This work was supported by a grant from the Russian Science Foundation (17-75-20102, the protocol development). Experiments described in the representative results section (analysis of phosphorylation) were supported by the Stockholm (181301) and Swedish (190345) Cancer Societies.

1. System preparation
NOTE: The molecular models of the native and mutant protein forms are built based on an appropriate crystal structure obtained from the Protein Data Bank15,16.
<ol>
	<li>To retrieve the selected PDB structure, use the Download Files drop-down list and click on PDB Format. Remove remarks and connectivity data, and insert a TER card between separate protein chains in the PDB file. Optionally, set the protonation state of histidine residues by replacing the residue name HIS with HIE, HID, or HIP (Supplementary File 1). 
	NOTE: It is reasonable not to remove crystallographically resolved water molecules (if present in the PDB file).</li>
	<li>To prepare the starting model, launch the tleap program (AmberTools package) and then enter commands that manipulate tleap objects.
	<ol>
		<li>Launch the program: tleap. Load the ff14SB force field to describe the protein with molecular mechanics: &#62; source leaprc.protein.ff14SB.</li>
		<li>Load force fields for water molecules and atomic ions (Na+, Cl-): &#62; source leaprc.water.tip3p.</li>
		<li>Load the PDB file and build coordinates for hydrogens, creating an object named mol: &#62; mol = loadpdb protein.pdb.</li>
		<li>Check for internal inconsistencies that could cause problems: &#62; check mol. 
		NOTE: Disulfide bridges, if present, must be specified manually. Replace the names of covalently bound cysteines CYS with CYX and type the following command in tleap to create a bond between SG atoms: bond mol.X.SG mol.Y.SG (X and Y are cysteine residue numbers).</li>
		<li>Create a solvent box around the protein (TIP3P water, 12 &#197; distance): &#62; solvatebox mol TIP3PBOX 12.0.</li>
		<li>Check the total charge: &#62; charge mol, and add counterions (Na+ or Cl-) to neutralize the system: 
		&#62; addions mol Na+ 0.</li>
		<li>Create the topology prmtop file and the coordinate inpcrd file (inputs for running a simulation): &#62; saveamberparm mol protein.prmtop protein.inpcrd. Quit the tleap program: &#62; quit. 
		&#8203;NOTE: Amber-format coordinate files can be easily converted to PDB format using the ambpdb tool (refer to the Users&#39; Manual, see Table of Materials).</li>
	</ol>
	</li>
</ol>
2. Energy minimization
NOTE: The energy minimization is necessary to remove any bad contacts and overlaps between atoms in the starting system that lead to instability when running MD.
<ol>
	<li>Carry out the first stage of the energy minimization (2,500 steps of the steepest descent algorithm + 2,500 steps of the conjugate gradient algorithm) to optimize the positions of added hydrogen atoms and water molecules while keeping the protein coordinates fixed by positional restraints on heavy atoms.
	<ol>
		<li>Run the pmemd program as follows: 
		pmemd -O -i min1.in -p protein.prmtop -c protein.inpcrd -o protein_min1.out 
		-r protein_min1.rst -ref protein.inpcrd.</li>
		<li>Follow the required arguments: -i FILE control data; -p FILE molecular topology, force field parameters, atom names; -c FILE initial coordinates; -o FILE user-readable log output; -r FILE final coordinates; -ref FILE reference coordinates for position restraints.</li>
		<li>Specify options in the input file min1.in: 
		&#38;cntrl 
		imin=1, maxcyc=5000, ncyc=2500, 
		cut=10.0, ntb=1, 
		ntc=1, ntf=1, 
		ntpr=10, 
		ntr=1, 
		restraintmask=&#39;:1-517 &#38; !@H=&#39;, 
		restraint_wt=2.0 
		/ 
		NOTE: Input options: imin=1 perform minimization; maxcyc=5000 maximum number of minimization cycles; ncyc=2500 minimization method is switched from steepest descent to conjugate gradient after ncyc cycles; cut=10.0 non-bonded cutoff (&#197;); ntb=1 periodic boundaries are imposed, constant volume; ntc=1 no constraints are applied to bond lengths (for better energy convergence); ntf=1 all interactions are calculated; ntpr=10 energy information is printed to the out file every ntpr steps; ntr=1 flag for restraining specified atoms using a harmonic potential; restraintmask=&#39;:1-517 &#38; !@H=&#39; specifies restrained atoms; restraint_wt=2.0 weight (kcal/mol&#8729;&#197;2) for positional restraints.</li>
	</ol>
	</li>
	<li>Carry out the second stage of the energy minimization (5,000 steepest descent steps + 5,000 conjugate gradient steps) without restraints to optimize the whole system.
	<ol>
		<li>Use min2.in and protein_min1.rst as inputs: pmemd -O -i min2.in -p protein.prmtop 
		-c protein_min1.rst -o protein_min2.out -r protein_min2.rst.</li>
