Topology Files Research Articles

Investigation of the behavior of dioxadet molecules in water by molecular dynamics simulation

The behaviour of dioxadet molecules in water is studied by the molecular dynamics simulation. This substance has anti-cancer properties and is used in clinical practice. However, its properties have not yet studied at the molecular level. This paper presents the first attempt of such investigation. Parametrization of dioxadet molecule was carried out using different available services: ATB, SwissParam as well as AmberTools in a standard form and with the use of additional quantum-chemical calculations. The obtained models are compared with each other. The number of hydrogen bonds of the molecule with water was calculated, the analysis of hydrated water was carried out. It was shown that the dioxadet molecules in water tend to associate. All the models obtained show similar properties, but the quantitative characteristics differ noticeably. Further research is needed to select the best model. Molecule topology files are available for use.

Supporting the CIF file format of proteins in molecular dynamics simulations

Molecular dynamics (MD) simulations can capture the dynamic behavior of proteins in full atomic detail and at very fine temporal resolution, so they have become an important tool in the study of protein dynamics. To date, several MD packages are widely used. An MD simulation starts from an initial structure that is generally taken from the Protein Data Bank (PDB). Until 2014, the PDB format was the standard file format for protein structures. However, there are certain intrinsic limitations in the PDB format, such as the storage of structural information in a fixed-width format, which is an issue for very large protein complexes. Therefore, the CIF (crystallographic information framework) format has been proposed, which is characterized by its superior expansibility. To our knowledge, the current mainstream MD packages support only the PDB format but do not support the CIF format directly. In this study, we modified the source code of one of the MD packages, GROMACS, which enables it to support CIF-formatted structure files as input and subsequently generate molecular topology files. This work simplifies the preprocessing of large protein complexes for MD simulations.

Biophysical assessment of amantadine and SDS surfactant mixture onto boron nitride nanotube: a molecular dynamics investigation.

The aggregation and adsorption of amantadine and sodium dodecyl sulfate on the boron nitride nanotubes in aqueous system were investigated, employing the classical molecular dynamics method. The aqueous system containing amantadine and sodium dodecyl sulfate was investigated by self-diffusion of the molecules, with particular emphasis on their center of mass mean square displacement. The radial distribution function and dipole moment measurement were used to analyze the water effect on the aggregation and molecular interaction between amantadine and sodium dodecyl sulfate in the complex. In turn, the amantadine molecules are able to develop water monolayers at the aqueous solution but show no noticeable aggregated adsorption in the fluid. In contrast, sodium dodecyl sulfate self-aggregation on the boron nitride nanotube efficiently occurs, and so the effect of sodium dodecyl sulfate on aggregated adsorption of amantadine was studied. Our results show that in the presence of sodium dodecyl sulfate at critical micelle concentration, its effect on the aggregation of amantadine was enhanced onto boron nitride nanotube compared to just pure sodium dodecyl sulfate or amantadine on boron nitride nanotube. Our simulations show a remarkable restructuring and enhanced orientation of the water molecules around sodium dodecyl sulfate and amantadine adsorbed on boron nitride nanotube. All molecular dynamics simulations were done using NAMD-2.9 package with CHARMM-36 force field. The nanotube PDB file was made by VMD with (12, 12) indexes. The nanotube atoms were considered to be fixed and periodic during the simulation process, and the ends did not cap with hydrogens. The initial PDB file of components was saved from ChemOffice software, and the webservers to obtain the charge and topology files were Reddb and Swiss Param webservers. The VMD software was used for structural visualizations and graphical analysis.

An implementation of the Martini coarse-grained force field in OpenMM

We describe a complete implementation of Martini 2 and Martini 3 in the OpenMM molecular dynamics software package. Martini is a widely used coarse-grained force field with applications in biomolecular simulation, materials, and broader areas of chemistry. It is implemented as a force field but makes extensive use of facilities unique to the GROMACS software, including virtual sites and bonded terms that are not commonly used in standard atomistic force fields. OpenMM is a flexible molecular dynamics package widely used for methods development and is competitive in speed on GPUs with other commonly used packages. OpenMM has facilities to easily implement new force field terms, external forces and fields, and other nonstandard features, which we use to implement all force field terms used in Martini 2 and Martini 3. This allows Martini simulations, starting with GROMACS topology files that are processed by custom scripts, with all the added flexibility of OpenMM. We provide a GitHub repository with test cases, compare accuracy and performance between GROMACS and OpenMM, and discuss the limitations of our implementation in terms of direct comparison with GROMACS. We describe a use case that implements the Modeling Employing Limited Data method to apply experimental constraints in a Martini simulation to efficiently determine the structure of a protein complex. We also discuss issues and a potential solution with the Martini 2 topology for cholesterol.

