QSAR, Docking, and Molecular Dynamics Simulation Studies of Sigmacidins as Antimicrobials against Streptococci

Abstract

Streptococci are a family of bacterial species significantly affecting human health. In addition, environmental Streptococci represent one of the major causes of diverse livestock diseases. Due to antimicrobial resistance, there is an urgent need for novel antimicrobial agent discovery against Streptococci. We discovered a class of benzoic acid derivatives named sigmacidins inhibiting the bacterial RNA polymerase-σ factor interaction and demonstrating excellent antimicrobial activity against Streptococci. In this work, a combinational computer approach was applied to gain insight into the structural basis and mechanism of action of sigmacidins as antimicrobials against Streptococcus pneumoniae. Both two- and three-dimensional quantitative structure-active relationships (2D and 3D QSAR) of sigmacidins displayed good predictive ability. Moreover, molecular docking and molecular dynamics simulation studies disclosed possible contacts between the inhibitors and the protein. The results obtained in this study provided understanding and new directions to the further optimizations of sigmacidins as novel antimicrobials.

Ligand-Based Drug Design of Novel Antimicrobials against Staphylococcus aureus by Targeting Bacterial Transcription

“…Besides NusB-NusE PPI, numerous PPIs are present in bacterial transcription such as RNAP-σ [32], RNAP-NusG PPI, and RNAP-NusA PPI [53][54][55], we believe that the workflow presented in this study will contribute to the further optimization of nusbiarylins, as well as the discovery of other novel bacterial transcription inhibitors.…”

“…As PPI inhibitors, the discovery and optimization of nusbiarylins has faced a series of challenges and taken a considerable time in drug design, hit identification, and lead optimization, which requested the assistance of computer-assisted calculation in each step. The similar path has been revealed in the discovery of another PPI inhibitor series, sigmacidins, designed by targeting RNAP-σ PPI [32]. On the basis of assay development [33], we have used a house-made library to identify hits [34], which were subjected to lead optimization [35][36][37][38][39].…”

“…Table 3 listed the statistical parameters related to the 3D QSAR model. In Maestro 10.2, r 2 represents the non-cross-validated value for regression, r 2 cv is the LOO cross validated correlation value and Q 2 is another non-cross-validated value which is based on the test predictions [32]. The predicted activity of the training and test sets of compounds was presented in Table 1 and the correlation with experimental activity was shown in Figure 4.…”

Inhibition of bacterial RNA polymerase function and protein–protein interactions: a promising approach for next-generation antibacterial therapeutics

“…110 The C3 series of compounds was coined sigmacidins to reflect the inhibitory function by mimicking σ factor and the benzoic acid structure. 111 C5 (DSHS00507). Compound C5 (5) (Fig.…”

FOMO: A Fragment-based Objective Molecule Optimization Framework

“…To address this, we employ permutation techniques to systematically enumerate all possible connection strategies, thereby enabling the generation of new molecules. As shown in Figure 4, we select a molecule that is newly discovered antimicrobial small molecule potential for next-generation antibiotic drug development [26,27,28,25]. When we change the sulfur atom into pyridine, 10(8 of 10 are shown in Figure 4) new molecules with different connection strategies are generated using the permutation method.…”