Atomic resolution structure of biotin-free Tyr43Phe streptavidin: what is in the binding site?

1999 ◽  
Vol 55 (6) ◽  
pp. 1118-1126 ◽  
Author(s):  
Stefanie Freitag ◽  
Isolde Le Trong ◽  
Lisa A. Klumb ◽  
Patrick S. Stayton ◽  
Ronald E. Stenkamp
Keyword(s):  
Binding Pocket ◽  
Crystal Form ◽  
Atomic Resolution ◽  
Side Chain ◽  
High Resolution Data ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Biotin Binding ◽  
The Impact ◽  
First Time

The streptavidin–biotin system is an example of a high-affinity protein–ligand pair (Ka ≃ 1013 mol−1). The thermodynamic and structural properties have been extensively studied as a model system for protein–ligand interactions. Here, the X-ray crystal structure of a streptavidin mutant of a residue hydrogen bonding to biotin [Tyr43Phe (Y43F)] is reported at atomic resolution (1.14 Å). The biotin-free structure was refined with anisotropic displacement parameters (using the SHELXL97 program package). The high-resolution data also allowed interpretation of side-chain and residue disorder in 41 residues where alternate conformations were refined. The Y43F mutation is unambiguously observed in difference maps, although only a single O atom per monomer is altered. The atomic resolution enabled the identification of 2-methyl-2,4-pentanediol (MPD) molecules in the biotin-binding pocket for the first time. Electron density for MPD was observed in all four subunit binding sites of the tetrameric protein. This was not possible with data at lower resolution (1.8–2.3 Å) for wild-type streptavidin or mutants in the same crystal form using MPD in the crystallization. The impact of MPD binding on these studies is discussed.

scholarly journals Structural Basis of Enantioselective Inhibition of Cyclooxygenase-1 by S-α-Substituted Indomethacin Ethanolamides

2007 ◽  
Vol 282 (38) ◽  
pp. 28096-28105 ◽  
Author(s):  
Christine A. Harman ◽  
Melissa V. Turman ◽  
Kevin R. Kozak ◽  
Lawrence J. Marnett ◽  
William L. Smith ◽  
...  
Keyword(s):  
Binding Pocket ◽  
Drug Binding ◽  
Structural Basis ◽  
Cyclooxygenase 1 ◽  
Cox 2 ◽  
The Impact ◽  
First Time ◽  
Side Pocket ◽  
Cox 1 ◽  
Equal Efficacy

The modification of the nonselective nonsteroidal anti-inflammatory drug, indomethacin, by amidation presents a promising strategy for designing novel cyclooxygenase (COX)-2-selective inhibitors. A series of α-substituted indomethacin ethanolamides, which exist as R/S-enantiomeric pairs, provides a means to study the impact of stereochemistry on COX inhibition. Comparative studies revealed that the R- and S-enantiomers of the α-substituted analogs inhibit COX-2 with almost equal efficacy, whereas COX-1 is selectively inhibited by the S-enantiomers. Mutagenesis studies have not been able to identify residues that manifest the enantioselectivity in COX-1. In an effort to understand the structural impact of chirality on COX-1 selectivity, the crystal structures of ovine COX-1 in complexes with an enantiomeric pair of these indomethacin ethanolamides were determined at resolutions between 2.75 and 2.85Å. These structures reveal unique, enantiomer-selective interactions within the COX-1 side pocket region that stabilize drug binding and account for the chiral selectivity observed with the (S)-α-substituted indomethacin ethanolamides. Kinetic analysis of binding demonstrates that both inhibitors bind quickly utilizing a two-step mechanism. However, the second binding step is readily reversible for the R-enantiomer, whereas for the S-enantiomer, it is not. These studies establish for the first time the structural and kinetic basis of high affinity binding of a neutral inhibitor to COX-1 and demonstrate that the side pocket of COX-1, previously thought to be sterically inaccessible, can serve as a binding pocket for inhibitor association.

scholarly journals Footprinting of Inhibitor Interactions ofIn SilicoIdentified Inhibitors of Trypanothione Reductase ofLeishmaniaParasite

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Santhosh K. Venkatesan ◽  
Vikash Kumar Dubey
Keyword(s):  
Virtual Screening ◽  
Leishmania Infantum ◽  
Trypanothione Reductase ◽  
Inhibition Kinetics ◽  
Screening Process ◽  
Protein Ligand Interactions ◽  
Enzymatic Reduction ◽  
Ligand Interactions ◽  
First Time

