Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity

Anti-inflammatory Activity: In silico and In vivo of Sapogenins Present in Agave brittoniana subsp. brachypus (Trel.)

BACKGROUND

Agave brittoniana subsp. brachypus is an endemic plant of Cuba, which contains different steroidal sapogenins with anti-inflammatory effects. This work aims to develop computational models which allow the identification of new chemical compounds with potential anti-inflammatory activity.

METHODS

The in vivo anti-inflammatory activity was evaluated in two rat models: carrageenaninduced paw edema and cotton pellet-induced granuloma. In each study, we used 30 Sprague Dawley male rats divided into five groups containing six animals. The products isolated and administrated were fraction rich in yuccagenin and sapogenins crude.

RESULTS

The obtained model, based on a classification tree, showed an accuracy value of 86.97% for the training set. Seven compounds (saponins and sapogenins) were identified as potential antiinflammatory agents in the virtual screening. According to in vivo studies, the yuccagenin-rich fraction was the greater inhibitor of the evaluated product from Agave.

CONCLUSION

The evaluated metabolites of the Agave brittoniana subsp. Brachypus showed an interesting anti-inflammatory effect.

Recent Advances in Classification of Brain Tumor from MR Images - State of the Art Review from 2017 to 2021

BACKGROUND

The task of identifying a tumor in the brain is a complex problem that requires sophisticated skills and inference mechanisms to accurately locate the tumor region. The complex nature of the brain tissue makes the problem of locating, segmenting, and ultimately classifying Magnetic Resonance (MR) images a complex problem. The aim of this review paper is to consolidate the details of the most relevant and recent approaches proposed in this domain for the binary and multi-class classification of brain tumors using brain MR images.

OBJECTIVE

In this review paper, a detailed summary of the latest techniques used for brain MR image feature extraction and classification is presented. A lot of research papers have been published recently with various techniques proposed for identifying an efficient method for the correct recognition and diagnosis of brain MR images. The review paper allows researchers in the field to familiarize themselves with the latest developments and be able to propose novel techniques that have not yet been explored in this research domain. In addition, the review paper will facilitate researchers, who are new to machine learning algorithms for brain tumor recognition, to understand the basics of the field and pave the way for them to be able to contribute to this vital field of medical research.

RESULTS

In this paper, the review is performed for all recently proposed methods for both feature extraction and classification. It also identifies the combination of feature extraction methods and classification methods that when combined would be the most efficient technique for the recognition and diagnosis of brain tumor from MR images. In addition, the paper presents the performance metrics particularly the recognition accuracy, of selected research published between 2017- 2021.

Isoxazole derivatives as anticancer agent: A review on synthetic strategies, mechanism of action and SAR studies

Breast cancer is the second most leading cause of death among women. Multiple drugs have been approved by FDA for the treatment of BC. The major drawbacks of existing drugs are the development of resistance, toxicity, selectivity problem. The other therapies like hormonal therapy, surgery, radiotherapy, and immune therapy are in use but showed many side effects like bioavailability issues, non-selectivity, pharmacokinetic-pharmacodynamic problems. Therefore, there is an urgent need to develop new moieties that are nonviolent and more effective in the treatment of cancer. Isoxazole derivatives have gain popularity in recent years due to anticancer potential with the least side effects. These derivatives act as an anticancer agent with different mechanisms like inducing apoptosis, aromatase inhibition, disturbing tubulin congregation, topoisomerase inhibition, HDAC inhibition, and ERα inhibition. In this article, we have explored the synthetic strategies, anticancer mechanism of action along with SAR studies of isoxazole derivatives.

Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree

Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation procedure and through a test set, achieving accuracy values over 90.5% and 92.2%, correspondingly. The values of sensitivity and specificity were around 90% in all series; also the false alarm rate values were under 10.5% for all sets. In addition, a simulated ligand-based virtual screening for several compounds recently reported as promising anti-chagasic agents was carried out, yielding good agreement between predictions and experimental results. Finally, the present work constitutes an example of how this rational computer-based method can help reduce the cost and increase the rate in which novel compounds are developed against Chagas disease.

Recent Development in Indole Derivatives as Anticancer Agents for Breast Cancer

BACKGROUND

Breast Cancer (BC) is the second most common cause of cancer related deaths in women. Due to severe side effects and multidrug resistance, current therapies like hormonal therapy, surgery, radiotherapy and chemotherapy become ineffective. Also, the existing drugs for BC treatment are associated with several drawbacks such as poor oral bioavailability, non-selectivity and poor pharmacodynamics properties. Therefore, there is an urgent need for the development of more effective and safer anti BC agents.

OBJECTIVE

This article explored in detail the possibilities of indole-based heterocyclic compounds as anticancer agents with breast cancer as their major target.

METHODS

Recent literature related to indole derivatives endowed with encouraging anti BC potential is reviewed. With special focus on BC, this review offers a detailed account of multiple mechanisms of action of various indole derivatives: aromatase inhibitor, tubulin inhibitor, microtubule inhibitor, targeting estrogen receptor, DNA-binding mechanism, induction of apoptosis, inhibition of PI3K/AkT/NFkB/mTOR, and HDAC inhibitors, by which these derivatives have shown promising anticancer potential.

RESULTS

Exhaustive literature survey indicated that indole derivatives are associated with properties of inducing apoptosis and disturbing tubulin assembly. Indoles are also associated with the inhibition of NFkB/mTOR/PI3K/AkT and regulation of estrogen-mediated activity. Furthermore, indole derivatives have been found to modulate critical targets such as topoisomerase and HDAC. These derivatives have shown significant activity against breast cancer cells.

CONCLUSION

In BC, indole derivatives seem to be quite competent and act through various mechanisms that are well established in case of BC. This review has shown that indole derivatives can further be explored for the betterment of BC chemotherapy. A lot of potential is still hidden which demands to be discovered for upgrading BC chemotherapy.

Towards understanding aromatase inhibitory activity via QSAR modeling

Aromatase is a rate-limiting enzyme for estrogen biosynthesis that is overproduced in breast cancer tissue. To block the growth of breast tumors, aromatase inhibitors (AIs) are employed to bind and inhibit aromatase in order to lower the amount of estrogen produced in the body. Although a number of synthetic aromatase inhibitors have been released for clinical use in the treatment of hormone-receptor positive breast cancer, these inhibitors may lead to undesirable side effects (e.g. increased rash, diarrhea and vomiting; effects on the bone, brain and heart) and therefore, the search for novel AIs continues. Over the past decades, there has been an intense effort in employing medicinal chemistry and quantitative structure-activity relationship (QSAR) to shed light on the mechanistic basis of aromatase inhibition. To the best of our knowledge, this article constitutes the first comprehensive review of all QSAR studies of both steroidal and non-steroidal AIs that have been published in the field. Herein, we summarize the experimental setup of these studies as well as summarizing the key features that are pertinent for robust aromatase inhibition.