Canonical and noncanonical roles of Fanconi anemia proteins: Implications in cancer predisposition

Fanconi anemia (FA) is a clinically and genetically heterogeneous disorder characterized by the variable presence of congenital somatic abnormalities, bone marrow failure (BMF), and a predisposition to develop cancer. Monoallelic germline mutations in at least five genes involved in the FA pathway are associated with the development of sporadic hematological and solid malignancies. The key function of the FA pathway is to orchestrate proteins involved in the repair of interstrand cross-links (ICLs), to prevent genomic instability and replication stress. Recently, many studies have highlighted the importance of FA genes in noncanonical pathways, such as mitochondria homeostasis, inflammation, and virophagy, which act, in some cases, independently of DNA repair processes. Thus, primary defects in DNA repair mechanisms of FA patients are typically exacerbated by an impairment of other cytoprotective pathways that contribute to the multifaceted clinical phenotype of this disease. In this review, we summarize recent advances in the understanding of the pathogenesis of FA, with a focus on the cytosolic noncanonical roles of FA genes, discussing how they may contribute to cancer development, thus suggesting opportunities to envisage novel therapeutic approaches

The effects of cerebrospinal fluid tap-test on idiopathic normal pressure hydrocephalus: an inertial sensors based assessment

BACKGROUND: Gait disturbances are typical of persons with idiopathic normal pressure hydrocephalus (iNPH) without signs distinctive from other neurodegenerative and vascular conditions. Cerebrospinal fluid tap-test (CSF-TT) is expected to improve the motor performance of iNPH patients and is a prognostic indicator in their surgical management. This observational prospective study aims to determine which spatio-temporal gait parameter(s), measured during instrumented motor tests, and clinical scale(s) may provide a relevant contribution in the evaluation of motor performance pre vs. post CSF-TT on iNPH patients with and without important vascular encephalopathy. METHODS: Seventy-six patients (20 with an associated vascular encephalopathy) were assessed before, and 24 and 72\u2009h after the CSF-TT by a timed up and go test (TUG) and an 18\u2009m walking test (18\u2009mW) instrumented using inertial sensors. Tinetti Gait, Tinetti Balance, Gait Status Scale, and Grading Scale were fulfilled before and 72\u2009h after the CSF-TT. Stride length, cadence and total time were selected as the outcome measures. Statistical models with mixed effects were implemented to determine the relevant contribution to response variables of each quantitative gait parameter and clinical scales. RESULTS AND CONCLUSION: From baseline to 72\u2009h post CSF-TT patients improved significantly by increasing cadence in 18\u2009mW and TUG (on average of 1.7 and 2.4 strides/min respectively) and stride length in 18\u2009mW (on average of 3.1\u2009cm). A significant reduction of gait apraxia was reflected by modifications in double support duration and in coordination index. Tinetti Gait, Tinetti Balance and Gait Status Scale were able to explain part of the variability of response variables not covered by instrumental data, especially in TUG. Grading Scale revealed the highest affinity with TUG total time and cadence when considering clinical scales alone. Patients with iNPH and an associated vascular encephalopathy showed worst performances compared to pure iNPH but without statistical significance. Gait improvement following CSF-TT was comparable in the two groups. Overall these results suggest that, in order to augment CSF-TT accuracy, is key to assess the gait pattern by analyzing the main spatio-temporal parameters and set post evaluation at 72\u2009h. TRIAL REGISTRATION: Approved by ethics committee: CE 14131 23/02/2015

Tautomerism in large databases

We have used the Chemical Structure DataBase (CSDB) of the NCI CADD Group, an aggregated collection of over 150 small-molecule databases totaling 103.5 million structure records, to conduct tautomerism analyses on one of the largest currently existing sets of real (i.e. not computer-generated) compounds. This analysis was carried out using calculable chemical structure identifiers developed by the NCI CADD Group, based on hash codes available in the chemoinformatics toolkit CACTVS and a newly developed scoring scheme to define a canonical tautomer for any encountered structure. CACTVS’s tautomerism definition, a set of 21 transform rules expressed in SMIRKS line notation, was used, which takes a comprehensive stance as to the possible types of tautomeric interconversion included. Tautomerism was found to be possible for more than 2/3 of the unique structures in the CSDB. A total of 680 million tautomers were calculated from, and including, the original structure records. Tautomerism overlap within the same individual database (i.e. at least one other entry was present that was really only a different tautomeric representation of the same compound) was found at an average rate of 0.3% of the original structure records, with values as high as nearly 2% for some of the databases in CSDB. Projected onto the set of unique structures (by FICuS identifier), this still occurred in about 1.5% of the cases. Tautomeric overlap across all constituent databases in CSDB was found for nearly 10% of the records in the collection

Combinatorial Clustering of Residue Position Subsets Predicts Inhibitor Affinity across the Human Kinome

