In silico investigation of molecular mechanism of laminopathy caused by a point mutation (R482W) in lamin A/C protein

Computational biophysical characterization of the effect of gatekeeper mutations on the binding of ponatinib to the FGFR kinase

Fibroblast Growth Factor Receptor (FGFR) is connected to numerous downstream signalling cascades regulating cellular behavior. Any dysregulation leads to a plethora of illnesses, including cancer. Therapeutics are available, but drug resistance driven by gatekeeper mutation impedes the treatment. Ponatinib is an FDA-approved drug against BCR-ABL kinase and has shown effective results against FGFR-mediated carcinogenesis. Herein, we undertake molecular dynamics simulation-based analysis on ponatinib against all the FGFR isoforms having Val to Met gatekeeper mutations. The results suggest that ponatinib is a potent and selective inhibitor for FGFR1, FGFR2, and FGFR4 gatekeeper mutations. The extensive electrostatic and van der Waals interaction network accounts for its high potency. The FGFR3_VM mutation has shown resistance towards ponatinib, which is supported by their lesser binding affinity than wild-type complexes. The disengaged molecular brake and engaged hydrophobic spine were believed to be the driving factors for weak protein-ligand interaction. Taken together, the inhibitory and structural characteristics exhibited by ponatinib may aid in thwarting resistance based on Val-to-Met gatekeeper mutations at an earlier stage of treatment and advance the design and development of other inhibitors targeted at FGFRs harboring gatekeeper mutations.

The Role of PNPLA3_rs738409 Gene Variant, Lifestyle Factors, and Bioactive Compounds in Nonalcoholic Fatty Liver Disease: A Population-Based and Molecular Approach towards Healthy Nutrition

This study aimed to investigate the impact of a common non-synonymous gene variant (C>G, rs738409) in patatin-like phospholipase domain-containing 3 (PNPLA3), leading to the substitution of isoleucine with methionine at position 148 (PNPLA3-I148M), on susceptibility to nonalcoholic fatty liver disease (NAFLD) and explore potential therapeutic nutritional strategies targeting PNPLA3. It contributed to understanding sustainable dietary practices for managing NAFLD, recently referred to as metabolic-dysfunction-associated fatty liver. NAFLD had been diagnosed by ultrasound in a metropolitan hospital-based cohort comprising 58,701 middle-aged and older Korean individuals, identifying 2089 NAFLD patients. The interaction between PNPLA3 and lifestyle factors was investigated. In silico analyses, including virtual screening, molecular docking, and molecular dynamics simulations, were conducted to identify bioactive compounds from foods targeting PNPLA3(I148M). Subsequent cellular experiments involved treating oleic acid (OA)-exposed HepG2 cells with selected bioactive compounds, both in the absence and presence of compound C (AMPK inhibitor), targeting PNPLA3 expression. Carriers of the risk allele PNPLA3_rs738409G showed an increased association with NAFLD risk, particularly with adherence to a plant-based diet, avoidance of a Western-style diet, and smoking. Delphinidin 3-caffeoyl-glucoside, pyranocyanin A, delta-viniferin, kaempferol-7-glucoside, and petunidin 3-rutinoside emerged as potential binders to the active site residues of PNPLA3, exhibiting a reduction in binding energy. These compounds demonstrated a dose-dependent reduction in intracellular triglyceride and lipid peroxide levels in HepG2 cells, while pretreatment with compound C showed the opposite trend. Kaempferol-7-glucoside and petunidin-3-rutinoside showed potential as inhibitors of PNPLA3 expression by enhancing AMPK activity, ultimately reducing intrahepatic lipogenesis. In conclusion, there is potential for plant-based diets and specific bioactive compounds to promote sustainable dietary practices to mitigate NAFLD risk, especially in individuals with genetic predispositions.

Network based approach to identify interactions between Type 2 diabetes and cancer comorbidities

High blood sugar and insulin insensitivity causes the lifelong chronic metabolic disease called Type 2 diabetes (T2D) which has a higher chance of developing different malignancies. T2D with comorbidities like Cancers can make normal medications for those disorders more difficult. There may be a significant correlation between comorbidities and have an impact on one another's health. These associations may be due to a number of direct and indirect mechanisms. Such molecular mechanisms that underpin T2D and cancer are yet unknown. However, the large volumes of data available on these diseases allowed us to use analytical tools for uncovering their interrelated pathways. Here, we tried to present a system for investigating potential comorbidity relationships between T2D and Cancer disease by looking at the molecular processes involved, analyzing a huge number of freely accessible transcriptomic datasets of various disorders using bioinformatics. Using semantic similarity and gene set enrichment analysis, we created an informatics pipeline that evaluates and integrates Gene Ontology (GO), expression of genes, and biological process data. We discovered genes that are common in T2D and Cancer along with molecular pathways and GOs. We compared the top 200 Differentially Expressed Genes (DEGs) from each selected T2D and cancer dataset and found the most significant common genes. Among all the common genes 13 genes were found most frequent. We also found 4 common GO terms: GO:0000003, GO:0000122, GO:0000165, and GO:0000278 among all the common GO terms between T2d and different cancers. Using these genes and GO term semantic similarity, we calculated the distance between these two diseases. The semantic similarity results of our study showed a higher association of Liver Cancer (LiC), Breast Cancer (BreC), Colorectal Cancer (CC), and Bladder Cancer (BlaC) with T2D. Furthermore we found KIF4A, NUSAP1, CENPF, CCNB1, TOP2A, CCNB2, RRM2, HMMR, NDC80, NCAPG, and IGFBP5 common hub proteins among different cancers correlated to T2D. AGE-RAGE signaling pathway in diabetic complications, Osteoclast differentiation, TNF signaling pathway, IL-17 signaling pathway, p53 signaling pathway, MAPK signaling pathway, Human T-cell leukemia virus 1 infection, and Non-alcoholic fatty liver disease are the 8 most significant pathways found among 18 common pathways between T2D and selected cancers. As a result of our technique, we now know more about disease pathways that are critical between T2D and cancer.

Underpinning Endogeneous Damp EDA-Fibronectin in the Activation of Molecular Targets of Rheumatoid Arthritis and Identifcation of its Effective Inhibitors by Computational Methods

Rheumatoid arthritis (RA) is one of the most severe inflammatory diseases that cause swelling, stiffness and pain in the joints, which pose a significant threat worldwide. Damage-associated molecular patterns (DAMPs) are danger molecules of endogenous origin, released during cell injury or cell death, interacts with various Pattern recognition receptors (PRRs) and activates various inflammatory diseases. One of the DAMP molecules, so-called EDA-fibronectin (Fn) is also responsible for causing RA. EDA-Fn triggers RA through its interaction with TLR4. Apart from TLR4, it is divulged that certain other PRR's are also responsible for RA, but the identity and mechanism of those PRRs remain unknown until now. Hence, for the first time, we tried to reveal those PRR's interaction with EDA-Fn in RA through computational methods. Protein-protein interaction (PPI) was checked using ClusPro between EDA-Fn and certain Pattern recognition receptors (PRRs) to explore the binding affinities of the potential PRRs. Protein-protein docking unveiled that TLR5, TLR2 and RAGE has good interaction with EDA-Fn than the well-reported TLR4. Macromolecular simulation was performed for TLR5, TLR2 and RAGE complexes along with the control group TLR4 for 50 ns to further investigate the stability, leading to the identification of TLR2, TLR5 and RAGE as the stable complexes. Hence, TLR2, TLR5 and RAGE on interaction with EDA-Fn may lead to the progression of RA that may need additional validations through in vitro and in vivo animal models. Molecular docking was used to analyse the binding force of the top 33 active anti-arthritic compounds with the target protein EDA-Fn. Molecular docking study showed that withaferin A has a good binding activity with EDA-fibronectin target. Hence, it is emphasized that guggulsterone and berberine could modulate the EDA-Fn-mediated TLR5/TLR2/RAGE pathways, thereby it could inhibit the deteriorating effects of RA which needs further in vitro and in vivo experimental validations.

