Progress in the Prediction of pKa Values in Proteins

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa-cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6–10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pKa calculations, emphasizing methods that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations

AMBRA1 regulates cyclin D to guard S-phase entry and genomic integrity

Mammalian development, adult tissue homeostasis and the avoidance of severe diseases including cancer require a properly orchestrated cell cycle, as well as error-free genome maintenance. The key cell-fate decision to replicate the genome is controlled by two major signalling pathways that act in parallel-the MYC pathway and the cyclin D-cyclin-dependent kinase (CDK)-retinoblastoma protein (RB) pathway(1,2). Both MYC and the cyclin D-CDK-RB axis are commonly deregulated in cancer, and this is associated with increased genomic instability. The autophagic tumour-suppressor protein AMBRA1 has been linked to the control of cell proliferation, but the underlying molecular mechanisms remain poorly understood. Here we show that AMBRA1 is an upstream master regulator of the transition from G1 to S phase and thereby prevents replication stress. Using a combination of cell and molecular approaches and in vivo models, we reveal that AMBRA1 regulates the abundance of D-type cyclins by mediating their degradation. Furthermore, by controlling the transition from G1 to S phase, AMBRA1 helps to maintain genomic integrity during DNA replication, which counteracts developmental abnormalities and tumour growth. Finally, we identify the CHK1 kinase as a potential therapeutic target in AMBRA1-deficient tumours. These results advance our understanding of the control of replication-phase entry and genomic integrity, and identify the AMBRA1-cyclin D pathway as a crucial cell-cycle-regulatory mechanism that is deeply interconnected with genomic stability in embryonic development and tumorigenesis

Isozyme-Specific Ligands for O-acetylserine sulfhydrylase, a Novel Antibiotic Target

Conceived and designed the experiments: FS PC BC ES AM. Performed the experiments: FS RS ES PF SR. Analyzed the data: FS BC ES PF GEK PFC AM. Contributed reagents/materials/analysis tools: PC PB GC. Wrote the paper: FS GEK BC AM.The last step of cysteine biosynthesis in bacteria and plants is catalyzed by O-acetylserine sulfhydrylase. In bacteria, two isozymes, O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, have been identified that share similar binding sites, although the respective specific functions are still debated. O-acetylserine sulfhydrylase plays a key role in the adaptation of bacteria to the host environment, in the defense mechanisms to oxidative stress and in antibiotic resistance. Because mammals synthesize cysteine from methionine and lack O-acetylserine sulfhydrylase, the enzyme is a potential target for antimicrobials. With this aim, we first identified potential inhibitors of the two isozymes via a ligand- and structure-based in silico screening of a subset of the ZINC library using FLAP. The binding affinities of the most promising candidates were measured in vitro on purified O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B from Salmonella typhimurium by a direct method that exploits the change in the cofactor fluorescence. Two molecules were identified with dissociation constants of 3.7 and 33 µM for O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, respectively. Because GRID analysis of the two isoenzymes indicates the presence of a few common pharmacophoric features, cross binding titrations were carried out. It was found that the best binder for O-acetylserine sulfhydrylase-B exhibits a dissociation constant of 29 µM for O-acetylserine sulfhydrylase-A, thus displaying a limited selectivity, whereas the best binder for O-acetylserine sulfhydrylase-A exhibits a dissociation constant of 50 µM for O-acetylserine sulfhydrylase-B and is thus 8-fold selective towards the former isozyme. Therefore, isoform-specific and isoform-independent ligands allow to either selectively target the isozyme that predominantly supports bacteria during infection and long-term survival or to completely block bacterial cysteine biosynthesis.Yeshttp://www.plosone.org/static/editorial#pee

Tautomer Preference in PDB Complexes and its Impact on Structure-Based Drug Discovery

Tautomer enrichment is a key step of ligand preparation prior to virtual screening. In this paper, we have investigated how tautomer preference in various media (water, gas phase, and crystal) compares to tautomer preference at the active site of the protein by analyzing the different possible H-bonding contacts for a set of 13 tautomeric structures. In addition, we have explored the impact of four different protocols for the enumeration of tautomers in virtual screening by using Flap, Glide, and Gold as docking tools on seven targets of the DUD data set. Excluding targets in which the binding does not involve tautomeric atoms (HSP90, p38, and VEGFR2), we found that the average receiver operating characteristic curve enrichment at 10% was 0.25 (Gold), 0.24 (Glide), and 0.50 (Flap) by considering only tautomers predicted to be unstable in water versus 0.41 (Gold), 0.56 (Glide), 0.51 (Flap) by limiting the enumeration process only to the predicted most stable tautomer. The inclusion of all tautomers (stable and unstable) yielded slightly poorer results than considering only the most stable form in water

Chemogenomics in Drug Discovery: Methods Based on the Comparison of Binding Sites

Novel computational methods for understanding relationships between ligands and all possible biological targets have emerged in recent years. Proteins are connected to each other based on the similarity of their ligands (or substrates), or based on the similarity of their binding sites. The assumption is that compounds sharing chemical similarity should share targets, and that targets with a similar binding site or profile on a common set of small molecules should also be similar. In the past years a large number of techniques have been developed to assess ligand and binding site similarity. These techniques can be applied to quantitatively predict the most probable biological target of a given compound. This review covers the recent advances in new methods for relating biological targets based on the similarity of their binding sites. Binding sites are compared to predict their most likely ligands, their possible cross-reactivity and selectivity and to infer the function of novel uncharacterized proteins. Moreover, binding site analysis opens additional opportunities such as assessing the druggability of pockets of pharmaceutically relevant targets

Case-control Indian buffet process identifies biomarkers of response to Codrituzumab

Abstract Background Codrituzumab, a humanized monoclonal antibody against Glypican-3 (GPC3), which is expressed in hepatocellular carcinoma (HCC), was tested in a randomized phase II trial in advanced HCC patients who had failed prior systemic therapy. Biomarker analysis was performed to identify a responder population that benefits from treatment. Methods A novel statistical method based on the Indian buffet process (IBP) was used to identify biomarkers predictive of response to treatment with Codrituzumab. The IBP is a novel method that allows flexibility in analysis design, and which is sensitive to slight, but meaningful between-group differences in biomarkers in very complex datasets Results The IBP model identified several subpopulations of patients having defined biomarker values. Tumor necrosis and viable cell content in the tumor were identified as prognostic markers of disease progression, as were the well-known HCC prognostic markers of disease progression, alpha-fetoprotein and Glypican-3 expression. Predictive markers of treatment response included natural killer (NK) cell surface markers and parameters influencing NK cell activity, all related to the mechanism of action of this drug Conclusions The Indian buffet process can be effectively used to detect statistically significant signals with high sensitivity in complex and noisy biological data Trial registration NCT01507168, January 6, 201