The protein kinases are a large family of enzymes that play fundamental roles in propagating signals within the cell. Because of the high degree of binding site similarity shared among protein kinases, designing drug compounds with high specificity among the kinases has proven difficult. However, computational approaches to comparing the 3-dimensional geometry and physicochemical properties of key binding site residue positions have been shown to be informative of inhibitor selectivity. The Combinatorial Clustering Of Residue Position Subsets (CCORPS) method, introduced here, provides a semi-supervised learning approach for identifying structural features that are correlated with a given set of annotation labels. Here, CCORPS is applied to the problem of identifying structural features of the kinase ATP binding site that are informative of inhibitor binding. CCORPS is demonstrated to make perfect or near-perfect predictions for the binding affinity profile of 8 of the 38 kinase inhibitors studied, while only having overall poor predictive ability for 1 of the 38 compounds. Additionally, CCORPS is shown to identify shared structural features across phylogenetically diverse groups of kinases that are correlated with binding affinity for particular inhibitors; such instances of structural similarity among phylogenetically diverse kinases are also shown to not be rare among kinases. Finally, these function-specific structural features may serve as potential starting points for the development of highly specific kinase inhibitors

Structure-guided selection of specificity determining positions in the human kinome

Background: The human kinome contains many important drug targets. It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. The increased availability of protein 3D structures has provided much information on the structural variation within a given protein family. However, the relationship between structural variations and binding specificity is complex and incompletely understood. We have developed a structural bioinformatics approach which provides an analysis of key determinants of binding selectivity as a tool to enhance the rational design of drugs with a specific selectivity profile. Results: We propose a greedy algorithm that computes a subset of residue positions in a multiple sequence alignment such that structural and chemical variation in those positions helps explain known binding affinities. By providing this information, the main purpose of the algorithm is to provide experimentalists with possible insights into how the selectivity profile of certain inhibitors is achieved, which is useful for lead optimization. In addition, the algorithm can also be used to predict binding affinities for structures whose affinity for a given inhibitor is unknown. The algorithm’s performance is demonstrated using an extensive dataset for the human kinome. Conclusion: We show that the binding affinity of 38 different kinase inhibitors can be explained with consistently high precision and accuracy using the variation of at most six residue positions in the kinome binding site. We show for several inhibitors that we are able to identify residues that are known to be functionally important

A high-throughput synthetic platform enables the discovery of proteomimetic cell penetrating peptides and bioportides

Collectively, cell penetrating peptide (CPP) vectors and intrinsically active bioportides possess tremendous potential for drug delivery applications and the discrete modulation of intracellular targets including the sites of protein–protein interactions (PPIs). Such sequences are usually relatively short (< 25 AA), polycationic in nature and able to access the various intracellular compartments of eukaryotic cells without detrimental influences upon cellular biology. The high-throughput platform for bioportide discovery described herein exploits the discovery that many human proteins are an abundant source of potential CPP sequences which are reliably predicted using QSAR algorithms or other methods. Subsequently, microwave-enhanced solid phase peptides synthesis provides a high-throughput source of novel proteomimetic CPPs for screening purposes. By focussing upon cationic helical domains, often located within the molecular interfaces that facilitate PPIs, bioportides which act by a dominant-negative mechanism at such sites can be reliably identified within small number libraries of CPPs. Protocols that employ fluorescent peptides, routinely prepared by N-terminal acylation with carboxytetramethylrhodamine, further enable both the quantification of cellular uptake kinetics and the identification of specific site(s) of intracellular accretion. Chemical modifications of linear peptides, including strategies to promote and stabilise helicity, are compatible with the synthesis of second-generation bioportides with improved drug-like properties to further exploit the inherent selectivity of biologics

Identifying Compound-Target Associations by Combining Bioactivity Profile Similarity Search and Public Databases Mining

Molecular target identification is of central importance to drug discovery. Here, we developed a computational approach, named bioactivity profile similarity search (BASS), for associating targets to small molecules by using the known target annotations of related compounds from public databases. To evaluate BASS, a bioactivity profile database was constructed using 4296 compounds that were commonly tested in the US National Cancer Institute 60 human tumor cell line anticancer drug screen (NCI-60). Each compound was used as a query to search against the entire bioactivity profile database, and reference compounds with similar bioactivity profiles above a threshold of 0.75 were considered as neighbor compounds of the query. Potential targets were subsequently linked to the identified neighbor compounds by using the known targets o

Let’s not forget tautomers

A compound exhibits tautomerism if it can be represented by two structures that are related by an intramolecular movement of hydrogen from one atom to another. The different tautomers of a molecule usually have different molecular fingerprints, hydrophobicities and pKa’s as well as different 3D shape and electrostatic properties; additionally, proteins frequently preferentially bind a tautomer that is present in low abundance in water. As a result, the proper treatment of molecules that can tautomerize, ~25% of a database, is a challenge for every aspect of computer-aided molecular design. Library design that focuses on molecular similarity or diversity might inadvertently include similar molecules that happen to be encoded as different tautomers. Physical property measurements might not establish the properties of individual tautomers with the result that algorithms based on these measurements may be less accurate for molecules that can tautomerize—this problem influences the accuracy of filtering for library design and also traditional QSAR. Any 2D or 3D QSAR analysis must involve the decision of if or how to adjust the observed Ki or IC50 for the tautomerization equilibria. QSARs and recursive partitioning methods also involve the decision as to which tautomer(s) to use to calculate the molecular descriptors. Docking virtual screening must involve the decision as to which tautomers to include in the docking and how to account for tautomerization in the scoring. All of these decisions are more difficult because there is no extensive database of measured tautomeric ratios in both water and non-aqueous solvents and there is no consensus as to the best computational method to calculate tautomeric ratios in different environments