Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/−bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy of more than 71%. Overall, the method captures the fundamental molecular descriptors, that can be used as an entity to facilitate prediction of oral bioavailability.

Carcinoma of the cervix is ranked second among the top 5 cancers affecting women globally. Parallel to other cancers, it is also a complex disease involving numerous factors such as human papillomavirus (HPV) infection followed by the activity of oncogenes and environmental factors. The incidence rate of the disease remains high in developing countries due to lack of awareness, followed by mass screening programs, various socioeconomic issues, and low usage of preventive vaccines. Over the past 3 decades, extensive research has taken place in cervical malignancy to elucidate the role of host genes in the pathogenesis of the disease, yet it remains one of the most prevalent diseases. It is imperative that recent genome-wide techniques be used to determine whether carcinogenesis of oncogenes is associated with cervical cancer at the molecular level and to translate that knowledge into developing diagnostic and therapeutic tools. The aim of this study was to discuss HPV predominance with their genotype distribution worldwide, and in India, as well as to discuss the newly identified oncogenes related to cervical cancer in current scenario. Using data from various databases and robust technologies, oncogenes associated with cervical malignancies were identified and are explained in concise manner. Due to the advent of recent technologies, new candidate genes are explored and can be used as precise biomarkers for screening and developing drug targets.

Thyroid hormone (TH) regulates the body's metabolism and iodine, a vital trace mineral, is vital for TH synthesis. As a TH biosynthesis catalyst, iodine has a substantial role in our health. When there is a modest iodine deficit, the thyroid gland grows autonomously, resulting in thyrotoxicosis. Those who consume excessive iodine risk developing hypothyroidism and thyroid autoimmunity. A transient hyperthyroid condition may rapidly increase iodine consumption. Iodine deficiency is common across the globe, and provision of supplementary iodine, in forms such as iodized salt or vegetable oil, has many benefits. Vegetarians, for instance, may not consume adequate amounts of iodine in some countries with high iodine content. Reduced dietary iodine intakes may be a consequence of efforts to reduce salt intakes to prevent hypertension. In addition, iodine consumption is decreasing in many countries, even among those where endemic goiter has previously been eradicated, leading to the re-emergence of iodine-deficiency-related disorders such as goiter. This review will discuss how iodine can contribute to the development of thyroid disease.