Journal of Biomolecular Structure & Dynamics最新文献

Mycobacterium tuberculosis (MTB) causing tuberculosis (TB) infection is a leading source of illness and death in developing nations, and the emergence of drug-resistant TB remains a significant global threat and a challenge in treating the disease. Mutations in the inhA and katG genes are connected to the principal molecular mechanism of isoniazid (INH) resistance, and continuous treatment of INH for more than a decade led to the evolution of INH resistant-TB (inhR-TB). Structure-based drug discovery approaches on traditional natural compounds are the contemporary source to identify significant lead molecules. This work focuses on discovering effective small compounds from natural compound libraries and applying pharmacophore-based virtual screening to filter out the molecules. The best-identified hit complexes were used for molecular dynamics simulations (MDS) to observe their stability and compactness. A three-dimensional e-pharmacophore hypothesis and screening generated 62 hits based on phase fitness scores from the pharmacophore-based virtual screening. Molecular docking experiments in Maestro's GLIDE module indicated that ZINC000002383126 and ASN22022 may be potential inhibitors of inhA and katG (native, inhA mutants S94A, Y158A, Y158F and Y158S and D137S, Y229F, S315T, W321F, and R418L mutants of katG). In addition, MDS analysis indicated that the native and mutant docked complexes of inhA and katG had good stability and remained compact in the binding pocket of the targets. In vitro studies can further validate the compounds that can act as INH competitive inhibitors.Communicated by Ramaswamy H. Sarma.

As a part of our continuous effort to find new therapeutic agents from natural sources, the hydroalcoholic (1:1) extract of Citrus maxima (Burm.) Merr. root was selected for the identification of possible antimalarial phytoconstituents. From the extract, three flavonoids including luteolin were isolated and evaluated for in vitro antimalarial activity against the chloroquine-sensitive (Pf3D7) and resistant (PfRKL-9) strains of Plasmodium falciparum. Among these, luteolin (CM3) showed the highest antimalarial activity with IC₅₀ values of 2.315 ± 0.489 and 2.691 ± 0.454 µg/ml against the Pf3D7 and PfRKL-9 strains respectively. To assess the safety of luteolin (CM3), a cytotoxicity study against a normal human embryonic kidney cell line (HEK-293) was performed and the compound was found to be safe with a CC₅₀ value of 222.3 ± 1.443 µg/ml. The docking study against 26 target proteins of P. falciparum revealed that luteolin (CM3) has a better binding affinity with two proteins, viz. P. falciparum lactate dehydrogenase (PfLDG) and P. falciparum enoyl-ACP reductase (PfEAR) in comparison to the co-crystallized ligands. Furthermore, the molecular dynamics simulation study of the protein-ligand complexes also supported the binding affinity and interactions of luteolin (CM3) at the active sites. Finally, the binding free energy calculation revealed that the luteolin formed a thermodynamically more stable complex with PfLDG (-50.955 ± 17.184 kJ/mol) than PfEAR (-24.856 ± 13.739 kJ/mol). Overall, in this study, we identified an antimalarial marker in the hydroalcoholic extract of C. maxima root which may act by inhibiting PfLDG.Communicated by Ramaswamy H. Sarma.

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is a potentially lethal infection that presents a substantial threat to health, especially in Middle East nations. Given that no FDA-approved specific therapy for MERS infection exists, designing and discovering a potent antiviral therapy for MERS-CoV is crucial. One pivotal strategy for inhibiting MERS replication is to focus on the viral main protease (M^pro). In this study, we identify potential novel M^pro inhibitors employing structure-based virtual screening of our recently reported Ugi reaction-derived library (URDL) consisting of cherry-picked molecules from the literature. The key features of the URDL library include synthetic tractability (1-2 pot synthesis) of the molecules scaffold and unexplored chemical space. The hits were ranked based on the docking score, MM-GBSA free energy of binding, and the interaction pattern with the active site residues. A molecular dynamics (MD) simulation study was performed for the first two top-ranked compounds to analyze the stability and free binding energy based on the molecular mechanics Poisson-Boltzmann surface area. The potential mean force calculated from the steered molecular dynamics (SMD) simulations of the hits indicates improved H-bond potential, enhanced conformational stability, and binding affinity toward the target, compared to the cocrystallized ligand. The discovered hits represent novel synthetically tractable scaffolds as potential MERS-CoV M^pro inhibitors.Communicated by Ramaswamy H. Sarma.