Elucidating the mutational impact in causing Niemann-Pick disease type C: an in silico approach

Niemann-Pick disease type C is a rare autosomal recessive of lysosomal storage disorder characterized by impaired intracellular lipid transport and has a tendency to accumulate the fatty acids and glycosphingolipids in a variety of neurovisceral tissues. This work includes computational tools to deciphere the mutational effect in NPC protein. The study initiated with the collection of 471 missense mutations from various databases, which were then analyzed using computational tools. The mutations (G549V, F703S, Q775P and L1244P) were said to be disease associated, altering the biophysical properties, in highly conserved regions and reduces the stability using several in silico methods and were subjected to molecular docking analysis. To analyze the ligand (Itraconazole: a small molecule of antifungal drug class, which is known to inhibit cholesterol export from lysosomes) activity Molecular docking study was performed for all the complex proteins. The average binding affinity was taken and found to be -10.76 kcal/mol (native) and -11.06 kcal/mol (Q775P was located in transmembrane region IV which impacts the sterol-sensing domain of the NPC1 protein and associated with a severe infantile neurological form). Finally, molecular dynamic simulation was performed in duplicate and trajectories were built for the backbone of the RMSD, RMSF, the number of intramolecular hydrogen bonds, the radius of gyration and the SSE percent for both the complex proteins. This work contributes to understand the effectiveness and may provide an insight on the stability of the drug with the complex variant structures.Communicated by Ramaswamy H. Sarma.

In silico investigation on the mutational analysis of BRCA1-BARD1 RING domains and its effect on nucleosome recognition and ubiquitination

The BRCA1-BARD1 complex is a crucial tumor suppressor E3 ubiquitin ligase involved in DNA double-stranded break repair. The BRCA1-BARD1 RING domains interact with UBE2D3 through the BRCA1 interface and this complex flexibly tether to the nucleosome core particle (NCP), where BRCA1 and BARD1 interacts with histone H2A and H2B of NCP. Mutations in the BRCA1-BARD1 RING domains have been linked to familial breast and ovarian cancer. Seven mutations were analyzed to understand their effect on the binding interface of protein partners and changes in conformational dynamics. Molecular dynamics simulations revealed that mutant complexes were less conformationally flexible than the wildtype complex. Protein-protein interaction profiling showed the importance of specific molecular interactions, hotspot and hub residues, and some of these were lost in the mutant complexes. Two mutations (BRCA1L51W-K65R and BARD1C53W) hindered significant interaction between protein partners and may prevent signaling for ubiquitination of histones in NCP and other cellular targets. The structural compactness and reduced significant interaction in mutant complexes may be the possible reason of preventing ubiquitination and hinder DNA repair, resulting cancer.

Exploring Prognostic Biomarkers of Acute Myeloid Leukemia to Determine Its Most Effective Drugs from the FDA-Approved List through Molecular Docking and Dynamic Simulation

Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.

In Silico Characterization and Analysis of Clinically Significant Variants of Lipase-H (LIPH Gene) Protein Associated with Hypotrichosis

Hypotrichosis is an uncommon type of alopecia (hair loss) characterized by coarse scalp hair caused by the reduced or fully terminated activity of the Lipase-H (LIPH) enzyme. LIPH gene mutations contribute to the development of irregular or non-functional proteins. Because several cellular processes, including cell maturation and proliferation, are inhibited when this enzyme is inactive, the hair follicles become structurally unreliable, undeveloped, and immature. This results in brittle hair, as well as altered hair shaft development and structure. Because of these nsSNPs, the protein's structure and/or function may be altered. Given the difficulty in discovering functional SNPs in genes associated with disease, it is possible to assess potential functional SNPs before conducting broader population investigations. As a result, in our in silico analysis, we separated potentially hazardous nsSNPs of the LIPH gene from benign representatives using a variety of sequencing and architecture-based bioinformatics approaches. Using seven prediction algorithms, 9 out of a total of 215 nsSNPs were shown to be the most likely to cause harm. In order to distinguish between potentially harmful and benign nsSNPs of the LIPH gene, in our in silico investigation, we employed a range of sequence- and architecture-based bioinformatics techniques. Three nsSNPs (W108R, C246S, and H248N) were chosen as potentially harmful. The present findings will likely be helpful in future large population-based studies, as well as in drug discovery, particularly in the creation of personalized medicine, since this study provides an initial thorough investigation of the functional nsSNPs of LIPH.

New insights on the catalytic center of proteins from peptidylprolyl isomerase group based on the FOD-M model

Generating the structure of the hydrophobic core is based on the orientation of hydrophobic residues towards the central part of the protein molecule with the simultaneous exposure of polar residues. Such a course of the protein folding process takes place with the active participation of the polar water environment. While the self-assembly process leading to the formation of micelles concerns freely moving bi-polar molecules, bipolar amino acids in polypeptide chain have limited mobility due to the covalent bonds. Therefore, proteins form a more or less perfect micelle-like structure. The criterion is the hydrophobicity distribution, which to a greater or lesser extent reproduces the distribution expressed by the 3D Gaussian function on the protein body. The vast majority of proteins must ensure solubility, so a certain part of it-as it is expected-should reproduce the structuring of micelles. The biological activity of proteins is encoded in the part that does not reproduce the micelle-like system. The location and quantitative assessment of the contribution of orderliness to disorder is of critical importance for the determination of biological activity. The form of maladjustment to the 3D Gauss function may be varied-hence the obtained high diversity of specific interactions with strictly defined molecules: ligands or substrates. The correctness of this interpretation was verified on the basis of the group of enzymes Peptidylprolyl isomerase-E.C.5.2.1.8. In proteins representing this class of enzymes, zones responsible for solubility-micelle-like hydrophobicity system-the location and specificity of the incompatible part in which the specific activity of the enzyme is located and coded were identified. The present study showed that the enzymes of the discussed group show two different schemes of the structure of catalytic center (taking into account the status as defined by the fuzzy oil drop model).

Conformational entropy of hyaluronic acid contributes to taste enhancement

Natural taste/flavor enhancers are essential ingredients that could potentially address condiments overconsumption. For the first time, we report that hyaluronic acid (HA) could modulate taste perception, governed by the dynamic interactions among taste compounds, mucin, and HA. Various conformations of HA impact taste perception. The high molecular weight (Mw) of 1090 kDa HA inhibits the sense of taste due to its increased viscosity, which hinders the penetration of Na⁺ into the mucin layer. HA with low and medium Mw (100 kDa, 400 kDa) could enhance taste perception. Isothermal titration calorimetry analysis confirms the stronger binding between mucin and HA. The intensity of their interaction increases as the Mw of HA increases from 8 kDa to 400 kDa. Quartz crystal microbalance with dissipation characterization further indicates that the rigid conformation of 100 kDa HA facilitates the binding of Na⁺ with taste receptors, thereby enhancing taste perception. The flexible conformation of 400 kDa HA may conceal the taste receptor cells, reducing taste enhancement. Our work advances the understanding of conformational entropy of natural mucoadhesion and mucopenetration polymers, which lays the foundation for their potential use as taste enhancers.

Conformational dynamics of A30G α-synuclein that causes familial Parkinson disease

The first gene shown to be responsible for autosomal-dominant Parkinson's disease (PD) is the SNCA gene, which encodes for alpha synuclein (α-Syn). Recently, a novel heterozygous A30G mutation of the SNCA gene associated with familial PD has been reported. However, little research has been done on how the A30G mutation affects the structure of α-Syn. So, using atomistic molecular dynamics (MD) simulation, we demonstrate here the key structural characteristics of A30G α-Syn in the free monomer form and membrane associated state. From the MD trajectory analysis, the structure of A30G α-Syn was noticed to exhibit rapid conformational change, increase in backbone flexibility near the site of mutation and decrease in α-helical propensity. The typical torsion angles in residues (Val26 and Glu28) near the mutation site were observed to deviate significantly in A30G α-Syn. In the case of membrane bound A30G α-Syn, the regions that were submerged in the lipid bilayer (N-helix (3-37) and turn region (38-44)) found to contain higher helical content than the elevated region above the lipid surface. The bending angle in the helix-N and helix-C regions were noticed to be relatively higher in the free form of A30G α-Syn (38.50) than in the membrane bound form (370). The A30G mutation in α-Syn was predicted to have an impact on the stability and function of the protein based on ΔΔG values obtained from the online servers. Our results demonstrate that the A30G mutation in α-Syn altered the protein's α-helical structure and slightly altered the membrane binding.Communicated by Ramaswamy H. Sarma.

