Journal of Biomolecular Structure & Dynamics最新文献

The escalating incidence of breast cancer globally presents a formidable challenge within oncology. Our research pursued an examination of the anti-cancer potential of Carissa carandas, a shrub traditionally used for medicinal purposes and known for its composition of vital nutrients and phytochemicals. We employed a network pharmacology strategy combined with molecular docking and molecular dynamics simulations to elucidate the intricate relationships between the phytochemical constituents of C. carandas, critical breast cancer proteins, and associated signaling pathways. The study highlighted a complex network of protein interactions, identifying AKT1, HIF1A, PTGS2, and GSK3B as key nodes within this network. These proteins are engaged by numerous investigated compounds from C. carandas and are fundamental in modulating crucial signaling pathways such as those involving Estrogen, HIF-1, Prolactin, VEGF, and Th17 cell differentiation-each of which plays a recognized role in breast cancer progression, affecting tumor growth, proliferation, and metastatic potential. Our analysis suggests that the phytochemicals in C. carandas may exert anti-cancer activity by synergistically modulating these pathways, highlighting the benefit of multi-targeted therapeutic approaches over single-targeted ones. In summary, through the application of advanced network pharmacology, molecular docking, MD simulations, and MM/PBSA analysis, our study offers a detailed exploration of the potential mechanisms by which C. carandas may exert anti-cancer effects. This sets a foundation for further in-depth experimental and clinical trials to validate these mechanisms and support the advancement of novel plant-derived therapeutic options towards breast cancer, with the possibility of significantly advancing the therapeutic options for this prevalent disease.

The PI3K/mTOR signaling pathway is often disrupted in human cancers, with PI3Kα being one of the most mutated kinases. There has been considerable interest in developing small-molecule inhibitors aimed at blocking the mutant PI3Kα-driven phosphatidylinositol 3-kinase (PI3K) signaling pathway as a potential treatment for cancer. In this study, we describe our effort to identify a compound, phenylacetamide-1H-imidazol-5-one (KIM-161), from our in-house oncogenic kinase-targeting inhibitors. KIM-161 showed excellent anti-proliferative activities at sub-nanomolar concentrations, primarily against mutant PI3Kα breast cancer cell lines, when compared with wild-type PI3Kα breast cancer cell lines, producing both dose- and time-dependent effects with an IC50 range of 1.42 - 0.064 µM. Next, we observed that KIM-161 was able to induce ROS production by modulating breast cancer metabolism, suggesting its broad effects on mutant PI3Kα regulated downstream pathways. We also computationally analyzed the binding interactions between KIM-161 and PI3K-alpha (PDB ID: 8EXL). Molecular docking showed that KIM-161 had a docking score of -7.44 Kcal/mol, compared to the reference compound, which had a docking score of -7.67 Kcal/mol. Moreover, molecular dynamics simulation studies demonstrated that the PI3Ka-KIM-161 complex remained stable throughout the 100 ns simulation, when compared to the PI3Ka complex with the co-crystallized inhibitor. These findings present KIM-161 as a promising lead, providing valuable insights into treatment approaches and resistance mechanisms associated with PI3K inhibitors in specific PIK3CA-mutant cancer subtypes.

Fungal infections are important types of infection that annually cause the death of many people around the world. Therefore, new antifungal agents that are more effective and less toxic are constantly needed. In this study, new imidazole derivatives were synthesized and their antifungal activities were investigated. Compound 5d showed antifungal activity against Candida albicans, Candida parapsilosis and Candida krusei with a minimum inhibitory concentration (MIC₅₀) of 0.98 µg/mL. While compound 5e showed antifungal effects against C. albicans and C. parapsilosis with MIC₅₀ of 0.98 µg/mL, it displayed potent antifungal activity against C. krusei with MIC₅₀ of 1.96 µg/mL. Compound 5h exhibited antifungal activity against C. albicans and C. parapsilosis with MIC₅₀ of 1.96 and 0.98 µg/mL, respectively. It is known that azole group antifungals inhibit ergosterol biosynthesis by inhibiting the 14α-demethylase enzyme. For this reason, in the present study in silico studies were performed on 14α-demethylase enzyme crystal (PDB ID: 1EA1). Molecular docking and dynamics studies were conducted to examine the binding modes of the active compounds (5d, 5e and 5h). The results of the in silico studies agreed with the biological activity results.

