Approaches to Backbone Flexibility in Protein-Protein Docking.

Proteins are the fundamental organic macromolecules in living systems that play a key role in a variety of biological functions including immunological detection, intracellular trafficking, and signal transduction. The docking of proteins has greatly advanced during recent decades and has become a crucial complement to experimental methods. Protein-protein docking is a helpful method for simulating protein complexes whose structures have not yet been solved experimentally. This chapter focuses on major search tactics along with various docking programs used in protein-protein docking algorithms, which include: direct search, exhaustive global search, local shape feature matching, randomized search, and broad category of post-docking approaches. As backbone flexibility predictions and interactions in high-resolution protein-protein docking remain important issues in the overall optimization context, we have put forward several methods and solutions used to handle backbone flexibility. In addition, various docking methods that are utilized for flexible backbone docking, including ATTRACT, FlexDock, FLIPDock, HADDOCK, RosettaDock, FiberDock, etc., along with their scoring functions, algorithms, advantages, and limitations are discussed. Moreover, what progress in search technology is expected, including not only the creation of new search algorithms but also the enhancement of existing ones, has been debated. As conformational flexibility is one of the most crucial factors affecting docking success, more work should be put into evaluating the conformational flexibility upon binding for a particular case in addition to developing new algorithms to replace the rigid body docking and scoring approach.

Decoding the Role of Epigenetics in Breast Cancer Using Formal Modeling and Machine-Learning Methods.

Breast carcinogenesis is known to be instigated by genetic and epigenetic modifications impacting multiple cellular signaling cascades, thus making its prevention and treatments a challenging endeavor. However, epigenetic modification, particularly DNA methylation-mediated silencing of key TSGs, is a hallmark of cancer progression. One such tumor suppressor gene (TSG) RUNX3 (Runt-related transcription factor 3) has been a new insight in breast cancer known to be suppressed due to local promoter hypermethylation mediated by DNA methyltransferase 1 (DNMT1). However, the precise mechanism of epigenetic-influenced silencing of the RUNX3 signaling resulting in cancer invasion and metastasis remains inadequately characterized. In this study, a biological regulatory network (BRN) has been designed to model the dynamics of the DNMT1-RUNX3 network augmented by other regulators such as p21, c-myc, and p53. For this purpose, the René Thomas qualitative modeling was applied to compute the unknown parameters and the subsequent trajectories signified important behaviors of the DNMT1-RUNX3 network (i.e., recovery cycle, homeostasis, and bifurcation state). As a result, the biological system was observed to invade cancer metastasis due to persistent activation of oncogene c-myc accompanied by consistent downregulation of TSG RUNX3. Conversely, homeostasis was achieved in the absence of c-myc and activated TSG RUNX3. Furthermore, DNMT1 was endorsed as a potential epigenetic drug target to be subjected to the implementation of machine-learning techniques for the classification of the active and inactive DNMT1 modulators. The best-performing ML model successfully classified the active and least-active DNMT1 inhibitors exhibiting 97% classification accuracy. Collectively, this study reveals the underlined epigenetic events responsible for RUNX3-implicated breast cancer metastasis along with the classification of DNMT1 modulators that can potentially drive the perception of epigenetic-based tumor therapy.

Discovering novel inhibitors of P2Y12 receptor using structure-based virtual screening, molecular dynamics simulation and MMPBSA approaches.

P2Y12, a G-protein coupled receptor is involved in platelets plug formation and it amplifies and maintains the process of platelet aggregation. P2Y12 is considered as a potent target to inhibit platelet aggregation in thrombotic and cardiac emergencies. This research focuses on in silico inhibition of P2Y12 by structure-based drug design techniques. Initially, drug-like compounds were selected from ZINC database by structure-based pharmacophore model. Subsequently, 4479 compounds matched with the pharmacophore model that were scrutinized by molecular docking. Later, based on docking score and rank, top 10% of the docked library was selected to predict their pharmacokinetic properties and 191 compounds possessed good pharmacokinetic profile. The binding pattern of those compounds were analyzed to select novel, less toxic and more potent P2Y12 antagonists. In protein-ligand interaction analysis, seven compounds showed significant binding potential, therefore examined through molecular dynamic simulation. Among the selected hits, two compounds (CP31 and CP32) exhibited higher binding energies in SANDER Poisson-Boltzmann Surface Area (PBSA) approach than agonist bound P2Y12 (4PXZ) and antithrombotic drug bound P2Y12 (4NTJ), while one compound (CP25) showed comparable binding energy than 4NTJ. The binding free energy analysis reflect that interactions of all selected Hits with P2Y12 are promising and specifically CP25, CP31, and CP32 could serve as novel inhibitors of P2Y12.

Recent Updates on the Role of Nanoparticles in the Treatment of Viral Diseases.

Viral infections such as AIDS, hepatitis, herpes keratitis, and herpes labialis became resistant to drugs and it is difficult to design vaccine. In current era drug-resistant viruses are now treated by nanoparticles (NPs) and this field is known as nanobiotechnology that relates nanoscience with the biological system. NPs due to their antiviral activity are used in the treatment of viral diseases. The advantages of using the NP is its specific target action and increase the efficiency of treatment with minimum side effects. Liposomes, quantum dots, polymeric NPs, solid lipid NPs, silver NPs, gold NPs, and magnetic NPs are used to treat viral infections. NP-based therapeutics have completely replaced the usage of drugs and vaccines for viral diseases treatment. Nano vaccines have been investigated for the delivery of drugs; biomaterials-based NPs are in development to be formulated into nano vaccines. But there are limitations in the manufacturing and stabilization of NPs in the body. This review focuses on the antiviral activity of several NPs, its uptake by different viruses for viral disease treatment, nano vaccines, and the limitation of the NPs as nanotherapeutics.