Scoring docking conformations using predicted protein interfaces

BACKGROUND: Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP). RESULTS: First, exhaustive evaluation of interface predictors demonstrates that T-PIP, whose predictions are customised to target complexity, is a state-of-the-art method. Second, comparative study between T-PioDock and other state-of-the-art scoring methods establishes T-PioDock as the best performing approach. Moreover, there is good correlation between T-PioDock performance and quality of docking models, which suggests that progress in docking will lead to even better results at recognising near-native conformations. CONCLUSION: Accurate identification of near-native conformations remains a challenging task. Although availability of 3D complexes will benefit from template-based methods such as T-PioDock, we have identified specific limitations which need to be addressed. First, docking software are still not able to produce native like models for every target. Second, current interface predictors do not explicitly consider pairwise residue interactions between proteins and their interacting partners which leaves ambiguity when assessing quality of complex conformations

Search for Exotic mono-jet and mono-photon signatures with the ATLAS detector

Mono-jet and mono-photon signatures are final states in a variety of scenarios beyond the Standard Model, such as the Large Extra Dimension models, gauge-mediated SUSY breaking scenarios, and models with pair production of Weakly Interacting Massive Particles considered as dark matter candidates. The produced exotic particles do not interact with the detector, resulting in missing transverse energy. The results of searches, performed in the ATLAS experiment at the LHC, for new physics in final states with an energetic jet or photon and large missing transverse energy are presented. The mono-jet search is performed using both 4.6 fb−1 of 7 TeV and 10.5 fb−1 of 8 TeV data, while the mono-photon results correspond to 4.6 fb−1 of 7 TeV data

Evaluation of Hyperprolactinemia Risk Factors in Infertile Women Referred to Yazd Infertility CENTER: A Cross-sectional Study

Background: Hyperprolactinemia is one of the most common causes of infertility in women. The prevalence of pituitary tumors is 25-30% among infertile participants with hyperprolactinemia. Objective: The aim of this study was to describe the causes of hyperprolactinemia in infertile women referred to Yazd Infertility Center. Materials and Methods: This cross-sectional study was conducted with 182 infertile women with hyperprolactinemia who were referred to Yazd Infertility Center from February 2018 to October 2019. Serum prolactin was assessed by the human prolactin ELISA kit according to the Padtan Gostar Isar protocol. The age, duration of infertility, causes of hyperprolactinemia, and type of infertility treatment were noted. The MRI findings were added. Results: The mean age of participants was 28.9 ± 0.36 yr and the prolactin level was 76 ± 8.97 ng/ml. The etiology of hyperprolactinemia among the study participants was 35 participants (19.2%) with pituitary adenoma, 47 participants (25.8%) with polycystic ovary syndrome, 14 participants (7.7%) with pituitary adenoma and polycystic ovary syndrome, and 86 participants (47.3%) with idiopathic hyperprolactinemia. The results of this study showed that there was no statistically significant difference between the mean prolactin levels in participants with different causes of hyperprolactinemia (p = 0.31). Conclusion: Idiopathic hyperprolactinemia and polycystic ovary syndrome are the most common reasons for hyperprolactinemia. Key words: Hyperprolactinemia, Infertility, PCOS

Polyamine Metabolism in Leishmania Parasites: A Promising Therapeutic Target

Parasites of the genus Leishmania cause a variety of devastating and often fatal diseases in humans and domestic animals worldwide. The need for new therapeutic strategies is urgent because no vaccine is available, and treatment options are limited due to a lack of specificity and the emergence of drug resistance. Polyamines are metabolites that play a central role in rapidly proliferating cells, and recent studies have highlighted their critical nature in Leishmania. Numerous studies using a variety of inhibitors as well as gene deletion mutants have elucidated the pathway and routes of transport, revealing unique aspects of polyamine metabolism in Leishmania parasites. These studies have also shed light on the significance of polyamines for parasite proliferation, infectivity, and host–parasite interactions. This comprehensive review article focuses on the main polyamine biosynthetic enzymes: ornithine decarboxylase, S-adenosylmethionine decarboxylase, and spermidine synthase, and it emphasizes recent discoveries that advance these enzymes as potential therapeutic targets against Leishmania parasites