The COVID-19 pandemic had a profound impact on global health. This study focuses on an in-depth analysis of the structural proteins (Spike (S), Nucleocapsid (N), Membrane (M), and Envelope (E) protein) of SARS-CoV-2 and its variants, aiming to develop a multiepitope vaccine construct that targets the virus independently of its variants. The analysis began by examining genetic variations in viral proteins relative to the reference strain Wuhan-Hu2, particularly in the S, M, N, and E proteins. T-cell epitope predictions for MHC Class-I and Class-II binding were conducted, shedding light on potential cytotoxic and helper T lymphocyte recognition. Identification of linear B-cell epitopes laid the groundwork for antibody-based humoral immune responses. The safety and efficacy of these epitopes were assessed for antigenicity, allergenicity, toxicity, immunogenicity, and conservancy. Population coverage analysis indicated promising global effectiveness of the designed vaccine construct. By incorporating 28 epitopes, we validated that was designed vaccine construct for stability through structural analysis. Molecular dynamics simulations and docking studies revealed its robust interaction with Toll-like receptor 4 (TLR4). Immune simulation studies suggested that the vaccine construct could induce a potent immune response by enhancing antibody titers, B-cell proliferation, memory cell development, and activation of T cells and natural killer cells upon administration. This comprehensive approach offers a promising multiepitope vaccine against SARS-CoV-2, with the potential for broad global coverage and strong immunogenicity. Further experimental validation holds the prospect of introducing a novel candidate vaccine to aid in the ongoing battle against the COVID-19 pandemic.

Coronaviruses (CoV), belonging to the family Coronaviridae, were not considered dangerous pathogens until the outbreaks of SARS, MERS, and more recently, COVID-19. The coronaviruses causing these respective diseases/syndromes, SARS, MERS, and SARS-CoV2, share high sequence and structural similarities. COVID-19 continues to have a global impact on human health and the economy. Human-to-human transmission is at the center of COVID-19's ability to stall the entire world and force lockdowns across the globe. The corona viruses' positive sense RNA genome is ∼30 kb long and encodes non-structural (ORF1ab) and structural (Spike, Envelope, Membrane, and Nucleo-capsid) proteins. The main viral protease (NSP5) is a Chymotrypsin-like protease (3CL^pro) that cleaves on the carboxy side of the glutamine (Q) of the polypeptide sequence motif x-(L/F/M)-Q-(G/A/S)-x. 3CL^PRO is highly conserved among coronaviruses and is critical in the replication and viral life cycle. Therefore, 3CL^PRO is considered a promising drug target. We have recently reported three natural compounds, flavonoid derivatives, to target the cysteine 145 of the catalytic dyad covalently. Here, we have screened for small molecules with pan coronavirus activity to target 3CL^pro. Our rigid body docking studies have identified 30 small molecules with comparable binding affinities to all the beta coronaviruses. Of these, five molecules have showed the possibility of covalently attacking the C145 of the catalytic dyad. MD simulations have revealed compounds 22 and 23 to be the most ideal lead compounds. Interestingly, one of the compounds, 22, identified in the current study has already shown to be an ideal lead compound against SARS-CoV2 3CL^PRO.

The human epidermal growth factor receptor 2 (HER2) is closely associated with the development and progression of breast cancer, making it a critical target for therapeutic interventions. In this study, we employed a comprehensive computational drug discovery strategy to identify potential inhibitors of HER2. Our approach combined virtual screening, re-docking procedures, molecular dynamics (MD) simulations, and free energy landscape analysis using principal component analysis (PCA). From the extensive PubChem library, we initially screened 733 compounds for their binding potential to HER2, using docking scores as a primary filter. These scores ranged notably from -11.172 to -7.028 kcal/mol, indicating substantial binding capacities. Following this screening, we selected four promising compounds (PubChem CID 166029206, 166544027, 21031510, and 11712721) along with a control compound (70I) for in-depth analysis. Utilizing the Amber software suite for MD simulations, we conducted 200-nanosecond simulations to assess the interactions and binding efficiencies of these selected compounds with HER2. We analysed the molecular interactions through various parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), and hydrogen bond formation patterns, free binding energy calculations. The PCA-based free energy landscape analysis revealed that these compounds consistently occupied a distinct low-energy basin, indicating their high stability and strong binding affinity for the HER2. This detailed analysis provided insights into the stability and conformational dynamics of these potential inhibitors when bound to the HER2. Our findings pave the way for further experimental validation and development of these compounds as therapeutic agents in breast cancer treatment.