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.

The interphase chromatin structure is extremely complex, precise and dynamic. Experimental methods can only show the frequency of interaction of the various parts of the chromatin. Therefore, it is extremely important to develop theoretical methods to predict the chromatin structure. In this publication, we implemented an extended version of the SBS model described by Barbieri et al. and created the ChroMC program that is easy to use and freely available (https://github.com/regulomics/chroMC) to other users. We also describe the necessary factors for the effective modeling of the chromatin structure in Drosophila melanogaster. We compared results of chromatin structure predictions using two methods: Monte Carlo and Molecular Dynamic. Our simulations suggest that incorporating black, non-reactive chromatin is necessary for successful prediction of chromatin structure, while the loop extrusion model with a long range attraction potential or Lennard-Jones (with local attraction force) as well as using Hi-C data as input are not essential for the basic structure reconstruction. We also proposed a new way to calculate the similarity of the properties of contact maps including the calculation of local similarity.Communicated by Ramaswamy H. Sarma.

In the present study, a requisite bonded force field for conducting molecular dynamics simulations of palladium compounds was derived utilizing a novel technique termed the "numbering system," implemented through a program named assign.py. A significant challenge in deriving a bonded force field for square-planar palladium compounds emanates from their cis-trans characteristics, whereby the bond angles of identical atoms diverge across different compounds due to the presence of cis and trans isomers. To navigate this challenge, atoms surrounding the palladium were assigned numerical identifiers; consecutively numbered neighboring atoms were designated as "cis," while atoms alternately numbered were regarded as "trans" relative to each other. Through the employment of the newly developed assign.py program, atoms common to GAFF were automatically assigned, facilitating the seamless integration of GAFF with the newly derived force field for cis and trans configurations. The tested innovative force field demonstrated results in close proximity to experimental findings. This research introduced two novel elements: firstly, a comparatively extensive force field was derived for palladium compounds, enabling the simulation of the previously non-simulable square planar geometry of palladium. Secondly, new software, assign.py, was developed, capable of amalgamating "numbering system atom types" with GAFF atom types into a unified force field. Conclusive tests within the study affirmed that the innovative bonded force field and technique utilizing the assign.py program was successful, simulating the square-planar geometry of palladium in a manner highly congruent with the experimental geometry. The program, licensed under Apache2, can be accessed via the following link: https://github.com/bkurt00/palladiumFF2/blob/main/assign_v2/assign_v2.pyCommunicated by Ramaswamy H. Sarma.

Two novel quinoline-anthracene conjugates comprising styrylquinoline and anthracene moieties linked by triazole bridges were designed and synthesized in good yields. These molecules were determined for some metabolic enzymes activities. Results indicated that the synthetic molecules exhibited powerful inhibitory actions against all aims as compared to the control molecules. K_i values of novel compound QA-1 for hCA I, hCA II, AChE, and α-glycosidase enzymes were obtained of 20.18 ± 2.46 µM, 14.63 ± 1.14 µM, 71.48 ± 7.76 nM, 401.35 ± 36.84 nM, respectively. Both compounds showed promising candidate complexes for drug development with considerable in vitro different enzymes inhibitory activities. The binding conformations patterns and interaction of QA-1 and QA-2 compounds with α-glucosidase, acetycholinesterase, carbonic anhydrase-I and carbonic anhydrase-II enzymes were investigated through molecular docking profiles. The docking outputs are consistent with the Ki and IC₅₀ values of novel compounds. Three dimensional geometries and electronic properties of the title compounds were obtained by the applicational computational approach at B3LYP/6-31++G(d,p) level of theory.Communicated by Ramaswamy H. Sarma.

