Hybrid Monte Carlo with multidimensional replica exchanges: conformational equilibria of the hypervariable regions of a llama VHH antibody domain.
Since the structural repertoire of the hypervariable regions of human antibodies is known to be more restricted than what is implied by sequence variability, a common approach to structural prediction is to use a knowledge-based (KB) method, such as the canonical structure model (C. Chothia and A. M. Lesk, Journal of Molecular Biology, 1987, Vol. 196, pp. 901-917). However, this model is less successful when applied to camelid heavy chain antibodies. In this study, molecular simulations were used to examine the conformational equilibria of the hypervariable regions (H1, H2, and H3) of a llama heavy chain variable domain, for which KB predictions are poor. Simulations were carried out using both conventional molecular dynamics (MD) and hybrid Monte Carlo with multidimensional replica exchanges (HYMREX). The advantage of the latter method is its ability to selectively target parts of the Hamiltonian that can most readily improve sampling. A novel variant of HYMREX was implemented in which, besides the temperature, torsional interactions and the range of nonbonded interactions were varied. To compare the sampling abilities of MD and this HYMREX scheme, simulations were started from a misfolded conformational state. Overall, MD yielded final conformations more similar to the initial state, implying quasi-ergodic sampling. In contrast, HYMREX achieved more ergodic sampling, and the majority of conformations that it sampled agreed well with the known crystal structure. The HYMREX simulation results were used to help identify the chief interactions governing the conformational equilibria and to reexamine the key assumptions underlying the KB predictions. The data show that the H1 region exhibited significant conformational freedom, in support of the hypothesis that main-chain structural variability in this region could play a greater role in antigen binding in camelid antibodies than it does in normal antibodies. Key H1 residues and associated inter-loop interactions are conjectured to account for the poor KB predictions.
Fenwick
Michael K
MK
School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14850-5201, USA.
Escobedo
Fernando A
FA
D000595:Amino Acid Sequence; D000818:Animals; D002161:Camelids, New World; D003198:Computer Simulation; D003460:Crystallization; D006801:Humans; D007143:Immunoglobulin Heavy Chains / Q000737:chemistry* / Q000235:genetics; D007135:Immunoglobulin Variable Region / Q000737:chemistry; D023421:Models, Animal; D008958:Models, Molecular; D009010:Monte Carlo Method; D010446:Peptide Fragments / Q000737:chemistry; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary
D007143:Immunoglobulin Heavy Chains; D007135:Immunoglobulin Variable Region; D010446:Peptide Fragments