In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of Proteins

RAD genes, known as double-strand break repair proteins, play a major role in maintaining the genomic integrity of a cell by carrying out essential DNA repair functions via double-strand break repair pathways. Mutations in the RAD class of proteins show high susceptibility to breast and ovarian cancers; however, adequate research on the mutations identified in these genes has not been extensively reported for their deleterious effects. Changes in the folding pattern of RAD proteins play an important role in protein-protein interactions and also functions. Missense mutations identified from four cancer databases, cBioPortal, COSMIC, ClinVar, and gnomAD, cause aberrant conformations, which may lead to faulty DNA repair mechanisms. It is therefore necessary to evaluate the effects of pathogenic mutations of RAD proteins and their subsequent role in breast and ovarian cancers. In this study, we have used eight computational prediction servers to analyze pathogenic mutations and understand their effects on the protein structure and function. A total of 5122 missense mutations were identified from four different cancer databases, of which 1165 were predicted to be pathogenic using at least five pathogenicity prediction servers. These mutations were characterized as high-risk mutations based on their location in the conserved domains and subsequently subjected to structural stability characterization. The mutations included in the present study were selected from clinically relevant mutants in breast cancer pedigrees. Comparative folding patterns and intra-atomic interaction results showed alterations in the structural behavior of RAD proteins, specifically RAD51C triggered by mutations G125V and L138F and RAD51D triggered by mutations S207L and E233G.

Insights into the binding mechanism between α-TOH and CYP4F2: A homology modeling, molecular docking, and molecular dynamics simulation study

α-Tocopherol (α-TOH) is a potent antioxidant. The concentrations of α-TOH in plasma are closely related to human health. α-TOH can be regulated by the metabolism of cytochrome P450 4F2 (CYP4F2). However, the atomic-level basis for this regulation process remains elusive. Here, we successfully constructed the structure of CYP4F2 by homology modeling and obtained the α-TOH-CYP4F2 complex models using molecular docking. Three parallel 500 ns molecular dynamics simulations were performed on each complex model to investigate the details of the interaction between α-TOH and CYP4F2. MM-GBSA method combined with principal component analysis shows that 8 key residues establish a hydrophobic cavity stabilizing α-TOH in the pocket of CYP4F2 and S423 forms an important hydrogen bond with α-TOH anchoring α-TOH in the favorable position for ω-hydroxylation. Based on our simulation results and the experimental facts, we designed mutation simulation experiments to clarify the important role of two key residues (S423 and V433) in the binding of α-TOH with CYP4F2. The results show that the mutations directly or indirectly change the binding mode of α-TOH and decrease its binding affinity with CYP4F2, which is unfavorable for ω-hydroxylation. Our results could enrich the information on structure-function relationships of CYP4F2 and provide valuable insights into the regulatory mechanism of CYP4F2 on the metabolism of α-TOH.

Lead modification via computational studies: Synthesis of pyrazole-containing β-amino carbonyls for the treatment of type 2 diabetes

This article describes studies on the design, synthesis, and biological evaluation of pyrazole-containing β-amino carbonyl compounds (5a-5q) as DPP-4 inhibitors and anti-diabetic agents. In contrast, mannich reactions went smoothly with bismuth nitrate (Bi (NO₃ )₃ ) catalyst in the presence of ethanol and produced pyrazole-containing β-amino carbonyl compounds in good yield. Molecular docking studies of designed derivatives with DPP-4 enzyme (PDB: 2OLE), compounds 5d, 5h, 5j, and 5k showed excellent interaction. 3D QSAR and pharmacophoric model studies were also carried out. ADMET parameters, pharmacokinetic properties, and in vivo toxicity studies further confirmed that all the designed compounds were found to have good bioavailability and were less toxic. Further, these compounds were evaluated as enzyme-based in vitro DPP-4 inhibitory activity, and 5d, 5h, 5i, 5j, and 5k exhibited IC₅₀ toward DPP-4 enzyme of 10.52, 10.41, 5.55, 4.16, and 7.5 nM, respectively. The most potent compound, 5j, was further selected for in vivo anti-diabetic activity using an STZ-induced diabetic mice model, and 5j showed a significant diabetic control effect.

Elucidating activation and deactivation dynamics of VEGFR-2 transmembrane domain with coarse-grained molecular dynamics simulations

The vascular endothelial growth factor receptor 2 (VEGFR-2) is a member of receptor tyrosine kinases (RTKs) and is a dimeric membrane protein that functions as a primary regulator of angiogenesis. As is usual with RTKs, spatial alignment of its transmembrane domain (TMD) is essential toward VEGFR-2 activation. Experimentally, the helix rotations within TMD around their own helical axes are known to participate importantly toward the activation process in VEGFR-2, but the detailed dynamics of the interconversion between the active and inactive TMD forms have not been clearly elucidated at the molecular level. Here, we attempt to elucidate the process by using coarse grained (CG) molecular dynamics (MD) simulations. We observe that inactive dimeric TMD in separation is structurally stable over tens of microseconds, suggesting that TMD itself is passive and does not allow spontaneous signaling of VEGFR-2. By starting from the active conformation, we reveal the mechanism of TMD inactivation through analyzing the CG MD trajectories. We observe that interconversions between a left-handed overlay and a right-handed one are essential for the process of going from an active TMD structure to the inactive form. In addition, our simulations find that the helices can rotate properly when the overlaying structure of the helices interconverts and when the crossing angle of the two helices changes by larger than ~40 degrees. As the activation right after the ligand attachment on VEGFR-2 will take place in the reverse manner of this inactivation process, these structural aspects will also appear importantly for the activation process. The rather large change in helix configuration for activation also explains why VEGFR-2 rarely self-activate and how the activating ligand structurally drive the whole VEGFR-2. This mechanism of TMD activation / inactivation within VEGFR-2 may help in further understanding the overall activation processes of other RTKs.

Molecular dynamics simulations reveal the effect of mutations in the RING domains of BRCA1-BARD1 complex and its relevance to the prognosis of breast cancer

The N-terminal RING-RING domain of BRCA1-BARD1 is an E3 ubiquitin ligase complex that plays a critical role in tumor suppression through DNA double stranded repair mechanism. Mutations in the BRCA1-BARD1 heterodimer RING domains were found to have an association with breast and ovarian cancer by a way of hampering the E3 ubiquitin ligase activity. Herein, the molecular mechanism of interaction, conformational change due to the specific mutations on the BRCA1-BARD1 complex at atomic level has been examined by employing molecular modeling techniques. Sixteen mutations have been selected for the study. Molecular dynamics simulation results reveal that the mutant complexes have more local perturbation with a high residual fluctuation in the zinc binding sites and central helix. A few of the BRCA1 (V11A, I21V, I42V, R71G, I31M and L51W) mutants have been experimentally identified that do not impair E3 ligase activity, display an enhanced number of H-bonds and non-bonded contacts at the interacting interface as revealed by MD simulation. The mutation of BRCA1 (C61G, C64Y, C39Y and C24R) and BARD1 (C53W, C71Y and C83R) zinc binding residues displayed a smaller number of significant H-bonds, other interactions and also loss of some of the hotspot residues. Additionally, most of the mutant complexes display relatively lower electrostatic energy, H-bonding and total stabilizing energy as compared to wild-type. The current study attempts to unravel the role of BRCA1-BARD1 mutations and delineates the structural and conformational dynamics in the progression of breast cancer.Communicated by Ramaswamy H. Sarma.

Molecular interaction of a putative inhibitor with bacterial SHV, an enzyme associated with antibiotic resistance

Tackling the ever-looming threat of antibiotic resistance remains a challenge for clinicians and microbiologists across the globe. Sulfhydryl variable (SHV) is a known bacterial enzyme associated with antibiotic resistance. The SHV enzyme has many variants. The present article describes identification and molecular interaction of a putative inhibitor with the bacterial SHV enzyme as a step towards novel antibacterial drug discovery. The MCULE-platform was used for screening a collection of 5 000 000 ligand molecules to evaluate their binding potential to the bacterial SHV-1 enzyme. Estimation of pharmacokinetic features was realized with the aid of the 'SWISS ADME' tool. Toxicity-checks were also performed. The docked complex of 'the top screened out ligand' and 'the bacterial SHV-1 protein' was subjected to molecular dynamics simulation of 101 ns. The obtained ligand molecule, 1,1'-(4H,8H-Bis[1,2,5]oxadiazolo[3,4-b:3',4'-e]pyrazine-4,8-diyl)diethanone, displayed the most favourable binding interactions with bacterial SHV-1. A total of 15 amino acid residues were found to hold the ligand in the binding site of SHV-1. Noticeably, 12 of the 15 residues were found as common to the binding residues of the reference (PDB ID: 4ZAM). The RMSD values plotted against the simulation time showed that nearby 11 ns, equilibrium was reached and, thenceforth, the 'SHV-1-Top ligand' complex remained typically stable. Starting from around 11 ns and straight to 101 ns, the backbone RMSD fluctuations were found to be confined inside a range of 1.0-1.6 Å. The ligand, 1,1'-(4H,8H-Bis[1,2,5]oxadiazolo[3,4-b:3',4'-e]pyrazine-4,8-diyl)diethanone, satisfied ADMET criteria. Furthermore, the practicability of the described 'SHV-1-Top ligand' complex was reinforced by a comprehensive molecular dynamics simulation of 101 ns. This ligand hence can be considered a promising lead for antibiotic design against SHV-1 producing resistant bacteria, and thus warrants wet laboratory evaluation.