HIV-PR is a prominent pharmacological target that is driving the development of various possible HIV inhibitors. Unfortunately, the viral strain population has evolved to be even more resistant to medications; therefore, studying the dynamic structures of both WT and mutant viruses, besides their interactions with inhibitors, may be advantageous. Molecular dynamics analyses and free-energy calculations on the WT and four important resistance mutants (V82F, I84V, I50V, and V82F/I84V) of HIV-PR complexed with fungal compounds were performed to completely examine the mechanism of HIV-PR drug resistance. To determine precise binding free energies, we utilized an MM/GBSA method based on molecular mechanics. In this study, we found that compared to WT and single mutants, the double mutant (V82F/I84V) exhibited less flexibility and less curling of the flap tips. Contradiction with prior studies, our data reveal that the double mutant (V82F/I84V) facilitates binding affinity, suggesting that this variant may be particularly well suited to Ganomycin-I. The energy decomposition study shows that an increase in E_vdw energy by 6.56 kcal/mol is responsible for much of the increased binding observed for the double mutant (V82F/I84V) HIV-PR, which plays a direct role in increasing the binding affinity by approximately -1.62 (Val82' to Phe82') and -1.08 (Ile84' to Val84') kcal/mol, accounts for 41% of the total gain of the binding affinity. In addition to the direct impacts of Phe82' and Val84', the residues Gly27, Ala28, Asp29, Asp30, Ile47, and Ile50 each contribute more than -1 kcal/mol to the enhanced binding affinity of (V82F/I84V) HIV-PR towards the inhibitor.

Breast cancer (BC) is the most dominant kind of cancer, which grows continuously and serves as the second highest cause of death for women worldwide. Early BC prediction helps decrease the BC mortality rate and improve treatment plans. Ultrasound is a popular and widely used imaging technique to detect BC at an earlier stage. Segmenting and classifying the tumors from ultrasound images is difficult. This paper proposes an optimal deep learning (DL)-based BC detection system with effective pre-trained transfer learning models-based segmentation and feature learning mechanisms. The proposed system comprises five phases: preprocessing, segmentation, feature learning, selection, and classification. Initially, the ultrasound images are collected from the breast ultrasound images (BUSI) dataset, and the preprocessing operations, such as noise removal using the Wiener filter and contrast enhancement using histogram equalization, are performed on the collected data to improve the dataset quality. Then, the segmentation of cancer-affected regions from the preprocessed data is done using a dilated convolution-based U-shaped network (DCUNet). The features are extracted or learned from the segmented images using spatial and channel attention including densely connected convolutional network-121 (SCADN-121). Afterwards, the system applies an enhanced cuckoo search optimization (ECSO) algorithm to select the features from the extracted feature set optimally. Finally, the ECSO-tuned long short-term memory (ECSO-LSTM) was utilized to classify BC into '3' classes, such as normal, benign, and malignant. The experimental outcomes proved that the proposed system attains 99.86% accuracy for BC classification, which is superior to the existing state-of-the-art methods.

Fanconi anemia is a rare chromosomal instability disorder associated with developmental abnormalities, bone marrow failure, and a heightened susceptibility to leukemia and other cancers. It is an autosomal recessive genetic disorder, necessitating both parents to carry the faulty gene. Diagnostic methods include blood tests, chromosome breakage assessments, and genetic testing. While there is no cure, treatments encompass blood transfusions, bone marrow transplants, and gene therapy, with patients requiring regular check-ups, supportive care, and cancer screening to enhance their quality of life. In this study, we identify a specific substitution (R258H) targeting the crucial binding site of the alpha-helix region in RAD51C. This substitution induces structural disorder in distinct regions, as indicated by the near absence of electron density for multiple amino acids. Intriguingly, these disordered regions do not follow a continuous sequence from the mutation site and extend across domain boundaries. We utilized computational prediction algorithms and Molecular Dynamics (MD) simulations to model RAD51C and its mutation (R258H) structurally. These simulations highlighted alterations in conformational dynamics, the Free Energy Landscape (FEL), and intrinsic molecular motions induced by the mutation, suggesting structural destabilization that could disrupt its function. This observed destabilization in RAD51C due to mutations offers valuable insights that may serve as diagnostic markers for individuals carrying these mutations, particularly in Fanconi anemia.

ATP-binding cassette (ABC) proteins are membrane transporters responsible for metabolites and active substances removal from cells. Their genes' variations have been associated with protein function and expression defects. Familial Hypercholesterolemia (FH) patients hosting those alterations might compromise the efficacy of high-dose statin treatment, a primary therapeutic strategy. ABCC1 is a member of the ABC-transporter superfamily, potentially relevant to pharmacological therapy responses and toxicity risks in hypercholesterolemic patients. Here, we evaluated specific non-synonymous (SNV) missense variants in the ABCC1 gene from a FH patient cohort, assessing potential impacts on protein structure, molecular dynamics and interactions with rosuvastatin, atorvastatin, pravastatin, pitavastatin, and lovastatin. Molecular docking, complemented by motion, visual and binding affinity analysis using the PLANNET model, suggested that these mutations had minimal impact on drug interactions. These findings prompted further analysis of two other efflux pumps, ABCG2 and P-gp, and their statin interactions. Interestingly, diminished binding affinities hinted at a compensatory mechanism wherein other transporters might mitigate potential ABCC1 mutation effects, ensuring effective drug efflux. Clinical profiles from the patient cohort did not show a correlation between these variants and clinical outcomes, potentially pointing to the role of alternate drug transporters in statin interaction.