Optimal selection of suitable templates in protein interface prediction.

MOTIVATION: Molecular-level classification of protein-protein interfaces can greatly assist in functional characterization and rational drug design. The most accurate protein interface predictions rely on finding homologous proteins with known interfaces since most interfaces are conserved within the same protein family. The accuracy of these template-based prediction approaches depends on the correct choice of suitable templates. Choosing the right templates in the immunoglobulin superfamily (IgSF) is challenging because its members share low sequence identity and display a wide range of alternative binding sites despite structural homology. RESULTS: We present a new approach to predict protein interfaces. First, template-specific, informative evolutionary profiles are established using a mutual information-based approach. Next, based on the similarity of residue level conservation scores derived from the evolutionary profiles, a query protein is hierarchically clustered with all available template proteins in its superfamily with known interface definitions. Once clustered, a subset of the most closely related templates is selected, and an interface prediction is made. These initial interface predictions are subsequently refined by extensive docking. This method was benchmarked on 51 IgSF proteins and can predict nontrivial interfaces of IgSF proteins with an average and median F-score of 0.64 and 0.78, respectively. We also provide a way to assess the confidence of the results. The average and median F-scores increase to 0.8 and 0.81, respectively, if 27% of low confidence cases and 17% of medium confidence cases are removed. Lastly, we provide residue level interface predictions, protein complexes, and confidence measurements for singletons in the IgSF. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at: https://gitlab.com/fiserlab.org/interdct_with_refinement.

miRNA-mediated loss of m6A increases nascent translation in glioblastoma.

Within the glioblastoma cellular niche, glioma stem cells (GSCs) can give rise to differentiated glioma cells (DGCs) and, when necessary, DGCs can reciprocally give rise to GSCs to maintain the cellular equilibrium necessary for optimal tumor growth. Here, using ribosome profiling, transcriptome and m6A RNA sequencing, we show that GSCs from patients with different subtypes of glioblastoma share a set of transcripts, which exhibit a pattern of m6A loss and increased protein translation during differentiation. The target sequences of a group of miRNAs overlap the canonical RRACH m6A motifs of these transcripts, many of which confer a survival advantage in glioblastoma. Ectopic expression of the RRACH-binding miR-145 induces loss of m6A, formation of FTO/AGO1/ILF3/miR-145 complexes on a clinically relevant tumor suppressor gene (CLIP3) and significant increase in its nascent translation. Inhibition of miR-145 maintains RRACH m6A levels of CLIP3 and inhibits its nascent translation. This study highlights a critical role of miRNAs in assembling complexes for m6A demethylation and induction of protein translation during GSC state transition.

INTERCAAT: identifying interface residues between macromolecules.

SUMMARY: The Interface Contact definition with Adaptable Atom Types (INTERCAAT) was developed to determine the atomic interactions between molecules that form a known three dimensional structure. First, INTERCAAT creates a Voronoi tessellation where each atom acts as a seed. Interactions are defined by atoms that share a hyperplane and whose distance is less than the sum of each atoms' Van der Waals radii plus the diameter of a solvent molecule. Interacting atoms are then classified and interactions are filtered based on compatibility. INTERCAAT implements an adaptive atom classification method; therefore, it can explore interfaces between a variety macromolecules. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at: https://gitlab.com/fiserlab.org/intercaat. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic resistance to purine nucleoside phosphorylase inhibition in Plasmodium falciparum.

Plasmodium falciparum causes the most lethal form of human malaria and is a global health concern. The parasite responds to antimalarial therapies by developing drug resistance. The continuous development of new antimalarials with novel mechanisms of action is a priority for drug combination therapies. The use of transition-state analog inhibitors to block essential steps in purine salvage has been proposed as a new antimalarial approach. Mutations that reduce transition-state analog binding are also expected to reduce the essential catalytic function of the target. We have previously reported that inhibition of host and P. falciparum purine nucleoside phosphorylase (PfPNP) by DADMe-Immucillin-G (DADMe-ImmG) causes purine starvation and parasite death in vitro and in primate infection models. P. falciparum cultured under incremental DADMe-ImmG drug pressure initially exhibited increased PfPNP gene copy number and protein expression. At increased drug pressure, additional PfPNP gene copies appeared with point mutations at catalytic site residues involved in drug binding. Mutant PfPNPs from resistant clones demonstrated reduced affinity for DADMe-ImmG, but also reduced catalytic efficiency. The catalytic defects were partially overcome by gene amplification in the region expressing PfPNP. Crystal structures of native and mutated PfPNPs demonstrate altered catalytic site contacts to DADMe-ImmG. Both point mutations and gene amplification are required to overcome purine starvation induced by DADMe-ImmG. Resistance developed slowly, over 136 generations (2136 clonal selection). Transition-state analog inhibitors against PfPNP are slow to induce resistance and may have promise in malaria therapy.