Computational Design of Plant-Based Antistress Agents Targeting Nociceptin Receptor

Stress is the body's reaction to the challenges it faces, and it produces a multitude of chemical molecules known as stressors as a result of these reactions. It's also a misalignment of the sympathetic and parasympathetic nervous systems causing changes in a variety of physiological reactions and perhaps leading to stress disorders. The reduction in neurotransmitter & neurohormonal hormones is mainly governed by the nociceptin receptor as G-protein coupled receptor and increased the level of reactive oxygen species. Various synthetic medicines that target nociceptin receptors were utilized to reduce the effects of stress but they come up with a variety of side effects. Because of the widespread utilization and renewed interest in medicinal herbal plants considered to be alternative antistress therapy. Our present work is an approach to decipher the molecular nature of novel herbal leads by targeting nociceptin receptor, under which herbal compounds were screened and validated through in-silico methods. Among screened leads, withanolide-B showed stable association in the active site of the nociceptin receptor as an antistress agent with no side effects. Furthermore, the selected lead was also evaluated for stability by molecular dynamic stimulation as well as for pharmacokinetics and toxicity profile. It has been concluded stable conformation of withanolide-B without presence of any major toxic effects. As a result, the in silico molecular docking technique is a highly successful method for selecting a prospective herbal lead molecule with respect to a specific target, and future research can pave the way for further exploration in the drug development field.

The Recurrent-Specific Regulation Network of Prognostic Stemness-Related Signatures in Low-Grade Glioma

Gliomas including astrocytomas, oligodendrogliomas, mixed oligoastrocytic, and mixed glioneuronal tumors are an important group of brain tumors. Based on the 2016 WHO classification for tumors in the central nervous system, gliomas were classified into four grades, from I to IV, and brain lower grade glioma (LGG) consists of grade II and grade III. Patients with LGG may undergo recurrence, which makes clinical treatment tough. Stem cell-like features of cancer cells play a key role in tumor's biological behaviors, including tumorigenesis, development, and clinical prognosis. In this article, we quantified the stemness feature of cancer cells using the mRNA stemness index (mRNAsi) and identified stemness-related key genes based on correlation with mRNAsi. Besides, hallmark gene sets and translate factors (TFs) which were highly related to stemness-related key genes were identified. Therefore, a recurrency-specific network was constructed and a potential regulation pathway was identified. Several online databases, assay for transposase-accessible chromatin using sequencing (ATAC-seq), single-cell sequencing analysis, and immunohistochemistry were utilized to validate the scientific hypothesis. Finally, we proposed that aurora kinase A (AURKA), positively regulated by Non-SMC Condensin I Complex Subunit G (NCAPG), promoted E2F target pathway in LGG, which played an important role in LGG recurrence.

In silico assessment of missense point mutations on human cathelicidin LL-37

Cathelicidin antimicrobial peptides are a diverse family of cationic amphipathic peptides with multiple activities. In humans, cathelicidin LL-37 is one of the main host defense peptides with a remarkable medical and biotechnological potential. Deregulation of LL-37 expression has been associated with inflammatory diseases. However the effects of point mutations driven by single nucleotide polymorphisms (SNPs) on LL-37 are unknown. Here we applied an array of computational tools to investigate the effects of such mutations on LL-37 structure and activity. Due to the fact that, on cathelicidins, the prodomain is more conserved than the mature peptide, the SNP effect predictions were biased and, overall, resulted in neutral effects; and due to the slight changes in physicochemical properties, the antimicrobial predictions indicated the maintenance of such activity. Nonetheless, R07P, R07W, R29Q, R29W mutations reduced the peptide net charge, which in turn could result in less active LL-37 variants. Molecular dynamics data indicated that R07Q and N30Y mutations altered the LL-37 structure, leading to potential deleterious effects. In addition, the helix dipole is altered in G03A, R07P, R07W and L31P mutations, which could also alter the antimicrobial activity. Our results indicated that despite the mutations did not alter the residues from LL-37 active core, they could influence the antimicrobial activity and consequently, could be involved in inflammatory diseases.

An In silico Approach towards Finding the Cancer-Causing Mutations in Human MET Gene

Mesenchymal-epithelial transition (MET) factor is a proto-oncogene encoding tyrosine kinase receptor with hepatocyte growth factor (HGF) or scatter factor (SF). It is found on the human chromosome number 7 and regulates the diverse cellular mechanisms of the human body. The impact of mutations occurring in the MET gene is demonstrated by their detrimental effects on normal cellular functions. These mutations can change the structure and function of MET leading to different diseases such as lung cancer, neck cancer, colorectal cancer, and many other complex syndromes. Hence, the current study focused on finding deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) and their subsequent impact on the protein's structure and functions, which may contribute to the emergence of cancers. These nsSNPs were first identified utilizing computational tools like SIFT, PROVEAN, PANTHER-PSEP, PolyPhen-2, I-Mutant 2.0, and MUpro. A total of 45359 SNPs of MET gene were accumulated from the database of dbSNP, and among them, 1306 SNPs were identified as non-synonymous or missense variants. Out of all 1306 nsSNPs, 18 were found to be the most deleterious. Moreover, these nsSNPs exhibited substantial effects on structure, binding affinity with ligand, phylogenetic conservation, secondary structure, and post-translational modification sites of MET, which were evaluated using MutPred2, RaptorX, ConSurf, PSIPRED, and MusiteDeep, respectively. Also, these deleterious nsSNPs were accompanied by changes in properties of MET like residue charge, size, and hydrophobicity. These findings along with the docking results are indicating the potency of the identified SNPs to alter the structure and function of the protein, which may lead to the development of cancers. Nonetheless, Genome-wide association study (GWAS) studies and experimental research are required to confirm the analysis of these nsSNPs.

Molecular simulation unravels the amyloidogenic misfolding of nascent ApoA1 protein, driven by deleterious point mutations occurring in between 170-178 hotspot region

Protein ApoA1 is extensively studied for its role in lipid metabolism. Its seedy dark side of amyloid formulation remains relatively understudied yet. Due to genetic mutations, the protein pathologically misshapes into its amyloid form that gets accumulated in various organs, including the heart. To contrive effective therapeutics against this debilitating congenital disorder, it is imperative to comprehend the structural ramifications induced by mutations in APoA1's dynamic conformation. Till now, several point mutations have been implicated in ApoA1's amyloidosis, although only a handful has been examined considerably. Especially, the single nucleotide polymorphisms (SNPs) that occur in-between 170-178 mutation hotspot site of APoA1 needs to be investigated, since most of them are culpable of amyloid deposition in the heart. To that effect, in the present study, we have computationally quantified and studied the ApoA1's biomolecular modifications fostered by SNPs in the 170-178 mutation hotspot. Findings from discrete molecular dynamics simulation studies indicate that the SNPs have noticeably steered the ApoA1's behaviour from its native structural dynamics. Analysis of protein's secondary structural changes exhibits a considerable change upon mutations. Further, subjecting the protein structures to simulated thermal denaturation shows increased resistance to denaturation among mutants when compared to native. Further, normal mode analysis of protein's dynamic motion also shows discrepancy in its dynamic structural change upon SNP. These structural digressions induced by SNPs can very well be the biomolecular incendiary that drives ApoA1 into its amyloidogenesis. And, understanding these structural modifications initiates a better understanding of SNP's amyloidogenic pathology on APoA1.Communicated by Ramaswamy H. Sarma.

