Data on molecular docking and molecular dynamics targeting Mycobacterium tuberculosis shikimic acid kinase.

We have previously performed a hierarchical in silico screening of a Mycobacterium tuberculosis shikimic acid kinase [1]. Specifically, 11 compounds were screened from a library of 154,118 compounds provided by ChemBridge [2] using UCSF DOCK [3] and the GOLD [4] program in the first and second steps, respectively. Molecular dynamic simulations were further performed on compound 2 (2-[(5Z)-5-(1-benzyl-5bromo-2-oxoindol-3-(5Z)-5-(1-benzyl-5-bromo-2-oxoindol-3-(5Z)-4-oxo-2 ylidene)-4oxo-2-sulfanylidene-1,3-thiazolidin-3-yl] acetic acid), which showed antimicrobial efficacy. These processes yielded ligand docking scores and trajectories. In this data article, we have added solvent-accessible surface area and PCA analyses, which were calculated from the raw docking scores and trajectories. Data obtained from molecular docking and molecular dynamic simulations are useful in two ways: (1) Further support for previous work (2) Provides a stepping stone for experimental scientists to conduct in silico studies and research ideas for other drug discovery researchers and computational biologists. We believe that this article will provide an opportunity to develop new Mycobacterium tuberculosis therapeutics through searching for analogs and inhibitors against new targets.

Identification of Novel Antimicrobial Compounds Targeting Mycobacterium tuberculosis S-Adenosyl-L-Homocysteine Hydrolase Using Dual Hierarchical In Silico Structure-Based Drug Screening.

The emergence of multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (M. tuberculosis) has become a major medical problem. S-adenosyl-L-homocysteine hydrolase (MtSAHH) was selected as the target protein for the identification of novel anti-TB drugs. Dual hierarchical in silico Structure-Based Drug Screening was performed using a 3D compound structure library (with over 150 thousand synthetic chemicals) to identify compounds that bind to MtSAHH's active site. In vitro experiments were conducted to verify whether the nine compounds selected as new drug candidates exhibited growth-inhibitory effects against mycobacteria. Eight of the nine compounds that were predicted by dual hierarchical screening showed growth-inhibitory effects against Mycobacterium smegmatis (M. smegmatis), a model organism for M. tuberculosis. Compound 7 showed the strongest antibacterial activity, with an IC50 value of 30.2 µM. Compound 7 did not inhibit the growth of Gram-negative bacteria or exert toxic effects on human cells. Molecular dynamics simulations of 40 ns using the MtSAHH-Compound 7 complex structure suggested that Compound 7 interacts stably with the MtSAHH active site. These in silico and in vitro results suggested that Compound 7 is a promising lead compound for the development of new anti-TB drugs.

In silico Identification of Potential Inhibitors Against Staphylococcus Aureus Tyrosyl-tRNA Synthetase.

BACKGROUND: Drug-resistant Staphylococcus aureus (S. aureus) has spread from nosocomial to community-acquired infections. Novel antimicrobial drugs that are effective against resistant strains should be developed.　S. aureus tyrosyl-tRNA synthetase (saTyrRS) is considered essential for bacterial survival and is an attractive target for drug screening. OBJECTIVE: The purpose of this study was to identify potential new inhibitors of saTyrRS by screening compounds in silico and evaluating them using molecular dynamics (MD) simulations. METHODS: A 3D structural library of 154,118 compounds was screened using the DOCK and GOLD docking simulations and short-time MD simulations. The selected compounds were subjected to MD simulations of a 75-ns time frame using GROMACS. RESULTS: Thirty compounds were selected by hierarchical docking simulations. The binding of these compounds to saTyrRS was assessed by short-time MD simulations. Two compounds with an average value of less than 0.15 nm for the ligand RMSD were ultimately selected. The long-time (75 ns) MD simulation results demonstrated that two novel compounds bound stably to saTyrRS in silico. CONCLUSION: Two novel potential saTyrRS inhibitors with different skeletons were identified by in silico drug screening using MD simulations. The in vitro validation of the inhibitory effect of these compounds on enzyme activity and their antibacterial effect on drug-resistant S. aureus would be useful for developing novel antibiotics.

