Identification Of Binding Sites Research Articles

Identification of AflR Binding Sites in the Genome of Aspergillus flavus by ChIP-Seq.

We report here the AflR binding motif of Aspergillus flavus for the first time with the aid of ChIP-seq analysis. Of the 540 peak sequences associated with AflR binding events, 66.8% were located within 2 kb upstream (promoter region) of translational start sites. The identified 18-bp binding motif was a perfect palindromic sequence, 5′-CSSGGGWTCGAWCCCSSG’3′ with S representing G or C and W representing A or T. On closer examination, we hypothesized that the 18-bp motif sequence identified contained two identical parts (here called motif A and motif B). Motif A was in positions 8–18 on the upper strand, while motif B was in positions 11-1 on the bottom strand. The inferred length and sequence of the putative motif identified in A. flavus were similar to previous findings in A. parasiticus and A. nidulans. Gene ontology analysis indicated that AflR bound to other genes outside the aflatoxin biosynthetic gene cluster.

Airway Relaxation Mechanisms and Structural Basis of Osthole to Improve Lung Function in Asthma

Background and objectiveOveruse of β2‐adrenoceptor agonist bronchodilators causes receptor desensitization, resulting in decreased efficacy and an increased risk of death in asthma patients. This is a critical unmet problem in asthma management, and novel drugs are urgently needed. Here, we report that osthole, a coumarin derived from a traditional Chinese medicine, induces complete relaxation of preconstricted airways in mouse precision‐cut lung slices, irrespective of β2‐adrenoceptor desensitization.MethodsMouse precision‐cut lung slices as an in vitro model were used to analyze airway relaxation. The cAMP level in human airway smooth muscle (ASM) or HEK293 cells was determined by phosphorylation of vasodilator‐stimulated phosphoprotein using Western blot or cAMP dependent reporter luciferase assay. The secretion of prostaglandin E2 (PGE2) in ASM cells or lung slices was measured by ELISA assay. The effect of osthole on airway hyperresponsiveness (AHR) was measured in both house dust mite (HDM)‐sensitized mice and naïve regulator of G‐protein signaling 2 (RGS2) KO mice. The binding sites of osthole with PDE4D5 catalytic domain were analyzed by crystallization and X‐ray diffraction.ResultsOsthole administered in vivo ameliorates AHR, a hallmark of asthma, in murine asthma models. Mechanistic studies revealed that osthole inhibits phosphodiesterase 4D (PDE4D) activity to amplify endogenous PGE2 signaling in ASM cells, which eventually triggers cAMP/protein kinase A‐dependent relaxation of airways. The crystal structure of the PDE4D complexed with osthole reveals that osthole binds to the catalytic site to prevent cAMP binding and hydrolysis. Together, our studies elucidate a specific molecular target and mechanism by which osthole induces airway relaxation.ConclusionIdentification of osthole binding sites on PDE4D will guide further development of novel therapeutics for β2‐adrenoceptor agonist‐resistant asthma.Support or Funding InformationThis work was supported in part by the National Institutes of Health (R01HL116849) and Nebraska State LB595 Research Program, USA; the National Laboratory of Biomacromolecules and the Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences (CAS); the CAS/SAFEA International Partnership Program for Creative Research Teams; the National Key R&D Program of China (2017YFA0205501); the National Natural Science Foundation of China (21777192 and 31500623)

Agonist-Specific Conformations of the M2 Muscarinic Acetylcholine Receptor Assessed by Molecular Dynamics.

