Screening of BindingDB database ligands against EGFR, HER2, Estrogen, Progesterone and NF-κB receptors based on machine learning and molecular docking.

Breast cancer, the second most prevalent cancer among women worldwide, necessitates the exploration of novel therapeutic approaches. To target the four subgroups of breast cancer "hormone receptor-positive and HER2-negative, hormone receptor-positive and HER2-positive, hormone receptor-negative and HER2-positive, and hormone receptor-negative and HER2-negative" it is crucial to inhibit specific targets such as EGFR, HER2, ER, NF-κB, and PR. In this study, we evaluated various methods for binary and multiclass classification. Among them, the GA-SVM-SVM:GA-SVM-SVM model was selected with an accuracy of 0.74, an F1-score of 0.73, and an AUC of 0.92 for virtual screening of ligands from the BindingDB database. This model successfully identified 4454, 803, 438, and 378 ligands with over 90% precision in both active/inactive and target prediction for the classes of EGFR+HER2, ER, NF-κB, and PR, respectively, from the BindingDB database. Based on to the selected ligands, we created a dendrogram that categorizes different ligands based on their targets. This dendrogram aims to facilitate the exploration of chemical space for various therapeutic targets. Ligands that surpassed a 90% threshold in the product of activity probability and correct target selection probability were chosen for further investigation using molecular docking. The binding energy range for these ligands against their respective targets was calculated to be between -15 and -5 kcal/mol. Finally, based on general and common rules in medicinal chemistry, we selected 2, 3, 3, and 8 new ligands with high priority for further studies in the EGFR+HER2, ER, NF-κB, and PR classes, respectively.

Anti-angiogenic biomolecules in neovascular age-related macular degeneration; therapeutics and drug delivery systems.

Blindness in the elderly is often caused by age-related macular degeneration (AMD). The advanced type of AMD known as neovascular AMD (nAMD) has been linked to being the predominant cause of visual impairment in these people. Multiple neovascular structures including choroidal neovascular (CNV) membranes, fluid exudation, hemorrhages, and subretinal fibrosis, are diagnostic of nAMD. These pathological alterations ultimately lead to anatomical and visual loss. It is known that vascular endothelial growth factor (VEGF), a type of proangiogenic factor, mediates the pathological process underlying nAMD. Therefore, various therapies have evolved to directly target the disease. In this review article, an attempt has been made to discuss general explanations about this disease, all common treatment methods based on anti-VEGF drugs, and the use of drug delivery systems in the treatment of AMD. Initially, the pathophysiology, angiogenesis, and different types of AMD were described. Then we described current treatments and future treatment prospects for AMD and outlined the advantages and disadvantages of each. In this context, we first examined the types of therapeutic biomolecules and anti-VEGF drugs that are used in the treatment of AMD. These biomolecules include aptamers, monoclonal antibodies, small interfering RNAs, microRNAs, peptides, fusion proteins, nanobodies, and other therapeutic biomolecules. Finally, we described drug delivery systems based on liposomes, nanomicelles, nanoemulsions, nanoparticles, cyclodextrin, dendrimers, and composite vehicles that are used in AMD therapy.

DFT study on CO 2 capture using boron, nitrogen, and phosphorus-doped C 20 in the presence of an electric field.

Burning fossil fuels emits a significant amount of CO 2 , causing climate change concerns. CO 2 Capture and Storage (CCS) aims to reduce emissions, with fullerenes showing promise as CO 2 adsorbents. Recent research focuses on modifying fullerenes using an electric field. In light of this, we carried out DFT studies on some B, N, and P doped C 20 ( C 20 - n X n , n = 0, 1, 2, and 3; X = B, N, and P) in the absence and presence of an electric field in the range of 0-0.02 a.u.. The cohesive energy was calculated to ensure their thermodynamic stability showing, that despite having lesser cohesive energies than C 20 , they appear in a favorable range. Moreover, the charge distribution for all structures was depicted using the ESP map. Most importantly, we evaluated the adsorption energy, height, and CO 2 angle, demonstrating the B and N-doped fullerenes had the stronger interaction with CO 2 , which by far exceeded C 20 's, improving its physisorption to physicochemical adsorption. Although the adsorption energy of P-doped fullerenes was not as satisfactory, in most cases, increasing the electric field led to enhancing CO 2 adsorption and incorporating chemical attributes to CO 2 -fullerene interaction. The HOMO-LUMO plots were obtained by which we discovered that unlike the P-doped C 20 , the surprising activity of B and N-doped C 20 s against CO 2 originates from a high concentration of the HOMO-LUMO orbitals on B, N and neighboring atoms. In the present article, we attempt to introduce more effective fullerene-based materials for CO 2 adsorption as well as strategies to enhance their efficiency and revealing adsorption nature over B, N, and P-doped fullerenes and in the end, hope to encourage more experimental research on these materials within growing electric field for CO 2 capture in the future.

