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The accuracy of sequence-based tertiary contact predictions was assessed in a blind prediction experiment at the CASP13 meeting. After 4 years of significant improvements in prediction accuracy, another dramatic advance has taken place since CASP12 was held 2 years ago. The precision of predicting the top L/5 contacts in the free modeling category, where L is the corresponding length of the protein in residues, has exceeded 70%. As a comparison, the best-performing group at CASP12 with a 47% precision would have finished below the top 1/3 of the CASP13 groups. Extensively trained deep neural network approaches dominate the top performing algorithms, which appear to efficiently integrate information on coevolving residues and interacting fragments or possibly utilize memories of sequence similarities and sometimes can deliver accurate results even in the absence of virtually any target specific evolutionary information. If the current performance is evaluated by F-score on L contacts, it stands around 24% right now, which, despite the tremendous impact and advance in improving its utility for structure modeling, also suggests that there is much room left for further improvement.

With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest-to-date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.

The proton-coupled folate transporter (PCFT) mediates intestinal absorption of folates and their transport from blood to cerebrospinal fluid across the choroid plexus. Substitutions at Asp-109 in the first intracellular loop between the first and second transmembrane domains (TMDs) abolish PCFT function, but protein expression and trafficking to the cell membrane are retained. Here, we used site-directed mutagenesis, the substituted-cysteine accessibility method, functional analyses, and homology modeling to determine whether the D109A substitution locks PCFT in one of its conformational states. Cys-substituted residues lining the PCFT aqueous translocation pathway and accessible in WT PCFT to the membrane-impermeable cysteine-biotinylation reagent, MTSEA-biotin, lost accessibility when introduced into the D109A scaffold. Substitutions at Gly-305 located exofacially within the eighth TMD, particularly with bulky residues, when introduced into the D109A scaffold largely restored function and MTSEA-biotin accessibility to Cys-substituted residues within the pathway. Likewise, Ser-196 substitution in the fifth TMD, predicted by homology modeling to be in proximity to Gly-305, also partially restored function found in solute transporters, is critical to oscillation of the carrier among its conformational states. Substitutions at Asp-109 and Gly-112 lock PCFT in an inward-open conformation, resulting in the loss of function. However, the integrity of the locked protein is preserved, indicated by the restoration of function after insertion of a second "unlocking" mutation. and accessibility. Similarly, the inactivating G112K substitution within the first intracellular loop was partially reactivated by introducing the G305L substitution. These data indicate that the first intracellular loop, with a sequence identical to "motif A" (GXXXDXXGR(R/K)).

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data, this approach also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also shows that methods for protein binding interface predictions should perform above approximately F‐score = 0.7 accuracy level to capture the biological function of a protein. [ABSTRACT FROM AUTHOR]

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today's UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849-851, 2007) has resulted from systematic targeting of large families. PSI's per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another approximately15 years to cover most sequences in the current UniProt database.

MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/).

Glaucoma is a leading cause of irreversible blindness, with advanced age being the single most significant risk factor. However, the mechanisms underlying the relationship between aging and glaucoma remain unclear. Genome‐wide association studies (GWAS) have successfully identified genetic variants strongly associated with increased glaucoma risk. Understanding how these variants function in pathogenesis is crucial for translating genetic associations into molecular mechanisms and, ultimately, clinical applications. The chromosome 9p21.3 locus is among the most replicated glaucoma risk loci discovered by GWAS. Nonetheless, the absence of protein‐coding genes in the locus makes interpreting the disease association challenging, leaving the causal variant and molecular mechanism elusive. In this study, we report the identification of a functional glaucoma risk variant, rs6475604. By employing computational and experimental methods, we demonstrated that rs6475604 resides in a repressive regulatory element. Risk allele of rs6475604 disrupts the binding of YY1, a transcription factor known to repress the expression of a neighboring gene in 9p21.3, p16INK4A, which plays a crucial role in cellular senescence and aging. These findings suggest that the glaucoma disease variant contributes to accelerated senescence, providing a molecular link between glaucoma risk and an essential cellular mechanism for human aging. [ABSTRACT FROM AUTHOR]

Cross-linking analysis of protein complexes and structures by tandem mass spectrometry (MS/MS) has advantages in speed, sensitivity, specificity, and the capability of handling complicated protein assemblies. However, detection and accurate assignment of the cross-linked peptides are often challenging due to their low abundance and complicated fragmentation behavior in collision-induced dissociation (CID). To simplify the MS analysis and improve the signal-to-noise ratio of the cross-linked peptides, we developed a novel peptide enrichment strategy that utilizes a crass-linker with a cryptic thiol group and using beads modified with a photocleavable cross-linker. The functional cross-linkers were designed to react with the primary amino groups in proteins. Human serum albumin was used as a model protein to detect intra- and intermolecular cross-linkages. Use of this protein-free selective retrieval method eliminates the contamination that can result from avidin--biotin based retrieval systems and simplifies data analysis. These features may make the method suitable to investigate protein--protein interactions in biological samples.

Author(s): Longyue L. Cao [1, 2]; Dario F. Riascos-Bernal [1, 2]; Prameladevi Chinnasamy [1, 2]; Charlene M. Dunaway [1, 2]; Rong Hou [1, 2]; Mario A. Pujato [3]; Brian P. [...]