ORIGINAL PAPER In silico docking and molecular dynamics simulation of 3-dehydroquinate synthase (DHQS) from Mycobacterium tuberculosis Mustafa Alhaji Isa 1 & Rita Singh Majumdhar 1 & Shazia Haider 1 Received: 28 September 2017 /Accepted: 8 March 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract The shikimate pathway is as an attractive target because it is present in bacteria, algae, fungi, and plants but does not occur in mammals. In Mycobacterium tuberculosis (MTB), the shikimate pathway is integral to the biosynthesis of naphthoquinones, menaquinones, and mycobactin. In these study, novel inhibitors of 3-dehydroquinate synthase (DHQS), an enzyme that catalyzes the second step of the shikimate pathway in MTB, were determined. 12,165 compounds were selected from two public databases through virtual screening and molecular docking analysis using PyRx 8.0 and Autodock 4.2, respectively. A total of 18 com- pounds with the best binding energies (-13.23 to -8.22 kcal/mol) were then selected and screened for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, and nine of those compounds were found to satisfy all of the ADME and toxicity criteria. Among those nine, the three compounds —ZINC633887 (binding energy = -10.29 kcal/mol), ZINC08983432 (-9.34 kcal/mol), and PubChem73393 (-8.61 kcal/mol)—with the best binding energies were further selected for molecular dynamics (MD) simulation analysis. The results of the 50-ns MD simulations showed that the two compounds ZINC633887 and PubChem73393 formed stable complexes with DHQS and that the structures of those two ligands remained largely unchanged at the ligand-binding site during the simulations. These two compounds identified through docking and MD simulation are potential candidates for the treatment of TB, and should undergo validation in vivo and in vitro. Keywords Docking . MD simulation . MTB . ADMET . 3-Dehydroquinate synthase Introduction Tuberculosis (TB) is a major infectious disease that poses a threat to public health [1]. It is responsible for the deaths of 2 million people annually (one death every 15 s) around the world, especially in regions where there tend to be high pov- erty, poor living conditions, a lack of basic amenities, and inadequate medical facilities. TB affects more than a quarter of the world’ s population, especially in low-resource nations, and is caused by the oldest known human pathogen, Mycobacterium tuberculosis (MTB) [1]. Despite the develop- ment of numerous antituberculosis drugs (isoniazid, rifampi- cin, ethambutol, pyrazinamide, streptomycin, etc.) and a vaccine for TB, the disease still claims the lives of many people around the globe, as effective treatment requires a long treatment period and expensive drugs, which limits its acces- sibility to the poorer individuals in most developing countries. This situation has been worsened by the presence of TB-HIV coinfection and the emergence of multidrug-resistant (MDR- TB), extensively drug-resistant (XDR), and totally drug- resistant (TDR) tuberculosis [2]. However, the conventional method used for drug discovery and development is generally time-consuming and laborious. It takes >10 years and about US $800 million to develop a new drug. This generally in- volves the generation of large libraries of compounds and high-throughput virtual screening for bioactivity. Even then, this process is often not successful due to a low hit rate and a failure to fulfill the required adsorption, distribution, metabo- lism, excretion, and toxicity (ADMET) criteria. A better meth- od of developing TB drugs is therefore required. Computer- aided drug design through modeling and docking represents a useful alternative method of drug discovery and development [3]. Also, given the availability of the complete genome of * Mustafa Alhaji Isa mustafaisa@unimaid.edu.ng 1 Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, India Journal of Molecular Modeling (2018) 24:132 https://doi.org/10.1007/s00894-018-3637-4