Binding of muscarinic ligands, both antagonists and agonists, and their effects on the conformation of the M2 acetylcholine receptor were modeled in silico and compared to experimental data. After docking of antagonists to the M2 receptor in an inactive conformation (3UON, 5ZK3, 5ZKB, or 5ZKB) and agonists in an active conformation (4MQS), 100 ns of conventional molecular dynamics (MD) followed by 500 ns of accelerated MD was run. Conventional MD revealed ligand-specific interactions with the receptor. Antagonists stabilized the receptor in an inactive conformation during accelerated MD. The receptor in complex with various agonists attained different conformations specific to individual agonists. The magnitude of the TM6 movement correlated with agonist efficacy at the non-preferential Gs pathway. The shape of the intracellular opening where the receptor interacts with a G-protein was different for the classical agonist carbachol, super-agonist iperoxo, and Gi/o-biased partial agonists JR-6 and JR-7, being compatible with experimentally observed agonist bias at the G-protein level. Moreover, a wash-resistant binding of the unique agonist xanomeline associated with interactions with membrane lipids was formed during accelerated MD. Thus, accelerated MD is suitable for modeling of ligand-specific receptor binding and receptor conformations that is essential for the design of experiments aimed at identification of the secondary binding sites and understanding molecular mechanisms underlying receptor activation.

Analyses on clustering of the conserved residues at protein-RNA interfaces and its application in binding site identification

BackgroundThe maintenance of protein structural stability requires the cooperativity among spatially neighboring residues. Previous studies have shown that conserved residues tend to occur clustered together within enzyme active sites and protein-protein/DNA interfaces. It is possible that conserved residues form one or more local clusters in protein tertiary structures as it can facilitate the formation of functional motifs. In this work, we systematically investigate the spatial distributions of conserved residues as well as hot spot ones within protein-RNA interfaces.ResultsThe analysis of 191 polypeptide chains from 160 complexes shows the polypeptides interacting with tRNAs evolve relatively rapidly. A statistical analysis of residues in different regions shows that the interface residues are often more conserved, while the most conserved ones are those occurring at protein interiors which maintain the stability of folded polypeptide chains. Additionally, we found that 77.8% of the interfaces have the conserved residues clustered within the entire interface regions. Appling the clustering characteristics to the identification of the real interface, there are 31.1% of cases where the real interfaces are ranked in top 10% of 1000 randomly generated surface patches. In the conserved clusters, the preferred residues are the hydrophobic (Leu, Ile, Met), aromatic (Tyr, Phe, Trp) and interestingly only one positively charged Arg residues. For the hot spot residues, 51.5% of them are situated in the conserved residue clusters, and they are largely consistent with the preferred residue types in the conserved clusters.ConclusionsThe protein-RNA interface residues are often more conserved than non-interface surface ones. The conserved interface residues occur more spatially clustered relative to the entire interface residues. The high consistence of hot spot residue types and the preferred residue types in the conserved clusters has important implications for the experimental alanine scanning mutagenesis study. This work deepens the understanding of the residual organization at protein-RNA interface and is of potential applications in the identification of binding site and hot spot residues.

Identification of Functional Transcriptional Binding Sites within Chicken Abcg2 Gene Promoter and Screening Its Regulators.

Breast cancer resistance protein (BCRP), an ATP-binding cassette (ABC) half transporter encoded by the Abcg2 gene, is reported to influence the pharmacokinetics of substrate drugs during clinical therapy. The aim of this study was to clarify the mechanisms that regulate the transcription of the chicken Abcg2 gene through cloning and characterization of its promoter region. Results showed that the Abcg2 gene is transcribed by a TATA-less promoter with several putative Sp1 sites upstream from two putative CpG islands. A luciferase reporter assay conducted both in chicken leghorn male hepatoma (LMH) cells and chicken primary hepatocytes mapped a basal promoter to nucleotides −110 to +30, which is responsible for the constitutive expression of Abcg2. The 5′-region upstream of the basal promoter was characterized by both positive and negative regulatory domains. Further, using the cell-based reporter gene assay combined with RT-PCR and drug accumulation analysis, we found that four xenobiotics, daidzein, clotrimazole, ivermectin, and lipopolysaccharide (LPS), influence the expression and function of BCRP through significant regulation of the Abcg2 gene promoter. Interaction sites with the Abcg2 gene promoter of these four selected regulators were clarified by progressive deletions and mutation assays. This study shed some light on the regulatory mechanisms involved in chicken Abcg2 gene expression and the results may have far-reaching significance regarding the usage and development of veterinary drugs.

Mammalian RNA Decay Pathways Are Highly Specialized and Widely Linked to Translation.