		<li>Specify options in the input file min2.in: 
		&#38;cntrl 
		imin=1, maxcyc=10000, ncyc=5000, 
		cut=10.0, ntb=1, 
		ntc=1, ntf=1, 
		ntpr=10 
		/</li>
	</ol>
	</li>
</ol>
3. Heating
NOTE: This stage aims to heat the system from 0 K to 300 K. Initial velocities are assigned to atoms since the starting model based on the PDB file does not contain velocity information.
<ol>
	<li>Carry out the heating process with positional restraints on the protein atoms (50 ps, constant volume).
	<ol>
		<li>Use heat.in and protein_min2.rst as inputs: pmemd -O -i heat.in -p protein.prmtop 
		-c protein_min2.rst -o protein_heat.out 
		-r protein_heat.rst -x protein_heat.mdcrd -ref protein_min2.rst</li>
		<li>Follow the required arguments: -x FILE coordinate sets saved over MD trajectory.</li>
		<li>Specify options in the input file heat.in: 
		&#38;cntrl 
		imin=0, irest=0, ntx=1, 
		nstlim=25000, dt=0.002, 
		ntc=2, ntf=2, 
		cut=10.0, ntb=1, 
		ntpr=500, ntwx=500, 
		ntt=3, gamma_ln=2.0, 
		tempi=0.0, temp0=300.0, 
		ntr=1, restraintmask=&#39;:1-517&#39;, 
		restraint_wt=1.0, 
		nmropt=1 
		/ 
		&#38;wt TYPE=&#39;TEMP0&#39;, 
		istep1=0, istep2=25000, 
		value1=0.1, value2=300.0 / 
		&#38;wt TYPE=&#39;END&#39; / 
		NOTE: Input options: imin=0 run MD; irest=0 run a new simulation; ntx=1 no initial velocities are read from the rst file; nstlim=25000 number of MD steps; dt=0.002 time step (ps); ntc=2 bonds involving hydrogen are constrained using the SHAKE algorithm; ntf=2 forces for the constrained bonds are not calculated; ntwx=500 coordinates are written to the mdcrd file every ntwx steps; ntt=3 Langevin temperature regulation; gamma_ln=2.0 collision frequency for Langevin dynamics (ps&#8722;1); tempi=0.0 initial temperature; temp0=300.0 reference temperature; nmropt=1 parameters specified in an &#38;wt namelist are read; TYPE=&#39;TEMP0&#39; vary the target temperature.</li>
	</ol>
	</li>
</ol>
4. Equilibration
NOTE: This stage is necessary to adjust the density of water and obtain the equilibrium state of the protein.
<ol>
	<li>Perform the equilibration at 300 K without any restraints (500 ps, constant pressure).
	<ol>
		<li>Use equil.in and protein_heat.rst as inputs: pmemd -O -i equil.in -p protein.prmtop 
		-c protein_heat.rst -o protein_equil.out -r protein_equil.rst -x protein_equil.mdcrd.</li>
		<li>Specify options in the input file equil.in: 
		&#38;cntrl 
		imin=0, irest=1, ntx=5, 
		nstlim=250000, 
		dt=0.002, 
		ntc=2, ntf=2, 
		cut=10.0, ntb=2, ntp=1, taup=2.0, 
		ntpr=1000, ntwx=1000, ntwr=50000, 
		ntt=3, gamma_ln=2.0, 
		temp0=300.0 
		/ 
		NOTE: Input options: irest=1 restart the simulation; ntx=5 coordinates and velocities are read from a previously generated rst file; ntb=2 periodic boundaries&#160;are imposed, constant pressure; ntp=1 isotropic pressure scaling; taup=2.0 pressure relaxation time (ps); ntwr=50000 every ntwr steps, the rst file is written, ensuring recovery from a crash.</li>
	</ol>
	</li>
</ol>
5. Production dynamics
<ol>
	<li>After equilibrium has successfully been achieved, carry out a production MD simulation (10 ns or longer) at constant pressure, and generate the trajectory file for subsequent analysis of the protein structure.
	<ol>
		<li>Use prod.in and protein_equil.rst as inputs: pmemd -O -i prod.in -p protein.prmtop 
		-c protein_equil.rst -o protein_prod.out -r protein_prod.rst -x protein_prod.mdcrd.</li>
		<li>Specify options in the input file prod.in: 
		&#38;cntrl 
		imin=0, irest=1, ntx=5, 
		nstlim=5000000, 
		dt=0.002, 
		ntc=2, ntf=2, 
		cut=10.0, ntb=2, ntp=1, taup=2.0, 
		ntpr=1000, ntwx=1000, ntwr=50000, 
		ntt=3, gamma_ln=2.0, 
		temp0=300.0, ig=-1 
		/ 
		NOTE: The parallel version of pmemd (pmemd.MPI) or GPU-accelerated version (pmemd.cuda) can be used on computer clusters and supercomputers. A long MD simulation may be broken into several segments and performed sequentially. It is strongly recommended to set ig=-1 (random seed option) for every simulation restart. The ptraj or cppptraj programs can be used for the analysis and processing of coordinate trajectories. For more information, see the software Users&#39; Manual.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Olsson, M., Zhivotovsky, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Caspases+and+cancer.">Caspases and cancer.</a> Cell Death and Differentiation. 18 (9), 1441-1449 (2011).</li><li>Lavrik, I. N., Golks, A., Krammer, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Caspase:+Pharmacological+manipulation+of+cell+death.">Caspase: Pharmacological manipulation of cell death.</a> Journal of Clinical Investigation. 115 (10), 2665-2672 (2005).