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1.
Adv Exp Med Biol ; 1163: 89-105, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31707701

RESUMO

Correlation between an allosteric site and its orthosteric site refers to the phenomenon that perturbations like ligand binding, mutation, or posttranslational modifications at the allosteric site leverage variation in the orthosteric site. Understanding this kind of correlation not only helps to disclose how information is transmitted in allosteric regulation but also provides clues for allosteric drug discovery. This chapter starts with an overview of correlation studies on allosteric and orthosteric sites and then introduces recent progress in evolutionary and simulation-based dynamic studies. Discussions and perspectives on future directions are also given.


Assuntos
Sítio Alostérico , Descoberta de Drogas , Proteínas , Relação Estrutura-Atividade , Regulação Alostérica , Sítios de Ligação , Simulação por Computador , Proteínas/química , Proteínas/genética
2.
Proc Natl Acad Sci U S A ; 116(46): 23264-23273, 2019 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-31662475

RESUMO

Glycolytic enzyme phosphoglycerate mutase 1 (PGAM1) plays a critical role in cancer metabolism by coordinating glycolysis and biosynthesis. A well-validated PGAM1 inhibitor, however, has not been reported for treating pancreatic ductal adenocarcinoma (PDAC), which is one of the deadliest malignancies worldwide. By uncovering the elevated PGAM1 expressions were statistically related to worse prognosis of PDAC in a cohort of 50 patients, we developed a series of allosteric PGAM1 inhibitors by structure-guided optimization. The compound KH3 significantly suppressed proliferation of various PDAC cells by down-regulating the levels of glycolysis and mitochondrial respiration in correlation with PGAM1 expression. Similar to PGAM1 depletion, KH3 dramatically hampered the canonic pathways highly involved in cancer metabolism and development. Additionally, we observed the shared expression profiles of several signature pathways at 12 h after treatment in multiple PDAC primary cells of which the matched patient-derived xenograft (PDX) models responded similarly to KH3 in the 2 wk treatment. The better responses to KH3 in PDXs were associated with higher expression of PGAM1 and longer/stronger suppressions of cancer metabolic pathways. Taken together, our findings demonstrate a strategy of targeting cancer metabolism by PGAM1 inhibition in PDAC. Also, this work provided "proof of concept" for the potential application of metabolic treatment in clinical practice.

3.
Cell Commun Signal ; 17(1): 124, 2019 Oct 10.
Artigo em Inglês | MEDLINE | ID: mdl-31601242

RESUMO

BACKGROUND: Cancer cells undergo global reprogramming of cellular metabolism to satisfy demands of energy and biomass during proliferation and metastasis. Computational modeling of genome-scale metabolic models is an effective approach for designing new therapeutics targeting dysregulated cancer metabolism by identifying metabolic enzymes crucial for satisfying metabolic goals of cancer cells, but nearly all previous studies neglect the existence of metabolic demands other than biomass synthesis and trade-offs between these contradicting metabolic demands. It is thus necessary to develop computational models covering multiple metabolic objectives to study cancer metabolism and identify novel metabolic targets. METHODS: We developed a multi-objective optimization model for cancer cell metabolism at genome-scale and an integrated, data-driven workflow for analyzing the Pareto optimality of this model in achieving multiple metabolic goals and identifying metabolic enzymes crucial for maintaining cancer-associated metabolic phenotypes. Using this workflow, we constructed cell line-specific models for a panel of cancer cell lines and identified lists of metabolic targets promoting or suppressing cancer cell proliferation or the Warburg Effect. The targets were then validated using knockdown and over-expression experiments in cultured cancer cell lines. RESULTS: We found that the multi-objective optimization model correctly predicted phenotypes including cell growth rates, essentiality of metabolic genes and cell line specific sensitivities to metabolic perturbations. To our surprise, metabolic enzymes promoting proliferation substantially overlapped with those suppressing the Warburg Effect, suggesting that simply targeting the overlapping enzymes may lead to complicated outcomes. We also identified lists of metabolic enzymes important for maintaining rapid proliferation or high Warburg Effect while having little effect on the other. The importance of these enzymes in cancer metabolism predicted by the model was validated by their association with cancer patient survival and knockdown and overexpression experiments in a variety of cancer cell lines. CONCLUSIONS: These results confirm this multi-objective optimization model as a novel and effective approach for studying trade-off between metabolic demands of cancer cells and identifying cancer-associated metabolic vulnerabilities, and suggest novel metabolic targets for cancer treatment.