In silico design of potential Mcl-1 peptide-based inhibitors.

CONTEXT: BIM (Bcl-2 interacting mediator of apoptosis)-derived peptides that specifically target over-expressed Mcl-1 (myeloid cell leukemia-1) protein and induce apoptosis are potentially anti-cancer agents. Since the helicity of BIM-derived peptides has a crucial role in their functionality, a range of strategies have been used to increase the helicity including the introduction of unnatural residues and stapling methods that have some drawbacks such as the accumulation in the liver. To avoid these drawbacks, this study aimed to design a more helical peptide by utilizing bioinformatics algorithms and molecular dynamics simulations without exploiting unnatural residues and stapling methods. MM-PBSA results showed that the mutations of A4fE and A2eE in analogue 5 demonstrate a preference towards binding with Mcl-1. As evidenced by Circular dichroism results, the helicity increases from 18 to 34%, these findings could enhance the potential of analogue 5 as an anti-cancer agent targeting Mcl-1. The applied strategies in this research could shed light on the in silico peptide design. Moreover, analogue 5 as a drug candidate can be evaluated in vitro and in vivo studies. METHODS: The sequence of the lead peptide was determined using the ApInAPDB database and PRALINE program. Contact finder and PDBsum web server softwares were used to determine the contact involved amino acids in complex with Mcl-1. All identified salt bridge contributing residues were unaltered to preserve the binding affinity. After proposing novel analogues, their secondary structures were predicted by Cham finder web server software and GOR, Neural Network, and Chou-Fasman algorithms. Finally, molecular dynamics simulations run for 100 ns were done using the GROMACS, version 5.0.7, with the CHARMM36 force field. MM-PBSA was used to assess binding affinity specificity in targeting Mcl-1 and Bcl-xL (B-cell lymphoma extra-large).

Molecular dynamics simulation as a promising approach for computational study of liquid crystal-based aptasensors.

As a potent computational methodology, molecular dynamics (MD) simulation provides advantageous knowledge about biological compounds from the molecular viewpoint. In particular, MD simulation gives exact information about aptamer strands, such as the short synthetic oligomers, their orientation, binding sites, folding-unfolding state, and conformational re-arrangement. Also, the effect of the different chemicals and biochemicals as the components of aptamer-based sensors (aptasensors) on the aptamer-target interaction can be investigated by MD simulation. Liquid crystals (LCs) as soft substances with characteristics of both solid anisotropy and liquid fluidity are new candidates for designing label-free aptasensors. To now, diverse aptasensors have been developed experimentally based on the optical anisotropy, fluidity, and long-range orientational order of LCs. Here, we represent a computational model of an LC-based aptasensor through a detailed MD simulation study. The different parameters are defined and studied to achieve a comprehensive understanding of the computational design of the LC-based aptasensor, including the density of LCs, their orientation angle, and lognormal distribution in the absence and presence of aptamer strands, both aptamer and target molecules with various concentrations, and interfering substance. As a case study, the tobramycin antibiotic is considered the target molecule for the computational model of the LC-based aptasensor.Communicated by Ramaswamy H. Sarma.

In silico approaches to investigate enzyme immobilization: a comprehensive systematic review.

