Visual dynamics: a WEB application for molecular dynamics simulation using GROMACS

BACKGROUND

The molecular dynamics is an approach to obtain kinetic and thermodynamic characteristics of biomolecular structures. The molecular dynamics simulation softwares are very useful, however, most of them are used in command line form and continue with the same common implementation difficulties that plague researchers who are not computer specialists.

RESULTS

Here, we have developed the VisualDynamics-a WEB tool developed to automate biological simulations performed in Gromacs using a graphical interface to make molecular dynamics simulation user-friendly task. In this new application the researcher can submit a simulation of the protein in the free form or complexed with a ligand. Can also download the graphics analysis and log files at the end of the simulation.

CONCLUSIONS

VisualDynamics is a tool that will accelerate implementations and learning in the area of molecular dynamics simulation. Freely available at https://visualdynamics.fiocruz.br/login , is supported by all major web browsers. VisualDynamics was developed with Flask, which is a Python-based free and open-source framework for web development. The code is freely available for download at GitHub https://github.com/LABIOQUIM/visualdynamics .

SARS-CoV-2 mutations in Brazil: from genomics to putative clinical conditions

Due to the high rate of transmissibility, Brazil became the new COVID-19 outbreak epicenter and, since then, is being monitored to understand how SARS-CoV-2 mutates and spreads. We combined genomic and structural analysis to evaluate genomes isolated from different regions of Brazil and show that the most prevalent mutations were located in the S, N, ORF3a and ORF6 genes, which are involved in different stages of viral life cycle and its interaction with the host cells. Structural analysis brought to light the positions of these mutations on protein structures, contributing towards studies of selective structure-based drug discovery and vaccine development.

Geo-Measures: A PyMOL plugin for protein structure ensembles analysis

Although molecular dynamics encompasses several applications, studies focusing on biomolecular systems are central issues of this research area. Such simulations require the generation of trajectory files, which provide a path for the analysis and interpretation of results with biological significance. However, although several programs have been developed in Python language for the analyses of molecular dynamics (MD) trajectories, they usually require some knowledge of programming languages in order to write or run the scripts using command lines, which certainly hinders the access of MD simulations to many scientists with the necessary biological background to interpret their results. To ease the access to Python packages focusing on MD trajectory analyses, we built a user-friendly and easy-to-install graphical PyMOL interface. Geo-Measures integrates the PyMOL functionalities with MDTraj, a powerful library of trajectory analyses, allowing the users to access up to 14 different types of analyses. Two sample cases are reported here to demonstrate the use of Geo-Measures. In the first example, which involves the use a MD trajectory file of hemoglobin from the MoDEL MD bank, we exemplified the analyses of the following variables: root mean square deviation, radius of gyration, free energy landscape and principal component analysis. In the second case, we built a trajectory file for the ecto-5'-nucleotidase using the LiGRO program to study the carbon alpha pincer angles, to define the secondary structure of the proteins and to analyze the Modevectors. This user-friendly graphical PyMOL plugin, which can be used to generate several descriptive analyses for protein structures, is open source and can be downloaded at: https://pymolwiki.org/index.php/Geo_Measures_Plugin.

Searching for potential mTOR inhibitors: Ligand-based drug design, docking and molecular dynamics studies of rapamycin binding site

The PI3K/Akt/mTOR pathway is an important intracellular signaling pathway in cell cycle regulation and its dysregulation is associated with various types of diseases. mTOR (mechanistic or mammalian target of rapamycin) is the main enzyme that performs intermediate control of the signaling pathway through a phosphotransfer process. The classical inhibition of the mTOR pathway is effected by rapamycin and its analogous blocking allosterically the catalytic phosphorylation site, avoiding the deleterious side effects induced by ATP-competitive inhibitors. We employed ligand-based drug design strategies such as pharmacophore searching and analysis, molecular docking, absorption, distribution, metabolism, excretion and toxicity (ADMETox) properties filtering, and molecular dynamics to select potential molecules to become non-ATP competitive inhibitors of the mTOR complex. According to our findings, we propose eight novel potential mTOR inhibitors with similar or better properties than the classic inhibitor complex, rapamycin.

LiGRO: a graphical user interface for protein-ligand molecular dynamics

To speed up the drug-discovery process, molecular dynamics (MD) calculations performed in GROMACS can be coupled to docking simulations for the post-screening analyses of large compound libraries. This requires generating the topology of the ligands in different software, some basic knowledge of Linux command lines, and a certain familiarity in handling the output files. LiGRO-the python-based graphical interface introduced here-was designed to overcome these protein-ligand parameterization challenges by allowing the graphical (non command line-based) control of GROMACS (MD and analysis), ACPYPE (ligand topology builder) and PLIP (protein-binder interactions monitor)-programs that can be used together to fully perform and analyze the outputs of complex MD simulations (including energy minimization and NVT/NPT equilibration). By allowing the calculation of linear interaction energies in a simple and quick fashion, LiGRO can be used in the drug-discovery pipeline to select compounds with a better protein-binding interaction profile. The design of LiGRO allows researchers to freely download and modify the software, with the source code being available under the terms of a GPLv3 license from http://www.ufrgs.br/lasomfarmacia/ligro/ .

