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Molecular dynamics (MD) simulation has been widely used in the field of biomedicine to study the conformational transition of proteins caused by mutation or ligand binding/unbinding. It provides some perspectives those are difficult to find in traditional biochemical or pathological experiments, for example, detailed effects of mutations on protein structure and protein–protein/ligand interaction at the atomic level. In this review, a broad overview on conformation changes and drug discovery by MD simulation is given. We first discuss the preparation of protein structure for MD simulation, which is a key step that determines the accuracy of the simulation. Then, we summarize the applications of commonly used force fields and MD simulations in scientific research. Finally, enhanced sampling methods and common applications of these methods are introduced. In brief, MD simulation is a powerful tool and it can be used to guide experimental study. The combination of MD simulation and experimental techniques is an a priori means to solve the biomedical problems and give a deep understanding on the relationship between protein structure and function. [ABSTRACT FROM AUTHOR]

Intrinsically disordered proteins (IDPs) are closely related to various human diseases. Because IDPs lack certain tertiary structure, it is difficult to use X‐ray and NMR methods to measure their structures. Therefore, molecular dynamics simulation is a useful tool to study the conformer distribution of IDPs. However, most generic protein force fields were found to be insufficient in simulations of IDPs. Here, we report our development for the CHARMM community. Our residue‐specific IDP force field (CHARMM36IDPSFF) was developed based on the base generic force field with CMAP corrections for all 20 naturally occurring amino acids. Multiple tests show that the simulated chemical shifts with the newly developed force field are in quantitative agreement with NMR experiment and are more accurate than the base generic force field. Comparison of J‐couplings with previous work shows that CHARMM36IDPSFF and its corresponding base generic force field have their own advantages. In addition, CHARMM36IDPSFF simulations also agree with experiment for SAXS profiles and radii of gyration of IDPs. Detailed analysis shows that CHARMM36IDPSFF can sample more diverse and disordered conformers. These findings confirm that the newly developed force field can improve the balance of accuracy and efficiency for the conformer sampling of IDPs. [ABSTRACT FROM AUTHOR]

Intrinsically disordered proteins are proteins which lack of specific tertiary structure and unable to fold spontaneously without the partner binding. These intrinsically disordered proteins are found to associate with various diseases, such as diabetes, cancer, and neurodegenerative diseases. However, current widely used force fields, such as ff99SB, ff14SB, OPLS/AA, and Charmm27, are insufficient in sampling the conformational characters of intrinsically disordered proteins. In this study, the CMAP method was used to correct the φ/ ψ distributions of disorder-promoting amino acids. The simulation results show that the force filed parameters ( ff14IDPs) can improve the φ/ ψ distributions of the disorder-promoting amino acids, with RMSD less than 0.10% relative to the benchmark data of intrinsically disordered proteins. Further test suggests that the calculated secondary chemical shifts under ff14IDPs are in quantitative agreement with the data of NMR experiment for five tested systems. In addition, the simulation results show that ff14IDPs can still be used to model structural proteins, such as tested lysozyme and ubiquitin, with better performance in coil regions than the original general Amber force field ff14SB. These findings confirm that the newly developed Amber ff14IDPs is a robust model for improving the conformation sampling of intrinsically disordered proteins. [ABSTRACT FROM AUTHOR]

CCR5 is the key receptor of HIV-1 virus entry into host cells and it becomes an attractive target for antiretroviral drug design. To date, six types of CCR5 antagonist were synthesized and evaluated. To search more potent bio-active compounds, non-linear support vector machine was used to construct the relationship models for 103 oximino-piperidino-piperidine CCR5 antagonists. Then, comparative molecular field analysis and comparative molecular similarity indices analysis models were constructed after alignment with their common substructure. Twenty-one structural diverse compounds, which were not included in the support vector machine, comparative molecular field analysis, and comparative molecular similarity indices analysis models, validated these models. The results show that these models possess good predictive ability. When comparing between support vector machine and 3D-quantitative structure activity relationship models, the results obtained from these two methods are compatible. However, 3D-quantitative structure activity relationship model is significantly better than support vector machine model and previous reported pharmacophore model. These models can help us to make quantitative prediction of their bio-activities before in vitro and in vivo stages. [ABSTRACT FROM AUTHOR]