Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy

Saposin C Coupled Lipid Nanovesicles Specifically Target Arthritic Mouse Joints for Optical Imaging of Disease Severity

Rheumatoid arthritis is a chronic inflammatory disease affecting approximately 1% of the population and is characterized by cartilage and bone destruction ultimately leading to loss of joint function. Early detection and intervention of disease provides the best hope for successful treatment and preservation of joint mobility and function. Reliable and non-invasive techniques that accurately measure arthritic disease onset and progression are lacking. We recently developed a novel agent, SapC-DOPS, which is composed of the membrane-associated lysosomal protein saposin C (SapC) incorporated into 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (DOPS) lipid nanovesicles. SapC-DOPS has a high fusogenic affinity for phosphatidylserine-enriched microdomains on surfaces of target cell membranes. Incorporation of a far-red fluorophore, CellVue Maroon (CVM), into the nanovesicles allows for in vivo non-invasive visualization of the agent in targeted tissue. Given that phosphatidylserine is present only on the inner leaflet of healthy plasma membranes but is “flipped” to the outer leaflet upon cell damage, we hypothesized that SapC-DOPS would target tissue damage associated with inflammatory arthritis due to local surface-exposure of phosphatidylserine. Optical imaging with SapC-DOPS-CVM in two distinct models of arthritis, serum-transfer arthritis (e.g., K/BxN) and collagen-induced arthritis (CIA) revealed robust SapC-DOPS-CVM specific localization to arthritic paws and joints in live animals. Importantly, intensity of localized fluorescent signal correlated with macroscopic arthritic disease severity and increased with disease progression. Flow cytometry of cells extracted from arthritic joints demonstrated that SapC-DOPS-CVM localized to an average of 7–8% of total joint cells and primarily to CD11b+Gr-1+ cells. Results from the current studies strongly support the application of SapC-DOPS-CVM for advanced clinical and research applications including: detecting early arthritis onset, assessing disease progression real-time in live subjects, and providing novel information regarding cell types that may mediate arthritis progression within joints

Machine learning for molecular and materials science

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.</p

Genetic control of immune-mediated necrosis of Mycobacterium avium granulomas

Intravenous infection of C57BL/6 and C57BL/10 mice with low doses of a highly virulent strain of Mycobacterium avium (ATCC 25291) led to the development of granulomas that underwent necrosis. In contrast, neither BALB/c nor DBA/1 mice developed granuloma necrosis after such infection despite a similar course of mycobacterial proliferation. Studies with C57BL/10 mice congenic for the Hc locus revealed that an intact complement C5 gene is required for granuloma necrosis. On the other hand, genetic disruption of the interleukin-10 gene in BALB/c mice made this strain susceptible to granuloma necrosis