New potential inhibitors of mTOR: a computational investigation integrating molecular docking, virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.

Role of Serine140 in the mode of action of Mycobacterium tuberculosis β-ketoacyl-ACP Reductase (MabA)

Background

Tuberculosis (TB) still remains one of the most deadly infectious diseases in the world. Mycobacterium tuberculosis β-ketoacyl-ACP Reductase (MabA) is a member of the fatty acid elongation system type II, providing precursors of mycolic acids that are essential to the bacterial cell growth and survival. MabA has been shown to be essential for M. tuberculosis survival and to play a role in intracellular signal transduction of bacilli.

Findings

Here we describe site-directed mutagenesis, recombinant protein expression and purification, steady-state kinetics, fluorescence spectroscopy, and molecular modeling for S140T and S140A mutant MabA enzymes. No enzyme activity could be detected for S140T and S140A. Although the S140T protein showed impaired NADPH binding, the S140A mutant could bind to NADPH. Computational predictions for NADPH binding affinity to WT, S140T and S140A MabA proteins were consistent with fluorescence spectroscopy data.

Conclusions

The results suggest that the main role of the S140 side chain of MabA is in catalysis. The S140 side chain appears to also play an indirect role in NADPH binding. Interestingly, NADPH titrations curves shifted from sigmoidal for WT to hyperbolic for S140A, suggesting that the S140 residue may play a role in displacing the pre-existing equilibrium between two forms of MabA in solution. The results here reported provide a better understanding of the mode of action of MabA that should be useful to guide the rational (function-based) design of inhibitors of MabA enzyme activity which, hopefully, could be used as lead compounds with anti-TB action.

Crystal structure and molecular dynamics studies of human purine nucleoside phosphorylase complexed with 7-deazaguanine

In humans, purine nucleoside phosphorylase (HsPNP) is responsible for degradation of deoxyguanosine, and genetic deficiency of this enzyme leads to profound T-cell mediated immunosuppression. HsPNP is a target for inhibitor development aiming at T-cell immune response modulation. Here we report the crystal structure of HsPNP in complex with 7-deazaguanine (HsPNP:7DG) at 2.75 A. Molecular dynamics simulations were employed to assess the structural features of HsPNP in both free form and in complex with 7DG. Our results show that some regions, responsible for entrance and exit of substrate, present a conformational variability, which is dissected by dynamics simulation analysis. Enzymatic assays were also carried out and revealed that 7-deazaguanine presents a lower inhibitory activity against HsPNP (K(i)=200 microM). The present structure may be employed in both structure-based design of PNP inhibitors and in development of specific empirical scoring functions.

Molecular dynamics studies of a hexameric purine nucleoside phosphorylase

Purine nucleoside phosphorylase (PNP) (EC.2.4.2.1) is an enzyme that catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is involved in purine-salvage pathway and has been proposed as a promising target for design and development of antimalarial and antibacterial drugs. Recent elucidation of the three-dimensional structure of PNP by X-ray protein crystallography left open the possibility of structure-based virtual screening initiatives in combination with molecular dynamics simulations focused on identification of potential new antimalarial drugs. Most of the previously published molecular dynamics simulations of PNP were carried out on human PNP, a trimeric PNP. The present article describes for the first time molecular dynamics simulations of hexameric PNP from Plasmodium falciparum (PfPNP). Two systems were simulated in the present work, PfPNP in ligand free form, and in complex with immucillin and sulfate. Based on the dynamical behavior of both systems the main results related to structural stability and protein-drug interactions are discussed.

Genomic databases and the search of protein targets for protozoan parasites

The development of databases devoted to biological information opened the possibility to integrate, query and analyze biological data obtained from several sources that otherwise would be scattered through the web. Several issues arise in the handling of biological information, mainly due to the diversity of biological subject matter and the complexity of biological approaches towards phenomena of the living world. The integration of genomic data, three-dimensional structures of proteins, biological activity, and drugs availability allows a system approach to the study of the biology. Here we review the current status of these research efforts to develop genomic databases for protozoan parasites, such as the apicomplexan parasites, Trypanosoma cruzi and Leishmania spp. These databases may help in the discovery and development of new drugs against parasite-mediated diseases.

In silico and in vitro: identifying new drugs

Drug development is a high cost and laborious process, requiring a number of tests until a drug is made available in the market. Therefore, the use of methods to screen large number of molecules with less cost is crucial for faster identification of hits and leads. One strategy to identify drug-like molecules is the search for molecules able to interfere with a protein function, since protein interactions control most biological processes. Ideally the use of in silico screenings would make drug development faster and less expensive. Currently, however, the confirmation of biological activity is still needed. Due to the complexity of the task of drug discovery, an integrated and multi-disciplinary approach is ultimately required. Here we discuss examples of drugs developed through a combination of in silico and in vitro strategies. The potential use of these methodologies for the identification of active compounds as well as for early toxicity and bioavailability is also reviewed.

