Homology modeling and virtual screening of inhibitors against TEM- and SHV-type-resistant mutants: A multilayer filtering approach

Identification and Evaluation of IGF1R and Its Associated Proteins as Targets and Design of Novel Inhibitors for Cancer Therapy

The insulin-like growth factor 1 receptor (IGF1R) is a crucial receptor tyrosine kinase involved in cellular growth, survival, and metabolism. Abnormal overexpression and activation are common in various cancers and contribute to tumor development and resistance to treatment. The STRING database was used to analyze the protein-protein interaction network of IGF1R and was visualized using Cytoscape to identify the key associated proteins. We assessed IGF1R and its associated protein expression levels across pan-cancer types and compared them to healthy controls using a TNMplot and cBioPortal. The objective of this study was to identify novel, low-toxicity inhibitors targeting the IGF1R and its associated proteins (e.g., AKT1 and EGFR) with better pharmacokinetic profiles for effective cancer treatment, including brain cancer. We screened 693 million drug-like compounds and selected the top 400 for toxicity analysis using ProTox-II, which identified 83 nontoxic candidates. These were categorized as either blood-brain barrier (BBB) permeant or impermeant. Molecular docking studies with AutoDock Vina 4.1 were performed on 17 target proteins, including IGF1R, with the top three compounds. Subsequently, molecular dynamics simulations using Desmond were conducted on the two most promising candidates: two BBB permeants and two impermeants. Our study identified six nontoxic IGF1R inhibitors and 16 other target protein inhibitors. Docking and MD simulations confirmed the potential of these compounds in targeted therapies. Notably, both BBB-permeant and -impermeant compounds in complex with the target proteins showed stability over 50 and 400 ns molecular simulation experiments, highlighting their potential in cancer therapy and suggesting the need for further in vitro and in vivo validation.

Differential gene expression analysis of RAGE-S100A6 complex for target selection and the design of novel inhibitors for anticancer drug discovery

Receptor for advanced glycation end products (RAGE), a member of the immunoglobulin family, interactions with its ligands trigger downstream signaling and induce an inflammatory response linked to diabetes, inflammation, carcinogenesis, cardiovascular disease, and a variety of other human disorders. The interaction of RAGE and S100A6 has been associated with a variety of malignancies. For the control of RAGE-related illnesses, there is a great demand for more specialized drug options. To identify the most effective target for combating human malignancies associated with RAGE-S100A6 complex, we conducted single and differential gene expression analyses of S100A6 and RAGE, comparing normal and malignant tissues. Further, a structure-based virtual screening was conducted using the ZINC15 database. The chosen compounds were then subjected to a molecular docking investigation on the RAGE active site region, recognized by the various cancer-related RAGE ligands. An optimized RAGE structure was screened against a library of drug-like molecules. The screening results suggested that three promising compounds were presented as the top acceptable drug-like molecules with a high binding affinity at the RAGE V-domain catalytic region. We depicted that these compounds may be potential RAGE inhibitors and could be used to produce a successful medication against human cancer and other RAGE-related diseases based on their various assorted parameters, binding energy, hydrogen bonding, ADMET characteristics, etc. MD simulation on a time scale of 50 ns was used to test the stability of the RAGE-inhibitor complexes. Therefore, targeting RAGE and its ligands using these drug-like molecules may be an effective therapeutic approach.

Identification of small molecular inhibitors for efflux protein Rv2688c of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is the pathogen, which causes tuberculosis. The development of multidrug-resistant and extensively drug-resistant strains in Mtb is due to an efflux mechanism of antibiotics in the bacteria. The efflux pump proteins in the bacteria are implicated in the active efflux of antibiotics. The efflux pump protein, "fluoroquinolones export ATP-binding protein Rv2688c" (FEAB), is considered as a potential therapeutic target to prevent tuberculosis. In the present work, in silico protocols are applied to identify inhibitors for the FEAB protein to arrest the efflux mechanism. Comparative modeling techniques are used to build the protein structure. The generated structure consists of 9 helices, 13 beta strands, and 3 β sheets. The active site is predicted using active site prediction server tools. The virtual screening protocols are carried out to generate small ligand inhibitor structures. The identified ligand molecules show selective binding with Ser97, Glu99, Lys149, Asp171, Glu172, and Ser175 amino acid residues of the protein. The ligand molecules are subjected to in silico prediction of pharmaco kinetic properties, and the predicted IC₅₀ (HERG) of all the molecules are less than -5.0, which is indicative of the identified ligand molecules is being potentially good FEAB inhibitors.