Unraveling the Structural Changes in the DNA-Binding Region of Tumor Protein p53 (TP53) upon Hotspot Mutation p53 Arg248 by Comparative Computational Approach

The vital tissue homeostasis regulator p53 forms a tetramer when it binds to DNA and regulates the genes that mediate essential biological processes such as cell-cycle arrest, senescence, DNA repair, and apoptosis. Missense mutations in the core DNA-binding domain (109-292) simultaneously cause the loss of p53 tumor suppressor function and accumulation of the mutant p53 proteins that are carcinogenic. The most common p53 hotspot mutation at codon 248 in the DNA-binding region, where arginine (R) is substituted by tryptophan (W), glycine (G), leucine (L), proline (P), and glutamine (Q), is reported in various cancers. However, it is unclear how the p53 Arg248 mutation with distinct amino acid substitution affects the structure, function, and DNA binding affinity. Here, we characterized the pathogenicity and protein stability of p53 hotspot mutations at codon 248 using computational tools PredictSNP, Align GVGD, HOPE, ConSurf, and iStable. We found R248W, R248G, and R248P mutations highly deleterious and destabilizing. Further, we subjected all five R248 mutant-p53-DNA and wt-p53-DNA complexes to molecular dynamics simulation to investigate the structural stability and DNA binding affinity. From the MD simulation analysis, we observed increased RMSD, RMSF, and Rg values and decreased protein-DNA intermolecular hydrogen bonds in the R248-p53-DNA than the wt-p53-DNA complexes. Likewise, due to high SASA values, we observed the shrinkage of proteins in R248W, R248G, and R248P mutant-p53-DNA complexes. Compared to other mutant p53-DNA complexes, the R248W, R248G, and R248P mutant-p53-DNA complexes showed more structural alteration. MM-PBSA analysis showed decreased binding energies with DNA in all five R248-p53-DNA mutants than the wt-p53-DNA complexes. Henceforth, we conclude that the amino acid substitution of Arginine with the other five amino acids at codon 248 reduces the p53 protein's affinity for DNA and may disrupt cell division, resulting in a gain of p53 function. The proposed study influences the development of rationally designed molecular-targeted treatments that improve p53-based therapeutic outcomes in cancer.

Application of Nano-SiO2 Reinforced Urea-Formaldehyde Resin and Molecular Dynamics Simulation Study

Nano-SiO₂ is a typical modifier used for urea-formaldehyde (UF) resins to balance the reduced formaldehyde content and maintain bond strength. However, the microstructure of UF resin and the interaction between UF resin and nano-SiO₂ are microscopic phenomena; it is difficult to observe and study its intrinsic mechanism in traditional experimental tests. In this work, the enhancement mechanism was explored by molecular dynamics simulations combined with an experiment of the effect of nano-SiO₂ additions on UF resin. The results showed that the best performance enhancement of UF resin was achieved when the addition of nano-SiO₂ was 3 wt%. The effects caused by different additions of nano-SiO₂ were compared and analyzed by molecular dynamics simulations in terms of free volume fraction, the radius of gyration, and mechanical properties, and the results were in agreement with the experimental values. Meanwhile, the changes in hydrogen bonding and radial distribution functions in these systems were counted to explore the interaction between nano-SiO₂ and UF resin. The properties of the UF resin were enhanced mainly through the large number of different forms of hydrogen bonds with nano-SiO₂, with the strongest hydrogen bond occurring between H_(SiO2)… O = _(PHMU).

Point mutation consideration in CcO protein of the electron transfer chain by MD simulation

In Acidithiobacillus ferrooxidans, proteins such as CcO are present in the electron transport pathway. They cause ferrous iron oxidation to ferric leading to the electron release. CcO has two copper atoms (CuA, CuB). CuA plays an important role in electron transfer. According to previous studies, the conversion of histidine to methionine in a similar protein increased the redox potential and was directly related to the number of electrons received. Also, the binding of methionine 233 to CuA and CuB in the wild protein structure is the reason for the selection of the H230 M mutation in the CuA site. Then, wild-type and H230 M mutant were simulated in the presence of a bilayer membrane POPC using the gromacs version 5.1.4. The changes performed in the H230 M mutant were evaluated by MD simulations analyzes. CcO and CoxA proteins are the last two proteins in the chain and were docked by the PatchDock server. By H230 M mutation, the connection between CuA and M230 weakens. The M230 moves further away from CuA, resulting become more flexible. Therefore, the Methionine gets closer to E149 of the CoxA leading to the higher stability of the CcO/CoxA complex. The results of RMSF analysis at the mutation point showed a significant increase. This indicates more flexibility in the active site. And leads to an increase in E₀ in the mutation point, an increase in the rate of electron reception, and an improved bioleaching process.

In silico investigation of nonsynonymous single nucleotide polymorphisms in BCL2 apoptosis regulator gene to design novel protein-based drugs against cancer

BCL2 apoptosis regulator gene encodes Bcl-2 pro-survival protein, which plays an important role to evade apoptosis in various cancers. Moreover, single nucleotide polymorphisms (SNPs) in the BCL2 gene can be nonsynonymous (nsSNPs), which might affect the protein stability and probably its function. Therefore, we implement cutting-edge computational techniques based on the Spherical Polar Fourier and Monte-Carlo algorithms to investigate the impact of these SNPs on the B cell lymphoma-2 (Bcl-2) stability and therapeutic potential of protein-based molecules to inhibit this protein. As a result, we identified two nsSNPs (Q118R and R129C) to be deleterious and highly conserved, having a negative effect on protein stability. Additionally, molecular docking and molecular dynamics simulations confirmed the decreased binding affinity of mutated Bcl-2 variants to bind three-helix bundle protein inhibitor as these mutations occurred in the protein-protein binding site. Overall, this computational approach investigating nsSNPs provides a useful basis for designing novel molecules to inhibit Bcl-2 pro-survival pathway in malignant cells.

Alignment of major-groove hydrogen bond arrays uncovers shared information between different DNA sequences that bind the same protein

Protein-DNA binding is of a great interest due to its importance in many biological processes. Previous studies have presented many factors responsible for the recognition and specificity, but understanding the minimal informational requirements for proteins that bind to multiple DNA-sites is still an understudied area of bioinformatics. Here we focus on the hydrogen bonds displayed by the target DNA in the major groove that take part in protein-binding. We show that analyses focused on the base pair identity may overlook key hydrogen bonds. We have developed an algorithm that converts a nucleotide sequence into an array of hydrogen bond donors and acceptors and methyl groups. It then aligns these non-covalent interaction arrays to identify what information is being maintained among multiple DNA sequences. For three different DNA-binding proteins, Lactose repressor, controller protein and λ-CI repressor, we uncovered the minimal pattern of hydrogen bonds that are common amongst all the binding sequences. Notably in the three proteins, key interacting hydrogen bonds are maintained despite nucleobase mutations in the corresponding binding sites. We believe this work will be useful for developing new DNA binding proteins and shed new light on evolutionary relationships.

Relationship between CRP gene polymorphisms and ischemic stroke risk: A systematic review and meta-analysis

Ischemic stroke (IS), usually caused due to an abrupt blockage of an artery, is the leading cause of disability and the second leading cause of death worldwide. The association of the C-reactive protein (CRP) gene (s3093059 T/C and rs1205 C/T) polymorphisms and IS susceptibility has been widely studied, but the results remain inconsistent. Our study aimed to assess the association between CRP gene (s3093059 T/C and rs1205 C/T) polymorphisms and IS risk. PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WanFang databases were searched up to April 2022 to identify eligible studies. The Newcastle-Ottawa scale (NOS) score was calculated to assess study quality. The odd ratios (ORs) with a 95% confidence interval (CI) were calculated to assess the association between CRP gene (rs3093059 T/C and rs1205 C/T) polymorphisms and IS risk. Eighteen case–control studies with 6339 cases and 29580 controls were identified. We found that CRP (s3093059 T/C and rs1205 C/T) polymorphism was not significantly associated with the risk of IS in any genetic model (recessive model: OR 1.00, 95% CI 0.79–1.26; OR 1.06, 95% CI 0.90–1.25). When stratified analysis by country, genotype method, source of controls, and NOS score, still no statistically significant association was found. Our study indicated that the CRP (rs3093059 T/C and rs1205 C/T) polymorphisms were not associated with the susceptibility to IS.