</li><li>Degterev, A., Boyce, M., Yuan, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+decade+of+caspases.">A decade of caspases.</a> Oncogene. 22 (53), 8543-8567 (2003).</li><li>Pop, C., Salvesen, G. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+caspases:+Activation,+specificity,+and+regulation.">Human caspases: Activation, specificity, and regulation.</a> Journal of Biological Chemistry. 284 (33), 21777-21781 (2009).</li><li>Zamaraev, A. V., Kopeina, G. S., Prokhorova, E. A., Zhivotovsky, B., Lavrik, I. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Post-translational+modification+of+caspases:+The+other+side+of+apoptosis+regulation.">Post-translational modification of caspases: The other side of apoptosis regulation.</a> Trends in Cell Biology. 27 (5), 322-339 (2017).</li><li>Pearlman, S. M., Serber, Z., Ferrell, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+mechanism+for+the+evolution+of+phosphorylation+sites.">A mechanism for the evolution of phosphorylation sites.</a> Cell. 147 (4), 934-946 (2011).</li><li>Zamaraev, A. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Requirement+for+Serine-384+in+Caspase-2+processing+and+activity.">Requirement for Serine-384 in Caspase-2 processing and activity.</a> Cell Death and Disease. 11 (10), 825 (2020).</li><li>Dagbay, K. B., Hill, M. E., Barrett, E., Hardy, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor-associated+mutations+in+caspase-6+negatively+impact+catalytic+efficiency.">Tumor-associated mutations in caspase-6 negatively impact catalytic efficiency.</a> Biochemistry. 56 (34), 4568-4577 (2017).</li><li>Ando, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer-associated+missense+mutations+of+caspase-8+activate+nuclear+factor-&#954;B+signaling.">Cancer-associated missense mutations of caspase-8 activate nuclear factor-&#954;B signaling.</a> Cancer Science. 104 (8), 1002-1008 (2013).</li><li>Case, D. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> AMBER 2020. , (2020).</li><li>Salomon-Ferrer, R., Case, D. A., Walker, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+overview+of+the+Amber+biomolecular+simulation+package.">An overview of the Amber biomolecular simulation package.</a> WIREs Computational Molecular Science. 3 (2), 198-210 (2013).</li><li>Roe, D. R., Cheatham, T. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PTRAJ+and+CPPTRAJ:+Software+for+processing+and+analysis+of+molecular+dynamics+trajectory+data.">PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data.</a> Journal of Chemical Theory and Computation. 9 (7), 3084-3095 (2013).</li><li>Maier, J. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ff14SB:+Improving+the+accuracy+of+protein+side+chain+and+backbone+parameters+from+ff99SB.">ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB.</a> Journal of Chemical Theory and Computation. 11 (8), 3696-3713 (2015).</li><li>Salomon-Ferrer, R., G&#246;tz, A. W., Poole, D., Le Grand, S., Walker, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Routine+microsecond+molecular+dynamics+simulations+with+AMBER+on+GPUs.+2.+Explicit+solvent+particle+mesh+ewald.">Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh ewald.</a> Journal of Chemical Theory and Computation. 9 (9), 3878-3888 (2013).</li><li>Berman, H. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Protein+Data+Bank.">The Protein Data Bank.</a> Nucleic Acids Research. 28 (1), 235-242 (2000).</li><li>Burley, S. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RCSB+Protein+Data+Bank:+Powerful+new+tools+for+exploring+3D+structures+of+biological+macromolecules+for+basic+and+applied+research+and+education+in+fundamental+biology,+biomedicine,+biotechnology,+bioengineering+and+energy+sciences.">RCSB Protein Data Bank: Powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences.</a> Nucleic Acids Research. 49, 437-451 (2021).</li><li>Martinez, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+graphics:+Bridging+structural+biologists+and+computer+scientists.">Molecular graphics: Bridging structural biologists and computer scientists.</a> Structure. 27 (11), 1617-1623 (2019).</li><li>Lee, T. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GPU-accelerated+molecular+dynamics+and+free+energy+methods+in+Amber18:+Performance+enhancements+and+new+features.">GPU-accelerated molecular dynamics and free energy methods in Amber18: Performance enhancements and new features.</a> Journal of Chemical Information and Modeling. 58 (10), 2043-2050 (2018).</li><li>J&#228;ger, R., Zwacka, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+enigmatic+roles+of+caspases+in+tumor+development.">The enigmatic roles of caspases in tumor development.</a> Cancers. 2 (4), 1952-1979 (2010).</li></ol>