Structure-based virtual screening of NCI Diversity set II compounds was performed to indentify novel inhibitor scaffolds of trypanothione reductase (TR) fromLeishmania infantum. The top 50 ranked hits were clustered using the AuPoSOM tool. Majority of the top-ranked compounds were Tricyclic. Clustering of hits yielded four major clusters each comprising varying number of subclusters differing in their mode of binding and orientation in the active site. Moreover, for the first time, we report selected alkaloids and dibenzothiazepines as inhibitors ofLeishmania infantumTR. The mode of binding observed among the clusters also potentiates the probablein vitroinhibition kinetics and aids in defining key interaction which might contribute to the inhibition of enzymatic reduction of T[S] 2. The method provides scope for automation and integration into the virtual screening process employing docking softwares, for clustering the small molecule inhibitors based upon protein-ligand interactions.

scholarly journals A systematic analysis of atomic protein–ligand interactions in the PDB

MedChemComm ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 1970-1981 ◽  
Author(s):  
Renato Ferreira de Freitas ◽  
Matthieu Schapira
Keyword(s):  
Small Molecule ◽  
Interaction Type ◽  
Systematic Analysis ◽  
Protein Ligand Interactions ◽  
Atom Pairs ◽  
Atomic Interactions ◽  
Small Molecule Ligands ◽  
Ligand Interactions ◽  
The Impact ◽  
Protein Atom

We compiled a list of 11 016 unique structures of small-molecule ligands bound to proteins representing 750 873 protein–ligand atomic interactions, and analyzed the frequency, geometry and the impact of each interaction type. The most frequent ligand–protein atom pairs can be clustered into seven interaction types.

scholarly journals Probing molecular specificity with deep sequencing and biophysically interpretable machine learning

2021 ◽  
Author(s):  
H. Tomas Rube ◽  
Chaitanya Rastogi ◽  
Siqian Feng ◽  
Judith Franziska Kribelbauer ◽  
Allyson Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Biological Networks ◽  
Specific Protein ◽  
Biophysical Parameters ◽  
Kinase Substrate ◽  
Protein Ligand Interactions ◽  
Sequence Recognition ◽  
Ligand Interactions ◽  
The Impact

Quantifying sequence-specific protein-ligand interactions is critical for understanding and exploiting numerous cellular processes, including gene regulation and signal transduction. Next-generation sequencing (NGS) based assays are increasingly being used to profile these interactions with high-throughput. However, these assays do not provide the biophysical parameters that have long been used to uncover the quantitative rules underlying sequence recognition. We developed a highly flexible machine learning framework, called ProBound, to define sequence recognition in terms of biophysical parameters based on NGS data. ProBound quantifies transcription factor (TF) behavior with models that accurately predict binding affinity over a range exceeding that of previous resources, captures the impact of DNA modifications and conformational flexibility of multi-TF complexes, and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with a new assay called Kd-seq, it determines the absolute affinity of protein-ligand interactions. It can also profile the kinetics of kinase-substrate interactions. By constructing a biophysically robust foundation for profiling sequence recognition, ProBound opens up new avenues for decoding biological networks and rationally engineering protein-ligand interactions.

scholarly journals How far are we in the rapid prediction of drug resistance caused by kinase mutations?

2020 ◽  
Author(s):  
Mehmet Erguven ◽  
Tülay Karakulak ◽  
M. Kasim Diril ◽  
Ezgi Karaca
Keyword(s):  
Protein Kinase ◽  
Protein Kinases ◽  
Binding Affinity ◽  
Point Mutations ◽  
Binding Pocket ◽  
Functional Study ◽  
Web Based ◽  
Diverse Range ◽  
Ligand Interactions ◽  
The Impact

ABSTRACTProtein kinases regulate various cell signaling events in a diverse range of species through phosphorylation. The phosphorylation occurs upon transferring the terminal phosphate of an ATP molecule to a designated target residue. Due to the central role of protein kinases in proliferative pathways, point mutations occurring within or in the vicinity of ATP binding pocket can render the enzyme overactive, leading to cancer. Combatting such mutation-induced effects with the available drugs has been a challenge, since these mutations usually happen to be drug resistant. Therefore, the functional study of naturally and/or artificially occurring kinase mutations have been at the center of attention in diverse biology-related disciplines. Unfortunately, rapid experimental exploration of the impact of such mutations remains to be a challenge due to technical and economical limitations. Therefore, the availability of kinase-ligand binding affinity prediction tools is of great importance. Within this context, we have tested six state-of-the-art web-based affinity predictors (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations with their ligand interactions. This assessment is performed on our structure-based protein kinase mutation benchmark, BINDKIN. BINDKIN contains 23 wild type-mutant pairs of kinase-small molecule complexes, together with their corresponding binding affinity data (in the form of IC50, Kd, and Ki). The web-server performances over BINDKIN show that the raw server predictions fail to produce good correlations with the experimental data. However, when we start looking in to the direction of change (whether a mutation improves/worsens the binding), we observe that over Ki data, DSX-ONLINE achieves a Pearson’s R correlation coefficient of 0.97. When we used homology models instead of crystal structures, this correlation drops to 0.45. These results highlight that there is still room to improve the available web-based predictors to estimate the impact of protein kinase point mutations. We present our BINDKIN benchmark and all the related results online for the sake of aiding such improvement efforts. Our files can be reached at https://github.com/CSB-KaracaLab/BINDKIN

scholarly journals Pillar[5]arene-Derived endo-Functionalized Molecular Tube for Mimicking Protein-Ligand Interactions