Comprehensive Automated Routine Implementation, Validation, and Benchmark of the Anisotropic Force Field (AUA4) Using Python and GROMACS

Molecular simulation users are sometimes discouraged from using specific molecular models because of the inconvenience of finding the force field parameters and preparing and validating the topology files. To facilitate this process and make the accurate anisotropic force field AUA4 available to molecular dynamics users, we have created and validated an automated topology and coordinate file creation routine for the GROMACS molecular simulation software. In the present work, we describe the AUA4, explain its particularities and how it was implemented, thoroughly validating the implementation, and for the first time, perform a molecular dynamics benchmark for this transferable force field. Several properties were computed, namely, liquid density, vapor pressure, and vaporization enthalpy by conducting explicit vapor-liquid interface simulations. The results evidence the correct implementation showing slight deviations from the parametrization studies. The benchmark shows the superior predictive capability of the AUA4 in recreating liquid density (RMSD equal to 17.0 kg/m3) and vaporization enthalpy (RMSD equal to 1.3 kJ/mol) compared to other transferable force fields. In addition, its superior computational time performance doubles or even triples compared to an all-atom force field such as the OPLS, depending on whether the workstation counts with GPU.

Molecular Dynamics Simulations of RNA Motifs to Guide the Architectural Parameters and Design Principles of RNA Nanostructures.

Molecular dynamics (MD) simulations can be used to investigate the stability and conformational characteristics of RNA nanostructures. However, MD simulations of an RNA nanostructure is computationally expensive due to the size of nanostructure and the number of atoms. Alternatively, MD simulations of RNA motifs can be used to estimate the conformational stability of constructed RNA nanostructure due to their small sizes. In this chapter, we introduce the preparation and MD simulations of two RNA kissing loop (KL) motifs, a linear KL complex and a bent KL complex, and an RNA nanoring. The initial solvated system and topology files of each system will be prepared by two major force fields, AMBER and CHARMM force fields. MD simulations will be performed by NAMD simulation package, which can accept both force fields. In addition, we will introduce the use of the AMBER cpptraj program and visual molecular dynamics (VMD) for data analysis. We will also discuss how MD simulations of two KL motifs can be used to estimate the conformation and stability of RNA nanoring as well as to explain the vibrational characteristics of RNA nanoring.

MoBioTools: A toolkit to setup quantum mechanics/molecular mechanics calculations.

We present a toolkit that allows for the preparation of QM/MM input files from a conformational ensemble of molecular geometries. The package is currently compatible with trajectory and topology files in Amber, CHARMM, GROMACS and NAMD formats, and has the possibility to generate QM/MM input files for Gaussian (09 and 16), Orca (≥4.0), NWChem and (Open)Molcas. The toolkit can be used in command line, so that no programming experience is required, although it presents some features that can also be employed as a python application programming interface. We apply the toolkit in four situations in which different electronic-structure properties of organic molecules in the presence of a solvent or a complex biological environment are computed: the reduction potential of the nucleobases in acetonitrile, an energy decomposition analysis of tyrosine interacting with water, the absorption spectrum of an azobenzene derivative integrated into a voltage-gated ion channel, and the absorption and emission spectra of the luciferine/luciferase complex. These examples show that the toolkit can be employed in a manifold of situations for both the electronic ground state and electronically excited states. It also allows for the automatic correction of the active space in the case of CASSCF calculations on an ensemble of geometries, as it is shown for the azobenzene derivative photoswitch case.

Dry trajectories and topology files of DENV virus inhibitory activity from molecular dynamics simulation

Dry trajectories and topology files of DENV virus inhibitory activity from molecular dynamics simulation

Integrated bioinformatics-cheminformatics approach toward locating pseudo-potential antiviral marine alkaloids against SARS-CoV-2-Mpro.

