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Structure-activity relationships of thiostrepton derivatives: implications for rational drug design
(2014)
Force field (FF) based molecular modeling is an often used method to investigate and study structural and dynamic properties of (bio-)chemical substances and systems. When such a system is modeled or refined, the force field parameters need to be adjusted. This force field parameter optimization can be a tedious task and is always a trade-off in terms of errors regarding the targeted properties. To better control the balance of various properties’ errors, in this study we introduce weighting factors for the optimization objectives. Different weighting strategies are compared to fine-tune the balance between bulk-phase density and relative conformational energies (RCE), using n-octane as a representative system. Additionally, a non-linear projection of the individual property-specific parts of the optimized loss function is deployed to further improve the balance between them. The results show that the overall error is reduced. One interesting outcome is a large variety in the resulting optimized force field parameters (FFParams) and corresponding errors, suggesting that the optimization landscape is multi-modal and very dependent on the weighting factor setup. We conclude that adjusting the weighting factors can be a very important feature to lower the overall error in the FF optimization procedure, giving researchers the possibility to fine-tune their FFs.
Energy Profiles of the Ring Puckering of Cyclopentane, Methylcyclopentane and Ethylcyclopentane
(2019)
Computational chemistry began with the birth of computers in the mid 1900s, and its growth has been directly coupled to the technological advances made in computer science and high-performance computing. A popular goal within the field, be it Newtonian or quantum based methods, is the accurate modelling of physical forces and energetics through mathematics and algorithm design. Through reliable modelling of the underlying forces, molecular simulations frequently provide atomistic insights into macroscopic experimental observations.
Treatment options for acute myeloid leukemia (AML) remain extremely limited and associated with significant toxicity. Nicotinamide phosphoribosyltransferase (NAMPT) is involved in the generation of NAD+ and a potential therapeutic target in AML. We evaluated the effect of KPT-9274, a p21-activated kinase 4/NAMPT inhibitor that possesses a unique NAMPT-binding profile based on in silico modeling compared with earlier compounds pursued against this target. KPT-9274 elicited loss of mitochondrial respiration and glycolysis and induced apoptosis in AML subtypes independent of mutations and genomic abnormalities. These actions occurred mainly through the depletion of NAD+, whereas genetic knockdown of p21-activated kinase 4 did not induce cytotoxicity in AML cell lines or influence the cytotoxic effect of KPT-9274. KPT-9274 exposure reduced colony formation, increased blast differentiation, and diminished the frequency of leukemia-initiating cells from primary AML samples; KPT-9274 was minimally cytotoxic toward normal hematopoietic or immune cells. In addition, KPT-9274 improved overall survival in vivo in 2 different mouse models of AML and reduced tumor development in a patient-derived xenograft model of AML. Overall, KPT-9274 exhibited broad preclinical activity across a variety of AML subtypes and warrants further investigation as a potential therapeutic agent for AML.