Structural dynamics and functional analysis of Saprolegnia parasitica chitin synthases 5 in a phospholipid bilayer.

Saprolegnia parasitica is an oomycete responsible for a fish disease called saprolegniosis, which poses an economic and environmental burden on aquaculture production. In Saprolegnia, CHS5 of S. parasitica (SpCHS5) contains an N-terminal domain, a catalytic domain of the glycosyltransferase -2 family containing a GT-A fold, and a C-terminal transmembrane domain. No three-dimensional structure of SpCHS5 is reported yet disclosing the structural details of this protein. We have developed a structural model of full-length SpCHS5 and validated it by molecular dynamics simulation technique. From the 1 microsecond simulations, we retrieved the stable RoseTTAFold model SpCHS5 protein to explain characteristics and structural features. Furthermore, from the analysis of the movement of chitin in the protein cavity, we assumed that ARG 482, GLN 527, PHE 529, PHE 530, LEU 540, SER 541, TYR 544, ASN 634, THR 641, TYR 645, THR 641, ASN 772 residues as a main cavity lining site. In SMD analysis, we investigated the opening of the transmembrane cavity required for chitin translocation. The pulling of chitin from the internal cavity to the extracellular region was observed through steered molecular dynamics simulations. A comparison of the initial and final structures of chitin complex showed that there's a transmembrane cavity opening in the simulations. Overall, this present work will help us understand the structural and functional basis of CHS5 and design inhibitors against SpCHS5.Communicated by Ramaswamy H. Sarma.

In silico peptide-based therapeutics against human colorectal cancer by the activation of TLR5 signaling pathways.

OBJECTIVE: Colorectal cancer (CRC) is the third leading cause of cancer-related deaths in both men and women. Toll-like receptor 5 (TLR5), an autoimmune signaling receptor that plays a role in cancer, can be exploited for the suppression of human colon cancer. Salmonella flagellin protein, a novel agonist of TLR5 activating downstream signaling, could be a basis for designing anticancer peptides. METHODS: The three-dimensional crystal structure of TLR5 (PDB ID: 3J0A, Resolution = 26.0 Å) was optimized using the AMBER force field in the YASARA suit. In silico enzymatic digestion tool, PeptideCutter, was used to identify peptides from Salmonella flagellin, an agonist against human TLR5. The 3D structure of the peptides was generated using PEP-FOLD3. These peptides were screened against human TLR5 using shape complementarity principles based on the binding affinity and interactions with the active residue of TLR5 monomer, and the selected peptides were further validated by molecular dynamic (MD) simulation. RESULTS: In this study, we generated 42 peptides from Salmonella flagellin protein by in silico protein digestion. Then, based on a new hidden Markov model sub-optimal conformation sampling approach as well as the size of the fragments, we select 38 effective peptides from these 42 cleavages. These peptides were screened against the monomeric Xray structure of human TLR5 using shape complementarity principles. Based on the binding affinity and interactions with the active residue of TLR5 monomer (residues 294 and 366 of TLR5), nine top-scored peptides were selected for the initial molecular dynamic (MD) simulation. Among these peptides, Clv10, Clv17, and Clv28 showed high stability and less flexibility during MD simulation. A 1 µs MD simulation was performed on TLR5-Clv10, TLR-Clv17, and TLR5-Clv28 complexes to further analyze the stability, conformational changes, and binding mode (Clv10, Clv17, and Clv28). During this MD study, the peptides showed high salt bridges and ionic interactions with residue ASP294 and residue ASP366 throughout the simulation and remained in the concave of the human TLR5 monomer. The RMSD and Rg values showed that the peptide-protein complexes become stable after 200 ns of contraction and extraction. CONCLUSION: These findings can facilitate the rational design of selected peptides as an agonist of TLR5, which have antitumor activity, suppress colorectal cancer tumors, and can be used as promising candidates and novel agonists of TLR5.

Virtual screening, molecular dynamics and structure-activity relationship studies to identify potent approved drugs for Covid-19 treatment.

Computer-aided drug screening by molecular docking, molecular dynamics (MD) and structural-activity relationship (SAR) can offer an efficient approach to identify promising drug repurposing candidates for COVID-19 treatment. In this study, computational screening is performed by molecular docking of 1615 Food and Drug Administration (FDA) approved drugs against the main protease (Mpro) of SARS-CoV-2. Several promising approved drugs, including Simeprevir, Ergotamine, Bromocriptine and Tadalafil, stand out as the best candidates based on their binding energy, fitting score and noncovalent interactions at the binding sites of the receptor. All selected drugs interact with the key active site residues, including His41 and Cys145. Various noncovalent interactions including hydrogen bonding, hydrophobic interactions, pi-sulfur and pi-pi interactions appear to be dominant in drug-Mpro complexes. MD simulations are applied for the most promising drugs. Structural stability and compactness are observed for the drug-Mpro complexes. The protein shows low flexibility in both apo and holo form during MD simulations. The MM/PBSA binding free energies are also measured for the selected drugs. For pattern recognition, structural similarity and binding energy prediction, multiple linear regression (MLR) models are used for the quantitative structural-activity relationship. The binding energy predicted by MLR model shows an 82% accuracy with the binding energy determined by molecular docking. Our details results can facilitate rational drug design targeting the SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.