The emergence of the severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) with the most contagious variants, alpha (B.1.1.7), beta (B.1.351), delta (B.1.617.2), and Omicron (B.1.1.529) has continuously added a higher number of morbidity and mortality, globally. The present integrated bioinformatics–cheminformatics approach was employed to locate potent antiviral marine alkaloids that could be used against SARS‐CoV‐2. Initially, 57 antiviral marine alkaloids and two repurposing drugs were selected from an extensive literature review. Then, the putative target enzyme SARS‐CoV‐2 main protease (SARS‐CoV‐2‐Mpro) was retrieved from the protein data bank and carried out a virtual screening‐cum‐molecular docking study with all candidates using PyRx 0.8 and AutoDock 4.2 software. Further, the molecular dynamics (MD) simulation of the two most potential alkaloids and a drug docking complex at 100 ns (with two ligand topology files from PRODRG and ATB server, separately), the molecular mechanics/Poisson‐Boltzmann surface area (MM/PBSA) free energy, and contributions of entropy were investigated. Then, the physicochemical‐toxicity‐pharmacokinetics‐drug‐likeness profiles, the frontier molecular orbitals energies (highest occupied molecular orbital, lowest unoccupied molecular orbital, and ΔE), and structural–activity relationship were assessed and analyzed. Based on binding energy, 8‐hydroxymanzamine (−10.5 kcal/mol) and manzamine A (−10.1 kcal/mol) from all alkaloids with darunavir (−7.9 kcal/mol) and lopinavir (−7.4 kcal/mol) against SARS‐CoV‐2‐Mpro were recorded. The MD simulation (RMSD, RMSF, Rg, H‐bond, MM/PBSA binding energy) illustrated that the 8‐hydroxymanzamine exhibits a static thermodynamic feature than the other two complexes. The predicted physicochemical, toxicity, pharmacokinetics, and drug‐likeness profiles also revealed that the 8‐hydroxymanzamine could be used as a potential lead candidate individually and/or synergistically with darunavir or lopinavir to combat SARS‐CoV‐2 infection after some pharmacological validation.

Topology files and MD trajectories for complexes of receptor-binding domain of S protein from SARS-CoV-2 (wild type and omicron variant) with extracellular domain of gateway receptor ACE2, neutralizing monoclonal antibody LY-CoV555 and engineered mini-protein LCB1

Topology files and MD trajectories for complexes of receptor-binding domain of S protein from SARS-CoV-2 (wild type and omicron variant) with extracellular domain of gateway receptor ACE2, neutralizing monoclonal antibody LY-CoV555 and engineered mini-protein LCB1

FEPrepare: A Web-Based Tool for Automating the Setup of Relative Binding Free Energy Calculations.

Relative binding free energy calculations in drug design are becoming a useful tool in facilitating lead binding affinity optimization in a cost- and time-efficient manner. However, they have been limited by technical challenges such as the manual creation of large numbers of input files to set up, run, and analyze free energy simulations. In this Application Note, we describe FEPrepare, a novel web-based tool, which automates the setup procedure for relative binding FEP calculations for the dual-topology scheme of NAMD, one of the major MD engines, using OPLS-AA force field topology and parameter files. FEPrepare provides the user with all necessary files needed to run a FEP/MD simulation with NAMD. FEPrepare can be accessed and used at https://feprepare.vi-seem.eu/.

PyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules.

The construction of a molecular topology file is a prerequisite for any classical molecular dynamics simulation. However, the generation of such a file may be very challenging at times, especially for large supramolecules. While many tools are available to provide topologies for large proteins and other biomolecules, the scientific community researching nonbiological systems is not equally well equipped. Here, we present a practical tool to generate topologies for arbitrary supramolecules: The pyPolyBuilder. In addition to linear polymer chains, it also provides the possibility to generate topologies of arbitrary, large, branched molecules, such as, e.g., dendrimers. Furthermore, it also generates reasonable starting structures for simulations of these molecules. pyPolyBuilder is a standalone command-line tool implemented in python. Therefore, it may be easily incorporated in persisting simulation pipelines on any operating systems and with different simulation engines. pyPolyBuilder is freely available on github: https://github.com/mssm-labmmol/pypolybuilder.

Role of Thermolysin in Catalytic-Controlled Self-Assembly of Fmoc-Dipeptides

In recent years, short peptide self-assembled materials, prepared under the control of the thermolysin catalyst, have been investigated extensively and shown to acquire various morphologies and fun...

