Abstract
Loop modeling is crucial for high-quality homology model construction outside conserved secondary structure elements. Dozens of loop modeling protocols involving a range of database and ab initio search algorithms and a variety of scoring functions have been proposed. Knowledge-based loop modeling methods are very fast and some can successfully and reliably predict loops up to about eight residues long. Several recent ab initio loop simulation methods can be used to construct accurate models of loops up to 12–13 residues long, albeit at a substantial computational cost. Major current challenges are the simulations of loops longer than 12–13 residues, the modeling of multiple interacting flexible loops, and the sensitivity of the loop predictions to the accuracy of the loop environment.
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References
Jaroszewski, L. (2009) Protein structure prediction based on sequence similarity, Methods Mol Biol 569, 129–156.
Moult, J., and James, M. N. (1986) An algorithm for determining the conformation of polypeptide segments in proteins by systematic search, Proteins 1, 146–163.
Schindler, T., Bornmann, W., Pellicena, P., Miller, W. T., Clarkson, B., and Kuriyan, J. (2000) Structural mechanism for STI-571 inhibition of abelson tyrosine kinase, Science 289, 1938–1942.
Kufareva, I., and Abagyan, R. (2008) Type-II kinase inhibitor docking, screening, and profiling using modified structures of active kinase states, J Med Chem 51, 7921–7932.
Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., and Bourne, P. E. (2000) The Protein Data Bank, Nucleic acids research 28, 235–242.
Fidelis, K., Stern, P. S., Bacon, D., and Moult, J. (1994) Comparison of systematic search and database methods for constructing segments of protein structure, Protein Eng 7, 953–960.
Deane, C. M., and Blundell, T. L. (2001) CODA: a combined algorithm for predicting the structurally variable regions of protein models, Protein Sci 10, 599–612.
van Vlijmen, H. W., and Karplus, M. (1997) PDB-based protein loop prediction: parameters for selection and methods for optimization, J Mol Biol 267, 975–1001.
Wojcik, J., Mornon, J. P., and Chomilier, J. (1999) New efficient statistical sequence-dependent structure prediction of short to medium-sized protein loops based on an exhaustive loop classification, J Mol Biol 289, 1469–1490.
Michalsky, E., Goede, A., and Preissner, R. (2003) Loops In Proteins (LIP) – a comprehensive loop database for homology modelling, Protein Eng 16, 979–985.
Burke, D. F., and Deane, C. M. (2001) Improved protein loop prediction from sequence alone, Protein Eng 14, 473–478.
Fernandez-Fuentes, N., and Fiser, A. (2006) Saturating representation of loop conformational fragments in structure databanks, BMC Struct Biol 6, 15.
Regad, L., Martin, J., Nuel, G., and Camproux, A. C. (2010) Mining protein loops using a structural alphabet and statistical exceptionality, BMC bioinformatics 11, 75.
Choi, Y., and Deane, C. M. (2010) FREAD revisited: Accurate loop structure prediction using a database search algorithm, Proteins 78, 1431–1440.
Simons, K. T., Kooperberg, C., Huang, E., and Baker, D. (1997) Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions, J Mol Biol 268, 209–225.
Rohl, C. A., Strauss, C. E., Chivian, D., and Baker, D. (2004) Modeling structurally variable regions in homologous proteins with rosetta, Proteins 55, 656–677.
Mandell, D. J., Coutsias, E. A., and Kortemme, T. (2009) Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling, Nat Methods 6, 551–552.
Deane, C. M., and Blundell, T. L. (2000) A novel exhaustive search algorithm for predicting the conformation of polypeptide segments in proteins, Proteins 40, 135–144.
Tosatto, S. C., Bindewald, E., Hesser, J., and Manner, R. (2002) A divide and conquer approach to fast loop modeling, Protein Eng 15, 279–286.
Spassov, V. Z., Flook, P. K., and Yan, L. (2008) LOOPER: a molecular mechanics-based algorithm for protein loop prediction, Protein Eng Des Sel 21, 91–100.
Galaktionov, S., Nikiforovich, G. V., and Marshall, G. R. (2001) Ab initio modeling of small, medium, and large loops in proteins, Biopolymers 60, 153–168.
Rapp, C. S., and Friesner, R. A. (1999) Prediction of loop geometries using a generalized born model of solvation effects, Proteins 35, 173–183.
