10 research outputs found
Efficient Characterization of Protein Cavities within Molecular Simulation Trajectories: <i>trj_cavity</i>
Protein cavities and tunnels are
critical in determining phenomena
such as ligand binding, molecular transport, and enzyme catalysis.
Molecular dynamics (MD) simulations enable the exploration of the
flexibility and conformational plasticity of protein cavities, extending
the information available from static experimental structures relevant
to, for example, drug design. Here, we present a new tool (<i>trj_cavity</i>) implemented within the GROMACS (www.gromacs.org) framework for the rapid identification and characterization of
cavities detected within MD trajectories. <i>trj_cavity</i> is optimized for usability and computational efficiency and is applicable
to the time-dependent analysis of any cavity topology, and optional
specialized descriptors can be used to characterize, for example,
protein channels. Its novel grid-based algorithm performs an efficient
neighbor search whose calculation time is linear with system size,
and a comparison of performance with other widely used cavity analysis
programs reveals an orders-of-magnitude improvement in the computational
cost. To demonstrate its potential for revealing novel mechanistic
insights, <i>trj_cavity</i> has been used to analyze long-time
scale simulation trajectories for three diverse protein cavity systems.
This has helped to reveal, respectively, the lipid binding mechanism
in the deep hydrophobic cavity of a soluble mite-allergen protein,
Der p 2; a means for shuttling carbohydrates between the surface-exposed
substrate-binding and catalytic pockets of a multidomain, membrane-proximal
pullulanase, PulA; and the structural basis for selectivity in the
transmembrane pore of a voltage-gated sodium channel (NavMs), embedded
within a lipid bilayer environment. <i>trj_cavity</i> is
available for download under an open-source license (http://sourceforge.net/projects/trjcavity). A simplified, GROMACS-independent version may also be compiled
cBOTv7_sbsv2_allreps_log.gct
<p>cBOTv7_sbsv2_allreps_log.gct is the raw normalized and logged read counts for the first group of cancer cell lines undergoing pooled shRNA screening.</p
Achilles_QC_v2.4.3.rnai.Gs.gct
Achilles_QC_v2.4.3.rnai.Gs.gct is the ATARiS-processed, gene level file for 216 cancer cell lines undergoing shRNA pooled screening
Achilles_QC_v2.4.3.rnai.gct
Achilles_QC_v2.4.3.rnai.gct is the final shRNA-level file from pooled screening of 216 cancer cell lines, performed in quadruplicate. See Achilles_Analysis_README_v2.4.3 for processing steps
Achilles_QC_v2.4.3.shRNA.table.txt
Per shRNA quality file from the ATARiS gene summarization of the shRNA data
Table2_SNP_genotyping.xls
<p>File of a panel of SNP genotypes (fingerprinting assays) per cell line for quality control purposes. This also includes the identity with either a pre-screen fingerprint of each cell line or the SNP genotype from the CCLE SNP6.0 array data for that cell line.</p
cBOTv8_sbsv3_allreps_log.gct
<p>cBOTv8_sbsv3_allreps_log.gct is the raw normalized and logged read counts for the second group of cancer cell lines undergoing pooled shRNA screening.</p
Achilles_Analysis_README_v2.4.3.txt
<p>Achilles_Analysis_README_v2.4.3.txt is the file describing data processing steps of pooled shRNA screening of 216 cancer cell lines.</p