4.
Phys Chem Chem Phys ; 21(36): 19795-19804, 2019 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-31482888

RESUMO

Allostery plays important roles in the regulation of many biological processes, such as signal transduction and transcriptional regulation. Although great advances have been achieved in understanding the allosteric mechanism through experimental and theoretical investigations, the details of the allosteric process are still not clear. Here, using the N-terminal domain of calmodulin (nCaM) as the model protein, we reported the atomic level characterization of the allosteric process induced by Ca2+ binding through extensive and unbiased molecular dynamics simulations. In two trajectories, it was found that Ca2+ first binds to EF-hand 2 and then induces the conformational transformation of nCaM from the Apo to Holo state assisted by second Ca2+ binding to EF-hand 1 completely. The binding order was consistent with a recent experimental result. The simulations also indicated that the two EF-hands changed conformations synergistically and the EF-hand 2 showed an earlier and more gradual conformational transition. Meanwhile, the allosteric process of nCaM triggered by Ca2+ binding might be completed within hundreds of nanoseconds in a two-state-like manner. This was validated by biased simulations, in which the Ca2+ ions were restrained near the binding sites. This work provides the molecular details of the conformational transition of nCaM triggered by Ca2+ binding.


Assuntos
Cálcio/química , Calmodulina/química , Íons/química , Simulação de Acoplamento Molecular , Domínios Proteicos , Ligação Proteica , Conformação Proteica
5.
Acta Pharmacol Sin ; 2019 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-31530902

RESUMO

Chinese herbal medicine (CHM) addresses complex diseases through polypharmacological interactions. However, systematic studies of herbal medicine pharmacology remain challenging due to the complexity of CHM ingredients and their interactions with various targets. In this study, we aim to address this challenge with computational approaches. We investigated the herb-target-disease associations of 197 commonly prescribed CHMs using the similarity ensemble approach and DisGeNET database. We demonstrated that this method can be applied to associate herbs with their putative targets. In the case study of three well-known herbs, Radix Glycyrrhizae, Flos Lonicerae, and Rhizoma Coptidis, approximately 70% of the predicted targets were supported by scientific literature. By linking 406 targets to 2439 annotated diseases, we further analyzed the pharmacological functions of 197 herbs. Finally, we proposed a strategy of target-oriented herbal formula design and illustrated the target profiles for four common chronic diseases, namely, Alzheimer's disease, depressive disorder, hypertensive disease, and non-insulin-dependent diabetes mellitus. This computational approach holds great potential in the target identification of herbs, understanding the molecular mechanisms of CHM, and designing novel herbal formulas.

6.
FEBS Lett ; 593(12): 1292-1302, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31102258

RESUMO

Compared to small molecule drugs, peptide therapeutics provides greater efficacy, selectivity, and safety. The intrinsic disadvantages of peptides are their sensitivity to proteases. To overcome this, we have developed a general computational strategy for de novo design of protein binding helical d-peptides. A d-helical fragment library was established and used in generating flexible d-helical conformations, which were then used to generate suitable sequences with the required structural and binding properties. Using this strategy, we successfully de novo designed d-helical peptides that bind to tumor necrosis factor-α (TNFα), inhibit TNFα-TNFR1 binding, reduce TNFα activity in cellular assays, and are stable against protease digestion. Our strategy of helical d-peptide design is generally applicable for discovering d-peptide modulators against protein-protein interactions.

