Inverse kinematics in biology: the protein loop closure problem
The International Journal of Robotics Research, 2005•journals.sagepub.com
Assembling fragments from known protein structures is a widely used approach to construct
structural models for new proteins. We describe an application of this idea to an important
inverse kinematics problem in structural biology: the loop closure problem. We have
developed an algorithm for generating the conformations of candidate loops that fit in a gap
of given length in a protein structure framework. Our method proceeds by concatenating
small fragments of protein chosen from small libraries of representative fragments. Our …
structural models for new proteins. We describe an application of this idea to an important
inverse kinematics problem in structural biology: the loop closure problem. We have
developed an algorithm for generating the conformations of candidate loops that fit in a gap
of given length in a protein structure framework. Our method proceeds by concatenating
small fragments of protein chosen from small libraries of representative fragments. Our …
Assembling fragments from known protein structures is a widely used approach to construct structural models for new proteins. We describe an application of this idea to an important inverse kinematics problem in structural biology: the loop closure problem. We have developed an algorithm for generating the conformations of candidate loops that fit in a gap of given length in a protein structure framework. Our method proceeds by concatenating small fragments of protein chosen from small libraries of representative fragments. Our approach has the advantages of ab initio methods since we are able to enumerate all candidate loops in the discrete approximation of the conformational space accessible to the loop, as well as the advantages of database search approach since the use of fragments of known protein structures guarantees that the backbone conformations are physically reasonable. We test our approach on a set of 427 loops, varying in length from four residues to 14 residues. The quality of the candidate loops is evaluated in terms of global coordinate root mean square (cRMS). The top predictions vary between 0.3 and 4.2 Å for four-residue loops and between 1.5 and 3.1 Å for 14-residue loops, respectively.
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