scholarly journals On the use of the experimentally determined enzyme inhibition constant as a measure of absolute binding affinity

2017 ◽  
Author(s):  
Fouad H. Darras ◽  
Yuan-Ping Pang
Keyword(s):  
Binding Affinity ◽  
Enzyme Inhibition ◽  
Rank Order ◽  
Glass Container ◽  
Inhibition Constant ◽  
State Function ◽  
Binding Affinities ◽  
Nitrobenzoic Acid ◽  
Electrophorus Electricus ◽  
Assay Conditions

ABSTRACTDefined as a state function representing an inhibitor’s absolute affinity for its target enzyme, the experimentally determined enzyme inhibition constant (Ki) is widely used to rank order binding affinities of different inhibitors for a common enzyme or different enzymes for a common inhibitor and to benchmark computational approaches to predicting binding affinity. Herein, we report that adsorption of bis(7)-tacrine to the glass container surface increased its Ki against Electrophorus electricus acetylcholinesterase (eeAChE) to 3.2 ± 0.1 nM (n = 5) compared to 2.9 ± 0.4 pM (n = 5) that was determined using plastic containers with other assay conditions kept the same. We also report that, due to binding or “adsorption” of bis(7)-tacrine to the inactive eeAChE, the bis(7)-tacrine Ki increased from 2.9 ± 0.4 pM (n = 5) to 734 ± 70 pM (n = 5) as the specific eeAChE activity decreased from 342 U/mg to 26 U/mg while other assay conditions were kept the same. These results caution against using Kis to rank order binding potencies, define selectivity, or benchmark computational methods without knowing detailed assay conditions.AbbreviationsKienzyme inhibition constantAChEacetylcholinesteraseeeAChEElectrophorus electricus AChEATChacetylthiocholine chloridebis(7)-tacrine1,7-N-heptylene-bis-9,9'-amino-1,2,3,4-tetrahydro-acridinium dihydrochlorideDTNB5,5’-dithiobis(2-nitrobenzoic acid)SEAspecific enzyme activitytacrine9-amino-1,2,3,4-tetrahydroacridinium monohydrochloride.

scholarly journals SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Surendra Kumar ◽  
Mi-hyun Kim
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Fingerprint Pattern ◽  
Comparable Performance ◽  
Direct Interpretation ◽  
Benchmark Datasets ◽  
Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

scholarly journals Evaluation of Division-Arrested Cells for Cell-Based High-Throughput Screening and Profiling

2005 ◽  
Vol 10 (6) ◽  
pp. 615-623 ◽  
Author(s):  
Mary Ellen Digan ◽  
Chantevy Pou ◽  
Honglin Niu ◽  
Ji-Hu Zhang
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Rank Order ◽  
Kinase Assay ◽  
Just In Time ◽  
Reporter Assay ◽  
A431 Cells ◽  
Dividing Cells ◽  
Epidermal Growth ◽  
Assay Conditions

Just-in-time cell supply for cell-based high-throughput screening (HTS) is frequently problematic. In addition to scheduling and logistical issues, quality issues and variability due to passage effect, cell cycle, or confluency contribute to day-to-day signal variability in the course of cell-based HTS campaigns. Cell division-arrest and cryopreservation technologies permit the use of cells as assay-ready reagents for HTS and other cell-based profiling and structure-activity studies. In this report, the authors compare division-arrested and dividing cells in 2 assay types that are dependent on movement of proteins within or through cell membranes: a receptor tyrosine kinase assay involving A431 cells responsive to epidermal growth factor, and a secretion reporter assay, which measures secretion of a reporter gene, secreted alkaline phosphatase. In both assays, dividing and division-arrested cells yielded similar basal and maximal signals at a given cell density. Similar IC50s were obtained for reference inhibitors in each assay, type in both dividing and division-arrested cells. In addition, for the secretion reporter assay, when comparing IC50s obtained from 44 compounds randomly chosen from a primary screening hit list, the rank order of potency obtained from dividing cells and division-arrested cells was essentially identical. Furthermore, the results show that, under certain assay conditions, data generated using division-arrested cells are less variable than those generated using dividing cells. In summary, the results suggest that, in many cases, division-arrested cells can substitute for dividing cells and offer certain advantages for cell-based assays.

scholarly journals Design of peptides with strong binding affinity to poly(methyl methacrylate) resin by use of molecular simulation-based materials informatics