Enzymes are popular catalysts with many applications, especially in industry. Biocatalyst usage on a large scale is facing some limitations, such as low operational stability, low recyclability, and high enzyme cost. Enzyme immobilization is a beneficial strategy to solve these problems. Bioinformatics tools can often correctly predict immobilization outcomes, resulting in a cost-effective experimental phase with the least time consumed. This study provides an overview of in silico methods predicting immobilization processes via a comprehensive systematic review of published articles till 11 December 2022. It also mentions the strengths and weaknesses of the processes and explains the computational analyses in each method that are required for immobilization assessment. In this regard, Web of Science and Scopus databases were screened to gain relevant publications. After screening the gathered documents (n = 3873), 60 articles were selected for the review. The selected papers have applied in silico procedures including only molecular dynamics (MD) simulations (n = 20), parallel tempering Monte Carlo (PTMC) and MD simulations (n = 3), MD and docking (n = 1), density functional theory (DFT) and MD (n = 1), only docking (n = 11), metal ion binding site prediction (MIB) server and docking (n = 2), docking and DFT (n = 1), docking and analysis of enzyme surfaces (n = 1), only DFT (n = 1), only MIB server (n = 2), analysis of an enzyme structure and surface (n = 12), rational design of immobilized derivatives (RDID) software (n = 3), and dissipative particle dynamics (DPD; n = 2). In most included studies (n = 51), enzyme immobilization was investigated experimentally in addition to in silico evaluation.

Kallistatin as an inhibitory protein against colorectal cancer cells through binding to LRP6.

Kallistatin (KL) is a member of the serine proteinase inhibitor (serpin) family regulating oxidative stress, vascular relaxation, inflammation, angiogenesis, cell proliferation, and invasion. The heparin-binding site of Kallistatin has an important role in the interaction with LRP6 leading to the blockade of the Wnt signaling pathway. In this study, we aimed to explore the structural basis of the Kallistatin-LRP6E1E4 complex using in silico approaches and evaluating the anti-proliferative, apoptotic, and cell cycle arrest activities of Kallistatin in colon cancer lines. The molecular docking showed Kallistatin could bind to the LRP6E3E4 much stronger than LRP6E1E2. The Kallistatin-LRP6E1E2 and Kallistatin-LRP6E3E4 complexes were stable during Molecular Dynamics (MD) simulation. The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) showed that the Kallistatin-LRP6E3E4 has a higher binding affinity compared to Kallistatin-LRP6E1E2. Kallistatin induced higher cytotoxicity and apoptosis in HCT116 compared to the SW480 cell line. This protein-induced cell-cycle arrest in both cell lines at the G1 phase. The B-catenin, cyclin D1, and c-Myc expression levels were decreased in response to treatment with Kallistatin in both cell lines while the LRP6 expression level was decreased in the HCT116 cell line. Kallistatin has a greater effect on the HCT116 cell line compared to the SW480 cell line. Kallistatin can be used as a cytotoxic and apoptotic-inducing agent in colorectal cancer cell lines.

Rational peptide design for targeting cancer cell invasion.

Cell invasion is an important process in cancer progression and recurrence. Invasion and implantation of cancer cells from their original place to other tissues, by disabling vital organs, challenges the treatment of cancer patients. Given the importance of the matter, many molecular treatments have been developed to inhibit cancer cell invasion. Because of their low production cost and ease of production, peptides are valuable therapeutic molecules for inhibiting cancer cell invasion. In recent years, advances in the field of computational biology have facilitated the design of anti-cancer peptides. In our investigation, using computational biology approaches such as evolutionary analysis, residue scanning, protein-peptide interaction analysis, molecular dynamics, and free energy analysis, our team designed a peptide library with about 100 000 candidates based on A6 (acetyl-KPSSPPEE-amino) sequence which is an anti-invasion peptide. During computational studies, two of the designed peptides that give the highest scores and showed the greatest sequence similarity to A6 were entered into the experimental analysis workflow for further analysis. In experimental analysis steps, the anti-metastatic potency and other therapeutic effects of designed peptides were evaluated using MTT assay, RT-qPCR, zymography analysis, and invasion assay. Our study disclosed that the IK1 (acetyl-RPSFPPEE-amino) peptide, like A6, has great potency to inhibit the invasion of cancer cells.