Assessment of chemical-crosslink-assisted protein structure modeling in CASP13.

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.

Crk at the quarter century mark: perspectives in signaling and cancer.

The Crk adaptor protein, discovered 25 years ago as the transforming gene (v-crk) product encoded by the CT10 avian retrovirus, has made a great impact on the field of signal transduction. By encoding an oncoprotein that contained a viral gag protein fused to only SH2 and SH3 domains, v-Crk demonstrated the significance of SH2 and SH3 domains in oncogenic signaling by their virtue of binding in a sequence-specific context to organize and assemble protein networks. In more recent years, the cellular homologs of Crk (Crk II, Crk I, and CrkL) have been extensively studied, and shown to have critical functions in a wide spectrum of biological and pathological processes that include cell motility, invasion, survival, bacterial pathogenesis, and the efferocytosis of apoptotic cells. Clinically, Crk proteins are implicated in the aggressive behavior of human cancers, including adenocarcinomas of the lung, breast, and stomach, as well as in sarcomas and gliomas. Over-expression of Crk proteins in human cancers has led to a renewed interest in both their signal transduction pathways and mechanisms of up-regulation. This prospect summarizes recent developments in Crk biology, including new structural and biochemical roles for the atypical carboxyl-terminal SH3 (SH3C) domain, revelations regarding the molecular differences between Crk II and Crk L, and the significance of Crk expression in stratified human tumor samples.

Protein structure based prediction of catalytic residues.

BACKGROUND: Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. RESULTS: We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. CONCLUSIONS: We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Chi3l1 Is a Modulator of Glioma Stem Cell States and a Therapeutic Target in Glioblastoma.

Chitinase 3-like 1 (Chi3l1) is a secreted protein that is highly expressed in glioblastoma. Here, we show that Chi3l1 alters the state of glioma stem cells (GSC) to support tumor growth. Exposure of patient-derived GSCs to Chi3l1 reduced the frequency of CD133+SOX2+ cells and increased the CD44+Chi3l1+ cells. Chi3l1 bound to CD44 and induced phosphorylation and nuclear translocation of ß-catenin, Akt, and STAT3. Single-cell RNA sequencing and RNA velocity following incubation of GSCs with Chi3l1 showed significant changes in GSC state dynamics driving GSCs towards a mesenchymal expression profile and reducing transition probabilities towards terminal cellular states. ATAC-seq revealed that Chi3l1 increases accessibility of promoters containing a Myc-associated zinc finger protein (MAZ) transcription factor footprint. Inhibition of MAZ downregulated a set of genes with high expression in cellular clusters that exhibit significant cell state transitions after treatment with Chi3l1, and MAZ deficiency rescued the Chi3L-induced increase of GSC self-renewal. Finally, targeting Chi3l1 in vivo with a blocking antibody inhibited tumor growth and increased the probability of survival. Overall, this work suggests that Chi3l1 interacts with CD44 on the surface of GSCs to induce Akt/ß-catenin signaling and MAZ transcriptional activity, which in turn upregulates CD44 expression in a pro-mesenchymal feed-forward loop. The role of Chi3l1 in regulating cellular plasticity confers a targetable vulnerability to glioblastoma. SIGNIFICANCE: Chi3l1 is a modulator of glioma stem cell states that can be targeted to promote differentiation and suppress growth of glioblastoma.

A Designer Quest for the Achilles' Heel of Influenza.