Virtual Screening and Network Pharmacology-Based Study to Explore the Pharmacological Mechanism of Clerodendrum Species for Anticancer Treatment

BACKGROUND

Cancer is a second leading cause of death in the world, killing approximately 3500 per million people each year. Therefore, the drugs with multitarget pharmacology based on biological networks are crucial to investigate the molecular mechanisms of cancer drugs and repurpose the existing drugs to reduce adverse effects. Clerodendrum is a diversified genus with a wide range of economic and pharmacological properties. Limited studies were conducted on the genus's putative anticancer properties and the mechanisms of action based on biological networks remains unknown. This study was aimed to construct the possible compound/target/pathway biological networks for anticancer effect of Clerodendrum sp. using docking weighted network pharmacological approach and to investigate its potential mechanism of action.

METHODS

A total of 194 natural Clerodendrum sp. Compounds were retrieved from public databases and screened using eight molecular descriptors. The cancer-associated gene targets were retrieved from databases and the function of the target genes with related pathways were examined. Cytoscape v3.7.2 was used to build three major networks: compound-target network, target-target pathway network, and compound-target-pathway network.

RESULTS

Our finding indicates that the anticancer activity of Clerodendrum sp. involves 6 compounds, 9 targets, and 63 signaling pathways, resulting in multicompounds, multitargets, and multipathways networks. Additionally, molecular dynamics (MD) simulations were used to estimate the binding affinity of the best hit protein-ligand complexes. Conclusion. This study suggests the potential anticancer activity of Clerodendrum sp. which could further contribute to scavenger novel compounds for the development of new alternative anticancer drugs.

Potential of paracetamol for reproductive disruption: Molecular interaction, dynamics and MM-PBSA based In-silico assessment

Paracetamol is generally recommended for pain and fever. However, as per experimental and epidemiological data, widespread and irrational or long-term use of paracetamol may be harmful to human endocrine homeostasis, especially during pregnancy. Some researchers suggest that prenatal exposure to paracetamol might alter foetal development and also enhance the risk of reproductive disorders. An imbalance in the levels of these hormones may play a significant role in the emergence of various diseases, including infertility. Therefore, in this study, the interaction mechanism of paracetamol with reproductive hormone receptors was investigated by molecular docking, molecular dynamics (MD) simulations, and poisson-Boltzmann surface area (MM-PBSA) for assessing paracetamol's potency to disrupt reproductive hormones. The results indicate that paracetamol has the ability to interact with reproductive hormone receptors (estrogen 1XP9; 1QKM with binding energy of -5.61 kcal/mol; -5.77 kcal/mol; androgen 5CJ6 -5.63 kcal/mol; and progesterone 4OAR-5.60 kcal/mol) by hydrogen bonds as well as hydrophobic and van der Waals interactions to maintain its stability. In addition, the results of the MD simulations and MM-PBSA confirm that paracetamol and reproductive receptor complexes are stable. This research provides a molecular and atomic level understanding of how paracetamols disrupt reproductive hormone synthesis. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), Radius of Gyration and hydrogen bonding exhibited that paracetamol mimic at various attribute to bisphenol and native ligand.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis

Methods

Gene expression profiles of GSE13904, GSE26378, GSE26440, GSE65682, and GSE69528 were obtained from the National Center for Biotechnology Information (NCBI). The differentially expressed genes (DEGs) were searched using limma software package. Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs and screen hub genes.

Results

A total of 108 DEGs were identified in the study, of which 67 were upregulated and 41 were downregulated. 15 superlative diagnostic biomarkers (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) for sepsis were identified by bioinformatics analysis.

Conclusion

15 hub genes (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) have been elucidated in this study, and these biomarkers may be helpful in the diagnosis and therapy of patients with sepsis.

Characterizing (un)binding mechanism of USP7 inhibitors to unravel the cause of enhanced binding potencies at allosteric checkpoint

The ability to predict the intricate mechanistic behavior of ligands and associated structural determinants during protein-ligand (un)binding is of great practical importance in drug discovery. Ubiquitin specific protease-7 (USP7) is a newly emerging attractive cancer therapeutic target with bound allosteric inhibitors. However, none of the inhibitors have reached clinical trials, allowing opportunities to examine every aspect of allosteric modulation. The crystallographic insights reveal that these inhibitors have common properties such as chemical scaffolds, binding site and interaction fingerprinting. However, they still possess a broader range of binding potencies, ranging from 22 nM to 1,300 nM. Hence, it becomes more critical to decipher the structural determinants guiding the enhanced binding potency of the inhibitors. In this regard, we elucidated the atomic-level insights from both interacting partners, that is, protein-ligand perspective, and established the structure-activity link between USP7 inhibitors by using classical and advanced molecular dynamics simulations combined with linear interaction energy and molecular mechanics-Poisson Boltzmann surface area. We revealed the inhibitor potency differences by examining the contributions of chemical moieties and USP7 residues, the involvement of water-mediated interactions, and the thermodynamic landscape alterations. Additionally, the dissociation profiles aided in the establishment of a correlation between experimental potencies and structural determinants. Our study demonstrates the critical role of blocking loop 1 in allosteric inhibition and enhanced binding affinity. Comprehensively, our findings provide a constructive expansion of experimental outcomes and show the basis for varying binding potency using in-silico approaches. We expect this atomistic approach to be useful for effective drug design.

Therapeutic Mechanism and Key Active Ingredients of Shenfu Injection in Sepsis: A Network Pharmacology and Molecular Docking Approach

At present, although the early treatment of sepsis is advocated, the treatment effect of sepsis is unsatisfactory, and the mortality rate remains high. Shenfu injection (SFI) has been used to treat sepsis with good clinical efficacy. Based on network pharmacology, this study adopted a new research strategy to identify the potential therapeutic targets and key active ingredients of SFI for sepsis from the perspective of the pathophysiology of sepsis. This analysis identified 28 active ingredients of SFI based on UHPLC-QQQ MS, including 18 ginsenosides and 10 aconite alkaloids. 59 targets were associated with the glycocalyx and sepsis pathways. Based on the number of targets related to the pathophysiological process of sepsis, we identified songorine, ginsenoside Rf, ginsenoside Re, and karacoline as the key active ingredients of SFI for the treatment of sepsis. According to the cluster analysis of MCODE and the validation on the GEO dataset, LGALS3, BCHE, AKT1, and IL2 were identified as the core targets. This study further explored the therapeutic mechanism and the key active ingredients of SFI in sepsis and provided candidate compounds for drug development.

To probe the activation mechanism of the Delta opioid receptor by an agonist ADL5859 started from inactive conformation using molecular dynamic simulations

The δ-opioid receptor (DOR) is a critical pharmaceutical target for pain management. Although the high-resolution crystal structures of the DOR with both agonist and antagonist have recently been solved, the activation mechanism remains to be elusive. In this study, a DOR agonist ADL5859 was docked to the inactive DOR and multiple microsecond molecular dynamic (MD) simulations were conducted to probe the activation mechanism. While the receptor with the crystal ligand (i.e. antagonist naltrindole) maintained the inactive conformation in all three independent simulations, the receptor with ADL5859 was adopting toward the active conformation in three out of six independent simulations. Major conformational differences were located on transmembrane (TM) 5 and 6, as well as intracellular loop 3. Compared to naltrindole, ADL5859 exhibited high conformational flexibility and strong interaction with the transmission switch. The putative key residues (W274, D95, V267, L139, V263, M142, T260, R146, R258 and others) involving in the activation pathway were identified through the conventional molecular switch analysis and a pairwise distance analysis, which provides a short list for experimental mutagenesis study. These insights will facilitate further development of therapeutic agents targeting the DOR.Communicated by Ramaswamy H. Sarma.

Network Pharmacology and Molecular Docking on the Molecular Mechanism of Jiawei-Huang Lian-Gan Jiang Decoction in the Treatment of Colorectal Adenomas

Purpose

Jiawei-Huang Lian-Gan Jiang decoction (JWHLGJD) was developed to treat and prevent the patients with colorectal adenomas (CRA) in China. This study is aimed to discover JWHLGJD's active compounds and demonstrate mechanisms of JWHLGJD against CRA through network pharmacology and molecular docking techniques.