SummaryRNA decay is crucial for mRNA turnover and surveillance and misregulated in many diseases. This complex system is challenging to study, particularly in mammals, where it remains unclear whether decay pathways perform specialized versus redundant roles. Cytoplasmic pathways and links to translation are particularly enigmatic. By directly profiling decay factor targets and normal versus aberrant translation in mouse embryonic stem cells (mESCs), we uncovered extensive decay pathway specialization and crosstalk with translation. XRN1 (5′-3′) mediates cytoplasmic bulk mRNA turnover whereas SKIV2L (3′-5′) is universally recruited by ribosomes, tackling aberrant translation and sometimes modulating mRNA abundance. Further exploring translation surveillance revealed AVEN and FOCAD as SKIV2L interactors. AVEN prevents ribosome stalls at structured regions, which otherwise require SKIV2L for clearance. This pathway is crucial for histone translation, upstream open reading frame (uORF) regulation, and counteracting ribosome arrest on small ORFs. In summary, we uncovered key targets, components, and functions of mammalian RNA decay pathways and extensive coupling to translation.

Identification of Sodium Sensitive Site and Chloride Sensitive Site on the C-Terminus of Rat KCNT1 Channel

KCNT1 channel is a sodium and chloride activated potassium channel that is widely expressed in nervous system. Our previous study had identified D818 mutants can dramatically decrease the sodium sensitivity of KCNT1 channel. But the full co-ordinate sodium sensitive site and chloride site of this channel remain unknown. In this abstract, we reported that identification of a sodium binding site of this channel by fully screening 109 negatively charged amino acids mutants on the C-terminus of Slack channel. Results show several mutants of these negative charged channel increased Kd of sodium sensitivity to more than 1 M while several mutants did not show currents. Subsequently, we screened mutants that did not show currents on the background of mutant M335A because the mutant M335A of KCNT1 channel can be activated without intracellular sodium. Thus, we got either macroscopic current or single channel current from all mutants. Combined with electrophysiology experimental data and molecular dynamic simulation, we found that one subunit of Slack channel could bind two sodium ions. One dominant sodium sensitive site is located on RCK1 domain of the Slack channel. Another weak sodium binding pocket that is composed of 6 spatially closed negative charged residues. In the meantime, by molecular dynamic prediction and alignment with C.elegan Slo2 channel, we screened mutants of some positive charged residues on the C-terminus of the rat KCNT1 channel. One chloride binding site was identified from RCK1 domain of KCNT1 channel. In conclusion, our results dissected sodium and chloride sensitive sites of KCNT1 channel.

Identification of Highest-Affinity Binding Sites of Yeast Transcription Factor Families.

Transcription factors (TFs) play a crucial role in controlling key cellular processes and responding to the environment. Yeast is a single-cell fungal organism that is a vital biological model organism for studying transcription and translation in basic biology. The transcriptional control process of yeast cells has been extensively calculated and studied using traditional methods and high-throughput technologies. However, the identities of transcription factors that regulate major functional categories of genes remain unknown. Due to the avalanche of biological data in the post-genomic era, it is an urgent need to develop automated computational methods to enable accurate identification of efficient transcription factor binding sites from the large number of candidates. In this paper, we analyzed high-resolution DNA-binding profiles and motifs for TFs, covering all possible contiguous 8-mers. First, we divided all 8-mer motifs into 16 various categories and selected all sorts of samples from each category by setting the threshold of E-score. Then, we employed five feature representation methods. Also, we adopted a total of four feature selection methods to filter out useless features. Finally, we used Extreme Gradient Boosting (XGBoost) as our base classifier and then utilized the one-vs-rest tactics to build 16 binary classifiers to solve this multiclassification problem. In the experiment, our method achieved the best performance with an overall accuracy of 79.72% and Mathew's correlation coefficient of 0.77. We found the similarity relationship among each category from different TF families and obtained sequence motif schematic diagrams via multiple sequence alignment. The complexity of DNA recognition may act as an important role in the evolution of gene regulation. Source codes are available at https://github.com/guofei-tju/tfbs.