ContraDRG: Automatic Partial Charge Prediction by Machine Learning.

In recent years, machine learning techniques have been widely used in biomedical research to predict unseen data based on models trained on experimentally derived data. In the current study, we used machine learning algorithms to emulate computationally complex predictions in a reverse engineering–like manner and developed ContraDRG, a software that can be used to predict partial charges for small molecules based on PRODRG and Automated Topology Builder (ATB) predictions. Both tools generate molecular topology files, including the partial atomic charge, by using different procedures. We show that ContraDRG can accurately predict partial charges in a fraction of the time, because it exploits existing complex models with intensive calculations by using machine learning techniques and thus can also be applied for screening projects with large amounts of molecules. We provide ContraDRG as a web server, which can be used to automatically assign partial charges to incoming user-specified molecules by using our machine learning models. In this study, we compared ContraDRG with PRODRG and ATB in regard of predictivity by statistical methods. ContraDRG allows predicting ATB-derived partial charges with an R2 value up to 0.980 and for PRODRG up to 1.00. While ATB requires hours or days for the quantum mechanical accurate calculation and refinements, ContraDRG does its approximation within seconds.

Atom: A MATLAB PACKAGE FOR MANIPULATION OF MOLECULAR SYSTEMS

This work presents Atomistic Topology Operations in MATLAB (atom), an open source library of modular MATLAB routines which comprise a general and flexible framework for manipulation of atomistic systems. The purpose of the atom library is simply to facilitate common operations performed for construction, manipulation, or structural analysis. Due to the data structure used, atoms and molecules can be operated upon based on different chemical names or attributes, such as atom- or molecule-ID, name, residue name, charge, positions, etc. Furthermore, the Bond Valence Method and a neighbor-distance analysis can be performed to assign many chemical properties of inorganic molecules. Apart from reading and writing common coordinate files (.pdb, .xyz, .gro, .cif) and trajectories (.dcd, .trr, .xtc; binary formats are parsed via third-party packages), the atom library can also be used to generate topology files with bonding and angle information taking the periodic boundary conditions into account, and supports basic Gromacs, NAMD, LAMMPS, and RASPA2 topology file formats. Focusing on clay-mineral systems, the library supports CLAYFF (Cygan, 2004) but can also generate topology files for the INTERFACE forcefield (Heinz, 2005, 2013) for Gromacs and NAMD.

ACPYPE update for nonuniform 1–4 scale factors: Conversion of the GLYCAM06 force field from AMBER to GROMACS

Herein we report an update to ACPYPE, a Python3 tool that now properly converts AMBER to GROMACS topologies for force fields that utilize nondefault and nonuniform 1–4 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 1–4 scaling factors and positive dihedral force constants. We demonstrate that the updated ACPYPE accurately transfers the GLYCAM06 force field from AMBER to GROMACS topology files, which employs non-uniform 1–4 scaling factors as well as negative dihedral force constants. Validation was performed using β-d-GlcNAc through gas-phase analysis of dihedral energy curves and probability density functions. The updated ACPYPE retains all of its original functionality, but now allows the simulation of complex glycomolecular systems in GROMACS using AMBER-originated force fields. ACPYPE is available for download at https://github.com/alanwilter/acpype.

NanoModeler: A Webserver for Molecular Simulations and Engineering of Nanoparticles.

Functionalized nanoparticles (NPs) are at the frontier of nanoscience. They hold the promise of innovative applications for human health and technology. In this context, molecular dynamics (MD) simulations of NPs are increasingly employed to understand the fundamental structural and dynamical features of NPs. While informative, such simulations demand a laborious two-step process for their setup. In-house scripts are required to (i) construct complex 3D models of the inner metal core and outer layer of organic ligands, and (ii) correctly assign force-field parameters to these composite systems. Here, we present NanoModeler ( www.nanomodeler.it ), the first Webserver designed to automatically generate and parametrize model systems of monolayer-protected gold NPs and gold nanoclusters. The only required input is a structure file of one or two ligand(s) to be grafted onto the gold core, with the option of specifying homogeneous or heterogeneous NP morphologies. NanoModeler then generates 3D models of the nanosystem and the associated topology files. These files are ready for use with the Gromacs MD engine, and they are compatible with the AMBER family of force fields. We illustrate NanoModeler's capabilities with MD simulations of selected representative NP model systems. NanoModeler is the first platform to automate and standardize the construction and parametrization of realistic models for atomistic simulations of gold NPs and gold nanoclusters.