Methods

All the components of JWHLGJD were retrieved from the pharmacology database of Traditional Chinese Medicine Systems Pharmacology (TCMSP). The GeneCards database, the Online Mendelian Inheritance in Man database (OMIM), the DrugBank database, and PharmGKB were used to obtain the genes matching the targets. Cytoscape created the compound-target network. The network of target protein-protein interactions (PPI) was constructed using the STRING database. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways involved in the targets were analyzed by using the DAVID database. Cytoscape created the component-target-pathway (C-T-P) network. AutoDock Vina software was used to verify the molecular docking of JWHLGJD components and key targets. Core genes linked with survival and tumor microenvironment were analyzed through the Kaplan–Meier plotter and TIMER 2.0 databases, respectively.

Results

Compound-target network mainly contained 38 compounds and 130 targets of the JWHLGJD associated with CRA. TP53, MAPK1, JUN, HSP90AA1, and AKT1 were identified as core targets by the PPI network. KEGG pathway shows that the pathways in cancer, lipids, and atherosclerosis, PI3K-Akt signaling pathway and MAPK signaling pathway, are the most relevant pathways to CRA. The C-T-P network suggests that the active component in JWHLGJD is capable of regulating target genes of these related pathways. The results of molecular docking showed that berberine and stigmasterol were the top two compounds of JWHLGJD, which had high affinity with TP53 and MAPK1, respectively. And, MAPK1 exerted a more significant effect on the prognosis of adenocarcinoma, for it was highly associated with various immune cells.

Conclusion

Findings in this study provided light on JWHLGJD's active components, prospective targets, and molecular mechanism. It also gave a potential way to uncovering the scientific underpinning and therapeutic mechanism of traditional Chinese medicine (TCM) formulas.

Mechanism of Danhong Injection in the Treatment of Arrhythmia Based on Network Pharmacology, Molecular Docking, and In Vitro Experiments

Background. Danhong injection (DHI) is widely used in the treatment of cardiovascular and cerebrovascular diseases, and its safety and effectiveness have been widely recognized and applied in China. However, the potential molecular mechanism of action for the treatment of arrhythmia is not fully understood. Aim. In this study, through network pharmacology and in vitro cell experiments, we explored the active compounds of DHI for the treatment of arrhythmia and predicted the potential targets of the drug to investigate its mechanism of action. Materials and Methods. First, the potential therapeutic effect of DHI on arrhythmia was investigated in an in vitro arrhythmia model using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), in which calcium transients were recorded to evaluate the status of arrhythmia. Next, the active compounds and key targets in the treatment of arrhythmia were identified through network pharmacology and molecular docking, and the key signaling pathways related to the treatment of arrhythmia were analyzed. Furthermore, we used real-time quantitative reverse transcription PCR (qRT–PCR) to verify the expression levels of key genes. Results. Early afterdepolarizations (EADs) were observed during aconitine treatment in hiPSC-CMs, and the proarrhythmic effect of aconitine was partially rescued by DHI, indicating that the antiarrhythmic role of DHI was verified in an in vitro human cardiomyocyte model. To further dissect the underlying molecular basis of this observation, network pharmacology analysis was performed, and the results showed that there were 108 crosstargets between DHI and arrhythmia. Moreover, 30 of these targets, such as AKT1 and HMOX1, were key genes. In addition, the mRNA expression of AKT1 and HMOX1 could be regulated by DHI. Conclusion. DHI can alleviate aconitine-induced arrhythmia in an in vitro model, presumably because of its multitarget regulatory mechanism. Key genes, such as AKT1 and HMOX1, may contribute to the antiarrhythmic role of DHI in the heart.

Investigating binding mechanism of thymoquinone to human transferrin, targeting Alzheimer's disease therapy

Iron deposition in the central nervous system (CNS) is one of the causes of neurodegenerative diseases. Human transferrin (hTf) acts as an iron carrier present in the blood plasma, preventing it from contributing to redox reactions. Plant compounds and their derivatives are frequently being used in preventing or delaying Alzheimer's disease (AD). Thymoquinone (TQ), a natural product has gained popularity because of its broad therapeutic applications. TQ is one of the significant phytoconstituent of Nigella sativa. The binding of TQ to hTf was determined by spectroscopic methods and isothermal titration calorimetry. We have observed that TQ strongly binds to hTf with a binding constant (K) of 0.22 × 10⁶ M^-1 and forming a stable complex. In addition, isothermal titration calorimetry revealed the spontaneous binding of TQ with hTf. Molecular docking analysis showed key residues of the hTf that were involved in the binding to TQ. We further performed a 250 ns molecular dynamics simulation which deciphered the dynamics and stability of the hTf-TQ complex. Structure analysis suggested that the binding of TQ doesn't cause any significant alterations in the hTf structure during the course of simulation and a stable complex is formed. Altogether, we have elucidated the mechanism of binding of TQ with hTf, which can be further implicated in the development of a novel strategy for AD therapy.

The Computer Simulation of Therapy with the NMDA Antagonist in Excitotoxic Neurodegeneration in an Alzheimer's Disease-like Pathology

(1) Background: The use of uncompetitive N-methyl-D-aspartate (NMDA) receptor antagonists results in neuroprotective benefits in patients with moderate to severe Alzheimer’s disease. In this study, we demonstrated mathematical and computer modelling of the excitotoxicity phenomenon and performed virtual memantine therapy. (2) Methods: A computer simulation environment of the N-methyl-D-aspartate receptor combining biological mechanisms of channel activation by means of excessive extracellular glutamic acid concentration in three models of excitotoxicity severity. The simulation model is based on sliding register tables, where each table is associated with corresponding synaptic inputs. Modelling of the increase in extracellular glutamate concentration, through over-stimulation of NMDA receptors and exacerbation of excitotoxicity, is performed by gradually increasing the parameters of phenomenological events by the power function. Pathological models were virtually treated with 3−30 µM doses of memantine compared to controls. (3) Results: The virtual therapy results of memantine at doses of 3−30 µM in the pathological models of excitotoxicity severity show statistically significant neuroprotective benefits in AD patients with moderate severity, 1.25 (95% CI, 1.18−1.32) vs. 1.76 (95% CI, 1.71−1.80) vs. 1.53 (95% CI, 1.48−1.59), (p < 0.001), to severe, 1.32 (95% CI, 1.12−1.53) vs. 1.77 (95% CI, 1.72−1.82) vs. 1.73 (95% CI, 1.68−1.79), (p < 0.001), in the area of effects on memory. A statistically significant benefit of memantine was demonstrated for all neuronal parameters in pathological models. In the mild severity model, a statistically significant increase in frequency was obtained relative to virtual memantine treatment with a dose of 3 µM, which was 23.5 Hz (95% CI, 15.5−28.4) vs. 38.8 Hz (95% CI, 34.0−43.6), (p < 0.0001). In the intermediate excitotoxicity severity model, a statistically significant increase in frequency was obtained relative to virtual memantine therapy with a 3 µM dose of 26.0 Hz (95% CI, 15.7−36.2) vs. 39.0 Hz (95% CI, 34.2−43.8) and a 10 µM dose of 26.0 Hz (95% CI, 15.7−36.2) vs. 30.9 Hz (95% CI, 26.4−35.4), (p < 0.0001). A statistically significant increase in frequency was obtained in the advanced excitotoxicity severity model as in the medium. (4) Conclusions: The NMDA antagonist memantine causes neuroprotective benefits in patients with moderate to severe AD. One of the most important benefits of memantine is the improvement of cognitive function and beneficial effects on memory. On the other hand, memantine provides only symptomatic and temporary support for AD patients. Memantine is prescribed in the US and Europe if a patient has moderate to severe AD. Memantine has also been approved for mild to moderate AD patients. However, its very modest effect provides motivation for further research into new drugs in AD. We are the first to present a mathematical model of the NMDA receptor that allows the simulation of excitotoxicity and virtual memantine therapy.