Gastric ulcers caused by Helicobacter pylori and Fusobacterium nucleatum remain a significant global health concern without an established vaccine. In this study, we utilized immunoinformatics methods to design a multi-epitope vaccine targeting these pathogens. Outer membrane proteins from H. pylori and F. nucleatum were scrutinized to identify high antigenic T-cell and B-cell epitopes. The resulting vaccine comprised carefully analyzed and evaluated epitopes, including cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocytes epitopes. This vaccine exhibited notable antigenicity, suitable immunogenicity, and demonstrated non-allergenicity and non-toxicity. It displayed favorable physiochemical characteristics and high solubility. In interaction studies, the vaccine exhibited robust binding to toll-like receptor 4 (TLR4). Molecular dynamic simulations revealed cohesive structural integrity and stable attachment. Codon adaptation utilizing Escherichia coli K12 host yielded a vaccine with elevated Codon Adaptation Index (CAI) and optimal GC content. In silico cloning into the pET28+(a) vector demonstrated efficient expression. Immune simulations indicated the vaccine's ability to initiate immune responses in humans, mirroring real-life scenarios. Based on these comprehensive findings, we propose that our developed vaccine has the potential to confer robust immunity against H. pylori and F. nucleatum infections.Communicated by Ramaswamy H. Sarma.

There has been an abrupt increase in brain tumor (BT) related medical cases during the past ten years. The tenth most typical type of tumor affecting millions of people is the BT. The cure rate can, however, rise if it is found early. When evaluating BT diagnosis and treatment options, MRI is a crucial tool. However, segmenting the tumors from magnetic resonance (MR) images is complex. The advancement of deep learning (DL) has led to the development of numerous automatic segmentation and classification approaches. However, most need improvement since they are limited to 2D images. So, this article proposes a novel and optimal DL system for segmenting and classifying the BTs from 3D brain MR images. Preprocessing, segmentation, feature extraction, feature selection, and tumor classification are the main phases of the proposed work. Preprocessing, such as noise removal, is performed on the collected brain MR images using bilateral filtering. The tumor segmentation uses spatial and channel attention-based three-dimensional u-shaped network (SC3DUNet) to segment the tumor lesions from the preprocessed data. After that, the feature extraction is done based on dilated convolution-based visual geometry group-19 (DCVGG-19), making the classification task more manageable. The optimal features are selected from the extracted feature sets using diagonal linear uniform and tangent flight included butterfly optimization algorithm. Finally, the proposed system applies an optimal hyperparameters-based deep neural network to classify the tumor classes. The experiments conducted on the BraTS2020 dataset show that the suggested method can segment tumors and categorize them more accurately than the existing state-of-the-art mechanisms.Communicated by Ramaswamy H. Sarma.

Globally, dental caries is a prevalent oral disease caused by cariogenic bacteria, primarily Streptococcus mutans. It establishes caries either through sucrose-dependent (via glycosyltransferases) or through sucrose-independent (via surface adhesins Antigen I/II) mechanism. Sortase A (srtA) attaches virulence-associated adhesins to host tissues. Because of their importance in the formation of caries, targeting these proteins is decisive in the development of new anticariogenic drugs. High-throughput virtual screening with LIPID MAPS -a fatty acid database was performed. The selected protein-ligand complexes were subjected to molecular dynamics simulation (MDs). The Binding Free Energy of complexes was predicted using MM/PBSA. Further, the drug-likeness and pharmacokinetic properties of ligands were also analyzed. Out of 46,200 FAs scrutinized virtually against the three protein targets (viz., GtfC, Ag I/II and srtA), top 5 FAs for each protein were identified as the best hit based on interaction energies viz., hydrogen bond numbers and hydrophobic interaction. Further, two common FAs (LMFA01050418 and LMFA01040045) that showed high binding affinity against Ag I/II and srtA were selected for MDs analysis. A 100ns MDs unveiled a stable conformation. Results of Rg signified that FAs does not induce significant structural & conformational changes. SASA indicated that the complexes maintain higher thermodynamic stability during MDs. The predicted binding free energy (MM/PBSA) of complexes elucidated their stable binding interaction. ADME analysis suggested the FAs are biologically feasible as therapeutic candidates. Overall, the presented in silico data is the first of its kind in delineating FAs as promising anticaries agents of future.Communicated by Ramaswamy H. Sarma.