In Silico Identification of a Key Residue for Substrate Recognition of the Riboflavin Membrane Transporter RFVT3.

Because of its specific physicochemical properties (fluorescence, photosensitizing, and redox reactions), vitamin B2, also called riboflavin (RF), has been generating a lot of interest in the fields of nanotechnology and bioengineering in the last decade. RF, by targeting its riboflavin transporters (RFVTs) overexpressed in some cancers, is particularly used to functionalize nanovectors for anticancer drug delivery. From a physiopathological point of view, an RF deficiency has been implicated in various pathologies, including mendelian diseases. RF deficiency is mainly due to natural variants of its RFVTs that make them inactive and therefore prevent RF transport. The lack of structural data about RFVT is a major drawback for a better understanding of the role of the mutations in the molecular mechanism of these transporters. In this context, this work was aimed at investigating the 3D structure of RFVT3 and its interactions with RF. For this purpose, we used an in silico procedure including protein threading, docking, and molecular dynamics. Our results propose that the natural variant W17R, known to be responsible for the Brown-Vialetto-Van Laere syndrome, prevents the recognition of RF by RFVT3 and thus blocks its transport. This in silico procedure could be used for elucidating the impact of pathogenic mutations of other proteins. Moreover, the identification of RF binding sites will be useful for the design of RF-functionalized nanovectors.

Identification of Chromatin Binding Sites for Long Noncoding RNAs by Chromatin Oligo-Affinity Precipitation (ChOP).

Revealing the interactions of long noncoding RNAs (LncRNAs) with specific genomic regions is of basic importance to explore the mechanisms by which they regulate gene expression. Chromatin oligo-affinity precipitation (ChOP) technique was the first method developed to analyze the association of LncRNAs with genomic regions in the chromatin context. The first step of the procedure is cell cross-linking, aimed at stabilizing the RNA-protein-DNA complexes. Next, after chromatin fragmentation, the RNA complexes are pulled down through hybridization with antisense oligonucleotides tagged with biotin and purification with anti-biotin antibody. After extensive wash, the RNA-interacting chromatin is eluted by RNase treatment. Subsequent protein elimination and DNA purification allow to retrieve DNA fragments for following analyses such as qPCR or sequencing.In the present chapter, we describe the ChOP protocol, as used in our laboratory for investigating the interaction of the LncRNA Kcnq1ot1 with chromatin at specific regulatory regions of the Cdkn1c locus.

A Review About RNA–Protein-Binding Sites Prediction Based on Deep Learning

RNA-binding proteins (RBPs) play crucial roles in gene regulation. The advent of high-throughput experimental methods, has generated a huge volume of experimentally verified binding sites of RNA-binding proteins and greatly advanced the genome-wide studies of RNA-protein interactions. Many computational approaches have been proposed, including deep learning models, which have achieved remarkable performance on the identification of RNA-protein binding affinities and sites. In this review, we discuss machine learning and deep learning approaches, mainly focusing on the prediction of RNA and proteins binding sites on RNAs by deep learning. Furthermore, we discuss the advantages and disadvantages of these approaches. The workflow of deep learning is also revealed. We recommend some promising future directions of deep learning models in the study of RBP-binding sites on RNAs, especially the embedding, generative adversarial net, and attention model. Extraction and visualization methods involving motif are illustrated. Finally, we summarize the previous studies, and then compare the performance on different dataset.

Docking-based identification of small-molecule binding sites at protein-protein interfaces

Protein-protein interactions play an essential role in many biological processes, and their perturbation is a major cause of disease. The use of small molecules to modulate them is attracting increased attention, but protein interfaces generally do not have clear cavities for binding small compounds. A proposed strategy is to target interface hot-spot residues, but their identification through computational approaches usually require the complex structure, which is not often available. In this context, pyDock energy-based docking and scoring can predict hot-spots on the unbound proteins, thus not requiring the complex structure. Here, we have devised a new strategy to detect protein–protein inhibitor binding sites, based on the integration of molecular dynamics for the generation of transient cavities, and docking-based interface hot-spot prediction for the selection of the suitable cavities. This integrative approach has been validated on a test set formed by protein–protein complexes with known inhibitors for which complete structural data of unbound molecules and complexes is available. The results show that local conformational sampling with short molecular dynamics can generate transient cavities similar to the known inhibitor binding sites, and that docking simulations can identify the best cavities with similar predictive accuracy as when knowing the real interface. In a few cases, these predicted pockets are shown to be suitable for protein–ligand docking. The proposed strategy will be useful for many protein–protein complexes for which there is no available structure, as long as the the unbound proteins do not deviate dramatically from the bound conformations.