Linear interaction energy (LIE) method in lead discovery and optimization

Currently, in order to accelerate the process of drug development and also reduce costs, many of the experimental assays related to lead discovery and lead optimization processes are being replaced by computational, in silico, methods. In this context, the LIE (linear interaction energy) method has been used to calculate binding free energies for widely different compounds by averaging interaction energies obtained from molecular dynamics (MD) or Monte Carlo (MC) simulations. In particular, the combination of docking and affinity predictions with the LIE method can thus save valuable resources in lead discovery and optimization projects. This review presents a description of LIE methodology and some recent studies that illustrate the importance and utility of the method in the field of pharmaceutical research.

Molecular modeling, dynamics and docking studies of purine nucleoside phosphorylase from Streptococcus pyogenes

Purine Nucleoside Phosphorylase (PNP) catalyzes the reversible phosphorolysis of N-glycosidic bonds of purine nucleosides and deoxynucleosides, except for adenosine, to generate ribose 1-phosphate and the purine base. PNP has been submitted to intensive structural studies. This work describes for the first time a structural model of PNP from Streptococcus pyogenes (SpPNP). We modeled the complexes of SpPNP with six different ligands in order to determine the structural basis for specificity of these ligands against SpPNP. Molecular dynamics (MD) simulations were performed in order to evaluate the overall stability of SpPNP model. The analysis of the MD simulation was assessed mainly by principal component analysis (PCA) to explore the trimeric structure behavior. Structural comparison, between SpPNP and human PNP, was able to identify the main features responsible for differences in ligand-binding affinities, such as mutation in the purine-binding site and in the second phosphate-binding site. The PCA analysis suggests a different behavior for each subunit in the trimer structure.

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT. A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT is stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution.

Structural bioinformatics study of PNP from Listeria monocytogenes

This work describes for the first time a model of Purine Nucleoside Phosphorylase from Listeria monocytogenes (LmPNP). We modeled the complexes of LmPNP with ligands in order to determine the structural basis for specificity. Comparative analysis of the model of LmPNP allowed identification of structural features responsible for ligand affinities.

Molecular modeling and dynamics studies of Shikimate Kinase from Bacillus anthracis

Bacillus anthracis has been used as weapon in bioterrorist activities, with high mortality, despite anti-microbial treatment, which strongly indicates a need of new drugs to treat anthrax. Shikimate Pathway is a seven-step biosynthetic route which generates chorismic acid. The shikimate pathway is essential for many pathological organisms, whereas it is absent in mammals. Therefore, these enzymes are potential targets for the development of non-toxic anti-microbial agents and herbicides and have been submitted to intensive structural studies. Shikimate Kinase is the fifth enzyme of shikimate pathway and catalyzes the specific phosphorylation of the 3-hydroxyl group of shikimate using ATP as a co-substrate, resulting in shikimate-3-phosphate and ADP. The present work describes for the first time a structural model for the Shikimate Kinase from B. anthracis using molecular modeling approach and molecular dynamics simulations. This study was able to identify the main residues of the ATP-binding and the shikimate pockets responsible for ligand affinities. Analysis of the molecular dynamics simulations indicates the structural features responsible for the stability of the structure. This study may help in the identification of new inhibitors for this enzyme.

CDK9 a potential target for drug development

The family of Cyclin-Dependent Kinases (CDKs) can be subdivided into two major functional groups based on their roles in cell cycle and/or transcriptional control. CDK9 is the catalytic subunit of positive transcription elongation factor b (P-TEFb). CDK9 is the kinase of the TAK complex (Tat-associated kinase complex), and binds to Tat protein of HIV, suggesting a possible role for CDK9 in AIDS progression. CDK9 complexed with its regulatory partner cyclin T1, serves as a cellular mediator of the transactivation function of the HIV Tat protein. P-TEFb is responsible for the phosphorylation of the carboxyl-terminal domain of RNA Pol II, resulting in stimulation of transcription. Furthermore, the complexes containing CDK9 induce the differentiation in distinct tissue. The CDK9/cyclin T1 complex is expressed at higher level in more differentiated primary neuroectodermal and neuroblastoma tumors, showing a correlation between the kinase expression and tumor differentiation grade. This may have clinical and therapeutical implications for these tumor types. Among the CDK inhibitors two have shown to be effective against CDK9: Roscovitine and Flavopiridol. These two inhibitors prevented the replication of human immunodeficiency virus (HIV) type 1 by blocking Tat transactivation of the HIV type 1 promoter. These compounds inhibit CDKs by binding to the catalytic domain in place of ATP, preventing transfer of a phosphate group to the substrate. More sensitive therapeutic agents of CDK9 can be designed, and structural studies can add information in the understanding of this kinase. The major features related to CDK9 inhibition will be reviewed in this article.