2021 ◽  
Author(s):  
Tomio Iwasaki ◽  
Masashi Maruyama ◽  
Tatsuya Niwa ◽  
Toshiki Sawada ◽  
Takeshi Serizawa
Keyword(s):  
Methyl Methacrylate ◽  
Binding Affinity ◽  
Molecular Simulation ◽  
Dynamics Simulation ◽  
Binding Affinities ◽  
Materials Informatics ◽  
Poly Methyl Methacrylate ◽  
Strong Binding ◽  
Experimental Values ◽  
Pmma Resin

AbstractPeptides with strong binding affinities for poly(methyl methacrylate) (PMMA) resin were designed by use of materials informatics technology based on molecular dynamics simulation for the purpose of covering the resin surface with adhesive peptides, which were expected to result in eco-friendly and biocompatible biomaterials. From the results of binding affinity obtained with this molecular simulation, it was confirmed that experimental values could be predicted with errors <10%. By analyzing the simulation data with the response-surface method, we found that three peptides (RWWRPWW, EWWRPWR, and RWWRPWR), which consist of arginine (R), tryptophan (W), and proline (P), have strong binding affinity to the PMMA resin. These amino acids were effective because arginine and tryptophan have strong binding affinities for methoxycarbonyl groups and methyl groups, which are the main constituents of the PMMA resin, and proline stabilizes the flat zigzag structures of the peptides in water. The strong binding affinities of the three peptides were confirmed by experiments (surface plasmon resonance methods).

scholarly journals Climbing up and down binding landscapes: a high-throughput study of mutational effects in homologous protein-protein complexes

2020 ◽  
Author(s):  
Michael Heyne ◽  
Jason Shirian ◽  
Itay Cohen ◽  
Yoav Peleg ◽  
Evette S. Radisky ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Protein Interactions ◽  
Enzyme Inhibitor ◽  
Binding Free Energy ◽  
Hot Spot ◽  
Cold Spot ◽  
Binding Affinities ◽  
High Affinity ◽  
Binding Interface ◽  
Biological Complexes

AbstractEach protein-protein interaction (PPI) has evolved to possess binding affinity that is compatible with its cellular function. As such, cognate enzyme/inhibitor interactions frequently exhibit very high binding affinities, while structurally similar non-cognate PPIs possess substantially weaker binding affinities. To understand how slight differences in sequence and structure could lead to drastic changes in PPI binding free energy (ΔΔGbind), we study three homologous PPIs that span nine orders of magnitude in binding affinity and involve a serine protease interacting with an inhibitor BPTI. Using state-of-the-art methodology that combines protein randomization and affinity sorting coupled to next-generation sequencing and data normalization, we report quantitative binding landscapes consisting of ΔΔGbind values for the three PPIs, gleaned from tens of thousands of single and double mutations in the BPTI binding interface. We demonstrate that the three homologous PPIs possess drastically different binding landscapes and lie at different points in respect to the landscape maximum. Furthermore, the three PPIs demonstrate distinct patterns of coupling energies between two simultaneous mutations that depend not only on positions involved but also on the nature of the mutation. Interestingly, we find that in all three PPIs positive epistasis is frequently observed at hot-spot positions where mutations lead to loss of high affinity, while conversely negative epistasis is observed at cold-spot positions, where mutations lead to affinity enhancement. The new insights on PPI evolution revealed in this study will be invaluable in understanding evolution of other biological complexes and can greatly facilitate design of novel high-affinity protein inhibitors.SignificanceProtein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and non-cognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we studied the effect of tens of thousands of single and double mutations on binding affinity of three homologous protease-inhibitor complexes. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to all biological complexes in the cell.

scholarly journals Robust, Efficient and Automated Methods for Accurate Prediction of Protein-Ligand Binding Affinities in AMBER Drug Discovery Boost

2021 ◽  
Author(s):  
Tai-Sung Lee ◽  
Hsu-Chun Tsai ◽  
Abir Ganguly ◽  
Timothy J Giese ◽  
Darrin M. York
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Single Step ◽  
Simulation Software ◽  
Rational Drug Design ◽  
Computer Hardware ◽  
Binding Affinities ◽  
Methodology Development ◽  
Industry Applications