Construction of an Exudative Age-Related Macular Degeneration Diagnostic and Therapeutic Molecular Network Using Multi-Layer Network Analysis, a Fuzzy Logic Model, and Deep Learning Techniques: Are Retinal and Brain Neurodegenerative Disorders Related?

Neovascular age-related macular degeneration (nAMD) is a leading cause of irreversible visual impairment in the elderly. The current management of nAMD is limited and involves regular intravitreal administration of anti-vascular endothelial growth factor (anti-VEGF). However, the effectiveness of these treatments is limited by overlapping and compensatory pathways leading to unresponsiveness to anti-VEGF treatments in a significant portion of nAMD patients. Therefore, a system view of pathways involved in pathophysiology of nAMD will have significant clinical value. The aim of this study was to identify proteins, miRNAs, long non-coding RNAs (lncRNAs), various metabolites, and single-nucleotide polymorphisms (SNPs) with a significant role in the pathogenesis of nAMD. To accomplish this goal, we conducted a multi-layer network analysis, which identified 30 key genes, six miRNAs, and four lncRNAs. We also found three key metabolites that are common with AMD, Alzheimer's disease (AD) and schizophrenia. Moreover, we identified nine key SNPs and their related genes that are common among AMD, AD, schizophrenia, multiple sclerosis (MS), and Parkinson's disease (PD). Thus, our findings suggest that there exists a connection between nAMD and the aforementioned neurodegenerative disorders. In addition, our study also demonstrates the effectiveness of using artificial intelligence, specifically the LSTM network, a fuzzy logic model, and genetic algorithms, to identify important metabolites in complex metabolic pathways to open new avenues for the design and/or repurposing of drugs for nAMD treatment.

EasyModel: a user-friendly web-based interface based on MODELLER.

Three-dimensional protein structures are invaluable sources of information for the functional annotation of protein molecules. Describing the function of a protein sequence is one of the most common problems in biology. Generally, this problem can be facilitated by studying the tertiary structure of proteins. In the lack of protein structures, comparative modeling often provides a useful three-dimensional model of the protein associated with at least one known protein structure. Comparative modeling predicts the tertiary structure of a certain protein sequence (target) mainly based on its homological sequence to the sequence of one or more proteins with known structures (templates). MODELLER is one of the most widely used tools for homology or comparative modeling of three-dimensional protein structures. However, most users find it challenging to start with MODELLER as it is a command line based and requires knowledge of basic Python scripting to use it efficiently. In this study, a web-based interface has been designed to predict the tertiary structure of proteins based on Modeller, which does the comparative modeling automatically, and uses PHP and Python programming languages. This tool is called "EasyModel" and is available at http://bioinf.modares.ac.ir/software/easymodel/ . EasyModel provides a straightforward graphical interface for Modeller that can be used in only one browser.

Computational designing of the ligands of Protein L affinity chromatography based on molecular docking and molecular dynamics simulations.

Protein L is a multidomain protein from Peptostreptococcus magnus with binding affinity to kappa light chain of human immunoglobulin (Ig) which is used for the purification of antibody fragments by affinity chromatography. The advances in protein engineering and computational biology approaches lead to the development of engineered affinity ligands with improved properties including binding affinity. In this study, molecular dynamics simulations (MDs) and Osprey software were used to design single B domains of the Protein L with higher affinity to antibody fragments. The modified B domains were then polymerized to ligand with six B domains by homology modeling methods. The results showed that single B domain mutants of MB1 (Thr865Trp) and MB2 (Thr847Met-Thr865Trp) had higher binding affinity to Fab compared to the wild single B domain. Also, MDs and molecular docking results showed that the polymerized Proteins L including the wild and mutated six B domains (6B0, 6B1, and 6B2) were stable during MDs and the two mutants of 6B1 and 6B2 showed higher binding affinity to Fab relative to the wild type.Communicated by Ramaswamy H. Sarma.

Reducing the assemblies of amyloid-beta multimers by sodium dodecyl sulfate surfactant at concentrations lower than critical micelle concentration: molecular dynamics simulation exploration.

