Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection

Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide-receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized

A Hermetic On-Cryostat Helium Source for Low Temperature Experiments

We describe a helium source cell for use in cryogenic experiments that is hermetically sealed $in$ $situ$ on the cold plate of a cryostat. The source cell is filled with helium gas at room temperature and subsequently sealed using a cold weld crimping tool before the cryostat is closed and cooled down. At low temperature the helium condenses and collects in a connected experimental volume, as monitored via the frequency response of a planar superconducting resonator device sensitive to small amounts of liquid helium. This on-cryostat helium source negates the use of a filling tube between the cryogenic volumes and room temperature, thereby preventing unwanted effects such as such as temperature instabilities that arise from the thermomechanical motion of helium within the system. This helium source can be used in experiments investigating the properties of quantum fluids or to better thermalize quantum devices.Comment: 5 pages, 3 figure

Monte Carlo Simulations of HIV Capsid Protein Homodimer

Capsid protein (CA) is the building block of virus coats. To help understand how the HIV CA proteins self-organize into large assemblies of various shapes, we aim to computationally evaluate the binding affinity and interfaces in a CA homodimer. We model the N- and C-terminal domains (NTD and CTD) of the CA as rigid bodies and treat the five-residue loop between the two domains as a flexible linker. We adopt a transferrable residue-level coarse-grained energy function to describe the interactions between the protein domains. In seven extensive Monte Carlo simulations with different volumes, a large number of binding/unbinding transitions between the two CA proteins are observed, thus allowing a reliable estimation of the equilibrium probabilities for the dimeric vs monomeric forms. The obtained dissociation constant for the CA homodimer from our simulations, 20–25 μM, is in reasonable agreement with experimental measurement. A wide range of binding interfaces, primarily between the NTDs, are identified in the simulations. Although some observed bound structures here closely resemble the major binding interfaces in the capsid assembly, they are statistically insignificant in our simulation trajectories. Our results suggest that although the general purpose energy functions adopted here could reasonably reproduce the overall binding affinity for the CA homodimer, further adjustment would be needed to accurately represent the relative strength of individual binding interfaces

Insights from the NeurIPS 2021 NetHack Challenge

In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge. Participants were tasked with developing a program or agent that can win (i.e., ‘ascend’ in) the popular dungeon-crawler game of NetHack by interacting with the NetHack Learning Environment (NLE), a scalable, procedurally generated, and challenging Gym environment for reinforcement learning (RL). The challenge showcased community-driven progress in AI with many diverse approaches significantly beating the previously best results on NetHack. Furthermore, it served as a direct comparison between neural (e.g., deep RL) and symbolic AI, as well as hybrid systems, demonstrating that on NetHack symbolic bots currently outperform deep RL by a large margin. Lastly, no agent got close to winning the game, illustrating NetHack’s suitability as a long-term benchmark for AI research

Association of a germline copy number polymorphism of APOBEC3A and APOBEC3B with burden of putative APOBEC-dependent mutations in breast cancer.

The somatic mutations in a cancer genome are the aggregate outcome of one or more mutational processes operative through the lifetime of the individual with cancer. Each mutational process leaves a characteristic mutational signature determined by the mechanisms of DNA damage and repair that constitute it. A role was recently proposed for the APOBEC family of cytidine deaminases in generating particular genome-wide mutational signatures and a signature of localized hypermutation called kataegis. A germline copy number polymorphism involving APOBEC3A and APOBEC3B, which effectively deletes APOBEC3B, has been associated with modestly increased risk of breast cancer. Here we show that breast cancers in carriers of the deletion show more mutations of the putative APOBEC-dependent genome-wide signatures than cancers in non-carriers. The results suggest that the APOBEC3A-APOBEC3B germline deletion allele confers cancer susceptibility through increased activity of APOBEC-dependent mutational processes, although the mechanism by which this increase in activity occurs remains unknown.We would like to thank the Wellcome Trust for support (grant reference 098051). SN-Z is a Wellcome-Beit Prize Fellow and is supported through a Wellcome Trust Intermediate Fellowship (grant reference WT100183MA). PJC is personally funded through a Wellcome Trust Senior Clinical Research Fellowship (grant reference WT088340MA). NB is an EHA fellow and is supported by a Lady Tata Memorial Trust award. The H.L. Holmes Award from the National Research Council Canada and an EMBO Fellowship supports AS

Improved Weighted Random Forest for Classification Problems

Several studies have shown that combining machine learning models in an appropriate way will introduce improvements in the individual predictions made by the base models. The key to make well-performing ensemble model is in the diversity of the base models. Of the most common solutions for introducing diversity into the decision trees are bagging and random forest. Bagging enhances the diversity by sampling with replacement and generating many training data sets, while random forest adds selecting a random number of features as well. This has made the random forest a winning candidate for many machine learning applications. However, assuming equal weights for all base decision trees does not seem reasonable as the randomization of sampling and input feature selection may lead to different levels of decision-making abilities across base decision trees. Therefore, we propose several algorithms that intend to modify the weighting strategy of regular random forest and consequently make better predictions. The designed weighting frameworks include optimal weighted random forest based on ac-curacy, optimal weighted random forest based on the area under the curve (AUC), performance-based weighted random forest, and several stacking-based weighted random forest models. The numerical results show that the proposed models are able to introduce significant improvements compared to regular random forest

