.1093/nar/28.1.235
  22. Case D.A., Darden T.A., Cheatham T.E., Simmerling C.L., Wang J., Duke R.E., Luo R., Crowley M., Walker R.C., Zhang W., Merz K.M., Wang B., Hayik S., Roitberg A., Seabra G., Kolossváry I., Wong K.F., Paesani F., Vanicek J., Wu X., Brozell S.R., Steinbrecher T., Gohlke H., Yang L., Tan C., Mongan J., Hornak V., Cui G., Mathews D.H., Seetin M.G., Sagui C., Babin V., Kollman P.A. AMBER 11. Users‛ Manual. San Francisco: University of California; 2010. 302 p.
  23. Jorgensen W.L., Chandrasekhar J., Madura J.D., Impey R.W., Klein M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983;79:926-935. doi: 10.1063/1.445869
  24. Ryckaert J.P., Ciccotti G., Berendsen H.J.C. Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 1977;23:327-341. doi: 10.1016/0021-9991(77)90098-5
  25. Massova I., Kollman P.A. Computational alanine scanning to probe protein-protein interactions: a novel approach to evaluate binding free energies J. Am. Chem. Soc. 1999;121:8133-8143. doi: 10.1021/ja990935j
  26. Masciocchi J., Frau G., Fanton M., Sturlese M., Floris M., Pireddu L., Palla P., Cedrati F., Rodriguez-Tome P., Moro S. MMsINC: a large-scale chemoinformatics database. Nucl. Acids Res. 2009;37:D284-D290. doi: 10.1093/nar/gkn727
  27. Ballester P.J., Richards W.G. Ultrafast shape recognition to search compound databases for similar molecular shapes. J. Comput. Chem. 2007;28:1711-1723. doi: 10.1002/jcc.20681
  28. Mason J.S., Morize I., Menard P.R., Cheney D.L., Hulme C., Labaudiniere R.F. New 4-point pharmacophore method for molecular similarity and diversity applications: overview of the method and applications, including a novel approach to the design of combinatorial libraries containing privileged substructures. J. Med. Chem. 1999;42:3251-3264. doi: 10.1021/jm9806998
  29. Karnachi P., Kulkarni A. Application of pharmacophore fingerprints to structure-based design and data mining. In: Pharmacophores and Pharmacophore Searches. Eds. Langer T., Hoffmannn R.D. Weinheim: Wiley-VCH; 2006. P. 193-206. doi: 10.1002/3527609164.ch9
  30. Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J. Lead- and drug-like compounds: the rule-of-five revolution. Adv. Drug Delivery Rev. 2001;46:3-26. doi: 10.1016/S0169-409X(00)00129-0
  31. Drug Likeness Tool (DruLiTo): HomePage. http://www.niper.gov.in/pi_dev_tools/DruLiToWeb/DruLiTo_index.html (accessed 21 July 2015).
  32. Trott O., Olson A.J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J. Comput. Chem. 2010;31:455-461.
  33. Morris G.M., Huey R., Lindstrom W., Sanner M.F., Belew R.K., Goodsell D.S., Olson A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem. 2009;30:2785-2791. doi: 10.1002/jcc.21256
  34. Durrant J.D., McCammon J.A. NNScore: A neural-network-based scoring function for the characterization of protein-ligand complexes. J. Chem. Inf. Model. 2010;50:1865-1871. doi: 10.1021/ci100244v
  35. Durrant J.D., McCammon J.A. NNScore 2.0: a neural-network receptor-ligand scoring function. J. Chem. Inf. Model. 2011;51:2897-2903. doi: 10.1021/ci2003889
  36. Ballester P.J., Mitchell J.B.O. A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking. Bioinformatics. 2010;26:1169-1175. doi: 10.1093/bioinformatics/btq112
  37. Cao Y., Li L. Improved protein-ligand binding affinity prediction by using a curvature-dependent surface-area model. Bioinformatics. 2014;30:1674-1680. doi: 10.1093/bioinformatics/btu104
  38. Wang J., Wolf R.M., Caldwell J.W., Kollman P.A., Case D.A. Development and testing of a general amber force field. J. Comput. Chem. 2004;25:1157-1174. doi: 10.1002/jcc.20035
  39. Durrant J.D., McCammon J.A. BINANA: A novel algorithm for ligand-binding characterization. J. Mol. Graph. Model. 2011;29:888-893. doi: 10.1016/j.jmgm.2011.01.004
  40. McDonald I.K., Thornton J.M. Satisfying hydrogen bonding potential in proteins. J. Mol. Biol. 1994;238:777-793. doi: 10.1006/jmbi.1994.1334
  41. Munoz-Barroso I., Salzwedel K., Hunter E., Blumenthal R. Role of the membrane-proximal domain in the initial stages of human immunodeficiency virus type 1 envelope glycoprotein-mediated membrane fusion. J. Virol. 1999;73:6089-6092.
  42. Salzwedel K., West J.T., Hunter E. A conserved tryptophan-rich motif in the membrane-proximal region of the human immunodeficiency virus type 1 gp41 ectodomain is important for Env-mediated fusion and virus infectivity. J. Virol. 1999;73:2469-2480.
  43. Cheng Y. Elicitation of antibody responses against the HIV-1 gp41 Membrane Proximal External Region (MPER): doctoral dissertation, Harvard University. Digital Access to Scholarship at Harvard. 2014. http://nrs.harvard.edu/urn-3:HUL.InstRepos:12269838 (accessed 21 July 2015).
  44. Sun Z.Y.J., Cheng Y., Kim M., Song L., Choi J., Kudahl U.J., Brusic V., Chowdhury B., Yu L., Seaman M.S., Bellot G., Shih W.M., Wagner G., Reinherz E.L. Disruption of helix-capping residues 671 and 674 reveals a role in HIV-1 entry for a specialized hinge segment of the membrane proximal external region of gp41. J. Mol. Biol. 2014;426:1095-1108. doi: 10.1016/j.jmb.2013.09.030
Table of Contents Original Article
Math. Biol. Bioinf.
2015;10(2):325-343
doi: 10.17537/2015.10.325
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)
References

 

  Copyright IMPB RAS © 2005-2024