In-silico phenotype prediction by normal mode variant analysis in TUBB4A-related disease

TUBB4A-associated disorder is a rare condition affecting the central nervous system. It displays a wide phenotypic spectrum, ranging from isolated late-onset torsion dystonia to a severe early-onset disease with developmental delay, neurological deficits, and atrophy of the basal ganglia and cerebellum, therefore complicating variant interpretation and phenotype prediction in patients carrying TUBB4A variants. We applied entropy-based normal mode analysis (NMA) to investigate genotype–phenotype correlations in TUBB4A-releated disease and to develop an in-silico approach to assist in variant interpretation and phenotype prediction in this disorder. Variants included in our analysis were those reported prior to the conclusion of data collection for this study in October 2019. All TUBB4A pathogenic missense variants reported in ClinVar and Pubmed, for which associated clinical information was available, and all benign/likely benign TUBB4A missense variants reported in ClinVar, were included in the analysis. Pathogenic variants were divided into five phenotypic subgroups. In-silico point mutagenesis in the wild-type modeled protein structure was performed for each variant. Wild-type and mutated structures were analyzed by coarse-grained NMA to quantify protein stability as entropy difference value (ΔG) for each variant. Pairwise ΔG differences between all variant pairs in each structural cluster were calculated and clustered into dendrograms. Our search yielded 41 TUBB4A pathogenic variants in 126 patients, divided into 11 partially overlapping structural clusters across the TUBB4A protein. ΔG-based cluster analysis of the NMA results revealed a continuum of genotype–phenotype correlation across each structural cluster, as well as in transition areas of partially overlapping structural clusters. Benign/likely benign variants were integrated into the genotype–phenotype continuum as expected and were clearly separated from pathogenic variants. We conclude that our results support the incorporation of the NMA-based approach used in this study in the interpretation of variant pathogenicity and phenotype prediction in TUBB4A-related disease. Moreover, our results suggest that NMA may be of value in variant interpretation in additional monogenic conditions.

A comprehensive in silico investigation into the nsSNPs of Drd2 gene predicts significant functional consequences in dopamine signaling and pharmacotherapy

DRD2 is a neuronal cell surface protein involved in brain development and function. Variations in the Drd2 gene have clinical significance since DRD2 is a pharmacotherapeutic target for treating psychiatric disorders like ADHD and schizophrenia. Despite numerous studies on the disease association of single nucleotide polymorphisms (SNPs) in the intronic regions, investigation into the coding regions is surprisingly limited. In this study, we aimed at identifying potential functionally and pharmaco-therapeutically deleterious non-synonymous SNPs of Drd2. A wide array of bioinformatics tools was used to evaluate the impact of nsSNPs on protein structure and functionality. Out of 260 nsSNPs retrieved from the dbSNP database, initially 9 were predicted as deleterious by 15 tools. Upon further assessment of their domain association, conservation profile, homology models and inter-atomic interaction, the mutant F389V was considered as the most impactful. In-depth analysis of F389V through Molecular Docking and Dynamics Simulation revealed a decline in affinity for its native agonist dopamine and an increase in affinity for the antipsychotic drug risperidone. Remarkable alterations in binding interactions and stability of the protein-ligand complex in simulated physiological conditions were also noted. These findings will improve our understanding of the consequence of nsSNPs in disease-susceptibility and therapeutic efficacy.

Exploring nod factor receptors activation process in chickpea by bridging modelling, docking and molecular dynamics simulations

Plasma membrane-bound receptor proteins play crucial roles in the perception and further transmission of regulatory signals to modulate numerous developmental and metabolic events. Precise functioning and fine-tuning of Nod factor receptor (NFR) mediated signalling is a critical requirement for root nodule symbiosis. Here, we have identified, cloned and phylogenetically characterized chickpea NFR1 and NFR5, which are showing significant homology with other legume NFR receptors. Homology modelling and molecular dynamics simulations highlight the molecular structure of ligand binding ectodomains [EDs] and cytosolic kinase domains [KDs] of NFRs in chickpea. Our detailed structural analysis also revealed that both NFR1 and NFR5 share resemblance as well as dissimilarity in sequence, structure and substrate-binding pocket. Further, molecular docking simulations provide us adequate insights into the active site of receptors where the Nod factor (NF) binds. The outcome of this work sheds light on the binding specificity of NFs towards NFRs and thus may significantly contribute to the design of new strategies in improving root-nodule symbiosis towards meeting the agricultural demands.

Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases

Peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PPARGC1A) regulates the expression of energy metabolism's genes and mitochondrial biogenesis. The essential roles of PPARGC1A encouraged the researchers to assess the relation between metabolism-related diseases and its variants. To study Gly482Ser (+1564G/A) single-nucleotide polymorphism (SNP) after PPARGC1A modeling, we substitute Gly482 for Ser482. Stability prediction tools showed that this substitution decreases the stability of PPARGC1A or has a destabilizing effect on this protein. We then utilized molecular dynamics simulation of both the Gly482Ser variant and wild type of the PPARGC1A protein to analyze the structural changes and to reveal the conformational flexibility of the PPARGC1A protein. We observed loss flexibility in the RMSD plot of the Gly482Ser variant, which was further supported by a decrease in the SASA value in the Gly482Ser variant structure of PPARGC1A and an increase of H-bond with the increase of β-sheet and coil and decrease of turn in the DSSP plot of the Gly482Ser variant. Such alterations may significantly impact the structural conformation of the PPARGC1A protein, and it might also affect its function. It showed that the Gly482Ser variant affects the PPARGC1A structure and makes the backbone less flexible to move. In general, molecular dynamics simulation (MDS) showed more flexibility in the native PPARGC1A structure. Essential dynamics (ED) also revealed that the range of eigenvectors in the conformational space has lower extension of motion in the Gly482Ser variant compared with WT. The Gly482Ser variant also disrupts PPARGC1A interaction. Due to this single-nucleotide polymorphism in PPARGC1A, it became more rigid and might disarray the structural conformation and catalytic function of the protein and might also induce type 2 diabetes mellitus (T2DM), coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). The results obtained from this study will assist wet lab research in expanding potent treatment on T2DM.

Identification of Conformational B-cell Epitopes in Diphtheria Toxin at Varying Temperatures Using Molecular Dynamics Simulations

The changes in temperature levels can potentially affect the toxins in terms of stability and immunological properties via alteration of their structures. Diphtheria Toxin (DT) is highly considered by scientists since its mechanism of action is similar to those of most bacterial toxins, such as botulinum, tetanus, and anthrax. The protection of conformational B-cell epitopes is critically important in the process of diphtheria vaccine production. This study aimed to evaluate the conformational changes of the DT structure at three different temperature levels (27˚C, 37˚C, and 47˚C) using molecular dynamic simulations. Secondary structures were analyzed in YASARA software. According to the results, significant decreases were observed in percentages of the &beta;-sheets, turns, and the helices of the DT structure at 47˚C in comparison with those at 27˚C and 37˚C. Furthermore, the tertiary structure of the DT was compared at different temperatures using the contact map. Accordingly, the results showed that the root-mean-square deviation of the DT structure increased upon temperature rising. In addition, amino acids D68, G128, G171, C186, and K534-S535 at 27˚C and 37˚C, as well as amino acids G26, P38, S291, T267, H384, A356, and V518 at 47˚C showed higher root mean square fluctuation values. The finding demonstrated that the stability of the DT structure decreased at high temperature (47˚C). The solvent-accessible surface area diagram showed that the hydrophobicity of the DT structure increased via temperature rising, and the amino acid residues belonging to B-cell epitopes extended through increasing temperature. However, B-cell epitopes belonging to the junction region of chains A and B were only present at 37˚C. The results of this study are expected to be applicable for determining a suitable temperature level for the production process of the diphtheria vaccine.

Structural based study to identify new potential inhibitors for dual specificity tyrosine-phosphorylation- regulated kinase

Background and Objectives The Dual-specificity tyrosine-phosphorylation regulated kinase-1A (DYRK1A) a serine/threonine kinase that has freshly gained recognition as an essential drug target due to the discovery of its involvement in pathological diseases. The development of new potent inhibitors of DYRK1A would contribute to clarify the molecular mechanisms of associated diseases. It would administer a new lead compound for molecular-targeted protein, which was the primary focus of our study. Methods The library of in-house synthesized pyrrolone-fused benzosuberene (PBS) compounds was docked with DYRK1A receptor. Further, molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) estimations were conducted to confirm our docking outcomes and compared the stability of chosen complexes with the 2C3 (standard molecule) complex. Results This study reports Ligand15, Ligand14, and Ligand11 as potent inhibitors which showed higher ligand efficiency, binding affinity, lipophilic ligand efficiency, and favorable torsion values as compared to 2C3. Conclusion The stated methodologies revealed a unique mechanism of active site binding. The binding interactions within the active site showed that the chosen molecules had notable interactions than the standard molecule, which led to the generation of potential compounds to inhibit DYRK1A.