Kolinski, A., and Skolnick, J. (1998) Assembly of protein structure from sparse experimental data: an efficient Monte Carlo model, Proteins 32, 475–494.
Olson, M. A., Feig, M., and Brooks, C. L., 3rd. (2008) Prediction of protein loop conformations using multiscale modeling methods with physical energy scoring functions, J Comput Chem 29, 820–831.
Go, N., and Scheraga, H. A. (1970) Ring Closure and Local Conformational Deformations of Chain Molecules, Macromolecules 3, 178–187.
Wedemeyer, W. J., and Scheraga, H. A. (1999) Exact analytical loop closure in proteins using polynomial equations, Journal of Computational Chemistry 20, 819–844.
Kolodny, R., Guibas, L., Levitt, M., and Koehl, P. (2005) Inverse Kinematics in Biology: The Protein Loop Closure Problem., Int J Robotics Research 24, 151–163.
Coutsias, E. A., Seok, C., Jacobson, M. P., and Dill, K. A. (2004) A kinematic view of loop closure, J Comput Chem 25, 510–528.
Nilmeier, J., Hua, L., Coutsias, E. A., and Jacobson, M. P. (2011) Assessing Protein Loop Flexibility by Hierarchical Monte Carlo Sampling, Journal of Chemical Theory and Computation 7, 1564–1574.
Cui, M., Mezei, M., and Osman, R. (2008) Prediction of protein loop structures using a local move Monte Carlo approach and a grid-based force field, Protein Eng Des Sel 21, 729–735.
Ramachandran, G. N., Ramakrishnan, C., and Sasisekharan, V. (1963) Stereochemistry of polypeptide chain configurations, J Mol Biol 7, 95–99.
Canutescu, A. A., and Dunbrack, R. L., Jr. (2003) Cyclic coordinate descent: A robotics algorithm for protein loop closure, Protein Sci 12, 963–972.
Berkholz, D. S., Shapovalov, M. V., Dunbrack, R. L., Jr., and Karplus, P. A. (2009) Conformation dependence of backbone geometry in proteins, Structure 17, 1316–1325.
Schaefer, L., and Cao, M. (1995) Predictions of protein backbone bond distances and angles from first principles, Journal of Molecular Structure: THEOCHEM 333, 201–208.
Karplus, P. A. (1996) Experimentally observed conformation-dependent geometry and hidden strain in proteins, Protein Sci 5, 1406–1420.
Bruccoleri, R. E., and Karplus, M. (1985) Chain closure with bond angle variations, Macromolecules 18, 2767–2773.
Boomsma, W., and Hamelryck, T. (2005) Full cyclic coordinate descent: solving the protein loop closure problem in Calpha space, BMC bioinformatics 6, 159.
Zhu, K., Pincus, D. L., Zhao, S., and Friesner, R. A. (2006) Long loop prediction using the protein local optimization program, Proteins 65, 438–452.
Jacobson, M. P., Pincus, D. L., Rapp, C. S., Day, T. J., Honig, B., Shaw, D. E., and Friesner, R. A. (2004) A hierarchical approach to all-atom protein loop prediction, Proteins 55, 351–367.
Shenkin, P. S., Yarmush, D. L., Fine, R. M., Wang, H. J., and Levinthal, C. (1987) Predicting antibody hypervariable loop conformation. I. Ensembles of random conformations for ringlike structures, Biopolymers 26, 2053–2085.
Xiang, Z., Soto, C. S., and Honig, B. (2002) Evaluating conformational free energies: the colony energy and its application to the problem of loop prediction, Proc Natl Acad Sci U S A 99, 7432–7437.
Zheng, Q., Rosenfeld, R., Vajda, S., and DeLisi, C. (1993) Determining protein loop conformation using scaling-relaxation techniques, Protein Sci 2, 1242–1248.
DePristo, M. A., de Bakker, P. I., Lovell, S. C., and Blundell, T. L. (2003) Ab initio construction of polypeptide fragments: efficient generation of accurate, representative ensembles, Proteins 51, 41–55.
Park, B. H., and Levitt, M. (1995) The complexity and accuracy of discrete state models of protein structure, J Mol Biol 249, 493–507.
