Catatonia associated with pediatric postoperative cerebellar mutism syndrome.

OBJECTIVE: To ascertain the presence of catatonia in cases of pediatric postoperative cerebellar mutism syndrome (PPCMS). METHOD: A systematic review of PPCMS case reports of patients aged 0-17 years with sufficient clinical information to extract catatonic phenomena was undertaken following PRISMA guidelines. Standardized catatonia rating scales were applied to selected cases retrospectively to ascertain whether diagnostic criteria for catatonia were met. A case known to the authors is also presented. RESULTS: Two hundred twenty-one suitable full-text articles were identified. Following screening and application of inclusion criteria, 51 articles were selected plus seven more from their references, reporting on 119 subjects. All cases met Bush and Francis (BF) diagnostic criteria for catatonia, 92.5% Pediatric Catatonia Rating Scale (PCRS), 52.9% ICD-11, and 44.5% DSM-5. All patients presented with mutism. The next most frequent signs were immobility/stupor (77.3%), withdrawal (35.3%), mannerisms (23.5%), and excitement/agitation (18.5%). Most cases presented with stuporous catatonia (75.6%). Catatonia most frequently occurred following resection of medulloblastoma (64.7%). Preoperative hydrocephalus occurred in 89 patients (74.8%). CONCLUSION: Catatonia was frequent in this PPCMS sample, with a predominant stuporous variant; it should be considered in patients with PPCMS and assessed with reliable and validated instruments for prompt diagnosis and management.

Illuminating the Chemical Space of Untargeted Proteins.

According to the Illuminating the Druggable Genome (IDG) initiative, 90% of the proteins encoded by the human genome still lack an identified active ligand, that is, a small molecule with biologically relevant binding potency or functional activity in an in vitro assay. Under this scenario, there is an urgent need for new approaches to chemically address these yet untargeted proteins. It is widely recognized that the best starting point for generating novel small molecules for proteins is to exploit the expected polypharmacology of known active ligands across phylogenetically related proteins following the paradigm that similar proteins are likely to interact with similar ligands. Here, we introduce a computational strategy to identify privileged structures that, when chemically expanded, are highly probable to contain active small molecules for untargeted proteins. The protocol was first tested on a set of 576 currently targeted proteins having at least one protein family sibling the year before their first active ligand was reported. A privileged structure contained in active ligands that were identified in the following years was correctly anticipated for 214 (37%) of those targeted proteins, a lower-bound recall estimate when considering data completeness issues. When applied to a set of 1184 untargeted potential druggable genes in cancer, the identification of privileged structures from known bioactive ligands of protein family siblings allowed for extracting a priority list of diverse commercially available small molecules for 960 of them. Assuming a minimum success rate of 37%, the chemical library selections should be able to deliver active ligands for at least 355 currently untargeted proteins associated with cancer.

Extended connectivity interaction features: improving binding affinity prediction through chemical description.

MOTIVATION: Machine-learning scoring functions (SFs) have been found to outperform standard SFs for binding affinity prediction of protein-ligand complexes. A plethora of reports focus on the implementation of increasingly complex algorithms, while the chemical description of the system has not been fully exploited. RESULTS: Herein, we introduce Extended Connectivity Interaction Features (ECIF) to describe protein-ligand complexes and build machine-learning SFs with improved predictions of binding affinity. ECIF are a set of protein-ligand atom-type pair counts that take into account each atom's connectivity to describe it and thus define the pair types. ECIF were used to build different machine-learning models to predict protein-ligand affinities (pKd/pKi). The models were evaluated in terms of 'scoring power' on the Comparative Assessment of Scoring Functions 2016. The best models built on ECIF achieved Pearson correlation coefficients of 0.857 when used on its own, and 0.866 when used in combination with ligand descriptors, demonstrating ECIF descriptive power. AVAILABILITY AND IMPLEMENTATION: Data and code to reproduce all the results are freely available at https://github.com/DIFACQUIM/ECIF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research.

In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen, and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Here, we describe a workflow we designed for a semiautomated integration of rapidly emerging data sets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 63 278 host-host protein, and 1221 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is made publicly accessible via a web interface and via API calls based on the Bolt protocol. Details for accessing the database are provided on a landing page (https://neo4covid19.ncats.io/). We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.

Catatonia in pediatric obsessive-compulsive disorder: report of two cases.

Catatonia is a psychomotor syndrome which may occur in a wide variety of medical, neurological, and psychiatric conditions. In pediatrics, this condition is rare and is associated with high morbidity and mortality if not correctly diagnosed and treated. Catatonia in obsessive-compulsive disorder is an infrequent association that has been understudied and underdiagnosed. To add to the knowledge on this unusual clinical presentation, two pediatric patients are reported and discussed together with the other two cases described in the literature. These four cases in total of catatonia associated with OCD confirm that it is a relationship that is infrequently reported, possibly because of lack of awareness in clinicians that catatonia can also be caused by OCD, and because the similarity between some catatonic signs and some compulsive phenomena may compound the identification of the former. Most cases of catatonia in this small series seemed to have responded to the optimization of the treatment for OCD. This highlights the clinical importance of an accurate diagnosis of catatonia when associated with OCD.