Recent concurrent advances in methodology development, computer hardware and simulation software has transformed our ability to make practical, quantitative predictions of relative ligand binding affinities to guide rational drug design. In the past, these calculations have been hampered by the lack of affordable software with highly efficient implementations of state-of-the-art methods on specialized hardware such as graphical processing units, combined with the paucity of available workflows to streamline throughput for real-world industry applications. Herein we discuss recent methodology development, GPU-accelerated implementation, and workflow creation for alchemical free energy simulation methods in the AMBER Drug Discovery Boost (AMBER-DD Boost) package available as a patch to AMBER20. Among the methodological advances are 1) new methods for the treatment of softcore potentials that overcome long standing end-point catastrophe and softcore imbalance problems and enable single-step alchemical transformations between ligands, and 2) new adaptive enhanced sampling methods in the "alchemical" (or "λ") dimension to accelerate convergence and obtain high precision ligand binding affinity predictions, 3) robust network-wide analysis methods that include cycle closure and reference constraints and restraints, and 4) practical workflows that enable streamlined calculations on large datasets to be performed. Benchmark calculations on various systems demonstrate that these tools deliver an outstanding combination of accuracy and performance, resulting in reliable high-throughput binding affinity predictions at affordable cost.<br>

Electron Transport from QA to Thymoquinone in a Synechococcus Oxygen-Evolving Photosystem II Preparation: Role of QB and Binding Affinity of Thymoquinone to the QB Site

1993 ◽  
Vol 48 (3-4) ◽  
pp. 174-178 ◽  
Author(s):  
Kazuhiko Satoh ◽  
Yasuhiro Kashino ◽  
Hiroyuki Koike
Keyword(s):  
Binding Affinity ◽  
Turnover Rate ◽  
Side Chain ◽  
Head Group ◽  
Binding Affinities ◽  
Ps Ii ◽  
Thermophilic Cyanobacteria ◽  
High Concentrations ◽  
Oxygen Evolving

Abstract We have recently shown that binding affinities of benzoquinones can be estimated by two methods in photosystem (PS) II particles (K. Satoh et al., Biochim. Biophys. Acta 1102, 45-52 (1992)). Using these methods we calculated the binding affinity of thymoquinone (2-methyl-5-isopropyl-p-benzoquinone) to the QB site and studied how the quinone accepts electrons in oxygen-evolving PS II particles isolated from the thermophilic cyanobacteria, Synechococcus elongatus and S. vulcanus. The results are as follows: (1) The binding constant of thymoqui­ none to the QB site determined by several methods was around 0.33 mᴍ . (2) At low thymoquinone concentrations the quinone was supposed to accept electrons via QB-plastoquinone, whereas at high concentrations the quinone seemed to bind to the QB site and accept an electron directly from Q-A. Lower rates of photoreduction of the quinone at high concentrations were attributed to a slower turnover rate of the quinone at the QB site than that of endogenous plastoquinone. (3) A model for the function of plastoquinone at the QB site, which can explain all the results, was presented. According to this model, the plastoquinone molecule at the QB site is not replaced by another plastoquinone molecule. Instead, it transfers electrons to pool plastoquinone molecules by turning over its head group but remaining its long side chain bound to the PS II complexes.

scholarly journals Docking of Platinum Compounds on Cube Rhombellane Functionalized Homeomorphs

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 749
Author(s):  
Beata Szefler ◽  
Przemysław Czeleń
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonds ◽  
Binding Affinity ◽  
Fullerene C60 ◽  
C60 Fullerene ◽  
Binding Affinities ◽  
Hydrogen Bond Network ◽  
Platinum Compounds ◽  
Anti Cancer ◽  
Bond Network

Platinum compounds are anti-cancer drugs and can bind to canonical purine bases, mainly guanine, found within double helical DNA. Platinum compounds can be transferred directly to pathologically altered sites in a specific and site-oriented manner by nanocarriers as potential nanocarriers for carboplatin. Two types of nanostructures were used as potential nanocarriers for carboplatin, the first were functionalized C60 fullerene molecules and the second were rhombellanes. The analyzed nanostructures show considerable symmetry, which affects the affinity of the studied nanocarriers and ligands. Thus symmetry of nanostructures affects the distribution of binding groups on their surface. After the docking procedure, analysis of structural properties revealed many interesting features. In all described cases, binding affinities of complexes of platinum compounds with functionalized fullerene C60 are higher compared with affinities of complexes of platinum compounds with rhombellane structures. All platinum compounds easily create complexes with functionalized fullerene C60, CID_16156307, and at the same time show the highest binding affinity. The binding affinities of lobaplatin and heptaplatin are higher compared with oxaliplatin and nedaplatin. The high value of binding affinity and equilibrium constant K is correlated with creation of strong and medium hydrogen bonds or is correlated with forming a hydrogen bond network. The performed investigations enabled finding nanocarriers for lobaplatin, heptaplatin, oxaliplatin and nedaplatin molecules.

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