Rooman, M. J., Kocher, J. P., and Wodak, S. J. (1991) Prediction of protein backbone conformation based on seven structure assignments. Influence of local interactions, J Mol Biol 221, 961–979.
Fiser, A., Do, R. K., and Sali, A. (2000) Modeling of loops in protein structures, Protein Sci 9, 1753–1773.
Liu, P., Zhu, F., Rassokhin, D. N., and Agrafiotis, D. K. (2009) A self-organizing algorithm for modeling protein loops, PLoS Comput Biol 5, e1000478.
Baysal, C., and Meirovitch, H. (1999) Free energy based populations of interconverting microstates of a cyclic peptide lead to the experimental NMR data, Biopolymers 50, 329–344.
Scott, W. R. P., Hünenberger, P. H., Tironi, I. G., Mark, A. E., Billeter, S. R., Fennen, J., Torda, A. E., Huber, T., Krüger, P., and van Gunsteren, W. F. (1999) The GROMOS Biomolecular Simulation Program Package, The Journal of Physical Chemistry A 103, 3596–3607.
Zhang, H., Lai, L., Wang, L., Han, Y., and Tang, Y. (1997) A fast and efficient program for modeling protein loops, Biopolymers 41, 61–72.
Ponder, J. W., and Case, D. A. (2003) Force fields for protein simulations, Adv Protein Chem 66, 27–85.
Bashford, D., and Case, D. A. (2000) Generalized born models of macromolecular solvation effects, Annu Rev Phys Chem 51, 129–152.
Samudrala, R., and Moult, J. (1998) An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction, J Mol Biol 275, 895–916.
de Bakker, P. I., DePristo, M. A., Burke, D. F., and Blundell, T. L. (2003) Ab initio construction of polypeptide fragments: Accuracy of loop decoy discrimination by an all-atom statistical potential and the AMBER force field with the Generalized Born solvation model, Proteins 51, 21–40.
Zhou, H., and Zhou, Y. (2002) Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction, Protein Sci 11, 2714–2726.
Zhang, C., Liu, S., and Zhou, Y. (2004) Accurate and efficient loop selections by the DFIRE-based all-atom statistical potential, Protein Sci 13, 391–399.
Danielson, M. L., and Lill, M. A. (2010) New computational method for prediction of interacting protein loop regions, Proteins 78, 1748–1759.
Rata, I. A., Li, Y., and Jakobsson, E. (2010) Backbone statistical potential from local sequence-structure interactions in protein loops, J Phys Chem B 114, 1859–1869.
Sali, A., and Blundell, T. L. (1993) Comparative protein modelling by satisfaction of spatial restraints, J Mol Biol 234, 779–815.
MacKerell, A. D., Bashford, D., Bellott, Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., Joseph-McCarthy, D., Kuchnir, L., Kuczera, K., Lau, F. T. K., Mattos, C., Michnick, S., Ngo, T., Nguyen, D. T., Prodhom, B., Reiher, W. E., Roux, B., Schlenkrich, M., Smith, J. C., Stote, R., Straub, J., Watanabe, M., Wiórkiewicz-Kuczera, J., Yin, D., and Karplus, M. (1998) All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins, The Journal of Physical Chemistry B 102, 3586–3616.
Melo, F., and Feytmans, E. (1997) Novel knowledge-based mean force potential at atomic level, J Mol Biol 267, 207–222.
Ponder, J. W., and Richards, F. M. (1987) Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes, J Mol Biol 193, 775–791.
Sellers, B. D., Zhu, K., Zhao, S., Friesner, R. A., and Jacobson, M. P. (2008) Toward better refinement of comparative models: predicting loops in inexact environments, Proteins 72, 959–971.
Soto, C. S., Fasnacht, M., Zhu, J., Forrest, L., and Honig, B. (2008) Loop modeling: Sampling, filtering, and scoring, Proteins 70, 834–843.
Kaminski, G. A., Friesner, R. A., Tirado-Rives, J., and Jorgensen, W. L. (2001) Evaluation and Reparametrization of the OPLS-AA Force Field for Proteins via Comparison with Accurate Quantum Chemical Calculations on Peptides, The Journal of Physical Chemistry B 105, 6474-6487.
Scheraga, H. A., and Gold, V. (1968) Calculations of Conformations of Polypeptides, in Advances in Physical Organic Chemistry, pp 103–184, Academic Press.