Screening for a Potential Therapeutic Agent from the Herbal Formula in the 4th Edition of the Chinese National Guidelines for the Initial-Stage Management of COVID-19 via Molecular Docking.

Background COVID-19 caused by SARS-CoV-2 infection has been spreading through many countries since the end of 2019. The 4th edition of the national guidelines for the management of COVID-19 provides an herbal formula with 9 herbs for its management. Aim of Study. We aimed to predict the mechanism of binding of SARS-CoV-2 and SARS-CoV spike glycoproteins with angiotensin-converting enzyme 2 (ACE2) to provide a molecular-level explanation of the higher pathogenicity of SARS-CoV-2 and to identify protein sites which may be targeted by therapeutic agents to disrupt virus-host interactions. Subsequently, we aimed to investigate the formula for the initial-stage management to identify a therapeutic agent with the most likely potential to become pharmaceutical candidate for the management of this disease. Materials and Methods GenBank and SWISS-MODEL were applied for model creation. ClusPro was used for protein-protein docking. PDBePISA was applied for identification of possible binding sites. TCMSP was employed for identification of the chemical compounds. AutoDock Vina together with PyRx was used for the prediction and evaluation of binding pose and affinity to ACE2. SwissADME and PreADME were applied to screening and prediction of the pharmacokinetic properties of the identified chemical compounds. PyMOL was used to visualise the structural models of SARS-CoV-2 and SARS-CoV spike glycoproteins complexed to ACE2 and to examine their interactions. Results SARS-CoV-2 had two chains (labelled chains B and C) which were predicted to bind with ACE2. In comparison, the SARS-CoV had only one chain (labelled chain C) predicted to bind with ACE2. The spike glycoproteins of both viruses were predicted to bind with ACE2 via position 487. Molecular docking screening and pharmacokinetic property prediction of the herbal compounds indicated that atractylenolide III (−9.1 kcal/mol) from Atractylodes lancea (Thunb.) Dc. (Cangzhu) may be a candidate therapeutic agent for initial-stage management. Conclusions Atractylenolide III is predicted to have a strong binding affinity with ACE2 and eligible pharmacokinetic properties, anti-inflammatory effects and antiviral effects in in vitro study, and high distribution on the lungs in in vivo study.

Phote-HrTH (Phormia terraenovae Hypertrehalosaemic Hormone), the Metabolic Hormone of the Fruit Fly: Solution Structure and Receptor Binding Model

Fruit flies are a widely distributed pest insect that pose a significant threat to food security. Flight is essential for the dispersal of the adult flies to find new food sources and ideal breeding spots. The supply of metabolic fuel to power the flight muscles of insects is regulated by adipokinetic hormones (AKHs). The fruit fly, Drosophila melanogaster, has the same AKH that is present in the blowfly, Phormia terraenovae; this AKH has the code-name Phote-HrTH. Binding of the AKH to the extra-cellular binding site of a G protein-coupled receptor causes its activation. In this paper, the structure of Phote-HrTH in sodium dodecyl sulfate (SDS) micelle solution was determined using NMR restrained molecular dynamics. The peptide was found to bind to the micelle and be fairly rigid, with an S2 order parameter of 0.96. The translated protein sequence of the AKH receptor from the fruit fly, D. melanogaster, Drome-AKHR, was used to construct two models of the receptor. It is proposed that these two models represent the active and inactive state of the receptor. The model based on the crystal structure of the β-2 adrenergic receptor was found to bind Phote-HrTH with a binding constant of −102kJmol−1, while the other model, based on the crystal structure of rhodopsin, did not bind the peptide. Under molecular dynamic simulation, in a palmitoyloleoylphosphatidylcholine (POPC) membrane, the receptor complex changed from an inactive to an active state. The identification and characterisation of the ligand binding site of Drome-AKHR provide novel information of ligand–receptor interaction, which could lead to the development of species-specific control substances to use discriminately against the fruit fly.

