N-Terminal-Driven Binding Mechanism of an Antigen Peptide to Human Leukocyte Antigen-A*2402 Elucidated by Multicanonical Molecular Dynamic-Based Dynamic Docking and Path Sampling Simulations

Binding Mechanism between Platelet Glycoprotein and Cyclic Peptide Elucidated by McMD-Based Dynamic Docking

The cyclic peptide OS1 (amino acid sequence: CTERMALHNLC), which has a disulfide bond between both termini cysteine residues, inhibits complex formation between the platelet glycoprotein Ibα (GPIbα) and the von Willebrand factor (vWF) by forming a complex with GPIbα. To study the binding mechanism between GPIbα and OS1 and, therefore, the inhibition mechanism of the protein-protein GPIbα-vWF complex, we have applied our multicanonical molecular dynamics (McMD)-based dynamic docking protocol starting from the unbound state of the peptide. Our simulations have reproduced the experimental complex structure, although the top-ranking structure was an intermediary one, where the peptide was bound in the same location as in the experimental structure; however, the β-switch of GPIbα attained a different conformation. Our analysis showed that subsequent refolding of the β-switch results in a more stable binding configuration, although the transition to the native configuration appears to take some time, during which OS1 could dissociate. Our results show that conformational changes in the β-switch are crucial for successful binding of OS1. Furthermore, we identified several allosteric binding sites of GPIbα that might also interfere with vWF binding, and optimization of the peptide to target these allosteric sites might lead to a more effective inhibitor, as these are not dependent on the β-switch conformation.

Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an experimental structure of their complex has been solved with the ligand bound deep inside the RNA molecule in a seemingly unreachable state, the binding mechanism between these molecules is not yet known. We have therefore used our Multicanonical Molecular Dynamics (McMD)-based dynamic docking protocol to analyze their binding mechanism by simulating the binding process between the riboswitch aptamer domain and the RBF, starting from the apo state of the riboswitch. Here, the refinement stage was crucial to identify the native binding configuration, as several other binding configurations were also found by McMD-based docking simulations. RBF initially binds the interface between P4 and P6 including U61 and G62, which forms a gateway where the ligand lingers until this gateway opens sufficiently to allow the ligand to pass through and slip into the hidden binding site including A48, A49, and A85.

Elucidation of binding mechanism, affinity, and complex structure between mWT1 tumor-associated antigen peptide and HLA-A*24:02

We have applied our advanced computational and experimental methodologies to investigate the complex structure and binding mechanism of a modified Wilms' Tumor 1 (mWT1) protein epitope to the understudied Asian-dominant allele HLA-A*24:02 (HLA-A24) in aqueous solution. We have applied our developed multicanonical molecular dynamics (McMD)-based dynamic docking method to analyze the binding pathway and mechanism, which we verified by comparing the highest probability structures from simulation with our experimentally solved x-ray crystal structure. Subsequent path sampling MD simulations elucidated the atomic details of the binding process and indicated that first an encounter complex is formed between the N-terminal's positive charge of the 9-residue mWT1 fragment peptide and a cluster of negative residues on the surface of HLA-A24, with the major histocompatibility complex (MHC) molecule preferring a predominantly closed conformation. The peptide first binds to this closed MHC conformation, forming an encounter complex, after which the binding site opens due to increased entropy of the binding site, allowing the peptide to bind to form the native complex structure. Further sequence and structure analyses also suggest that although the peptide loading complex would help with stabilizing the MHC molecule, the binding depends in a large part on the intrinsic affinity between the MHC molecule and the antigen peptide. Finally, our computational tools and analyses can be of great benefit to study the binding mechanism of different MHC types to their antigens, where it could also be useful in the development of higher affinity variant peptides and for personalized medicine.

Development of Molecular Dynamics and Research Progress in the Study of Slag

Molecular dynamics is a method of studying microstructure and properties by calculating and simulating the movement and interaction of molecules. The molecular dynamics simulation method has become an important method for studying the structural and dynamic characteristics of slag systems and can make up for the shortcomings of existing detection methods and experiments. Firstly, this paper analyzes the development process and application fields of molecular dynamics, summarizes the general simulation steps and software algorithms of molecular dynamics simulation methods, and discusses the advantages and disadvantages of the algorithms and the common functions of the software. Secondly, the research status and application progress of molecular dynamics simulation methods in the study of phosphate, silicate, aluminate and aluminosilicate are introduced. On this basis, a method of combining molecular dynamics simulation with laboratory experiments is proposed, which will help obtain more accurate simulation results. This review provides theoretical guidance and a technical framework for the effective analysis of the microstructure of different slag systems via molecular dynamics, so as to finally meet the needs of iron and steel enterprises in producing high-quality steel grades.

Mutual induced-fit mechanism drives binding between intrinsically disordered Bim and cryptic binding site of Bcl-xL

The intrinsically disordered region (IDR) of Bim binds to the flexible cryptic site of Bcl-xL, a pro-survival protein involved in cancer progression that plays an important role in initiating apoptosis. However, their binding mechanism has not yet been elucidated. We have applied our dynamic docking protocol, which correctly reproduced both the IDR properties of Bim and the native bound configuration, as well as suggesting other stable/meta-stable binding configurations and revealed the binding pathway. Although the cryptic site of Bcl-xL is predominantly in a closed conformation, initial binding of Bim in an encounter configuration leads to mutual induced-fit binding, where both molecules adapt to each other; Bcl-xL transitions to an open state as Bim folds from a disordered to an α-helical conformation while the two molecules bind each other. Finally, our data provides new avenues to develop novel drugs by targeting newly discovered stable conformations of Bcl-xL.

Advancing the field of computational drug design using multicanonical molecular dynamics-based dynamic docking

Multicanonical molecular dynamics (McMD)-based dynamic docking is a powerful tool to not only predict the native binding configuration between two flexible molecules, but it can also be used to accurately simulate the binding/unbinding pathway. Furthermore, it can also predict alternative binding sites, including allosteric ones, by employing an exhaustive sampling approach. Since McMD-based dynamic docking accurately samples binding/unbinding events, it can thus be used to determine the molecular mechanism of binding between two molecules. We developed the McMD-based dynamic docking methodology based on the powerful, but woefully underutilized McMD algorithm, combined with a toolset to perform the docking and to analyze the results. Here, we showcase three of our recent works, where we have applied McMD-based dynamic docking to advance the field of computational drug design. In the first case, we applied our method to perform an exhaustive search between Hsp90 and one of its inhibitors to successfully predict the native binding configuration in its binding site, as we refined our analysis methods. For our second case, we performed an exhaustive search of two medium-sized ligands and Bcl-xL, which has a cryptic binding site that differs greatly between the apo and holo structures. Finally, we performed a dynamic docking simulation between a membrane-embedded GPCR molecule and a high affinity ligand that binds deep within its receptor's pocket. These advanced simulations showcase the power that the McMD-based dynamic docking method has, and provide a glimpse of the potential our methodology has to unravel and solve the medical and biophysical issues in the modern world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01010-z.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.