Identification of the Core Chemical Structure in SureChEMBL Patents.

The SureChEMBL database provides open access to 17 million chemical entities mentioned in 14 million patents published since 1970. However, alongside with molecules covered by patent claims, the database is full of starting materials and intermediate products of little pharmacological relevance. Herein, we introduce a new filtering protocol to automatically select the core chemical structures best representing a congeneric series of pharmacologically relevant molecules in patents. The protocol is first validated against a selection of 890 SureChEMBL patents for which a total of 51,738 manually curated molecules are deposited in ChEMBL. Our protocol was able to select 92.5% of the molecules in ChEMBL from all 270,968 molecules in SureChEMBL for those patents. Subsequently, the protocol was applied to all 240,988 US pharmacological patents for which 9,111,706 molecules are available in SureChEMBL. The unsupervised filtering process selected 5,949,214 molecules (65.3% of the total number of molecules) that form highly congeneric chemical series in 188,795 of those patents (78.3% of the total number of patents). A SureChEMBL version enriched with molecules of pharmacological relevance is available for download at https://ftp.ebi.ac.uk/pub/databases/chembl/SureChEMBLccs.

Congenericity of Claimed Compounds in Patent Applications.

A method is presented to analyze quantitatively the degree of congenericity of claimed compounds in patent applications. The approach successfully differentiates patents exemplified with highly congeneric compounds of a structurally compact and well defined chemical series from patents containing a more diverse set of compounds around a more vaguely described patent claim. An application to 750 common patents available in SureChEMBL, SureChEMBLccs and ChEMBL is presented and the congenericity of patent compounds in those different sources discussed.

Catatonia in elderly psychiatric inpatients is not always associated with intense anxiety: Factor analysis and correlation with psychopathology.

OBJECTIVE: Catatonic stupor has been linked to extreme fear. Whether the underlying phenomenology of every catatonic dimension is intense anxiety or fear remains unknown. METHODS: One hundred and six patients aged ≥64 years were assessed for catatonia and clinical variables during the first 24 hours of admission. Two-sample t test were used to test for group differences. A principal component analysis was developed. Analysis of variance was performed to assess for differences in the diagnostic groups. Correlation coefficients were used to examine the association between catatonic dimensions and psychopathological variables. RESULTS: There were statistically significant differences between catatonic and non-catatonic patients in the Hamilton and NPI scores. The three factor-model accounted for 52.23% of the variance. Factor 1 loaded on items concerned with "excitement," factor 2 on "inhibition" items, and factor 3 on "parakinetic" items. There was a significant effect for factor 1 (F [5.36] = 2.83, P = .02), and not significant for factor 2 and factor 3. Compared with patients with depression, patients with mania scored significantly higher on factor "excitement" (P < .05). Factor 2 showed a moderate correlation with Hamilton total score (r = .346, P = .031) and Hamilton psychic score (r = .380, P = .017). CONCLUSIONS: Catatonic patients experienced more anxiety and hyperactivity. A three-factor solution provided best fit for catatonic symptoms. Patients with mania scored highest on Excitement, patients with depression on Inhibition, and patients with schizophrenia on Parakinetic. The main finding in this study was a positive moderate correlation between the Hamilton psychic score and the Inhibition factor score, meaning that not every catatonic dimension is associated to intense anxiety.

Skin sensitization in silico protocol.

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

Depression and depressive symptoms in patients with polymyalgia rheumatica: discussion points, grey areas and unmet needs emerging from a systematic review of published literature.

OBJECTIVES: In 1979, Bird et al. proposed depression as a diagnostic criterion for polymyalgia rheumatica (PMR). More recently, the significance of depression in PMR patients has been re-proposed, , and some researchers have suggested that PMR may increase the risk of depression. The aim of our article is to evaluate the relationship between PMR and depression. MATERIAL AND METHODS: Systematic literature searches were performed on 19th and 20th May 2020 based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The search was restricted to all studies and case reports with English abstract, published in any language, since 1979 (when depression was first proposed as a diagnostic criterion for PMR) describing the association of PMR with depression. Exclusion criteria were as follows: reviews, conference abstracts, comments, non-original articles; and articles discussing giant cell arteritis (GCA) and PMR when data and observations for the two conditions were not clearly subdivided. RESULTS: The initial search yielded 812 papers, of which 115 duplicates were removed. A total of 697 articles had a first screening and 506 were excluded based on title and abstract reviews; 117 articles underwent full-length scrutiny, and 99 full-text articles were excluded because they did not meet the inclusion and exclusion criteria (reviews and comments = 58; articles with outcome of interest not reported = 34; low-quality articles = 7). At least, 18 articles were included in this review. CONCLUSIONS: The review did not find any studies that clarified the prevalence rates of depression in patients with PMR. Furthermore, the studies reviewed did not offer any clarity as to whether patients suffered from just depressive symptoms or clinical depression, and that accepted diagnostic criteria for depression had not been employed, indicating that a robust method for diagnosing depression had not been employed. Collaboration of different professionals should be improved through shared guidelines.

