Новые возможности Visual Dynamics 3.0

According to the IUPAC definition, MD is the simulation procedure that consists of computing the motion of atoms in a molecule or of individual atoms or molecules in solids, liquids, and gases, according to Newton's laws of motion. The forces acting on atoms, necessary to simulate their motion, are commonly calculated using force fields from molecular mechanics¹. It can be applied to any phenomenon that seeks to extract information at a molecular and often atomic level².

MD is one of the techniques incorporated into bioinformatics, specifically structural bioinformatics. With it, it is possible to obtain kinetic and thermodynamic characteristics of biomolecular structures. For example, macromolecular stability, identification of allosteric sites, elucidation of mechanisms of enzymatic activity, molecular recognition and properties of complexes with small molecules, association between proteins, protein folding, and its hydration³. Furthermore, MD enables a wide range of studies, including molecular design (widely used in drug design), in determining the structure and its refinement (X-ray, NMR, and protein modeling)³. The results obtained at the end of an MD are the richest and most complete in terms of non-quantum simulation⁴.Classical MD is much more efficient than might be expected from a full consideration of the physics of biomolecular systems due to the number of substantial approximations. Notably, quantum dynamical effects are usually ignored³. However, implementing an MD experiment is not trivial⁵. It requires knowledge of computing, especially the Linux Terminal, as most structural bioinformatics software is made for it. Even with that knowledge, learning Gromacs commands and parametrization is another steep learning curve.

Since its first application to biology in 1977⁶, much has evolved due to increased computational processing and improved coding. More than two decades ago, the first MD software intended for biological problems was launched, namely Gromacs⁷, AMBER⁸, and NAMD⁹.

Since their first versions, these software still remain the most used and cited. However, they continue with the same common implementation difficulties that plague researchers who are not computer specialists⁵. Some have complex installation and configuration steps, sometimes requiring extensive knowledge about the hardware it will run on to get the most out of it and highly computer-centric technical documentation. An easier way to interface with them, aside from the command line and infinite parameters, is needed.

An interface acts as an intermediary between the logical process to be performed and the human¹⁰. The paradigm of how software is executed has evolved as computing resources have improved. The first digital paradigm was the command line interfaces (CLI) followed by the evolution to the known graphical user interfaces (GUI)¹¹. Following the evolutionary cycle, the interface produced by the World Wide Web (or simply WEB) is considered an evolution of GUIs¹¹. These three paradigms currently co-exist depending on developers. CLI applications use textual commands on the operating system console. GUI applications, also called graphical desktops, use a graphical interface made up of windows, buttons, and other components. It is specific and pre-programmed for an operating system. The main difference from the CLI is the use of the mouse as an additional element in human-machine interaction¹². WEB applications, despite being confused with a GUI, are more complex to develop but are more versatile and by far the most agile in operation. Furthermore, they only depend on an interpreter software called a browser, which makes it possible for the client application to communicate with the server through a network independent of the operating system¹³.

Structural bioinformatics software most commonly use CLI and GUI paradigms. Some examples of classic software that use CLI are Modeller¹⁴ for similarity modeling, Autodock¹⁵ for molecular docking, and Gromacs¹⁶ for molecular dynamics. Examples of software that adopt the GUI type are SwissPDBviewer¹⁷, Pymol¹⁸, VMD¹⁹, UCSF Chimera²⁰, Autodock tools¹⁵, PyRx²¹, Biovia²², Maestro²³, and Moe²⁴, among others.

With the emergence of Hypertext Markup Language version 5 (HTML5)²⁵, Cascading Style Sheets (CSS)²⁶, and Javascript²⁷ technologies, among others, many structural bioinformatics applications could be brought to the WEB, thus becoming more accessible. Examples of similarity modeling WEB servers are MODWEB²⁸, which uses Modeller¹⁴ as a back-end and Swissmodel²⁹. Examples of web application servers for molecular docking are Haddock³⁰, Swissdock³¹, Cluspro³², Dockthor³³, and others.

While structural analysis, modeling, and docking methodologies evolved from CLI paradigms to GUI and finally to WEB, MD continues to be mostly supported by command line execution (CLI type). Some good initiatives have emerged to improve this panorama. Examples of these initiatives are the implementation of plugins in existing software, such as QwikMD plugin to VMD³⁴, GROMACS Plugin to PyMOL, and the Molecular Dynamics Simulation option in UCSF Chimera²⁰, some new and easier CLI applications, such as ASGARD³⁵, Gmx_qk³⁶, and CHAPERONg³⁷, and a robust web platform, BioBB-Wfs³⁸. Although the use of these plugins and applications is an advance, their implementation is still a challenge for most unskilled researchers. Common difficulties include problems installing and configuring the MD software, which often compromise the full execution of the simulation⁵.

In 2022, the Visual Dynamics software for web-based computational simulation was made available by the Laboratório de Bioinformática e Química Medicinal at Fiocruz Rondônia³⁹. Its initial version was built in Python and Flask, allowing simulations of systems with free proteins (apoenzymes) for only 2 ns. Subsequently, it was enhanced to include an automated simulation version with ligands prepared using PRODRG⁴⁰.

VD was built to assist all researchers in the field of structural biophysics, biotechnology, and related areas who have limitations in computational knowledge; the tool allows these researchers to test their hypotheses involving MD simulations from any operational system and without access to a high-performance computer (HPC). The purpose of this work is to present the new features of Visual Dynamics version 3.0. Additionally, it aims to introduce an updated usage protocol for the tool and highlight the limitations to be addressed in the future, along with usage statistics up to the present moment (Figure 1).