7.
Biochem Soc Trans ; 47(3): 909-918, 2019 06 28.
Artigo em Inglês | MEDLINE | ID: mdl-31085614

RESUMO

Medical research has identified over 500 brain disorders. Among these, there are still only very few neuropathologies whose causes are fully understood and, consequently, very few drugs whose mechanism of action is known. No FDA drug has been identified for major neurodegenerative diseases, such as Alzheimer's and Parkinson's. We still lack effective treatments and strategies for modulating progression or even early neurodegenerative disease onset diagnostic tools. A great support toward the highly needed identification of neuroactive drugs comes from computer simulation methods and, in particular, from molecular dynamics (MD). This provides insight into structure-function relationship of a target and predicts structure, dynamics and energetics of ligand/target complexes under biologically relevant conditions like temperature and physiological saline concentration. Here, we present examples of the predictive power of MD for neuroactive ligands/target complexes. This brief survey from our own research shows the usefulness of partnerships between academia and industry, and from joint efforts between experimental and theoretical groups.

8.
Ann Rheum Dis ; 78(6): 773-780, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30936065

RESUMO

OBJECTIVE: The strong genetic contribution of the major histocompatibility complex (MHC) region to rheumatoid arthritis (RA) has been generally attributed to human leukocyte antigen (HLA)-DRB1. However, due to the high polymorphisms and linkage disequilibrium within MHC, it is difficult to define novel and/or independent genetic risks using conventional HLA genotyping or chip-based microarray technology. This study aimed to identify novel RA risk variants by performing deep sequencing for MHC. METHODS: We first conducted target sequencing for the entire MHC region in 357 anticitrullinated protein antibodies (ACPA)-positive patients with RA and 1001 healthy controls, and then performed HLA typing in an independent case-control cohort consisting of 1415 samples for validation. All study subjects were Han Chinese. Genetic associations for RA susceptibility and severity were analysed. Comparative modelling was constructed to predict potential functions for the newly discovered RA association variants. RESULTS: HLA-DQα1:160D conferred the strongest and independent susceptibility to ACPA-positive RA (p=6.16×10-36, OR=2.29). DRß1:37N had an independent protective effect (p=5.81×10-16, OR=0.49). As predicted by comparative modelling, the negatively charged DQα1:160D stabilises the dimer of dimers, thus may lead to an increased T cell activation. The negatively charged DRß1:37N encoding alleles preferentially bind with epitope P9 arginine, thus may result in a decreased RA susceptibility. CONCLUSIONS: We provide the first evidence that HLA-DQα1:160D, instead of HLA-DRB1*0405, is the strongest and independent genetic risk for ACPA-positive RA in Han Chinese. Our study also illustrates the value of deep sequencing for fine-mapping disease risk variants in the MHC region.

9.
Analyst ; 144(9): 2881-2890, 2019 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-30788466

RESUMO

Although natural herbs have been a rich source of compounds for drug discovery, identification of bioactive components from natural herbs suffers from low efficiency and prohibitive cost of the conventional bioassay-based screening platforms. Here we develop a new strategy that integrates virtual screening, affinity mass spectrometry (MS) and targeted metabolomics for efficient discovery of herb-derived ligands towards a specific protein target site. Herb-based virtual screening conveniently selects herbs of potential bioactivity whereas affinity MS combined with targeted metabolomics readily screens candidate compounds in a high-throughput manner. This new integrated approach was benchmarked on screening chemical ligands that target the hydrophobic pocket of the nucleoprotein (NP) of Ebola viruses for which no small molecule ligands have been reported. Seven compounds identified by this approach from the crude extracts of three natural herbs were all validated to bind to the NP target in pure ligand binding assays. Among them, three compounds isolated from Piper nigrum (HJ-1, HJ-4 and HJ-6) strongly promoted the formation of large NP oligomers and reduced the protein thermal stability. In addition, cooperative binding between these chemical ligands and an endogenous peptide ligand was observed, and molecular docking was employed to propose a possible mechanism. Taken together, we established a platform integrating in silico and experimental screening approaches for efficient discovery of herb-derived bioactive ligands especially towards non-enzyme protein targets.