Synthesis, pharmacological evaluation and molecular docking of pyranopyrazole-linked 1,4-dihydropyridines as potent positive inotropes.

1,4-Dihydropyridines are well-known calcium channel blockers, but variations in the substituents attached to the ring have resulted in their role reversal making them calcium channel activators in some cases. We describe the microwave-assisted eco-friendly approach for the synthesis of pyranopyrazole-1,4-dihydropyridines, a new class of 1,4-DHPs, under solvent-free conditions in good yield, and screen them for various in silico, in vitro and in vivo activities. The in vivo experimentation results show that the compounds possess positive inotropic effect, and the docking results validate their good binding with calcium channels. Compounds 7c, 7g and 7i appear to be the most effective positive inotropes, even at low doses, and bind with the calcium channels even more strongly than Bay K 8644, a well-known calcium channel activator. The chronotropic effect for the new compounds was also studied. The target and off-target affinity profiling supported the in vivo results and revealed that the hybridized pyranopyrazole dihydropyridine scaffold has delivered new moderate hits, to be optimized, for the cytochrome P450 3A4 enzymes, opening avenues for combined pharmacological activity through standard structural modification.

The In Vitro Pharmacological Profile of Drugs as a Proxy Indicator of Potential In Vivo Organ Toxicities.

The potential of a drug to cause certain organ toxicities is somehow implicitly contained in its full pharmacological profile, provided the drug reaches and accumulates at the various organs where the different interacting proteins in its profile, both targets and off-targets, are expressed. Under this assumption, a computational approach was implemented to obtain a projected anatomical profile of a drug from its in vitro pharmacological profile linked to protein expression data across 47 organs. It was observed that the anatomical profiles obtained when using only the known primary targets of the drugs reflected roughly the intended organ targets. However, when both known and predicted secondary pharmacology was considered, the projected anatomical profiles of the drugs were able to clearly highlight potential organ off-targets. Accordingly, when applied to sets of drugs known to cause cardiotoxicity and hepatotoxicity, the approach is able to identify heart and liver, respectively, as the organs where the proteins in the pharmacological profile of the corresponding drugs are specifically expressed. When applied to a set of drugs linked to a risk of Torsades de Pointes, heart is again the organ clearly standing out from the rest and a potential protein profile hazard is proposed. The approach can be used as a proxy indicator of potential in vivo organ toxicities.

Large-Scale Predictive Drug Safety: From Structural Alerts to Biological Mechanisms.

The recent explosion of data linking drugs, proteins, and pathways with safety events has promoted the development of integrative systems approaches to large-scale predictive drug safety. The added value of such approaches is that, beyond the traditional identification of potentially labile chemical fragments for selected toxicity end points, they have the potential to provide mechanistic insights for a much larger and diverse set of safety events in a statistically sound nonsupervised manner, based on the similarity to drug classes, the interaction with secondary targets, and the interference with biological pathways. The combined identification of chemical and biological hazards enhances our ability to assess the safety risk of bioactive small molecules with higher confidence than that using structural alerts only. We are still a very long way from reliably predicting drug safety, but advances toward gaining a better understanding of the mechanisms leading to adverse outcomes represent a step forward in this direction.

Insights from Fragment Hit Binding Assays by Molecular Simulations.

Novel bioactive molecules can be rationally designed by growing and linking small fragments. Because fragments are fast and promiscuous, it is common to have contradictory hit results between different experimental screening techniques. Here, we simultaneously determine fragment binding poses, affinities, and kinetics on a focused library of 42 fragments against the serine protease factor Xa using multimillisecond molecular dynamics simulations. We predict experimental poses of 12 over 15 S1 crystal structures, and affinities are recovered for 4 out of 6. A kinetic map of protein cavities is computed in terms of on- and off-rates as well as insights into secondary ligand poses. The results suggest that the approach can be useful to recapitulate discordant fragment screening data.

Prediction of the P. falciparum target space relevant to malaria drug discovery.