The authors have no conflicts of interest to disclose.

The described MD approach allows for modeling both the wild-type and mutant forms of caspase using the biomolecular simulation packages. Several important issues of the methodology are discussed here. First, a representative crystal structure of caspase needs to be selected from the Protein Data Bank. Importantly, both monomeric and dimeric forms of caspase are acceptable. Choosing high-resolution structures with a minimum number of missing residues is a good idea. The protonation state of some residues can be set manual...

Apoptosis is one of the most widely-studied cellular processes that regulate the morphogenesis and tissue homeostasis of multicellular organisms. Apoptosis can be initiated by a wide range of external or internal stimuli, such as the activation of death receptors, disturbance in the cell cycle signals, DNA damage, endoplasmic reticulum (ER) stress, and various bacterial and viral infections1. The caspases - key apoptotic players - are conventionally classified into two groups: initiators (caspase-2, caspase-8, caspase-9, and caspase-10) and effectors (caspase-3, caspase-6, and caspase-7), depending on their domain structure and the place in the caspase cascade2,3. Upon cell death signals, the initiator caspases interact with adaptor molecules that facilitate proximity-induced dimerization and autoprocessing to form an active enzyme. The effector caspases are activated through cleavage by initiator caspases and perform downstream execution steps by cleaving multiple cellular substrates4.
The maturation and function of the initiator and effector caspases are regulated by a large number of different intracellular mechanisms, among which the post-translational modification plays an indispensable role in cell death modulation5. The addition of modifying groups (phosphorylation, nitrosylation, methylation, or acetylation) or proteins (ubiquitination or SUMOylation) changes the enzymatic activity of caspases or the protein conformation and stability that regulate apoptosis. Site-directed mutagenesis is widely applied to investigate the potential post-translational modification sites and discern their role. A putative modification site is usually replaced by another amino acid, which cannot be further modified. Thus, potentially phosphorylated serine and threonine are mutated to alanine, and lysine ubiquitination sites are replaced with arginine. Another strategy includes substituting an amino acid that particularly mimics post-translational modification (e.g., glutamate and aspartate have been used to mimic phosphorylated serine or threonine)6. However, some of these substitutions located in the high vicinity of an active site or in critical positions could change caspase structure, disturb catalytic activity, and suppress apoptotic cell death7. Similar effects could be observed in cases of tumor-associated missense mutations in caspase genes. For example, the tumor-associated mutation of caspase-6 - R259H - resulted in conformational changes of loops in the substrate-binding pocket, reducing the efficient catalytic turnover of substrates8. The G325A amino acid substitution in caspase-8 identified in head and neck squamous cell carcinoma could hamper caspase-8 activity, which led to the modulation of nuclear factor-kB (NF-kB) signaling and promoted tumorigenesis9.
To assess the potential effect of amino acid substitutions on caspase structure and function, molecular modeling can be applied. The molecular dynamics (MD) approach is described in this work for modeling the wild-type caspase and its mutant forms using the biomolecular simulation package (Amber). The MD method gives a view of the dynamic evolution of the protein structure following the introduction of mutations. Originally developed by Peter Kollman&#39;s group, the Amber package became one of the most popular software tools for biomolecular simulations10,11,12,13. This software is divided into two parts: (1) AmberTools, a collection of programs routinely used for system preparation (atom type assignment, adding hydrogens and explicit-water molecules, etc.) and trajectory analysis; and (2) Amber, which is centered around the pmemd simulation program. AmberTools is a free package (and a prerequisite for installing Amber itself), while Amber is distributed with a separate license and fee structure. Parallel simulations on a supercomputer and/or using graphics processing units (GPUs) can substantially improve the performance for the scientific research of protein structure dynamics14. The latest available software versions are AmberTools21 and Amber20, but the described protocols can also be used with the former versions.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Amber20</td>
			<td>University of California, San Francisco</td>
			<td></td>
			<td>Software for molecular dynamics simulation 
			http://ambermd.org</td>
		</tr>
		<tr>
			<td>AmberTools21</td>
			<td>University of California, San Francisco</td>
			<td></td>
			<td>Software for molecular modeling and analysis 
			http://ambermd.org</td>
		</tr>
	</tbody>
</table>

exploring caspase mutations and post-translational modification by molecular modeling approaches