Némethy, G., Gibson, K. D., Palmer, K. A., Yoon, C. N., Paterlini, G., Zagari, A., Rumsey, S., and Scheraga, H. A. (1992) Energy parameters in polypeptides .10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to praline-containing peptides Journal of physical chemistry 96, 6472.
Felts, A. K., Gallicchio, E., Chekmarev, D., Paris, K. A., Friesner, R. A., and Levy, R. M. (2008) Prediction of Protein Loop Conformations using the AGBNP Implicit Solvent Model and Torsion Angle Sampling, J Chem Theory Comput 4, 855–868.
Pickersgill, R. W. (1988) A rapid method of calculating charge-charge interaction energies in proteins, Protein Eng 2, 247–248.
Levy, R. M., Zhang, L. Y., Gallicchio, E., and Felts, A. K. (2003) On the Nonpolar Hydration Free Energy of Proteins: Surface Area and Continuum Solvent Models for the Solute-Solvent Interaction Energy, Journal of the American Chemical Society 125, 9523–9530.
Gallicchio, E., and Levy, R. M. (2004) AGBNP: an analytic implicit solvent model suitable for molecular dynamics simulations and high-resolution modeling, J Comput Chem 25, 479–499.
Das, B., and Meirovitch, H. (2001) Optimization of solvation models for predicting the structure of surface loops in proteins, Proteins 43, 303–314.
Das, B., and Meirovitch, H. (2003) Solvation parameters for predicting the structure of surface loops in proteins: transferability and entropic effects, Proteins 51, 470–483.
Szarecka, A., and Meirovitch, H. (2006) Optimization of the GB/SA solvation model for predicting the structure of surface loops in proteins, J Phys Chem B 110, 2869–2880.
Wesson, L., and Eisenberg, D. (1992) Atomic solvation parameters applied to molecular dynamics of proteins in solution, Protein Sci 1, 227–235.
Arnautova, Y. A., Abagyan, R. A., and Totrov, M. (2011) Development of a new physics-based internal coordinate mechanics force field and its application to protein loop modeling, Proteins 79, 477–498
Abagyan, R., Totrov, M., and Kuznetsov, D. (1994) ICM-A new method for protein modeling and design: Applications to J Comp Chem 15, 488–506.
Abagyan, R., and Totrov, M. (1994) Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins, J Mol Biol 235, 983–1002.
Kryshtafovych, A., Venclovas, C., Fidelis, K., and Moult, J. (2005) Progress over the first decade of CASP experiments, Proteins 61 Suppl 7, 225–236.
Nikiforovich, G. V., Taylor, C. M., Marshall, G. R., and Baranski, T. J. (2010) Modeling the possible conformations of the extracellular loops in G-protein-coupled receptors, Proteins 78, 271–285.
Sellers, B. D., Nilmeier, J. P., and Jacobson, M. P. (2010) Antibodies as a model system for comparative model refinement, Proteins 78, 2490–2505.
Tsai, C. J., Kumar, S., Ma, B., and Nussinov, R. (1999) Folding funnels, binding funnels, and protein function, Protein Sci 8, 1181–1190.
Wong, S., and Jacobson, M. P. (2008) Conformational selection in silico: loop latching motions and ligand binding in enzymes, Proteins 71, 153–164.
Fernandez-Fuentes, N., Zhai, J., and Fiser, A. (2006) ArchPRED: a template based loop structure prediction server, Nucleic acids research 34, W173–176.
Fiser, A., and Sali, A. (2003) ModLoop: automated modeling of loops in protein structures, Bioinformatics (Oxford, England) 19, 2500–2501.
Alland, C., Moreews, F., Boens, D., Carpentier, M., Chiusa, S., Lonquety, M., Renault, N., Wong, Y., Cantalloube, H., Chomilier, J., Hochez, J., Pothier, J., Villoutreix, B. O., Zagury, J. F., and Tuffery, P. (2005) RPBS: a web resource for structural bioinformatics, Nucleic acids research 33, W44–49.
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Totrov, M. (2011). Loop Simulations. In: Orry, A., Abagyan, R. (eds) Homology Modeling. Methods in Molecular Biology, vol 857. Humana Press. https://doi.org/10.1007/978-1-61779-588-6_9
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