New computational method for prediction of interacting protein loop regions

Danielson, Matthew L.; Lill, Markus A.

doi:10.1002/prot.22690

Cited by 13 publications

(20 citation statements)

References 61 publications

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“…Building two neighboring loops using ab initio methods in a non-native environment is challenging (52, 53), because multiple loop sampling can produce false positive structures and require significantly more computational time. The forcing of the disulfide bond between the CDR H3 and H1 loops in respective CDRs also reduced the conformational space of the CDR H1 loop.…”

Section: Discussionmentioning

confidence: 99%

Analysis and Modeling of the Variable Region of Camelid Single-Domain Antibodies

Sircar

Sanni

Shi

et al. 2011

The Journal of Immunology

102

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Camelids have a special type of antibodies, known as heavy chain antibodies (HCAbs), that are devoid of classical antibody light chains. Relative to classical antibodies, camelid HCAbs (cAbs) have comparable immunogenicity, antigen recognition diversity and binding affinities, higher stability and solubility, and better manufacturability, making them promising candidates for alternate therapeutic scaffolds. Rational engineering of cAbs to improve therapeutic function requires knowledge of the differences of sequence and structural features between cAbs and classical antibodies. Here, amino acid sequences of 27 cAb variable regions (VHH) were aligned with the respective regions of 54 classical antibodies to detect amino acid differences, enabling automatic identification of cAb VHH complementarity determining regions (CDRs). CDR analysis revealed that the H1 often (and sometimes the H2) adopts diverse conformations not classifiable by established canonical rules. Also, while the cAb H3 is much longer than classical H3 loops, it often contains common structural motifs and sometimes a disulfide bond to the H1. Leveraging these observations, we created a Monte Carlo based cAb VHH structural modeling tool, where the CDR H1 and H2 loops exhibited a median root-mean-square-deviation (rmsd) to native of 3.1 and 1.5 Å respectively. The protocol generated 8-12, 14-16 and 16-24 residue H3 loops with a median rmsd to native of 5.7, 4.5 and 6.8 Å respectively. The large deviation of the predicted loops underscores the challenge in modeling such long loops. cAb VHH homology models can provide structural insights into interaction mechanisms to enable development of novel antibodies for therapeutic and biotechnological use.

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Section: Discussionmentioning

confidence: 99%

Analysis and Modeling of the Variable Region of Camelid Single-Domain Antibodies

Sircar

Sanni

Shi

et al. 2011

The Journal of Immunology

102

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“…Although it is possible to combine our approach with other protein conformational search methods (e.g. elastic network models, 52-58 loop prediction, 59-64 etc.) for sampling large conformational changes, we do not expect the ligand-model approach alone to be feasible for sampling large scale changes in protein structure, such as alternative loop conformation or large hinge-bending motions.…”

Section: Discussionmentioning

confidence: 99%

Significant Enhancement of Docking Sensitivity Using Implicit Ligand Sampling

Lill

2011

J. Chem. Inf. Model.

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The efficient and accurate quantification of protein-ligand interactions using computational methods is still a challenging task. Two factors strongly contribute to the failure of docking methods to predict free energies of binding accurately: the insufficient incorporation of protein flexibility coupled to ligand binding and the neglected dynamics of the protein-ligand complex in current scoring schemes. We have developed a new methodology, named the ‘ligand-model’ concept, to sample protein conformations that are relevant for binding structurally diverse sets of ligands. In the ligand-model concept, molecular-dynamics (MD) simulations are performed with a virtual ligand, represented by a collection of functional groups that binds to the protein and dynamically changes its shape and properties during the simulation. The ligand model essentially represents a large ensemble of different chemical species binding to the same target protein. Representative protein structures were obtained from the MD simulation, and docking was performed into this ensemble of protein conformation. Similar binding poses were clustered, and the averaged score was utilized to re-rank the poses. We demonstrate that the ligand-model approach yields significant improvements in predicting native-like binding poses and quantifying binding affinities compared to static docking and ensemble docking simulations into protein structures generated from an apo MD simulation.

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“…This task is still too difficult for most of the existing methods, although some progress was reported recently by Sellers et al 5 who examined how loop refinement accuracy is affected by errors in surrounding side chains. Although the majority of prediction methods focus on individual loops, Danielson and Lill12 proposed a method for simultaneously predicting interacting loop regions.…”

Section: Introductionmentioning

confidence: 99%

“…Energy or scoring functions that have been used for loop modeling are very diverse and include statistical9, 12, 34, 35 and physics‐based4, 5, 7 potentials or their combination 7, 10, 11. Physics‐based potentials usually consist of an all‐atom force field, such as OPLS,4, 5, 11 CHARMM,7, 36 or AMBER,9 and a variety of treatments of electrostatics and solvation 6, 8, 9, 20–22, 36–39.…”

Section: Introductionmentioning

confidence: 99%

Development of a new physics‐based internal coordinate mechanics force field and its application to protein loop modeling

2010

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We report the development of ICMFF, new force field parameterized using a combination of experimental data for crystals of small molecules and quantum mechanics calculations. The main features of ICMFF include: (a) parameterization for the dielectric constant relevant to the condensed state (ε=2) instead of vacuum; (b) an improved description of hydrogen-bond interactions using duplicate sets of van der Waals parameters for heavy atom-hydrogen interactions; and (c) improved backbone covalent geometry and energetics achieved using novel backbone torsional potentials and inclusion of the bond angles at the C α atoms into the internal variable set. The performance of ICMFF was evaluated through loop modeling simulations for 4-13 residue loops. ICMFF was combined with a solvent-accessible surface area solvation model optimized using a large set of loop decoys. Conformational sampling was carried out using the Biased Probability Monte Carlo method. Average/median backbone root-mean-square deviations of the lowest energy conformations from the native structures were 0.25/0.21 Å for 4 residues loops, 0.84/0.46 Å for 8 residue loops, and 1.16/0.73 Å for 12 residue loops. To our knowledge, these results are significantly better than or comparable to those reported to date for any loop modeling method that does not take crystal packing into account. Moreover, the accuracy of our method is on par with the best previously reported results obtained considering the crystal environment. We attribute this success to the high accuracy of the new ICM force field achieved by meticulous parameterization, to the optimized solvent model, and the efficiency of the search method.

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New computational method for prediction of interacting protein loop regions

Cited by 13 publications

References 61 publications

Analysis and Modeling of the Variable Region of Camelid Single-Domain Antibodies

Analysis and Modeling of the Variable Region of Camelid Single-Domain Antibodies

Significant Enhancement of Docking Sensitivity Using Implicit Ligand Sampling

Development of a new physics‐based internal coordinate mechanics force field and its application to protein loop modeling

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