Apoptosis is a type of programmed cell death that eliminates damaged cells and controls the development and tissue homeostasis of multicellular organisms. Caspases, a family of cysteine proteases, play a key role in apoptosis initiation and execution. The maturation of caspases and their activity is fine-tuned by post-translational modifications in a highly dynamic fashion. To assess the effect of post-translational changes, potential sites are routinely mutated with residues persistent to any modifications. For example, the serine residue is replaced with alanine or aspartic acid. However, such substitutions could alter the caspase active site's conformation, leading to disturbances in catalytic activity and cellular functions. Moreover, mutations of other amino acid residues located in critical positions could also break the structure and functions of caspases and lead to apoptosis perturbation. To avoid the difficulties of employing mutated residues, molecular modeling approaches can be readily applied to estimate the potential effect of amino acid substitutions on caspase structure. The present protocol allows the modeling of both the wild-type caspase and its mutant forms with the biomolecular simulation package (Amber) and supercomputer facilities to test the effect of mutations on the protein structure and function.

The present protocol can be readily applied in studies of post-translational modification of caspases or pathogenic mutations. In this section, the MD modeling workflow is illustrated (Figure 1), which has been successfully used in the study of caspase-27. Using in vitro site-directed mutagenesis of potential phosphorylation sites (Ser/Thr to Ala) and biochemical approaches, it was demonstrated that the Ser384Ala mutation prevented caspase-2 processing and bl...

Watch this Scientific Journal Video about Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches at JoVE.com

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

The present protocol uses a biomolecular simulation package and describes the molecular dynamics (MD) approach for modeling the wild-type caspase and its mutant forms. The MD method allows for assessing the dynamic evolution of the caspase structure and the potential effect of mutations or post-translational modifications.

Apoptosis is a type of programmed cell death that eliminates damaged cells and controls the development and tissue homeostasis of multicellular organisms. ...

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1.2K Views.  Lomonosov Moscow State University. The present protocol uses a biomolecular simulation package and describes the molecular dynamics (MD) approach for modeling the wild-type caspase and its mutant forms. The MD method allows for assessing the dynamic evolution of the caspase structure and the potential effect of mutations or post-translational modifications.

Video: Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Detection of Post-translational Modifications on Native Intact Nucleosomes by ELISA

The genome of eukaryotes exists as chromatin which contains both DNA and proteins. The fundamental unit of chromatin is the nucleosome, which contains 146 base pairs of DNA associated with two each of histones H2A, H2B, H3, and H41. The N-terminal tails of histones are rich in lysine and arginine and are modified post-transcriptionally by acetylation, methylation, and other post-translational modifications (PTMs). The PTM configuration of nucleosomes can affect the transcriptional activity of associated DNA, thus providing a mode of gene regulation that is epigenetic in nature 2,3. We developed a method called nucleosome ELISA (NU-ELISA) to quantitatively determine global PTM signatures of nucleosomes extracted from cells. NU-ELISA is more sensitive and quantitative than western blotting, and is useful to interrogate the epiproteomic state of specific cell types. This video journal article shows detailed procedures to perform NU-ELISA analysis.

Nucleosome ELISA (NU-ELISA) is a sensitive and quantitative method to detect global patterns of post-translational modifications in preparations of native, intact nucleosomes. These modifications include methylations, acetylations, and phosphorylations at specific histone amino acid residues, and hence NU-ELISA provides a global proteomic assay of the overall chromatin modification states of specific cell types.

The genome of eukaryotes exists as chromatin which contains both DNA and proteins. The fundamental unit of chromatin is the nucleosome, which contains 146 ...

Budding Yeast Protein Extraction and Purification for the Study of Function, Interactions, and Post-translational Modifications