Assuntos
Produtos Biológicos/metabolismo , Espectrometria de Massas/métodos , Metabolômica/métodos , Nucleoproteínas/metabolismo , Extratos Vegetais/metabolismo , Proteínas do Core Viral/metabolismo , Sítios de Ligação , Produtos Biológicos/química , Produtos Biológicos/isolamento & purificação , Descoberta de Drogas/métodos , Ebolavirus/química , Ligantes , Simulação de Acoplamento Molecular , Nucleoproteínas/química , Ophiopogon/química , Piper nigrum/química , Componentes Aéreos da Planta/química , Extratos Vegetais/química , Extratos Vegetais/isolamento & purificação , Ligação Proteica , Salvia miltiorrhiza/química , Sementes/química , Proteínas do Core Viral/química
10.
Angew Chem Int Ed Engl ; 58(15): 4858-4862, 2019 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-30762296

RESUMO

Phase separation of proteins/nucleic acids to form non-membrane organelles is crucial in cellular gene-expression regulation. However, little is known about transcriptional regulator phase separation and the underlying molecular mechanism. Vernalization 1 (VRN1) encodes a crucial transcriptional repressor involved in plant vernalization that contains two B3 DNA-binding domains connected by an intrinsic disorder region (IDR) and nonspecifically binds DNA. We found that the Arabidopsis VRN1 protein undergoes liquid-liquid phase separation (LLPS) with DNA that is driven by multivalent protein-DNA interactions (LLPS), and that both B3 domains are required. The distribution of charged residues in the VRN1 IDR modulates the interaction strength between VRN1 and DNA, and changes in the charge pattern lead to interconversion between different states (precipitates, liquid droplets, and no phase separation). We further showed that VRN1 forms puncta in plant cell nuclei, suggesting that it may stabilize the vernalized state by repressing gene expression through LLPS.

11.
Future Med Chem ; 11(6): 567-597, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30698019

RESUMO

De novo drug design aims to generate novel chemical compounds with desirable chemical and pharmacological properties from scratch using computer-based methods. Recently, deep generative neural networks have become a very active research frontier in de novo drug discovery, both in theoretical and in experimental evidence, shedding light on a promising new direction of automatic molecular generation and optimization. In this review, we discussed recent development of deep learning models for molecular generation and summarized them as four different generative architectures with four different optimization strategies. We also discussed future directions of deep generative models for de novo drug design.

12.
Nat Chem Biol ; 15(3): 213-216, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30617292

RESUMO

The identification of host protein substrates is key to understanding effector glycosyltransferases secreted by pathogenic bacteria and to using them for glycoprotein engineering. Here we report a chemical method for tagging, enrichment, and site-specific proteomic profiling of effector-modified proteins in host cells. Using this method, we discover that Legionella effector SetA α-O-glucosylates various eukaryotic proteins by recognizing a S/T-X-L-P/G sequence motif, which can be exploited to site-specifically introduce O-glucose on recombinant proteins.


Assuntos
Glicosiltransferases/metabolismo , Proteínas de Transporte de Monossacarídeos/metabolismo , Engenharia de Proteínas/métodos , Sequência de Aminoácidos , Proteínas de Bactérias , Eucariotos , Glucosiltransferases/metabolismo , Interações Hospedeiro-Patógeno , Legionella/metabolismo , Proteômica , Proteínas Recombinantes
13.
Nat Commun ; 9(1): 5442, 2018 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-30575741

