Multisite randomised controlled trial of trauma-focused cognitive behaviour therapy for psychosis to reduce post-traumatic stress symptoms in people with co-morbid post-traumatic stress disorder and psychosis, compared to treatment as usual: study protocol for the STAR (Study of Trauma And Recovery) trial.

BACKGROUND: People with psychosis have high rates of trauma, with a post-traumatic stress disorder (PTSD) prevalence rate of approximately 15%, which exacerbates psychotic symptoms such as delusions and hallucinations. Pilot studies have shown that trauma-focused (TF) psychological therapies can be safe and effective in such individuals. This trial, the largest to date, will evaluate the clinical effectiveness of a TF therapy integrated with cognitive behaviour therapy for psychosis (TF-CBTp) on post-traumatic stress symptoms in people with psychosis. The secondary aims are to compare groups on cost-effectiveness; ascertain whether TF-CBTp impacts on a range of other meaningful outcomes; determine whether therapy effects endure; and determine acceptability of the therapy in participants and therapists. METHODS: Rater-blind, parallel arm, pragmatic randomised controlled trial comparing TF-CBTp + treatment as usual (TAU) to TAU only. Adults (N = 300) with distressing post-traumatic stress and psychosis symptoms from five mental health Trusts (60 per site) will be randomised to the two groups. Therapy will be manualised, lasting 9 months (m) with trained therapists. We will assess PTSD symptom severity (primary outcome); percentage who show loss of PTSD diagnosis and clinically significant change; psychosis symptoms; emotional well-being; substance use; suicidal ideation; psychological recovery; social functioning; health-related quality of life; service use, a total of four times: before randomisation; 4 m (mid-therapy); 9 m (end of therapy; primary end point); 24 m (15 m after end of therapy) post-randomisation. Four 3-monthly phone calls will be made between 9 m and 24 m assessment points, to collect service use over the previous 3 months. Therapy acceptability will be assessed through qualitative interviews with participants (N = 35) and therapists (N = 5-10). An internal pilot will ensure integrity of trial recruitment and outcome data, as well as therapy protocol safety and adherence. Data will be analysed following intention-to-treat principles using generalised linear mixed models and reported according to Consolidated Standards of Reporting Trials-Social and Psychological Interventions Statement. DISCUSSION: The proposed intervention has the potential to provide significant patient benefit in terms of reductions in distressing symptoms of post-traumatic stress, psychosis, and emotional problems; enable clinicians to implement trauma-focused therapy confidently in this population; and be cost-effective compared to TAU through reduced service use. TRIAL REGISTRATION: ISRCTN93382525 (03/08/20).

SARS-Arena: Sequence and Structure-Guided Selection of Conserved Peptides from SARS-related Coronaviruses for Novel Vaccine Development.

The pandemic caused by the SARS-CoV-2 virus, the agent responsible for the COVID-19 disease, has affected millions of people worldwide. There is constant search for new therapies to either prevent or mitigate the disease. Fortunately, we have observed the successful development of multiple vaccines. Most of them are focused on one viral envelope protein, the spike protein. However, such focused approaches may contribute for the rise of new variants, fueled by the constant selection pressure on envelope proteins, and the widespread dispersion of coronaviruses in nature. Therefore, it is important to examine other proteins, preferentially those that are less susceptible to selection pressure, such as the nucleocapsid (N) protein. Even though the N protein is less accessible to humoral response, peptides from its conserved regions can be presented by class I Human Leukocyte Antigen (HLA) molecules, eliciting an immune response mediated by T-cells. Given the increased number of protein sequences deposited in biological databases daily and the N protein conservation among viral strains, computational methods can be leveraged to discover potential new targets for SARS-CoV-2 and SARS-CoV-related viruses. Here we developed SARS-Arena, a user-friendly computational pipeline that can be used by practitioners of different levels of expertise for novel vaccine development. SARS-Arena combines sequence-based methods and structure-based analyses to (i) perform multiple sequence alignment (MSA) of SARS-CoV-related N protein sequences, (ii) recover candidate peptides of different lengths from conserved protein regions, and (iii) model the 3D structure of the conserved peptides in the context of different HLAs. We present two main Jupyter Notebook workflows that can help in the identification of new T-cell targets against SARS-CoV viruses. In fact, in a cross-reactive case study, our workflows identified a conserved N protein peptide (SPRWYFYYL) recognized by CD8+ T-cells in the context of HLA-B7+. SARS-Arena is available at https://github.com/KavrakiLab/SARS-Arena.

DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins.

An unprecedented research effort has been undertaken in response to the ongoing COVID-19 pandemic. This has included the determination of hundreds of crystallographic structures of SARS-CoV-2 proteins, and numerous virtual screening projects searching large compound libraries for potential drug inhibitors. Unfortunately, these initiatives have had very limited success in producing effective inhibitors against SARS-CoV-2 proteins. A reason might be an often overlooked factor in these computational efforts: receptor flexibility. To address this issue we have implemented a computational tool for ensemble docking with SARS-CoV-2 proteins. We have extracted representative ensembles of protein conformations from the Protein Data Bank and from in silico molecular dynamics simulations. Twelve pre-computed ensembles of SARS-CoV-2 protein conformations have now been made available for ensemble docking via a user-friendly webserver called DINC-COVID (dinc-covid.kavrakilab.org). We have validated DINC-COVID using data on tested inhibitors of two SARS-CoV-2 proteins, obtaining good correlations between docking-derived binding energies and experimentally-determined binding affinities. Some of the best results have been obtained on a dataset of large ligands resolved via room temperature crystallography, and therefore capturing alternative receptor conformations. In addition, we have shown that the ensembles available in DINC-COVID capture different ranges of receptor flexibility, and that this diversity is useful in finding alternative binding modes of ligands. Overall, our work highlights the importance of accounting for receptor flexibility in docking studies, and provides a platform for the identification of new inhibitors against SARS-CoV-2 proteins.