Consequences of chronic diseases and other limitations associated with old age - A scoping review

Funding Information: This work supported in part by the LTC INTER COST, Evaluation of the Potential for Reducing Health and Social Expenses for Elderly People Using the Smart Environment, through the Ministry of Education, Youth and Sports, Czech Republic, under Project LTC18035; and in part by the project of Excellence, University of Hradec Kralove, FIM, Czech Republic (ID: 2205–2019). First author – Petra Maresova is principle investigator of LTC18035 INTER COST project, from which Petra Maresova, Ondrej Krejcar and Kamil Kuca are funded for all expenses including personal costs. Ehsan Javanmardi is funded from project of Excellence ID: 2205–2019 for personal costs. Sabina Barakovic, Jasmina Barakovic Husic and Signe Tomsone are members of COST ACTION 16226 of which also Petra Maresova and Ondrej Krejcar are paticipants, while this article also ACKnowledge this project CA16226. Funding Information: The authors would like to hereby acknowledge COST Action CA16226 for their networking support. The Indoor Living Space Improvement: Smart Habitat for the Elderly played a role of networking platform for knowledge sharing and interchanging ideas for joint research and publication, what was the base for creating this study. Based on CA16226 project LTC18035 INTER COST was proposed for national funding support of COST ACTION Framework. COST is a funding agency that helps innovation and research networks. Our Action was instrumental in connecting research programmes throughout the EU region. Their contribution has made it possible for scientists to connect with each other and share their ideas and findings. This allows for more research and better innovation. More information can be found at www.cost.eu. The authors would also like to acknowledge the Excellence 2019 internal research project, Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic. Publisher Copyright: © 2019 The Author(s).Background: The phenomenon of the increasing number of ageing people in the world is arguably the most significant economic, health and social challenge that we face today. Additionally, one of the major epidemiologic trends of current times is the increase in chronic and degenerative diseases. This paper tries to deliver a more up to date overview of chronic diseases and other limitations associated with old age and provide a more detailed outlook on the research that has gone into this field. Methods: First, challenges for seniors, including chronic diseases and other limitations associated with old age, are specified. Second, a review of seniors' needs and concerns is performed. Finally, solutions that can improve seniors' quality of life are discussed. Publications obtained from the following databases are used in this scoping review: Web of Science, PubMed, and Science Direct. Four independent reviewers screened the identified records and selected relevant publications published from 2010 to 2017. A total of 1916 publications were selected. In all, 52 papers were selected based on abstract content. For further processing, 21 full papers were screened." Results: The results indicate disabilities as a major problem associated with seniors' activities of daily living dependence. We founded seven categories of different conditions - psychological problems, difficulties in mobility, poor cognitive function, falls and incidents, wounds and injuries, undernutrition, and communication problems. In order to minimize ageing consequences, some areas require more attention, such as education and training; technological tools; government support and welfare systems; early diagnosis of undernutrition, cognitive impairment, and other diseases; communication solutions; mobility solutions; and social contributions. Conclusions: This scoping review supports the view on chronic diseases in old age as a complex issue. To prevent the consequences of chronic diseases and other limitations associated with old age related problems demands multicomponent interventions. Early recognition of problems leading to disability and activities of daily living (ADL) dependence should be one of essential components of such interventions.publishersversionPeer reviewe

Human BRCA1-BARD1 ubiquitin ligase activity counters chromatin barriers to DNA resection

The opposing activities of 53BP1 and BRCA1 influence pathway choice of DNA double-strand break repair. How BRCA1 counters the inhibitory effect of 53BP1 on DNA resection and homologous recombination is unknown. Here we identify the site of BRCA1-BARD1 required for priming ubiquitin transfer from E2~ubiquitin. We demonstrate that BRCA1-BARD1’s ubiquitin ligase activity is required for repositioning 53BP1 on damaged chromatin. We confirm H2A ubiquitylation by BRCA1-BARD1 and show that an H2A-ubiquitin fusion protein promotes DNA resection and repair in BARD1 deficient cells. We show BRCA1-BARD1 function in homologous recombination requires the chromatin remodeler SMARCAD1. SMARCAD1 binding to H2A-ubiquitin, optimal localization to sites of damage and activity in DNA repair requires its ubiquitin-binding CUE domains. SMARCAD1 is required for 53BP1 repositioning and the need for SMARCAD1 in Olaparib or camptothecin resistance is alleviated by 53BP1 loss. Thus BRCA1- BARD1 ligase activity and subsequent SMARCAD1-dependent chromatin remodeling are critical regulators of DNA repair

Representing and comparing protein structures as paths in three-dimensional space

BACKGROUND: Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction. RESULTS: We propose a structure comparison approach based on a simplified representation of proteins that describes its three-dimensional path by local curvature along the generalized backbone of the polypeptide. We have implemented a dynamic programming procedure that aligns curvatures of proteins by optimizing a defined sum turning angle deviation measure. CONCLUSION: Although our procedure does not directly optimize global structural similarity as measured by RMSD, our benchmarking results indicate that it can surprisingly well recover the structural similarity defined by structure classification databases and traditional structure alignment programs. In addition, our program can recognize similarities between structures with extensive conformation changes that are beyond the ability of traditional structure alignment programs. We demonstrate the applications of procedure to several contexts of structure comparison. An implementation of our procedure, CURVE, is available as a public webserver