Identification of the potential dual inhibitor of protein tyrosine phosphatase sigma and leukocyte common antigen-related phosphatase by virtual screen, molecular dynamic simulations and post-analysis

Virtual Screening-Based Drug Development for the Treatment of Nervous System Diseases

The incidence rate of nervous system diseases has increased in recent years. Nerve injury or neurodegenerative diseases usually cause neuronal loss and neuronal circuit damage, which seriously affect motor nerve and autonomic nervous function. Therefore, safe and effective treatment is needed. As traditional drug research becomes slower and more expensive, it is vital to enlist the help of cutting- edge technology. Virtual screening (VS) is an attractive option for the identification and development of promising new compounds with high efficiency and low cost. With the assistance of computer- aided drug design (CADD), VS is becoming more and more popular in new drug development and research. In recent years, it has become a reality to transform non-neuronal cells into functional neurons through small molecular compounds, which provides a broader application prospect than transcription factor-mediated neuronal reprogramming. This review mainly summarizes related theory and technology of VS and the drug research and development using VS technology in nervous system diseases in recent years, and focuses more on the potential application of VS technology in neuronal reprogramming, thus facilitating new drug design for both prevention and treatment of nervous system diseases.

Investigation of the structural dynamics of a knotted protein and its unknotted analog using molecular dynamics

The role of knots in proteins remains elusive. Some studies suggest an impact on stability; the difficulty in comparing systems to assess this effect, however, has been a significant challenge. In this study, we produced and analyzed molecular dynamic trajectories considering three different temperatures of two variants of ornithine transcarbamylase (OTC), only one of which has a 3₁ knot, in order to evaluate the relative stability of the two molecules. RMSD showed equilibrated structures for the produced trajectories, and RMSF showed subtle differences in flexibility. In the knot moiety, the knotted protein did not show a great deal of fluctuation at any temperature. For the unknotted protein, the residue GLY243 showed a high fluctuation in the corresponding moiety. The fraction of native contacts (Q) showed a similar profile at all temperatures, with the greatest decrease by 436 K. The investigation of conformational behavior with principal component analysis (PCA) and dynamic cross-correlation map (DCCM) showed that knotted protein is less likely to undergo changes in its conformation under the conditions employed compared to unknotted. PCA data showed that the unknotted protein had greater dispersion in its conformations, which suggests that it has a greater capacity for conformation transitions in response to thermal changes. DCCM graphs comparing the 310 K and 436 K temperatures showed that the knotted protein had less change in its correlation and anti-correlation movements, indicating stability compared to the unknotted.

Identifying potential inhibitors of biofilm-antagonistic proteins to promote biofilm formation: a virtual screening and molecular dynamics simulations approach

Microbial biofilms play a critical role in environmental biotechnology and associated applications. Biofilm production can be enhanced by inhibiting the function of proteins that negatively regulate their formation. With this objective, an in silico approach was adopted to identify competitive inhibitors of eight biofilm-antagonistic proteins, namely AbrB and SinR (from Bacillus subtilis) and AmrZ, PDE (EAL), PslG, RetS, ShrA and TpbA (from Pseudomonas aeruginosa). Fifteen inhibitors that structurally resembled the natural ligand of each protein were shortlisted using ligand-based and structure-based virtual screening. The top four inhibitors obtained from molecular docking using Autodock Vina were further docked using SwissDock and DOCK 6.9 to obtain a consensus hit for each protein based on different scoring functions. Further analysis of the protein-ligand complexes revealed that these top inhibitors formed significant non-covalent interactions with their respective protein binding sites. The eight protein-ligand complexes were then subjected to molecular dynamics simulations for 30 ns using GROMACS. RMSD and radius of gyration values of 0.1-0.4 nm and 1.0-3.5 nm, respectively, along with hydrogen bond formation throughout the trajectory indicated that all the complexes remained stable, compact and intact during the simulation period. Binding energy values between -20 and -77 kJ/mol obtained from MM-PBSA calculations further confirmed the high affinities of the eight inhibitors for their respective receptors. The outcome of this study holds great promise to enhance biofilms that are central to biotechnological processes associated with microbial electrochemical technologies, wastewater treatment, bioremediation and the industrial production of value-added products.