Since its early days in the 19th century, medicinal chemistry has concentrated its efforts on the treatment of diseases, using tools from areas such as chemistry, pharmacology, and molecular biology. The understanding of biological mechanisms and signaling pathways is crucial information for the development of potential agents for the treatment of diseases mainly because they are such complex processes. Given the limitations that the experimental approach presents, computational chemistry is a valuable alternative for the study of these systems and their behavior. Thus, classical molecular dynamics, based on Newton's laws, is considered a technique of great accuracy, when appropriated force fields are used, and provides satisfactory contributions to the scientific community. However, as many configurations are generated in a large MD simulation, methods such as Statistical Inefficiency and Optimal Wavelet Signal Compression Algorithm are great tools that can reduce the number of subsequent QM calculations. Accordingly, this review aims to briefly discuss the importance and relevance of medicinal chemistry allied to computational chemistry as well as to present a case study where, through a molecular dynamics simulation of AMPK protein (50 ns) and explicit solvent (TIP3P model), a minimum number of snapshots necessary to describe the oscillation profile of the protein behavior was proposed. For this purpose, the RMSD calculation, together with the sophisticated OWSCA method was used to propose the minimum number of snapshots.

• Klíčová slova
• Medicinal chemistry, OWSCA, computational chemistry., conformational choice, molecular dynamics, snapshots,
• MeSH
• algoritmy MeSH
• chemie farmaceutická MeSH
• kvantová teorie MeSH
• lidé MeSH
• proteinkinasy aktivované AMP metabolismus   chemie   MeSH
• simulace molekulární dynamiky * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH
• Názvy látek
• proteinkinasy aktivované AMP MeSH

Early phase diagnosis of human diseases has still been a challenge in the medicinal field, and one of the efficient non-invasive techniques that is vastly used for this purpose is magnetic resonance imaging (MRI). MRI is able to detect a wide range of diseases and conditions, including nervous system disorders and cancer, and uses the principles of NMR relaxation to generate detailed internal images of the body. For such investigation, different metal complexes have been studied as potential MRI contrast agents. With this in mind, this work aims to investigate two systems containing the vanadium complexes [VO(metf)2]·H2O (VC1) and [VO(bpy)2Cl]+ (VC2), being metformin and bipyridine ligands of the respective complexes, with the biological targets AMPK and ULK1. These biomolecules are involved in the progression of Alzheimer's disease and triple-negative breast cancer, respectively, and may act as promising spectroscopic probes for detection of these diseases. To initially evaluate the behavior of the studied ligands within the aforementioned protein active sites and aqueous environment, four classical molecular dynamics (MD) simulations including VC1 + H2O (1), VC2 + H2O (2), VC1 + AMPK + H2O (3), and VC2 + ULK1 + H2O (4) were performed. From this, it was obtained that for both systems containing VCs and water only, the theoretical calculations implied a higher efficiency when compared with DOTAREM, a famous commercially available contrast agent for MRI. This result is maintained when evaluating the system containing VC1 + AMPK + H2O. Nevertheless, for the system VC2 + ULK1 + H2O, there was observed a decrease in the vanadium complex efficiency due to the presence of a relevant steric hindrance. Despite that, due to the nature of the interaction between VC2 and ULK1, and the nature of its ligands, the study gives an insight that some modifications on VC2 structure might improve its efficiency as an MRI probe.

• Klíčová slova
• NMR relaxation, OWSCA, computational chemistry, molecular dynamics, vanadium complexes,
• Publikační typ
• časopisecké články MeSH

Wavelets are mathematical tools used to decompose and represent another function described in the time domain, allowing the study of each component of the original function with a scale-compatible resolution. Thus, these transforms have been used to select conformations from molecular dynamics (MD) trajectories in systems of fundamental and technological interest. Recently, our research group has used wavelets to develop and validate a method, meant to select structures from MD trajectories, which we named OWSCA (optimal wavelet signal compression algorithm). Here, we moved forward on this project by demonstrating the efficacy of this method on the study of three different systems (non-flexible organic, flexible organic, and protein). For each system, 93 wavelets were investigated to verify which is the best one for a given organic system. The results show that the best wavelets were different for each system and, also, very close to the experimental values, with the wavelets db1, rbio 3.1, and bior1.1 being selected for the non-flexible, flexible organic, and protein systems, respectively. This reinforces our OWSCA as a very efficient and promising method for the selection of structures from MD trajectories of different classes of compounds. Our findings also point out that additional studies considering wavelet families are needed for defining the best wavelet for representing each system under study.

• MeSH
• algoritmy * MeSH
• lidé MeSH
• simulace molekulární dynamiky * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH