Sub-Loop Inverse Kinematics Monte Carlo

Click here to download SLIKMC software package.

Package Dependencies

System requirement: Cygwin/Linux, Cygwin is recommended.

Required software libraries:

  GNU Scientific Library (GSL)

  Mesa 3D Graphics Library (Mesa) version 8.0.2 is recommended.

  GLUI User Interface Library


Install LoopTK package.

  For installing LoopTK, please refer to the instruction here.

Install SLIKMC

  Simply go to LoopTK/slikmc and "make". An executable file will be gerenated with name slikmc.


SLIKMC is implemented as an add-on of LoopTK software package. If you use our package in research, please cite our papers:

Y. Zhang, K. Hauser, and J. Luo. Unbiased, Scalable Sampling of Closed Kinematic Chains. To appear in IEEE Int'l Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 2013.

Y. Zhang, K. Hauser Unbiased, scalable sampling of protein loop conformations from probabilistic priors. To appear in BMC Structural Biology, CSBW issue

Please also cite the publication for LoopTK package:

P. Yao, A. Dhanik, N. Marz, R. Propper, C. Kou, G. Liu, H. van den Bedem, J.C. Latombe, I. Halperin-Landsberg, R.B. Altman. Efficient Algorithms to Explore Conformation Spaces of Flexible Protein Loops. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 5, pp. 534-545, 2008.

Furthermore, we included database generated from the 500 High-resolution Proteins created by S.C.Lowell and the 2010 Backbone-Dependent Rotamer Library created by R.Dunbrack's group in our SLIKMC package. Please also cite the following two papers if your work involves using Ramachandran plots and side-chain rotamers.

S. C. Lovell, I. Davis, W. Arendall III, P. de Bakker, J. Word, M. Prisant, J. Richardson, and D. Richardson Structure validation by calpha geometry: phi,psi and cbeta deviation. Proteins: Structure, Function, and Bioinformatics, 50, Issue 3:437ĘC450, 2003.

M. Shapovalov and R. Dunbrack Jr. A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions. Structure, 19:844ĘC858, 2011