Monoclonal antibodies are attractive but, in certain applications, limited therapeutic modalities due to their large size and high specificity. In this issue of Structure, Sevy at al. describe a computationally designed cyclic peptide mimicking the CDRH3 loop of the C05 antibody against influenza showing the potential utility of designer biologics.

M4T: a comparative protein structure modeling server.

Multiple Mapping Method with Multiple Templates (M4T) (http://www.fiserlab.org/servers/m4t) is a fully automated comparative protein structure modeling server. The novelty of M4T resides in two of its major modules, Multiple Templates (MT) and Multiple Mapping Method (MMM). The MT module of M4T selects and optimally combines the sequences of multiple template structures through an iterative clustering approach that takes into account the 'unique' contribution of each template, its sequence similarity to other template sequences and to the target sequences, and the quality of its experimental resolution. MMM module is a sequence-to-structure alignment method that is aimed at improving the alignment accuracy, especially at lower sequence identity levels. The current implementation of MMM takes inputs from three profile-to-profile-based alignment methods and iteratively compares and ranks alternatively aligned regions according to their fit in the structural environment of the template structure. The performance of M4T was benchmarked on CASP6 comparative modeling target sequences and on a larger independent test set and showed a favorable performance to current state-of-the-art methods.

Comparative protein structure modeling by combining multiple templates and optimizing sequence-to-structure alignments.

MOTIVATION: Two major bottlenecks in advancing comparative protein structure modeling are the efficient combination of multiple template structures and the generation of a correct input target-template alignment. RESULTS: A novel method, Multiple Mapping Method with Multiple Templates (M4T) is introduced that implements an algorithm to automatically select and combine Multiple Template structures (MT) and an alignment optimization protocol (Multiple Mapping Method, MMM). The MT module of M4T selects and combines multiple template structures through an iterative clustering approach that takes into account the 'unique' contribution of each template, their sequence similarity among themselves and to the target sequence, and their experimental resolution. MMM is a sequence-to-structure alignment method that optimally combines alternatively aligned regions according to their fit in the structural environment of the template structure. The resulting M4T alignment is used as input to a comparative modeling module. The performance of M4T has been benchmarked on CASP6 comparative modeling target sequences and on a larger independent test set, and showed favorable performance to current state of the art methods.

MMM: a sequence-to-structure alignment protocol.

MOTIVATION: Accurate alignment of a target sequence to a template structure continues to be a bottleneck in producing good quality comparative protein structure models. RESULTS: Multiple Mapping Method (MMM) is a comparative protein structure modeling server with an emphasis on a novel alignment optimization protocol. MMM takes inputs from five profile-to-profile based alignment methods. The alternatively aligned regions from the input alignment set are combined according to their fit in the structural environment of the template structure. The resulting, optimally spliced MMM alignment is used as input to an automated comparative modeling module to produce a full atom model. AVAILABILITY: The MMM server is freely accessible at http://www.fiserlab.org/servers/mmm

Transactivation of Abl by the Crk II adapter protein requires a PNAY sequence in the Crk C-terminal SH3 domain.

To gain a better understanding of how Crk II regulates the function of the Abl tyrosine kinase, we explored the function of the C-terminal linker and SH3 domain, a region of Crk II that is still poorly understood. Molecular modeling, tryptophan fluorescence, and covariation sequence alignment indicate that the Crk-SH3-C has a unique binding groove and RT loop not observed in typical SH3 domains. Based on these models, we made a series of mutations in the linker and in residues predicted to destabilize the putative binding pocket and RT loop. In Abl transactivation assays, Y222F and P225A mutations in the linker resulted in strong transactivation of Abl by Crk II. However, mutations predicted to be at the surface of the Crk SH3-C were not activators of Abl. Interestingly, combinations of activating mutations of Crk II with mutations in the highly conserved PNAY sequence in the SH3-C inactivated the activating mutations, suggesting that the SH3-C is necessary for activation. Our data provide insight into the role of highly conserved residues in the Crk-SH3-C, suggesting a mechanism for how the linker and the Crk-SH3-C function in the transactivation of the Abl tyrosine kinase.

PSI-2: structural genomics to cover protein domain family space.