2021 ◽  
Author(s):  
Ke Wen ◽  
Zhuo Wang ◽  
Tao Chen ◽  
Hua Liu ◽  
Yahu Liu ◽  
...  
Keyword(s):  
Protein Binding ◽  
Binding Affinity ◽  
Binding Pocket ◽  
Model Systems ◽  
Enzymatic Reactions ◽  
Protein Ligand Interactions ◽  
Donor And Acceptor ◽  
Inner Surface ◽  
Ligand Interactions ◽  
Molecular Tube

Abstract Artificial tubular molecular pockets bearing polar functionalities on their inner surface are useful model systems for understanding the mechanisms of protein-ligand interactions in living systems. We herein report a pillar[5]arene-derived molecular tube, [P4-(OH)BPO], whose endo conformational isomer endo-[P4-(OH)BPO] possesses an inwardly pointing hydrogen-bond (H-bond) donor (OH) in its deep cavity, a strong H-bond acceptor (C=O) on the predominantly hydrophobic inner surface, rendering it a perfect protein binding pocket mimetic. By measuring the binding affinity of this pocket-mimetic tube, we screened a library of various shape-complementary organic guests (1–38) resembling the fragment ligands in fragment-based drug design (FBDD). On the basis of the data for “fragment-pocket” complexes (1–38)⊂endo-[P4-(OH)BPO], two rationally designed “lead molecules” (39 and 40) were identified to be able to enhance binding affinity significantly by forming H-bonds with both the donor and acceptor of endo-[P4-(OH)BPO]. The described work opens new avenues for developing pillar[n]arene-derived protein binding pocket-mimetic systems for studies on protein-ligand interactions and mechanisms of enzymatic reactions.

scholarly journals Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis

2020 ◽  
Author(s):  
Neil A. McCracken ◽  
Sarah A. Peck Justice ◽  
Aruna B. Wijeratne ◽  
Amber L. Mosley
Keyword(s):  
Data Analysis ◽  
Proteome Profiling ◽  
Protein Ligand Interactions ◽  
Calculation Step ◽  
Ligand Interactions ◽  
Analysis Workflow ◽  
Cellular Context ◽  
Essential Resource ◽  
Key Steps ◽  
The Impact

ABSTRACTThe use of CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impacts the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and will make the R based program Inflect available for research community use. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared towards specific applications.

scholarly journals Protonation of Glutamate 208 Induces the Release of Agmatine in an Outward-facing Conformation of an Arginine/Agmatine Antiporter

2011 ◽  
Vol 286 (22) ◽  
pp. 19693-19701 ◽  
Author(s):  
Elia Zomot ◽  
Ivet Bahar
Keyword(s):  
Binding Pocket ◽  
Substrate Binding Pocket ◽  
Time Resolved ◽  
Extracellular Region ◽  
Acidic Conditions ◽  
Using Data ◽  
Dynamics Simulations ◽  
The Impact ◽  
First Time

Virulent enteric pathogens have developed several systems that maintain intracellular pH to survive extreme acidic conditions. One such mechanism is the exchange of arginine (Arg+) from the extracellular region with its intracellular decarboxylated form, agmatine (Agm2+). The net result of this process is the export of a virtual proton from the cytoplasm per antiport cycle. Crystal structures of the arginine/agmatine antiporter from Escherichia coli, AdiC, have been recently resolved in both the apo and Arg+-bound outward-facing conformations, which permit us to assess for the first time the time-resolved mechanisms of interactions that enable the specific antiporter functionality of AdiC. Using data from ∼1 μs of molecular dynamics simulations, we show that the protonation of Glu-208 selectively causes the dissociation and release of Agm2+, but not Arg+, to the cell exterior. The impact of Glu-208 protonation is transmitted to the substrate binding pocket via the reorientation of Ile-205 carbonyl group at the irregular portion of transmembrane (TM) helix 6. This effect, which takes place only in the subunits where Agm2+ is released, invites attention to the functional role of the unwound portion of TM helices (TM6 Trp-202–Glu-208 in AdiC) in facilitating substrate translocation, reminiscent of the behavior observed in structurally similar Na+-coupled transporters.

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