The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Predicting antibody hypervariable loop conformations II: Minimization and molecular dynamics studies of MCPC603 from many randomly generated loop conformations
Abstract
We describe a method for predicting the conformations of loops in proteins and its application to four of the complementarity determining regions [CDRs] in the crystallographically determined structure of MCPC603. The method is based on the generation of a large number of randomly generated conformations for the backbone of the loop being studied, followed by either minimization or molecular dynamics followed by minimization starting from these random structures. The details of the algorithm for the generation of the loops are presented in the first paper in this series (Shenkin etal.[submitted]). The results of minimization and molecular dynamics applied to these loops is presented here. For the two shortest CDRs studied (H1 and L2, which are five and seven amino acids long), minimizations and dynamics simulations which ignore interactions of the loop amino acids beyond the carbon ture closely. This suggests that these loops fold independently of sequence variation. For the third CDR (L3, which is nine amino acids), those portions of the CDR near its base which are hydrogen bonded to framework are well replicated by our procedures, but the top of the loop shows singificant conformational variability. This variability persists when side chain interactions for the MCPC603 sequence are included. For a fourth CDR (H3, which is 11 amino acids long), new low‐energy backbone conformations are found; however, only those which are close to the crystal are compatible with the sequence when side chain interactions are taken into account. Results from minimuzation and dynamics on single CDRs with all other CDRs removed are presented. These allow us to explore the extent to which individual CDR conformations are determined by interactions with framework only.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Wu, T. T., & Kabat, E. A. (1970) · The Journal of Experimental Medicine · doi:10.1084/jem.132.2.211 · Cited by 1,340
Cited by
Comparative Protein Structure Modeling Using Modeller
Eswar, N., Webb, B., Marti‐Renom, M. A., Madhusudhan, M. S., Eramian, D., Shen, M., Pieper, U., & Sali, A. (2006) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0506s15 · Cited by 4,478
Comparative Protein Structure Modeling Using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.3 · Cited by 4,316
Comparative Protein Structure Modeling of Genes and Genomes
Martí-Renom, M. A., Stuart, A. C., Fiser, A., Sánchez, R., Melo, F., & Šali, A. (2000) · Annual Review of Biophysics and Biomolecular Structure · doi:10.1146/annurev.biophys.29.1.291 · Cited by 3,169
Modeling of loops in protein structures
Fiser, A., Do, R. K. G., & Šali, A. (2000) · Protein Science · doi:10.1110/ps.9.9.1753 · Cited by 2,116
Comparative protein structure modeling using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Protein Science · doi:10.1002/cpps.20 · Cited by 730
“The search algorithms include the minimum perturbation method (Fine et al., 1986), dihedral angle search through a rotamer library (Zhu et al., 2006; Sellers et al., 2008), molecular dynamics simulations (Bruccoleri and Karplus, 1990; van Vlijmen and Karplus, 1997), genetic algorithms (Ring et al.,…”
MethodAccurate modeling of protein conformation by automatic segment matching
Levitt, M. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)90964-l · Cited by 558
Cyclic coordinate descent: A robotics algorithm for protein loop closure
Canutescu, A. A., & Dunbrack, R. L. (2003) · Protein Science · doi:10.1110/ps.0242703 · Cited by 521
Advances in comparative protein-structure modelling
Sánchez, R., & Šali, A. (1997) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(97)80027-9 · Cited by 329
Homology modeling a fast tool for drug discovery: Current perspectives
Vyas, V., Ukawala, R., Chintha, C., & Ghate, M. (2012) · Indian Journal of Pharmaceutical Sciences · doi:10.4103/0250-474x.102537 · Cited by 266
Metadata
- Authors
- Fine, R. M., Wang, H., Shenkin, P. S., Yarmush, D. L., & Levinthal, C.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 1986-04
- Volume
- 1
- Issue
- 4
- Pages
- 342-362
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2003331005
- Cited by
- 209
- References
- 1
- FWCI
- 2.62
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.