Malaria is still one of the most devastating infectious diseases, affecting hundreds of millions of patients worldwide. Even though there are several established drugs in clinical use for malaria treatment, there is an urgent need for new drugs acting through novel mechanisms of action due to the rapid development of resistance. Resistance emerges when the parasite manages to mutate the sequence of the drug targets to the extent that the protein can still perform its function in the parasite but can no longer be inhibited by the drug, which then becomes almost ineffective. The design of a new generation of malaria drugs targeting multiple essential proteins would make it more difficult for the parasite to develop full resistance without lethally disrupting some of its vital functions. The challenge is then to identify which set of Plasmodium falciparum proteins, among the millions of possible combinations, can be targeted at the same time by a given chemotype. To do that, we predicted first the targets of the close to 20,000 antimalarial hits identified recently in three independent phenotypic screening campaigns. All targets predicted were then projected onto the genome of P. falciparum using orthologous relationships. A total of 226 P. falciparum proteins were predicted to be hit by at least one compound, of which 39 were found to be significantly enriched by the presence and degree of affinity of phenotypically active compounds. The analysis of the chemically compatible target combinations containing at least one of those 39 targets led to the identification of a priority set of 64 multi-target profiles that can set the ground for a new generation of more robust malaria drugs.

[Streptococcus agalactiae late-onset neonatal infections in Barcelona (1996-2010)]. / La infección neonatal tardía por Streptococcus agalactiae en el área de Barcelona (1996-2010).

OBJETIVE: To study the characteristics and evolution of group B Streptococcus (GBS) late-onset diseases, over a period of 15years in 8hospitals the Barcelona area and analyze the possible impact of prophylactic measures for the prevention of early-onset neonatal infections. METHODS: Retrospective review of all patients diagnosed with late-onset neonatal disease due to GBS from 1996 to 2010. RESULTS: A total of 143 patients were diagnosed. Of these, 51 were born in others hospitals. The overalll incidence was 0.42 per 1000 live births, varying between 0.14‰ in the year 2000 and 0.80‰ in 2009. A slight but sustained tendency of increased risk was observed over the years, 6.9% in the overall disease (with no statistical significance). Sepsis/bacteremia was detected in 63.6% of the newborns, meningitis in 32.8%, and arthritis/osteomyelitis in 3.5%. In cases with known obstetrics dates, 53% of mothers had been colonized by GBS during pregnancy, 53.8% received intrapartum antibiotic prophylaxis, and 41.2% had some obstetric risk factors, particularly premature birth in 35.9%. There was a 2.8% mortality rate in the neonates, and predominant serotypes were III and Ia. CONCLUSIONS: The incidence of GBS late-onset disease has not decreased despite the control practices of early-onset disease, and possibility of this appearing must be taken into account.

CIPSI: An open chemical intellectual property service for medicinal chemists.

The availability of patent chemical data offers public access to a chemical space that is not well covered by other sources collecting small molecules from scholarly literature. However, open applications to facilitate the search and analysis of biologically-relevant molecular structures present in patents are still largely missing. We have developed CIPSI, an open Chemical Intellectual Property Service @ IMIM to assist medicinal chemists in searching and analysing molecules in SureChEMBL patents. The current version contains 6,240,500 molecules from 236,689 pharmacological patents, of which 5,949,214 are confidently assigned to core chemical structures reminiscent of the Markush structure in the patent claim. The platform includes some graphical tools to facilitate comparative patent analyses between drugs, chemical substructures, and company assignees. CIPSI is available at https://cipsi.org.

Design, quality and validation of the EU-OPENSCREEN fragment library poised to a high-throughput screening collection.

The EU-OPENSCREEN (EU-OS) European Research Infrastructure Consortium (ERIC) is a multinational, not-for-profit initiative that integrates high-capacity screening platforms and chemistry groups across Europe to facilitate research in chemical biology and early drug discovery. Over the years, the EU-OS has assembled a high-throughput screening compound collection, the European Chemical Biology Library (ECBL), that contains approximately 100 000 commercially available small molecules and a growing number of thousands of academic compounds crowdsourced through our network of European and non-European chemists. As an extension of the ECBL, here we describe the computational design, quality control and use case screenings of the European Fragment Screening Library (EFSL) composed of 1056 mini and small chemical fragments selected from a substructure analysis of the ECBL. Access to the EFSL is open to researchers from both academia and industry. Using EFSL, eight fragment screening campaigns using different structural and biophysical methods have successfully identified fragment hits in the last two years. As one of the highlighted projects for antibiotics, we describe the screening by Bio-Layer Interferometry (BLI) of the EFSL, the identification of a 35 µM fragment hit targeting the beta-ketoacyl-ACP synthase 2 (FabF), its binding confirmation to the protein by X-ray crystallography (PDB 8PJ0), its subsequent rapid exploration of its surrounding chemical space through hit-picking of ECBL compounds that contain the fragment hit as a core substructure, and the final binding confirmation of two follow-up hits by X-ray crystallography (PDB 8R0I and 8R1V).