The Lack of a Centralized and Universal Tool for Input File Generation for Molecular Dynamics Simulations and the Development of such a Tool: A Review

This study aims to design and develop a tool that can efficiently generate Molecular Dynamics (MD) simulation input files and systems for various simulation software such as NAMD, Amber and GROMACS collectively using a single platform. Molecular Dynamics simulation is performed in order to understand the structure, dynamics and thermodynamic behavior of biomolecular system. There are a lot of MD simulation software available which are very efficient and fast. However, there are some hurdles in making an input file for simulation purpose, such as the use of command line instructions and the need of using multiple sources in order to generateparameter and topology files. This is a very hectic job for any bio-informatician working in this area and it requires a lot of man hours to develop these files. The main challenge which the scientists encounter working in this field is that there are a lot of different simulation software available online and each one of them has some common features and some uncommon and distinctive features. These facts make input file and system generation a slow and hectic process. To solve this issue and to minimize the time consumed in the preparation of input files, there is a need to develop a tool which is user friendly and provides a graphical user interface to make aninput file. For this purpose, programming languages like Python and Java will be used during the designing and development process. This will also incorporate all the mathematical equations and calculations that are going on at the back end in the making of input files. Embedding PDB into this tool will also be helpful as users will directly be able to import protein structures from PDB. This software will allow the users to create input files and systems for MD simulations in the shortest possible time.

Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations.

The analysis of coevolutionary signals from families of evolutionarily related sequences is a recent conceptual framework that provides valuable information about unique intramolecular interactions and, therefore, can assist in the elucidation of biomolecular conformations. It is based on the idea that compensatory mutations at specific residue positions in a sequence help preserve stability of protein architecture and function and leave a statistical signature related to residue-residue interactions in the 3D structure of the protein. Consequently, statistical analysis of these correlated mutations in subsets of protein sequence alignments can be used to predict which residue pairs should be in spatial proximity in the native functional protein fold. These predicted signals can be then used to guide molecular dynamics (MD) simulations to predict the three-dimensional coordinates of a functional amino acid chain. In this chapter, we introduce a general and efficient methodology to perform coevolutionary analysis on protein sequences and to use this information in combination with computational physical models to predict the native 3D conformation of functional polypeptides. We present a step-by-step methodology that includes the description and application of software tools and databases required to infer tertiary structures of a protein fold. The general pipeline includes instructions on (1) how to obtain direct amino acid couplings from protein sequences using direct coupling analysis (DCA), (2) how to incorporate such signals as interaction potentials in Cα structure-based models (SBMs) to drive protein-folding MD simulations, (3) a procedure to estimate secondary structure and how to include such estimates in the topology files required in the MD simulations, and (4) how to build full atomic models based on the top Cα candidates selected in the pipeline. The information presented in this chapter is self-contained and sufficient to allow a computational scientist to predict structures of proteins using publicly available algorithms and databases.

Molecular dynamics investigation of surfactant micelles as a potential drug delivery vehicle

A new molecular dynamics study is being initiated in which micellar structures of cetyltrimethylammonium bromide (CTAB) are simulated within computationally constructed physiological conditions. Leading up to the simulation phase, several programs and reference files were used to construct a topology file, initial structure/coordinate files, and parameter files to accurately represent a single molecule of CTAB. This single molecule is utilized in making the initial configuration of a system. All systems begin in one of three configurations: a random assembly of molecules in a box, a pre-formed micelle, or an inverse micelle. These initial configurations, once assembled, are placed under generated physiological conditions by using Visual Molecular Dynamics (VMD) to solvate the system with water and add Na+ and Cl- ions to neutralize the system to 0.15 M NaCl, then using Nanoscale Molecular Dynamics (NAMD) to minimize energy and heat the system to 310 K. The system is then simulated using NAMD until a micelle has formed and stabilized. Following each simulation, quantitative and qualitative analysis is used to characterize the system. The overarching goal of this study is to determine the viability of CTAB as a drug carrier in a targeted drug delivery system. Funding for the project is provided by the College of Science and Technology at Fairmont State University and the NASA WV Space Grant Consortium.