We show that the origin of this failure is a result of using mass-dependent features to fit the THF MM force field, which unintentionally biases the bonded terms of the force field to represent only the isotopologue used during the original force-field parameterization. In addition, we make use of our isotopologue-corrected force field for D8THF to examine the molecular origins of the isotope-dependent loss of the THF-water miscibility gap.Proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases; however, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data generated by a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched twice using MSGF+ database matching, with and without a dynamic +0.9840 Da mass shift modification on amino acids asparagine, glutamine, and arginine (NQR).  https://www.selleckchem.com/products/nutlin-3a.html  Consequently, each spectrum generates two peptide-to-spectrum matches (PSMs) with MSGF+ scores, which were used for the Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR) of modified peptides, a "target-mock" strategy was applied in which data sets were searched against a concatenated database containing "real-modified" (+0.9840 Da) and "mock-modified" (+1.0227 Da) peptide masses. The FDR was controlled to ∼2% using a Delta Score filter value greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score values contained deamidated/citrullinated fragments in their MS/MS spectra. Many citrullinated sites identified in this study were biochemically confirmed as autoimmunogenic epitopes of autoimmune diseases in literature. The results demonstrated that in situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data using this dual-search Delta Score strategy. Raw MS data is available at ProteomeXchange (PXD010150).Cryptic pockets are protein cavities that remain hidden in resolved apo structures and generally require the presence of a co-crystallized ligand to become visible. Finding new cryptic pockets is crucial for structure-based drug discovery (SBDD) in order to identify new ways of modulating protein activity and thus expand the druggable space. We present here a new method and associated web application leveraging mixed-solvent molecular dynamics (MD) simulations using benzene as a hydrophobic probe to detect cryptic pockets. Our all-atom MD-based workflow was systematically tested on 18 different systems and 5 additional kinases and represents the largest validation study of this kind. CrypticScout identifies benzene probe binding hotspots on a protein surface by mapping probe occupancy, residence time and the benzene occupancy re-weighed by the residence time. The method is presented to the scientific community in a web application available via www.playmolecule.org using a distributed computing infrastructure to perform the simulations.The number of high-resolution structures of protein complexes obtained using cryo-electron microscopy (cryo-EM) is increasing rapidly. Cryo-EM maps of large macromolecular complexes frequently contain regions resolved at different resolution levels, and modeling atomic structures de novo can be difficult for domains determined at worse than 5 Å in the absence of atomic information from other structures. Here we describe the details and step-by-step decisions in the strategy we followed to model the RUVBL2-binding domain (RBD), a 14 kDa domain at the C-terminus of RNA Polymerase II associated protein 3 (RPAP3) for which atomic information was not available. Modeling was performed on a cryo-EM map at 4.0-5.5 Å resolution, integrating information from secondary structure predictions, homology modeling, restraints from cross-linked mass spectrometry, and molecular dynamics (MD) in AMBER. Here, we compare our model with the structure of RBD determined by NMR to evaluate our strategy. We also perform new MD simulations to describe important residues mediating the interaction of RBD with RUVBL2 and analyze their conservation in RBD homologous domains. Our approach and its evaluation can serve as an example to address the analysis of medium resolution regions in cryo-EM maps.In structure-based drug design (SBDD), the molecular mechanics generalized Born surface area (MM/GBSA) approach has been widely used in ranking the binding affinity of small molecule ligands. However, an accurate estimation of protein-ligand binding affinity still remains a challenge due to the intrinsic limitation of the standard generalized Born (GB) model used in MM/GBSA. In this study, we proposed and evaluated the MM/GBSA approach based on a variable dielectric generalized Born (VDGB) model using residue-type-based dielectric constants. In the VDGB model, different dielectric values were assigned for the three types of protein residues, and the magnitude of the dielectric constants for residue types follows this order charged ≥ polar ≥ nonpolar. We found that MM/GBSA based on a VDGB model (MM/GBSAVDGB) with an optimal dielectric constant of 4.0 for the charged residues and 1.0 for the noncharged residues together with a net-charge-dependent dielectric value for ligands achieved better predictions as judged by Pearson's correlation coefficient than the standard MM/GBSA with a uniform solute dielectric constant of 4.0 for the training set of 130 protein-ligand complexes. The prediction on the test set with 165 protein-ligand complexes also validated the better performance of MM/GBSAVDGB. Moreover, this method exhibited potential in predicting the relative binding free energies for multiple ligands against the same target. Furthermore, we found that rational truncation of protein residues far from the binding site can significantly speed up the MM/GBSAVDGB calculations, while it almost does not influence the prediction accuracy. Therefore, it is feasible to implement the system-truncated MM/GBSAVDGB as a scoring function for SBDD.