One major objective of structural genomics efforts, including the NIH-funded Protein Structure Initiative (PSI), has been to increase the structural coverage of protein sequence space. Here, we present the target selection strategy used during the second phase of PSI (PSI-2). This strategy, jointly devised by the bioinformatics groups associated with the PSI-2 large-scale production centers, targets representatives from large, structurally uncharacterized protein domain families, and from structurally uncharacterized subfamilies in very large and diverse families with incomplete structural coverage. These very large families are extremely diverse both structurally and functionally, and are highly overrepresented in known proteomes. On the basis of several metrics, we then discuss to what extent PSI-2, during its first 3 years, has increased the structural coverage of genomes, and contributed structural and functional novelty. Together, the results presented here suggest that PSI-2 is successfully meeting its objectives and provides useful insights into structural and functional space.

Pentapeptide repeat proteins.

The pentapeptide repeat protein (PRP) family has more than 500 members in the prokaryotic and eukaryotic kingdoms. These proteins are composed of, or contain domains composed of, tandemly repeated amino acid sequences with a consensus sequence of [S,T,A,V][D,N][L,F][S,T,R][G]. The biochemical function of the vast majority of PRP family members is unknown. The three-dimensional structure of the first member of the PRP family was determined for the fluoroquinolone resistance protein (MfpA) from Mycobacterium tuberculosis. The structure revealed that the pentapeptide repeats encode the folding of a novel right-handed quadrilateral beta-helix. MfpA binds to DNA gyrase and inhibits its activity. The rod-shaped, dimeric protein exhibits remarkable similarity in size, shape, and electrostatics to DNA.

A novel role for the immunophilin FKBP52 in copper transport.

FK506-binding protein 52 (FKBP52) is an immunophilin that possesses peptidylprolyl cis/trans-isomerase (PPIase) activity and is a component of a subclass of steroid hormone receptor complexes. Several recent studies indicate that immunophilins can regulate neuronal survival and nerve regeneration although the molecular mechanisms are poorly understood. To investigate the function of FKBP52 in the nervous system, we employed a yeast two-hybrid strategy using the PPIase domain (domain I) as bait to screen a neonatal rat dorsal root ganglia cDNA expression library. We identified an interaction between FKBP52 domain I and Atox1, a copper-binding metallochaperone. Atox1 interacts with Menkes disease protein and Wilson disease protein (WD) and functions in copper efflux. The interaction between FKBP52 and Atox1 was observed in both glutathione S-transferase pull-down experiments and when proteins were ectopically expressed in human embryonic kidney (HEK) 293T cells and was sensitive to FK506. Interestingly, the FKBP52/Atox1 interaction was enhanced when HEK 293T cells were cultured in copper-supplemented medium and decreased in the presence of the copper chelator, bathocuproine disulfate, suggesting that the interaction is regulated in part by intracellular copper. Overexpression of FKBP52 increased rapid copper efflux in (64)Cu-loaded cells, as did the overexpression of WD transporter. Taken together, our present findings suggest that FKBP52 is a component of the copper efflux machinery, and in so, may also promote neuroprotection from copper toxicity.

High-throughput computational and experimental techniques in structural genomics.

Structural genomics has as its goal the provision of structural information for all possible ORF sequences through a combination of experimental and computational approaches. The access to genome sequences and cloning resources from an ever-widening array of organisms is driving high-throughput structural studies by the New York Structural Genomics Research Consortium. In this report, we outline the progress of the Consortium in establishing its pipeline for structural genomics, and some of the experimental and bioinformatics efforts leading to structural annotation of proteins. The Consortium has established a pipeline for structural biology studies, automated modeling of ORF sequences using solved (template) structures, and a novel high-throughput approach (metallomics) to examining the metal binding to purified protein targets. The Consortium has so far produced 493 purified proteins from >1077 expression vectors. A total of 95 have resulted in crystal structures, and 81 are deposited in the Protein Data Bank (PDB). Comparative modeling of these structures has generated >40,000 structural models. We also initiated a high-throughput metal analysis of the purified proteins; this has determined that 10%-15% of the targets contain a stoichiometric structural or catalytic transition metal atom. The progress of the structural genomics centers in the U.S. and around the world suggests that the goal of providing useful structural information on most all ORF domains will be realized. This projected resource will provide structural biology information important to understanding the function of most proteins of the cell.