Insight on Multidrug Resistance and Nanomedicine Approaches to Overcome MDR.

Multidrug resistance (MDR) remains a major obstacle to ensure effective chemotherapy in cancer patients. Several factors could be associated with cancer cells' drug resistance such as overexpression of P-glycoprotein (P-gp), cancer stem cells (CSCs), defect in apoptosis, mutation and alteration in DNA repair pathways, angiogenesis, autophagy, and modulation in metabolic enzymes. Until now, drug efflux by ABC transporters has been a univocal and well-established mechanism of chemotherapeutic associated drug resistance. To explore the mechanics involved in ABC transporter associated drug resistance, many crucial studies have been conducted from identification of drug binding sites to elucidation of their structure. Due to our continuous battle with drug resistance, several strategies have been employed to combat MDR, including P-gp modulators, siRNAs, antibodies, as well as peptides. Furthermore, various nanoparticle and different effective combination nanomedicine strategies also suggest some exciting results. Thus, to improve nanomedicine approaches to overcome MDR, in this evolutionary review, we have focused on fundamentals of possible strategies as well as the latest accomplishments to reverse MDR.

Identification of Novel Cyclin A2 Binding Site and Nanomolar Inhibitors of Cyclin A2-CDK2 Complex.

Given the diverse roles of cyclin A2 both in cell cycle regulation and in DNA damage response, identifying small molecule regulators of cyclin A2 activity carries significant potential to regulate diverse cellular processes in both ageing/neurodegeneration and in cancer. Based on cyclin A2's recently discovered role in DNA repair, we hypothesized that small molecule inhibitors that were predicted to bind to both cyclin A2 and CDK2 will be useful as a radiosensitizer of cancer cells. In this study, we used structure-based drug discovery to find inhibitors that target both cyclin A2 and CDK2. Molecular dynamics simulations were used to generate diverse binding pocket conformations for application of the relaxed complex scheme. We then used structure-based virtual screening to find potential dual cyclin A2 and CDK2 inhibitors. Based on a consensus score of docked poses from Glide and AutoDock Vina, we identified about 40 promising hit compounds, where all PAINS scaffolds were removed from consideration. A biochemical luminescence assay of cyclin A2-CDK2 function was used for experimental verification. Four lead inhibitors of cyclin A2-CDK2 complex have been identified using a relaxed complex scheme virtual screen have been verified in a biochemical luminescence assay of cyclin A2- CDK2 function. Two of the four lead inhibitors had inhibitory concentrations in the nanomolar range. The four cyclin A2-CDK2 complex inhibitors are the first reported inhibitors that were specifically designed not to target the cyclin A2-CDK2 protein-protein interface. Overall, our results highlight the potential of combined advanced computational tools and biochemical verification to discover novel binding scaffolds.

Genome-wide global identification of NRF2 binding sites in A549 non-small cell lung cancer cells by ChIP-Seq reveals NRF2 regulation of genes involved in focal adhesion pathways.