RESUMO

Phosphoglycerate dehydrogenase (PHGDH) catalyzes the committed step in de novo serine biosynthesis. Paradoxically, PHGDH and serine synthesis are required in the presence of abundant environmental serine even when serine uptake exceeds the requirements for nucleotide synthesis. Here, we establish a mechanism for how PHGDH maintains nucleotide metabolism. We show that inhibition of PHGDH induces alterations in nucleotide metabolism independent of serine utilization. These changes are not attributable to defects in serine-derived nucleotide synthesis and redox maintenance, another key aspect of serine metabolism, but result from disruption of mass balance within central carbon metabolism. Mechanistically, this leads to simultaneous alterations in both the pentose phosphate pathway and the tri-carboxylic acid cycle, as we demonstrate based on a quantitative model. These findings define a mechanism whereby disruption of one metabolic pathway induces toxicity by simultaneously affecting the activity of multiple related pathways.


Assuntos
Ciclo do Ácido Cítrico , Nucleotídeos/biossíntese , Via de Pentose Fosfato , Fosfoglicerato Desidrogenase/metabolismo , Células HCT116 , Humanos , Células MCF-7 , Análise do Fluxo Metabólico , Serina/biossíntese
14.
Front Pharmacol ; 9: 1120, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30337875

RESUMO

The anti-oxidative enzyme, glutathione peroxidase 4 (GPX4), helps to promote inflammation resolution by eliminating oxidative species produced by the arachidonic acid (AA) metabolic network. Up-regulating its activity has been proposed as a promising strategy for inflammation intervention. In the present study, we aimed to study the effect of GPX4 activator on the AA metabolic network and inflammation related pathways. Using combined computational and experimental screen, we identified a novel compound that can activate the enzyme activity of GPX4 by more than two folds. We further assessed its potential in a series of cellular assays where GPX4 was demonstrated to play a regulatory role. We are able to show that GPX4 activation suppressed inflammatory conditions such as oxidation of AA and NF-κB pathway activation. We further demonstrated that this GPX4 activator can decrease the intracellular ROS level and suppress ferroptosis. Our study suggests that GPX4 activators can be developed as anti-inflammatory or cyto-protective agent in lipid-peroxidation-mediated diseases.

15.
Science ; 362(6415): 700-705, 2018 11 09.
Artigo em Inglês | MEDLINE | ID: mdl-30287618

RESUMO

The maintenance of autoreactive B cells in a quiescent state is crucial for preventing autoimmunity. Here we identify a variant of human immunoglobulin G1 (IgG1) with a Gly396→Arg substitution (hIgG1-G396R), which positively correlates with systemic lupus erythematosus. In induced lupus models, murine homolog Gly390→Arg (G390R) knockin mice generate excessive numbers of plasma cells, leading to a burst of broad-spectrum autoantibodies. This enhanced production of antibodies is also observed in hapten-immunized G390R mice, as well as in influenza-vaccinated human G396R homozygous carriers. This variant potentiates the phosphorylation of the IgG1 immunoglobulin tail tyrosine (ITT) motif. This, in turn, alters the availability of phospho-ITT to trigger longer adaptor protein Grb2 dwell times in immunological synapses, leading to hyper-Grb2-Bruton's tyrosine kinase (Btk) signaling upon antigen binding. Thus, the hIgG1-G396R variant is important for both lupus pathogenesis and antibody responses after vaccination.

16.
Drug Discov Today ; 2018 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-30278223

RESUMO

Intrinsically disordered proteins or intrinsically disordered regions (IDPs or IDRs) are those that do not fold into defined tertiary structures under physiological conditions. Given their prevalence in various diseases, IDPs are attractive therapeutic targets. However, because of the dynamic nature of the IDP structure, conventional structure-based drug design methods cannot be directly applied. Thanks to recent progress in understanding the mechanisms underlying IDP and ligand interactions, computational strategies for IDP-targeted rational drug discovery are emerging. Here, we summarize recent developments in computational IDP drug design strategies and their successful applications, analyze the typical properties of reported IDP-binding compounds (iIDPs), and discuss the major challenges ahead as well as possible solutions.

