Immunomics Datasets and Tools: To Identify Potential Epitope Segments for Designing Chimeric Vaccine Candidate to Cervix Papilloma

Binding energy analysis and molecular dynamic simulation studies of the designed orally active, non-toxic GABARAP modulators

Epilepsy is a severe neurological disorder that occurs when the communication between the neurons is disturbed. Gamma-amino butyric acid-associated protein (GABARAP) plays a key role in balancing Gamma-aminobutyric acid-A (GABA(A)) receptor functions of inhibiting the neurotransmission and controlling the seizure. In this study, we introduce the derivatives of the selected anti-epileptic drugs, namely Felbamate and Clobazam, by substituting different hydrophilic and hydrophobic groups at the specified positions. Molecular docking studies between the derivatives and GABARAP were carried out using PyRx software. The interacting residues were identified from LigPlot⁺. Drug-likeness, drug-related properties, and toxic endpoints of each derivative were analyzed using the SwissADME, Osiris property explorer, and ProTox-II servers. After analyzing the binding energy, drug-properties, and toxicity, the best five derivatives of Felbamate and Clobazam were selected. Molecular Dynamic simulation studies involving the target-ligand interaction were carried out for 100 nanoseconds using GROMACS 2018. The root mean square deviation, root mean square fluctuation, radius of gyration, Solvent accessible area, Energy plots and trajectories of the ten GABARAP complexes of the derivatives, and two GABARAP complexes of parent drugs were compared and critically analyzed. Among the five Felbamate derivatives, F7 formed the most stable complex with GABARAP. Among the five Clobazam derivatives, C27, C33 and C32 showed stable GABARAP interaction. In light of the above systematic computational analysis, we propose F7, C27, C33, and C32 as the potential anti-epileptic drug candidates for developing novel therapeutics. The substitution of hydrophobic groups at para position on benzene ring has promoted strong binding to GABARAP. Communicated by Ramaswamy H. Sarma.

An overview of in silico vaccine design against different pathogens and cancer

INTRODUCTION

Due to overcome the hardness of the vaccine design, computational vaccinology is emerging widely. Prediction of T cell and B cell epitopes, antigen processing analysis, antigenicity analysis, population coverage, conservancy analysis, allergenicity assessment, toxicity prediction, and protein-peptide docking are important steps in the process of designing and developing potent vaccines against various viruses and cancers. In order to perform all of the analyses, several bioinformatics tools and online web servers have been developed. Scientists must take the decision to apply more suitable and precise servers for each part based on their accuracy.

AREAS COVERED

In this review, a wide-range list of different bioinformatics tools and online web servers has been provided. Moreover, some studies were proposed to show the importance of various bioinformatics tools for predicting and developing efficient vaccines against different pathogens including viruses, bacteria, parasites, and fungi as well as cancer.

EXPERT OPINION

Immunoinformatics is the best way to find potential vaccine candidates against different pathogens. Thus, the selection of the most accurate tools is necessary to predict and develop potent preventive and therapeutic vaccines. To further evaluation of the computational and in silico vaccine design, in vitro/in vivo analyses are required to develop vaccine candidates.

Viewing the Emphasis on State-of-the-Art Magnetic Nanoparticles: Synthesis, Physical Properties, and Applications in Cancer Theranostics

Cancer-related mortality is a leading cause of death among both men and women around the world. Target-specific therapeutic drugs, early diagnosis, and treatment are crucial to reducing the mortality rate. One of the recent trends in modern medicine is "Theranostics," a combination of therapeutics and diagnosis. Extensive interest in magnetic nanoparticles (MNPs) and ultrasmall superparamagnetic iron oxide nanoparticles (NPs) has been increasing due to their biocompatibility, superparamagnetism, less-toxicity, enhanced programmed cell death, and auto-phagocytosis on cancer cells. MNPs act as a multifunctional, noninvasive, ligand conjugated nano-imaging vehicle in targeted drug delivery and diagnosis. In this review, we primarily discuss the significance of the crystal structure, magnetic properties, and the most common method for synthesis of the smaller sized MNPs and their limitations. Next, the recent applications of MNPs in cancer therapy and theranostics are discussed, with certain preclinical and clinical experiments. The focus is on implementation and understanding of the mechanism of action of MNPs in cancer therapy through passive and active targeting drug delivery (magnetic drug targeting and targeting ligand conjugated MNPs). In addition, the theranostic application of MNPs with a dual and multimodal imaging system for early diagnosis and treatment of various cancer types including breast, cervical, glioblastoma, and lung cancer is reviewed. In the near future, the theranostic potential of MNPs with multimodality imaging techniques may enhance the acuity of personalized medicine in the diagnosis and treatment of individual patients.