The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG.

Human ether a-go-go related gene (hERG) or KV11.1 potassium channels mediate the rapid delayed rectifier current (IKr) in cardiac myocytes. Drug-induced inhibition of hERG channels has been implicated in the development of acquired long QT syndrome type (aLQTS) and fatal arrhythmias. Several marketed drugs have been withdrawn for this reason. Therefore, there is considerable interest in developing better tests for predicting drugs which can block the hERG channel. The drug-binding pocket in hERG channels, which lies below the selectivity filter, normally contains K+ ions and water molecules. In this study, we test the hypothesis that these water molecules impact drug binding to hERG. We developed 3D QSAR models based on alignment independent descriptors (GRIND) using docked ligands in open and closed conformations of hERG in the presence (solvated) and absence (non-solvated) of water molecules. The ligand–protein interaction fingerprints (PLIF) scheme was used to summarize and compare the interactions. All models delineated similar 3D hERG binding features, however, small deviations of about ~0.4 Å were observed between important hotspots of molecular interaction fields (MIFs) between solvated and non-solvated hERG models. These small changes in conformations do not affect the performance and predictive power of the model to any significant extent. The model that exhibits the best statistical values was attained with a cryo_EM structure of the hERG channel in open state without water. This model also showed the best R2 of 0.58 and 0.51 for the internal and external validation test sets respectively. Our results suggest that the inclusion of water molecules during the docking process has little effect on conformations and this conformational change does not impact the predictive ability of the 3D QSAR models.

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The Mitsunobu reaction plays a vital part in organic chemistry due to its wide synthetic applications. It is considered as a significant reaction for the interconversion of one functional group (alcohol) to another (ester) in the presence of oxidizing agents (azodicarboxylates) and reducing agents (phosphines). It is a renowned stereoselective reaction which inverts the stereochemical configuration of end products. One of the most important applications of the Mitsunobu reaction is its role in the synthesis of natural products. This review article will focus on the contribution of the Mitsunobu reaction towards the total synthesis of natural products, highlighting their biological potential during recent years.

Disease modeling using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has both challenges and promise. While patient-derived iPSC-CMs provide a unique opportunity for disease modeling with isogenic cells, the challenge is that these cells still demonstrate distinct properties which make it functionally less akin to adult cardiomyocytes. In response to this challenge, numerous innovations in differentiation and modification of hiPSC-CMs and culture techniques have been developed. Here, we provide a focused commentary on hiPSC-CMs for use in disease modeling, the progress made in generating electrically and metabolically mature hiPSC-CMs and enabling investigative platforms. The solutions are bringing us closer to the promise of modeling heart disease using human cells in vitro.

Abstract-The aim of telemedicine system is to diagnose patients remotely; this includes healthcare provision to patients in far flung areas. The process of remote diagnosis is mainly dependent on bandwidths which are absolutely essential in terms of communications via the networks. Such communications have to be carefully monitored, because randomly sending data across the network and loading of packets as direct stream of cameras would result in chocking the bandwidth. Hence it is extremely important to make sure that the data is compressed so that there is minimum usage of bandwidth. But this has to be done in a way that maintains the quality at its best. This retention of good quality along with minimizing the usage of data is done by means of compression the streams obtained through cameras and then decompressing the data at the other end. This purpose was previously achieved by H.264 codec. Our major target was up gradation of the existing codec by introducing the latest; H.265. The Libde265 (Decoder) and the x265 (encoder) libraries have been used for the purpose of developing the H.265 codec. The H265 is an advanced codec, having better quality and ability to achieve far better compression than its predecessor. It has been shown through the algorithm and coding of H.265 that is has better compressing ability and the quality is maintained during the transmission of videos. This is highly desirable for the field of telemedicine as it can make improvements in providing healthcare services by easing the transmission of data in the form of videos from the patient end to the doctor's end.

Over the last two decades, an exponentially expanding number of genetic variants have been identified associated with inherited cardiac conditions. These tremendous gains also present challenges in deciphering the clinical relevance of unclassified variants or variants of uncertain significance (VUS). This review provides an overview of the advancements (and challenges) in functional and computational approaches to characterize variants and help keep pace with VUS identification related to inherited heart diseases.

Polio viral proteinase 2A performs several essential functions in genome replication. Its inhibition prevents viral replication, thus making it an excellent substrate for drug development. In this study, the three-dimensional structure of 2A protease was determined and optimized by homology modelling. To predict the molecular basis of the interaction of small molecular agonists, docking simulations were performed on a structurally diverse dataset of poliovirus 2A protease (PV2Apr°) inhibitors. Docking results were employed to identify high risk missense mutations that are highly damaging to the structure, as well as the function, of the protease. Intrinsic disorder regions (IDRs), drug binding sites (DBS), and protein stability changes upon mutations were also identified among them. Our results demonstrated dominant roles for Lys 15, His 20, Cys 55, Cys 57, Cys 64, Asp 108, Cys 109 and Gly 110, indicating the presence of various important drug binding sites of the protein. Upon subjecting these sites to single-nucleotide polymorphism (SNP) analysis, we observed that out of 155 high risk SNPs, 139 residues decrease the protein stability. We conclude that these missense mutations can affect the functionality of the 2A protease, and that identified protein binding sites can be directed for the attachment and inhibition of the target proteins.