Homogenization by bead beating is a fast and efficient way to release DNA, RNA, proteins, and metabolites from budding yeast cells, which are notoriously hard to disrupt. Here we describe the use of a bead mill homogenizer for the extraction of proteins into buffers optimized to maintain the functions, interactions and post-translational modifications of proteins. Logarithmically growing cells expressing the protein of interest are grown in a liquid growth media of choice. The growth media may be supplemented with reagents to induce protein expression from inducible promoters (e.g. galactose), synchronize cell cycle stage (e.g. nocodazole), or inhibit proteasome function (e.g. MG132). Cells are then pelleted and resuspended in a suitable buffer containing protease and/or phosphatase inhibitors and are either processed immediately or frozen in liquid nitrogen for later use. Homogenization is accomplished by six cycles of 20 sec&#160;bead-beating (5.5 m/sec), each followed by one minute incubation on ice. The resulting homogenate is cleared by centrifugation and small particulates can be removed by filtration. The resulting cleared whole cell extract (WCE) is precipitated using 20% TCA for direct analysis of total proteins by SDS-PAGE followed by Western blotting. Extracts are also suitable for affinity purification of specific proteins, the detection of post-translational modifications, or the analysis of co-purifying proteins. As is the case for most protein purification protocols, some enzymes and proteins may require unique conditions or buffer compositions for their purification and others may be unstable or insoluble under the conditions stated. In the latter case, the protocol presented may provide a useful starting point to empirically determine the best bead-beating strategy for protein extraction and purification. We show the extraction and purification of an epitope-tagged SUMO E3 ligase, Siz1, a cell cycle regulated protein that becomes both sumoylated and phosphorylated, as well as a SUMO-targeted ubiquitin ligase subunit, Slx5.

The preparation of high quality yeast cell extracts is a necessary first step in the analysis of individual proteins or entire proteomes. Here we describe a fast, efficient, and reliable homogenization protocol for budding yeast cells that has been optimized to preserve protein functions, interactions, and post-translational modifications.

Homogenization by bead beating is a fast and efficient way to release DNA, RNA, proteins, and metabolites from budding yeast cells, which are notoriously ...

Analysis of Apoptosis in Zebrafish Embryos by Whole-mount Immunofluorescence to Detect Activated Caspase 3

Whole-mount immunofluorescence to detect activated Caspase 3 (Casp3 assay) is useful to identify cells undergoing either intrinsic or extrinsic apoptosis in zebrafish embryos. The whole-mount analysis provides spatial information in regard to tissue specificity of apoptosing cells, although sectioning and/or colabeling is ultimately required to pinpoint the exact cell types undergoing apoptosis. The whole-mount Casp3 assay is optimized for analysis of fixed embryos between the 4-cell stage and 32 hr-post-fertilization and is useful for a number of applications, including analysis of zebrafish mutants and morphants, overexpression of mutant and wild-type mRNAs, and exposure to chemicals. Compared to acridine orange staining, which can identify apoptotic cells in live embryos in a matter of hours, Casp3 and TUNEL assays take considerably longer to complete (2-4 days). However, because of the dynamic nature of apoptotic cell formation and clearance, analysis of fixed embryos ensures accurate comparison of apoptotic cells across multiple samples at specific time points. We have also found the Casp3 assay to be superior to analysis of apoptotic cells by the whole-mount TUNEL assay in regard to cost and reliability. Overall, the Casp3 assay represents a robust, highly reproducible assay in which to analyze apoptotic cells in early zebrafish embryos.

Certain genetic perturbations or exposure to toxins can disrupt normal developmental processes leading to death of specific cell types. The analysis of activated Caspase 3 by whole-mount immunofluorescence in zebrafish embryos reveals stage- and tissue-specific localization of cells specifically undergoing apoptosis.

Whole-mount immunofluorescence to detect activated Caspase 3 (Casp3 assay) is useful to identify cells undergoing either intrinsic or extrinsic apoptosis ...

Identification of Post-translational Modifications of Plant Protein Complexes

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to infection via the recruitment and activation of immune complexes. Activation of immune complexes is associated with post-translational modifications (PTMs) of proteins, such as phosphorylation, glycosylation, or ubiquitination. Understanding how these PTMs are choreographed will lead to a better understanding of how resistance is achieved.
Here we describe a protein purification method for nucleotide-binding leucine-rich repeat (NB-LRR)-interacting proteins and the subsequent identification of their post-translational modifications (PTMs). With small modifications, the protocol can be applied for the purification of other plant protein complexes. The method is based on the expression of an epitope-tagged version of the protein of interest, which is subsequently partially purified by immunoprecipitation and subjected to mass spectrometry for identification of interacting proteins and PTMs.
This protocol demonstrates that: i). Dynamic changes in PTMs such as phosphorylation can be detected by mass spectrometry; ii). It is important to have sufficient quantities of the protein of interest, and this can compensate for the lack of purity of the immunoprecipitate; iii). In order to detect PTMs of a protein of interest, this protein has to be immunoprecipitated to get a sufficient quantity of protein.

We describe here a protocol for the purification and characterization of plant protein complexes. We demonstrate that by immunoprecipitating a single protein within a complex, so we can identify its post-translational modifications and its interacting partners.

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to ...