Amyloid-ß peptide, the predominant proteinaceous component of senile plaques, is responsible for the incidence of Alzheimer's disease (AD), an age-associated neurodegenerative disorder. Specifically, the amyloid-ß(1-42) (Aß1-42) isoform, known for its high toxicity, is the predominant biomarker for the preliminary diagnosis of AD. The aggregation of the Aß1-42 peptides can be affected by the components of the cellular medium through changing their structures and molecular interactions. In this study, we investigated the effect of sodium dodecyl sulfate (SDS) at much lower concentrations than the critical micelle concentration (CMC) on Aß1-42 aggregation. For this purpose, we studied mono-, di-, tri- and tetramers of Aß1-42 peptide in two different concentrations of SDS molecules (10 and 40 molecules) using a 300 ns molecular dynamics simulation for each system. The distance between the center of mass (COM) of Aß1-42 peptides confirms that an increase in the number of SDS molecules decreases their aggregation probability due to greater interaction with SDS molecules. Besides, the less compactness parameter reveals the reduced aggregation probability of Aß1-42 peptides. Based on the energetic FEL landscapes, SDS molecules with the concentration closer to the CMC are an effective inhibitory agent to prevent the formation of Aß1-42 fibrils. Also, the aggregation direction of the peptide pairs can be predicted by determining the direction of the accumulation-deterrent forces.Communicated by Ramaswamy H. Sarma.

Investigation of thermal stability characteristic in family A DNA polymerase - A theoretical study.

DNA polymerases create complementary DNA strands in living cells and are crucial to genome transmission and maintenance. These enzymes possess similar human right-handed folds which contain thumb, fingers, and palm subdomains and contribute to polymerization activities. These enzymes are classified into seven evolutionary families, A, B, C, D, X, Y, and RT, based on amino acid sequence analysis and biochemical characteristics. Family A DNA polymerases exist in an extended range of organisms including mesophilic, thermophilic, and hyper-thermophilic bacteria, participate in DNA replication and repair, and have a broad application in molecular biology and biotechnology. In this study, we attempted to detect factors that play a role in the thermostability properties of this family member despite their remarkable similarities in structure and function. For this purpose, similarities and differences in amino acid sequences, structure, and dynamics of these enzymes have been inspected. Our results demonstrated that thermophilic and hyper-thermophilic enzymes have more charged, aromatic, and polar residues than mesophilic ones and consequently show further electrostatic and cation-pi interactions. In addition, in thermophilic enzymes, aliphatic residues tend to position in buried states more than mesophilic enzymes. These residues within their aliphatic parts increase hydrophobic core packing and therefore enhance the thermostability of these enzymes. Furthermore, a decrease in thermophilic cavities volumes assists in the protein compactness enhancement. Moreover, molecular dynamic simulation results revealed that increasing temperature impacts mesophilic enzymes further than thermophilic ones that reflect on polar and aliphatic residues surface area and hydrogen bonds changes.

Reconstructing the cell-cell interaction network among mouse immune cells.

Intercellular interactions and cell-cell communication are critical to regulating cell functions, especially in normal immune cells and immunotherapies. Ligand-receptor pairs mediating these cell-cell interactions can be identified using diverse experimental and computational approaches. Here, we reconstructed the intercellular interaction network between Mus musculus immune cells using publicly available receptor-ligand interaction databases and gene expression data from the immunological genome project. This reconstructed network accounts for 50,317 unique interactions between 16 cell types between 731 receptor-ligand pairs. Analysis of this network shows that cells of hematopoietic lineages use fewer communication pathways for interacting with each other, while nonhematopoietic stromal cells use the most network communications. We further observe that the WNT, BMP, and LAMININ pathways are the most significant contributors to the overall number of cell-cell interactions among the various pathways in the reconstructed communication network. This resource will enable the systematic analysis of normal and pathologic immune cell interactions, along with the study of emerging immunotherapies.

The coat protein of tobacco mosaic virus as an anti-tobacco mosaic virus: a molecular dynamics simulation.