Identification of a Chemical Inhibitor with a Novel Scaffold Targeting Decaprenylphosphoryl-ß-D-Ribose Oxidase (DprE1).

BACKGROUND: Tuberculosis is the second leading cause of death from infectious diseases worldwide. Multidrug-resistant Mycobacterium tuberculosis is spreading throughout the world, creating a crisis. Hence, there is a need to develop anti-tuberculosis drugs with novel structures and versatile mechanisms of action. OBJECTIVE: In this study, we identified antimicrobial compounds with a novel skeleton that inhibits mycobacterium decaprenylphosphoryl-ß-D-ribose oxidase (DprE1). METHODS: A multi-step, in silico, structure-based drug screening identified potential DprE1 inhibitors from a library of 154,118 compounds. We experimentally verified the growth inhibitory effects of the eight selected candidate compounds against Mycobacterium smegmatis. Molecular dynamics simulations were performed to understand the mechanism of molecular interactions between DprE1 and ompound 4. RESULTS: Eight compounds were selected through in silico screening. Compound 4 showed strong growth inhibition against M. smegmatis. Molecular dynamics simulation (50 ns) predicted direct and stable binding of Compound 4 to the active site of DprE1. CONCLUSION: The structural analysis of the novel scaffold in Compound 4 can pave way for antituberculosis drug development and discovery.

Computational Screening and Experimental Validation of Inhibitor Targeting the Complex Formation of Grb14 and Insulin Receptor.

The development of drugs targeting gene products associated with insulin resistance holds the potential to enhance our understanding of type 2 diabetes mellitus (T2DM). The virtual screening, based on a three-dimensional (3D) protein structure, is a potential technique to accelerate the development of molecular target drugs. Among the targets implicated in insulin resistance, the genetic characterization and protein function of Grb14 have been clarified without contradiction. The Grb14 gene displays significant variations in T2DM, and its gene product is known to inhibit the function of the insulin receptor (IR) by directly binding to the tyrosine kinase domain. In the present study, a virtual screening, based on a 3D structure of the IR tyrosine kinase domain (IRß) in complex with part of Grb14, was conducted to find compounds that can disrupt the complex formation between Grb14 and IRß. First, ten compounds were selected from 154,118 compounds via hierarchical in silico structure-based drug screening, composed of grid docking-based and genetic algorithm-based programs. The experimental validations suggested that the one compound can affect the blood glucose level. The molecular dynamics simulations and co-immunoprecipitation analysis showed that the compound did not completely suppress the protein-protein interaction between Grb14 and IR, though competitively bound to IR with the tyrosine kinase pseudosubstrate region in Grb14.

Identification of novel inhibitors for mycobacterial polyketide synthase 13 via in silico drug screening assisted by the parallel compound screening with genetic algorithm-based programs.

Identifying small compounds capable of inhibiting Mycobacterium tuberculosis polyketide synthase 13 (Pks13), in charge of final step of mycolic acid biosynthesis, could lead to the development of a novel antituberculosis drug. This study screened for lead compounds capable of targeting M. tuberculosis Pks13 from a chemical library comprising 154,118 compounds through multiple in silico docking simulations. The parallel compound screening (PCS), conducted via two genetic algorithm-based programs was applied in the screening strategy. Out of seven experimentally validated compounds, four compounds showed inhibitory effects on the growth of the model mycobacteria (Mycobacterium smegmatis). Subsequent docking simulation of analogs of the promising leads with the assistance of PCS resulted in the identification of three additional compounds with potent antimycobacterial effects (compounds A1, A2, and A5). Further, molecular dynamics simulation predicted stable interaction between M. tuberculosis Pks13 active site and compound A2, which showed potent antimycobacterial activity comparable to that of isoniazid. The present study demonstrated the efficacy of in silico structure-based drug screening through PCS in antituberculosis drug discovery.