In Vivo Biosensor Tracks Non-apoptotic Caspase Activity in Drosophila

Caspases are the key mediators of apoptotic cell death via their proteolytic activity. When caspases are activated in cells to levels detectable by available technologies, apoptosis is generally assumed to occur shortly thereafter. Caspases can cleave many functional and structural components to cause rapid and complete cell destruction within a few minutes. However, accumulating evidence indicates that in normal healthy cells the same caspases have other functions, presumably at lower enzymatic levels. Studies of non-apoptotic caspase activity have been hampered by difficulties with detecting low levels of caspase activity and with tracking ultimate cell fate in vivo. Here, we illustrate the use of an ultrasensitive caspase reporter, CaspaseTracker, which permanently labels cells that have experienced caspase activity in whole animals. This in vivo dual color CaspaseTracker biosensor for Drosophila melanogaster transiently expresses red fluorescent protein (RFP) to indicate recent or on-going caspase activity, and permanently expresses green fluorescent protein (GFP) in cells that have experienced caspase activity at any time in the past yet did not die. Importantly, this caspase-dependent in vivo biosensor readily reveals the presence of non-apoptotic caspase activity in the tissues of organ systems throughout the adult fly. This is demonstrated using whole mount dissections of individual flies to detect biosensor activity in healthy cells throughout the brain, gut, malpighian tubules, cardia, ovary ducts and other tissues. CaspaseTracker detects non-apoptotic caspase activity in long-lived cells, as biosensor activity is detected in adult neurons and in other tissues at least 10 days after caspase activation. This biosensor serves as an important tool to uncover the roles and molecular mechanisms of non-apoptotic caspase activity in live animals.

In Vivo Biosensor Tracks Non-apoptotic Caspase Activity in Drosophila

To detect healthy cells in whole animals that contain low levels of caspase activity, the highly sensitive biosensor designated CaspaseTracker was generated for Drosophila. Caspase-dependent biosensor activity is detected in long-lived healthy cells throughout the internal organs of adult animals reared under optimized conditions in the absence of death stimuli.

Caspases are the key mediators of apoptotic cell death via their proteolytic activity. When caspases are activated in cells to levels detectable by ...

Complete Workflow for Analysis of Histone Post-translational Modifications Using Bottom-up Mass Spectrometry: From Histone Extraction to Data Analysis

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone function is mediated by extensive post-translational modification by a myriad of nuclear proteins. These modifications are critical for nuclear integrity as they regulate chromatin structure and recruit enzymes involved in gene regulation, DNA repair and chromosome condensation. Even though a large part of the scientific community adopts antibody-based techniques to characterize histone PTM abundance, these approaches are low throughput and biased against hypermodified proteins, as the epitope might be obstructed by nearby modifications. This protocol describes the use of nano liquid chromatography (nLC) and mass spectrometry (MS) for accurate quantification of histone modifications. This method is designed to characterize a large variety of histone PTMs and the relative abundance of several histone variants within single analyses. In this protocol, histones are derivatized with propionic anhydride followed by digestion with trypsin to generate peptides of 5 - 20 aa in length. After digestion, the newly exposed N-termini of the histone peptides are derivatized to improve chromatographic retention during nLC-MS. This method allows for the relative quantification of histone PTMs spanning four orders of magnitude.

This protocol outlines a fully integrated workflow for characterizing histone post-translational modifications using mass spectrometry (MS). The workflow includes histone purification from cell cultures or tissues, histone derivatization and digestion, MS analysis using nano-flow liquid chromatography and instructions for data analysis. The protocol is designed for completion within 2 - 3 days.

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone ...

Genetic Modification of Cyanobacteria by Conjugation Using the CyanoGate Modular Cloning Toolkit

Cyanobacteria are a diverse group of prokaryotic photosynthetic organisms that can be genetically modified for the renewable production of useful industrial commodities. Recent advances in synthetic biology have led to development of several cloning toolkits such as CyanoGate, a standardized modular cloning system for building plasmid vectors for subsequent transformation or conjugal transfer into cyanobacteria. Here we outline a detailed method for assembling a self-replicating vector (e.g., carrying a fluorescent marker expression cassette) and conjugal transfer of the vector into the cyanobacterial strains Synechocystis sp. PCC 6803 or Synechococcus elongatus UTEX 2973. In addition, we outline how to characterize the performance of a genetic part (e.g., a promoter) using a plate reader or flow cytometry.

Here, we present a protocol describing how to i) assemble a self-replicating vector using the CyanoGate modular cloning toolkit, ii) introduce the vector into a cyanobacterial host by conjugation, and iii) characterize transgenic cyanobacteria strains using a plate reader or flow cytometry.

Cyanobacteria are a diverse group of prokaryotic photosynthetic organisms that can be genetically modified for the renewable production of useful ...

