Three independent 100-ns MD simulations in aqueous solution were conducted starting from the crystal structure of each protein

Three independent 100-ns MD simulations in aqueous solution were conducted starting from the crystal structure of each protein. development, CHARMM-GUI has been widely used in the biomolecular modeling and simulation community, and it has grown into a platform of web-based tools for simulations: for free energy perturbation molecular dynamics (FEP/MD) simulations for protein-ligand binding affinity calculations (Sunhwan Jo, Jiang, Lee, Roux, & Im, 2013), for protein-micelle complex simulation system generation (Cheng, Jo, Lee, Klauda, & Im, 2013), ion simulator CDK4 for Brownian dynamics of ions across ion channels (K. I. Lee et al., 2012), for preparation of simulation systems containing carbohydrates or proteoglycans (Sunhwan Jo, Song, Desaire, MacKerell Jr, & Im, 2011), and recently, for coarse-grained simulation system preparation (Qi et al., 2014). BMN673 Here, we describe the newest functionalities that have been integrated into CHARMM-GUI (Sunhwan Jo et al., 2013) for further ranking of the poses (Figure 3). Open in a separate window Figure 3 (A) Ligand structures. (B) Schematic of the docking and FEP/MD protocol used by Im and co-workers (H. S. Lee et al., 2012). (C) The correlation between binding affinity of near-native poses and the nonnative poses. The FEP/MD method can discriminate near-native and non-native poses better than a docking score. The figures are reproduced with permission from the Journal of Chemical Information and Modeling. The target small molecules are antagonists of MDM2 and MDMX. Figure 3A shows the chemical structures BMN673 of the small molecules used in their study, and the FF parameters were generated using the CGenFF option without any further modification. The calculated binding free energies for MDM2 complexes were overestimated compared to experimental measurements (Figure 3C) mainly due to the difficulties in sampling highly flexible apo-MDM2 conformations within the simulation timescale. Nonetheless, the FEP/MD binding free energy calculations are more promising in discriminating binders from nonbinders than commonly used docking scores (Figures 3BCC). In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions. Therefore, CHARMM-GUI is expected to be useful as a platform that can rapidly prepare necessary FF parameters of small molecules of interest with help of other tools. Setting up such sophisticated simulations can allow researchers to tackle more complex biological problems of protein-ligand interactions. 3. MTS REAGENTS MTS reagents are often used for protein structure and function studies. Their use includes labeling and blocking groups, cross-linking groups, affinity-labeling groups, and reporter groups for chemical modification of peptides and proteins. MTS reagents are introduced to a specific site in a protein through site-directed mutagenesis (Hubbell, Mchaourab, Altenbach, & Lietzow, 1996). These reagents react very rapidly and specifically with cysteine residues, converting cysteine sulfhydryls to cysteine disulfide bonds. MTS reagents of cysteine residues may produce a measurable change in different protein functional states, which BMN673 can be measured by various biophysical techniques. For example, MTSSL (1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl methanethiosulfonate; CYR1 in Figure 4) is an MTS reagent that is widely used as a spin-label probe in ESR (electron spin resonance) spectroscopy. MTSSL has an unpaired electron, which offers a very strong signal in the ESR spectrum that provides valuable information about the structure, dynamics, and function of a protein system. In particular, site-specific mutagenesis with MTS reagents has proved to be a very useful technique in characterizing the structure-function relationship of membrane proteins, such as ion channels and transporter proteins, as well as enzymes and receptors (D. D. Roberts, Lewis, Ballou, Olson, & Shafer, 1986; Chen, LiuChen, & Rudnick, 1997; Perozo, Cortes, & Cuello, 1998; Choi et al., 2000; Tombola, Pathak, & Isacoff, 2006; Hvorup et al., 2007; Forrest et al., 2008; J. A. Roberts et al., 2008; Jeschke, 2012; Kazmier et al., 2014; Raghuraman, Islam, Mukherjee, Roux, & Perozo, 2014). Since many biophysical experiments are routinely performed with these MTS reagents, it is often necessary to introduce them into proteins for the purpose of MD simulation. Keeping this in mind, the FF parameters for a number of MTS reagents have been incorporated into CHARMM-GUI, which is expected to help users to readily prepare initial systems and simulation input files for MD simulation with selected MTS reagents. Open in a separate window Figure 4 MTS side chains.