17.
Medchemcomm ; 9(2): 239-243, 2018 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-30108917

RESUMO

I kappa B kinase ß (IKKß) is one of the primary targets to regulate canonical NF-κB activity. The misregulation of NF-κB is associated with various diseases, including chronic inflammation and cancers. Most of the known IKKß inhibitors target its active form and suffer from poor selectivity. In the present study, we aim to design inhibitors that can bind to the IKKß inactive form and block its activation. We identified a potential allosteric site between the kinase domain (KD) and ubiquitin-like domain (ULD) of human IKKß and used it to virtually screen a chemical library for allosteric inhibitors. Among the 133 compounds tested, 16 inhibited NF-κB activity by over 50% at 50 µM in a reporter gene assay. Further quantitative measurements and cytotoxicity study gave one compound 124 (3,4-dichloro-2-ethoxy-N-(2,2,6,6-tetramethylpiperidin-4-yl)benzenesulfonamide) which specifically targets the IKKß inactive form. In cells, 124 inhibited IκBα phosphorylation and NF-κB transcriptional activity for the reporter gene with an IC50 of 35 µM by decreasing the phosphorylation level of Ser177/181 on IKKß and blocking its activation upon TNFα stimulation. Molecular dynamics simulations demonstrated that 124 binds to the pocket between KD and ULD in the inactive conformation of IKKß rather than the active conformation. As the first allosteric inhibitor that prevents IKKß activation, 124 provides a good starting point for further inhibitor discovery and a probe for IKKß enzyme cycle and regulatory mechanism study.

18.
Future Med Chem ; 10(18): 2129-2132, 2018 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-30043635
19.
Protein Sci ; 27(9): 1600-1610, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30019371

RESUMO

There are many multidomain allosteric proteins where an allosteric signal at the allosteric domain modifies the activity of the functional domain. Intrinsically disordered regions (linkers) are widely involved in this kind of regulation process, but the essential role they play therein is not well understood. Here, we investigated the effect of linkers in stabilizing the open or the closed states of multidomain proteins using combined thermodynamic deduction and coarse-grained molecular dynamics simulations. We revealed that the influence of linker can be fully characterized by an effective local concentration [B]0 . When Kd is smaller than [B]0 , the closed state would be favored; while the open state would be preferred when Kd is larger than [B]0 . We used four protein systems with markedly different domain-domain binding affinity and structural order/disorder as model systems to understand the relationship between [B]0 and the linker length as well as its flexibility. The linker length is the main practical determinant of [B]0 . [B]0 of a flexible linker with 40-60 residues was determined to be in a narrow range of 0.2-0.6 mM, while a too short or too long length would dramatically decrease [B]0 . With the revealed [B]0 range, the introduction of a flexible linker makes the regulation of weakly interacting partners possible.

20.
Proteins ; 86(10): 1075-1087, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30019778

RESUMO

Many proteins exhibit a critical property called allostery, which enables intra-molecular transmission of information between distal sites. Microscopically, allosteric response is closely related to correlated atomic fluctuations. Conventional correlation analysis correlates the atomic fluctuations at two sites by taking the dot product (DP) between the fluctuations, which accounts only for the parallel and antiparallel components. Here, we present a singular value decomposition (SVD) method that analyzes the correlation coefficient of fluctuation dynamics with an arbitrary angle between the correlated directions. In a model allosteric system, the second PDZ domain (PDZ2) in the human PTP1E protein, approximately one third of the strong correlations have near-perpendicular directions, which are underestimated in the conventional method. The discrimination becomes more prominent for residue pairs with larger separation. The results of the proposed SVD method are more consistent with the experimentally determined PDZ2 dynamics than those of conventional method. In addition, the SVD method improved the prediction accuracy of the allosteric sites in a dataset of 23 known allosteric monomer proteins. The proposed method may inspire extended investigation not only into allostery, but also into protein dynamics and drug design.

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