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Studying multiple post-translational modifications (PTMs) of proteins is a crucial step to understand PTM crosstalk and gain more holistic insights into protein function. Despite the importance of multi-PTM enrichment studies, few studies investigate more than one PTM at a time, due partially to the expenses, time, and large protein quantities required to perform multiple global proteomic analysis of PTMs. The &#34;one-pot&#34; affinity enrichment detailed in this protocol overcomes these barriers by permitting the simultaneous identification and quantification of peptides with lysine residues containing acetylation and succinylation PTMs with low amounts of sample input. The protocol involves preparation of protein lysate from mouse livers of SIRT5 knockout mice, performance of trypsin digestion, enrichment for PTMs, and performance of mass spectrometric analysis using a data-independent acquisition (DIA) workflow. Because this workflow allows for the enrichment of two PTMs from the same sample simultaneously, it provides a practical tool to study PTM crosstalk without requiring large amounts of samples, and it greatly reduces the time required for sample preparation, data acquisition, and analysis. The DIA component of the workflow provides comprehensive PTM-specific information. This is particularly important when studying PTM site localization, as DIA provides comprehensive sets of fragment ions that can be computationally deciphered to differentiate between different PTM localization isoforms.

This workflow describes the performance of time- and cost-efficient enrichment of multiple protein post-translational modifications (PTMs) simultaneously for quantitative global proteomic analysis. The protocol utilizes peptide-level PTM enrichment with multiple conjugated antibodies, followed by data-independent acquisition mass spectrometry analysis to gain biological insights into PTM crosstalk.

Studying multiple post-translational modifications (PTMs) of proteins is a crucial step to understand PTM crosstalk and gain more holistic insights into ...

Exploring Adipose Tissue Structure by Methylsalicylate Clearing and 3D Imaging

Obesity is a major worldwide public health issue that increases the risk to develop cardiovascular diseases, type-2 diabetes, and liver diseases. Obesity is characterized by an increase in adipose tissue (AT) mass due to adipocyte hyperplasia and/or hypertrophia, leading to profound remodeling of its three-dimensional structure. Indeed, the maximal capacity of AT to expand during obesity is pivotal to the development of obesity-associated pathologies. This AT expansion is an important homeostatic mechanism to enable adaptation to an excess of energy intake and to avoid deleterious lipid spillover to other metabolic organs, such as muscle and liver. Therefore, understanding the structural remodeling that leads to the failure of AT expansion is a fundamental question with high clinical applicability. In this article, we describe a simple and fast clearing method that is routinely used in our laboratory to explore the morphology of mouse and human white adipose tissue by fluorescent imaging. This optimized AT clearing method is easily performed in any standard laboratory equipped with a chemical hood, a temperature-controlled orbital shaker and a fluorescent microscope. Moreover, the chemical compounds used are readily available. Importantly, this method allows one to resolve the 3D AT structure by staining various markers to specifically visualize the adipocytes, the neuronal and vascular networks, and the innate and adaptive immune cells distribution.

Here, we describe a simple, inexpensive and fast clearing method to resolve the 3D structure of both mouse and human white adipose tissue using a combination of markers to visualize vasculature, nuclei, immune cells, neurons, and lipid-droplet coat proteins by fluorescent imaging.

Obesity is a major worldwide public health issue that increases the risk to develop cardiovascular diseases, type-2 diabetes, and liver diseases. Obesity ...

Global Level Quantification of Histone Post-Translational Modifications in a 3D Cell Culture Model of Hepatic Tissue

Flat cultures of mammalian cells are a widely used in vitro approach for understanding cell physiology, but this system is limited in modeling solid tissues due to unnaturally rapid cell replication. This is particularly challenging when modeling mature chromatin, as fast replicating cells are frequently involved in DNA replication and have a heterogeneous polyploid population. Presented below is a workflow for modeling, treating, and analyzing quiescent chromatin modifications using a three-dimensional (3D) cell culture system. Using this protocol, hepatocellular carcinoma cell lines are grown as reproducible 3D spheroids in an incubator providing active nutrient diffusion and low shearing forces. Treatment with sodium butyrate and sodium succinate induced an increase in histone acetylation and succinylation, respectively. Increases in levels of histone acetylation and succinylation are associated with a more open chromatin state. Spheroids are then collected for isolation of cell nuclei, from which histone proteins are extracted for the analysis of their post-translational modifications. Histone analysis is performed via liquid chromatography coupled online with tandem mass spectrometry, followed by an in-house computational pipeline. Finally, examples of data representation to investigate the frequency and occurrence of combinatorial histone marks are shown.

This protocol outlines how a three-dimensional cell culture system can be used to model, treat, and analyze chromatin modifications in a near-physiological state.

Flat cultures of mammalian cells are a widely used in vitro approach for understanding cell physiology, but this system is limited in modeling solid ...