Nuclear factor erythroid-derived-2-like 2(NRF2) regulates its downstream genes through binding with antioxidant responsive elements in their promoter regions. Hyperactivation of NRF2 results in oncogenesis and drug resistance in various cancers including non-small cell lung cancer (NSCLC). However, identification of the genes and pathways regulated by NRF2 in NSCLC warrants further investigation. We investigated the global NRF2 genomic binding sites using the high-throughput ChIP-Seq technique in KEAP1 (Kelch-like ECH-associated protein 1)-mutated A549 (NSCLC) cells. We next carried out an integrated analysis of the ChIP-Seq data with transcriptomic data from A549 cells with NRF2-knockdown and RNA-Seq data from TCGA patients with altered KEAP1 to identify downstream and clinically-correlated genes respectively. Furthermore, we applied transcription factor enrichment analysis, generated a protein-protein interaction network, and used kinase enrichment analysis. Moreover, functional annotation of NRF2 binding sites using DAVID v7 identified the genes involved in focal adhesion. Putative focal adhesion genes regulated by NRF2 were validated using qRT-PCR. Further, we selected one novel conserved focal adhesion gene regulated by NRF2–LAMC1 (laminin subunit gamma 1) and validated it using a reporter assay. Overall, the identification of NRF2 target genes paves the way for identifying the molecular mechanism of NRF2 signaling in NSCLC development and therapy. Moreover, our data highlight the complexity of the pathways regulated by NRF2 in lung tumorigenesis.

Identification of a Cry1Fa binding site of cadherin in Plutella xylostella through fragment exchanging and molecular docking methods

Binding to the cadherin in target pests is the primary step in the action mechanism of Cry toxins, but little is known regarding the interaction of Cry1Fa with cadherin. Our previous study suggested that a Plutella xylostella cadherin fragment (PxCad-TBR) can bind to Cry1Fa, while its homologous fragment (HaCad-TBR) in Helicoverpa armigera cannot. In this study, we expressed two cadherin fragments that combine parts of PxCad-TBR and HaCad-TBR in Escherichia coli and tested their binding to the Cry1Fa. The results showed that the fragment containing amino acids T1202-A1341 of P. xylostella cadherin showed binding ability to Cry1Fa. Furthermore, two regions (V1219-E1233 and D1326-F1337) were predicted as hot spot regions that are involved in the interaction of Cry1Fa and PxCad-TBR with computer-aided molecular docking. We then constructed two PxCad-TBR mutations by fragment exchanging based on the molecular docking results and verified the mutations' binding abilities to the Cry1Fa. The results showed that the region that contains amino acids D1326-F1337 was one important binding site to Cry1Fa in P. xylostella cadherin. These results suggested that a combination of computer-aided molecular docking and fragment exchanging is an effective way to locate the key binding sites of Bt toxins in receptors.

Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites.

The accurate identification of protein-ligand binding sites helps elucidate protein function and facilitate the design of new drugs. Machine-learning-based methods have been widely used for the prediction of protein-ligand binding sites. Nevertheless, the severe class imbalance phenomenon, where the number of nonbinding (majority) residues is far greater than that of binding (minority) residues, has a negative impact on the performance of such machine-learning-based predictors. In this study, we aim to relieve the negative impact of class imbalance by Boosting Multiple Granular Support Vector Machines (BGSVM). In BGSVM, each base SVM is trained on a granular training subset consisting of all minority samples and some reasonably selected majority samples. The efficacy of BGSVM for dealing with class imbalance was validated by benchmarking it with several typical imbalance learning algorithms. We further implemented a protein-nucleotide binding site predictor, called BGSVM-NUC, with the BGSVM algorithm. Rigorous cross-validation and independent validation tests for five types of proteinnucleotide interactions demonstrated that the proposed BGSVM-NUC achieves promising prediction performance and outperforms several popular sequence-based protein-nucleotide binding site predictors. The BGSVM-NUC web server is freely available at http://csbio.njust.edu.cn/bioinf/BGSVM-NUC/ for academic use.

Identification of an allosteric binding site on the human glycine transporter, GlyT2, for bioactive lipid analgesics.

The treatment of chronic pain is poorly managed by current analgesics, and there is a need for new classes of drugs. We recently developed a series of bioactive lipids that inhibit the human glycine transporter GlyT2 (SLC6A5) and provide analgesia in animal models of pain. Here, we have used functional analysis of mutant transporters combined with molecular dynamics simulations of lipid-transporter interactions to understand how these bioactive lipids interact with GlyT2. This study identifies a novel extracellular allosteric modulator site formed by a crevice between transmembrane domains 5, 7, and 8, and extracellular loop 4 of GlyT2. Knowledge of this site could be exploited further in the development of drugs to treat pain, and to identify other allosteric modulators of the SLC6 family of transporters.