The Coat Protein (CP) of the Tobacco Mosaic Virus (TMV) executes an important duty in the protection of virus RNA. The interaction between the virus CP and host plant proteins induces infection in the host and creates dark and light green mosaics on crops, which disturb the growth and function of the plant. The interaction between the virus CP and the modified CP, expressed in transgenic plants, causes Coat Protein-Mediated Resistance (CP-MR), which reduces virus infection in transgenic plants. In this study, a model is suggested for resistance as "stop assembly of CP" in the virus. It is based on the fact that the CP, when mutated, acts as a dead-end in virus assembly. For evaluation of the model, we investigated the effect of four mutants including CBT28I, ABT42W, ABD77R, and ABT89W complexes on plant resistance against TMV infection by molecular dynamics simulation. Previous studies had shown the influence of such mutations on the CP-MR. The MD results of in the present study further confirmed the mentioned effect and demonstrated how the mutations could be the cause of CP-MR. The results are calculated by the RMSD, Rg, H-bond, and g-MMPBSA scripts. The change in binding energy between two chains is consistent with CP-MR such that with increase in binding energy, the affinity between two chains was reduced and the CP-MR increased. Based on this model, it is possible to design mutants with a high level of efficiency.Communicated by Ramaswamy H. Sarma.

In Silico Analysis of Neutralizing Antibody Epitopes on The Hepatitis C Virus Surface Glycoproteins.

OBJECTIVE: Despite of antiviral drugs and successful treatment, an effective vaccine against hepatitis C virus (HCV) infection is still required. Recently, bioinformatic methods same as prediction algorithms, have greatly contributed to the use of peptides in the design of immunogenic vaccines. Therefore, finding more conserved sites on the surface glycoproteins (E1 and E2) of HCV, as major targets to design an effective vaccine against genetically different viruses in each genotype was the goal of the study. MATERIALS AND METHODS: In this experimental study, 100 entire sequences of E1 and E2 were retrieved from the NCBI website and analyzed in terms of mutations and critical sites by Bioedit 7.7.9, MEGA X software. Furthermore, HCV-1a samples were obtained from some infected people in Iran, and reverse transcriptase-polymerase chain reaction (RTPCR) assay was optimized to amplify their E1 and E2 genes. Moreover, all three-dimensional structures of E1 and E2 downloaded from the PDB database were analyzed by YASARA. In the next step, three interest areas of humoral immunity in the E2 glycoprotein were evaluated. OSPREY3.0 protein design software was performed to increase the affinity to neutralizing antibodies in these areas. RESULTS: We found the effective in silico binding affinity of residues in three broadly neutralizing epitopes of E2 glycoprotein. First, positions that have substitution capacity were detected in these epitopes. Furthermore, residues that have high stability for substitution in these situations were indicated. Then, the mutants with the strongest affinity to neutralize antibodies were predicted. I414M, T416S, I422V, I414M-T416S, and Q412N-I414M-T416S substitutions theoretically were exhibited as mutants with the best affinity binding. CONCLUSION: Using an innovative filtration strategy, the residues of E2 epitopes which have the best in silico binding affinity to neutralizing antibodies were exhibited and a distinct peptide library platform was designed.

A Novel in silico SELEX Method to Screen and Identify Aptamers against Vibrio cholerae.

BACKGROUND: Vibrio cholerae, the causative agent of cholera, has been responsible for global epidemics and many other problems over the centuries. It is one of the main public health issues in less-developed and developing countries and is considered one of the deadliest infectious agents. Therefore, precise and susceptible detection of V. cholerae from environmental and biological samples is critical. Aptamers provide a rapid, sensitive, highly specific, and inexpensive alternative to traditional methods. OBJECTIVE: The present study develops a new protocol inspired by the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) to implement an in silico aptamer selection against V. cholerae, which can also be employed in the case of other pathogenic microorganisms. METHODS: First, we built an oligonucleotide pool and screened it based on the secondary structure. Following that, we modeled the tertiary structures of filtered sequences and performed RNAprotein dockings to assess binding affinities between RNA sequences and Outer Membrane Protein U (OmpU), an effective marker in distinguishing epidemic strains of V. cholerae, which constitute up to 60% of the total outer membrane protein. Finally, we used molecular dynamics simulation to validate the results. RESULTS: Three sequences (ChOmpUapta) were proposed as final aptameric candidates. Analysis of the top-ranked docking results revealed that these candidate aptamers bound to all subunits of OmpU at the extracellular side with high affinity. Moreover, ChOmpUapta-3 and ChOmpUapta-2 were fully stable and formed strong bonds under dynamic conditions. CONCLUSION: We propose incorporating these candidate sequences into aptasensors for V. cholerae detection.

A comprehensive computer simulation insight into inhibitory mechanisms of EGCG and NQTrp ligands on amyloid-beta assemblies as the Alzheimer's disease insignia.

Amyloid-ß peptide with predominant presence in the senile plaques is the most common agent for Alzheimer's disease (AD) incidence. Assembly of the amyloid-ß(1-42) (Aß1-42) isoform is known as the main reason for the AD appearance. Epigallocatechin gallate (EGCG) and 1,4-naphthoquinone-2-yl-L-tryptophan (NQTrp) are two small molecules that inhibit the formation of the Aß1-42 fibrils. The present study provides molecular insight to clarify the inhibitory mechanisms of the EGCG and NQTrp ligands on the Aß1-42 assemblies by using molecular dynamics (MD) simulation. Hence, nine different Aß1-42-containing systems including the monomer, dimer, and hexamer of Aß1-42 considering each of them in a media with no ligands, in the presence of one EGCG ligand, and in the presence of one EGCG ligand were studied with a simulation time of 1 µs for each system. The precise investigation of the peptide-ligand distance, conformational factor (Pi), solvent accessible surface area (SASA), dictionary of secondary structure (DSSP), and Lys28-Ala42 salt bridge analyses confirmed that the hydroxyl-rich structure of the EGCG ligand applied its inhibitory effect on the aggregation of the peptides indirectly by involving water molecules. While the hydroxyl-free structure of the NQTrp ligand exposed its inhibitory effect through a direct interaction with the Aß1-42 peptides. Besides, reduced density gradient (RDG) analysis clarified the hydrogen bonding interactions as the dominant ones for the peptide-EGCG systems, and also, steric and van der Waals interactions for the peptide-NQTrp systems.Communicated by Ramaswamy H. Sarma.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01.

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Design, synthesis, spectroscopic characterizations, antidiabetic, in silico and kinetic evaluation of novel curcumin-fused aldohexoses.

Curcumin (bis-α,ß-unsaturated ß-diketone) plays an important role in the prevention of numerous diseases, including diabetes. Curcumin, as an enzyme inhibitor, has ideal structural properties including hydrophobic nature, flexible backbone, and several available hydrogen bond (H-bond) donors and acceptors. In this study, curcumin-fused aldohexose derivatives 3(a-c) were synthesized and used as influential agents in the treatment of diabetes with inhibitory properties against two carbohydrate-hydrolyzing enzymes α-glucosidase (α-Gls) and α-amylase (α-Amy) which are known to be significant therapeutic targets for the reduction of postprandial hyperglycemia. These compounds were isolated, purified, and then spectrally characterized via FT-IR, Mass, 1H, and 13C NMR, which strongly confirmed the targeted product's formation. Also, their inhibitory properties against α-Gls and α-Amy were evaluated spectroscopically. The Results indicated that all compounds strongly inhibited α-Amy and α-Gls by mixed and competitive mechanisms, respectively. The intrinsic fluorescence of α-Amy was quenched by the interaction with compounds 1 and 3b through a dynamic quenching mechanism, and the 1 and 3b/α-Amy complexes were spontaneously formed, mainly driven by the hydrophobic interaction and hydrogen bonding. Fourier transform infrared spectra (FT-IR) comprehensively verified that the binding of compounds 1 and 3b to α-Amy would change the conformation and microenvironment of α-Amy, thereby inhibiting the enzyme activity. Docking and molecular dynamics (MD) simulations showed that all compounds interacted with amino acid residues located in the active pocket site of the proteins. In vivo studies confirmed the plasma glucose diminution after the administration of compound 3b to Wistar rats. Accordingly, the results of the current work may prompt the scientific communities to investigate the possibility of compound 3b application in the clinic.