Correlating drug–target kinetics and in vivo pharmacodynamics: long residence time inhibitors of the FabI enoyl-ACP reductase

The kinetics of drug binding and unbinding is assuming an increasingly crucial role in the long, costly process of bringing a new medicine to patients. For example, the time a drug spends in contact with its biological target is known as residence time (the inverse of the kinetic constant of the drug-target unbinding, 1/ koff). Recent reports suggest that residence time could predict drug efficacy in vivo, perhaps even more effectively than conventional thermodynamic parameters (free energy, enthalpy, entropy). There are many experimental and computational methods for predicting drug-target residence time at an early stage of drug discovery programs. Here, we review and discuss the methodological approaches to estimating drug binding kinetics and residence time. We first introduce the theoretical background of drug binding kinetics from a physicochemical standpoint. We then analyze the recent literature in the field, starting from the experimental methodologies and applications thereof and moving to theoretical and computational approaches to the kinetics of drug binding and unbinding. We acknowledge the central role of molecular dynamics and related methods, which comprise a great number of the computational methods and applications reviewed here. However, we also consider kinetic Monte Carlo. We conclude with the outlook that drug (un)binding kinetics may soon become a go/no go step in the discovery and development of new medicines.

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Structure-Unbinding Kinetics Relationship of p38α MAPK Inhibitors

10.1101/510255 ◽

2019 ◽

Author(s):

Xiaoxia Ge ◽

Hepan Tan ◽

Lei Xie

Keyword(s):

Residence Time ◽

Drug Target ◽

Kinase Inhibitors ◽

Drug Efficacy ◽

Distinct Type ◽

Rational Drug Design ◽

Average Lifetime ◽

Kinetics Of

AbstractRational Drug Design still faces a major hurdle for the prediction of drug efficacyin vivosolely based on its binding affinity for the targetin vitro. The traditional perspective has proven to be inadequate as it lacks the consideration of essential aspects such as pharmacokinetics and binding kinetics in determining drug efficacy and toxicity. Residence time, the average lifetime of drug-target complex, has gained broader recognition as a better predictor for lead optimization. Long residence time could contribute to sustained pharmacological effect and may mitigate off-target toxicity as well. To unravel the underlining mechanism for variation of residence time and determine the ligand features governing the unbinding kinetics, unbinding kinetics of two distinct type II inhibitors of p38α MAP kinase were investigated and compared by molecular dynamics and metadynamics simulation approaches. Free energy landscape of key motions associated with unbinding was constructed for both inhibitors. Multiple unbinding pathways and rebinding were revealed during the drug-target dissociation process of faster unbinder Lig3 and slower unbinder Lig8 respectively, suggesting a novel mechanism of unbinding kinetics. This comparative study implies that hydrophobic and hydrogen-bonding interactions in the R1 group of ligands are crucial for slow unbinding. Such kind of structure-kinetics relationship approaches could also be applied to predict unbinding pathways and kinetics of many other small molecules, and facilitate the design of efficient kinase inhibitors.

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Drug-Target Residence Time Affects in Vivo Target Occupancy through Multiple Pathways

ACS Central Science ◽

10.1021/acscentsci.9b00770 ◽

2019 ◽

Vol 5 (9) ◽

pp. 1614-1624 ◽

Cited By ~ 6

Author(s):

Kin Sing Stephen Lee ◽

Jun Yang ◽

Jun Niu ◽

Connie J. Ng ◽

Karen M. Wagner ◽

...

Keyword(s):

Residence Time ◽

Drug Target

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Faculty Opinions recommendation of The drug-target residence time model: a 10-year retrospective.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726022688.793512630 ◽

2015 ◽

Author(s):

John Lowe

Keyword(s):

Residence Time ◽

Drug Target ◽

Time Model

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Sulpiride Serves, a Substrate for the Gut Microbiome

Dose-Response ◽

10.1177/1559325820987943 ◽

2021 ◽

Vol 19 (1) ◽

pp. 155932582098794

Author(s):

Imran Mukhtar ◽

Haseeb Anwar ◽

Osman Asghar Mirza ◽

Qasim Ali ◽

Muhammad Umar Ijaz ◽

...

Keyword(s):

Oral Administration ◽

Gut Microbiome ◽

Drug Target ◽

Membrane Transporters ◽

Intestinal Microbiome ◽

Albino Rats ◽

Body Organ ◽

Total Absorbance ◽

Research World

In the contemporary research world, the intestinal microbiome is now envisioned as a new body organ. Recently, the gut microbiome represents a new drug target in the gut, since various orthologues of intestinal drug transporters are also found present in the microbiome that lines the small intestine of the host. Owing to this, absorbance of sulpiride by the gut microbiome in an in vivo albino rats model was assessed after the oral administration with a single dose of 20mg/kg b.w. The rats were subsequently sacrificed at 2, 3, 4, 5 and 6 hours post oral administration to collect the gut microbial mass pellet. The drug absorbance by the gut microbiome was determined by pursuing the microbial lysate through RP-HPLC-UV. Total absorbance of sulpiride by the whole gut microbiome and drug absorbance per milligram of microbial pellet were found significantly higher at 4 hours post-administration as compared to all other groups. These results affirm the hypothesis that the structural homology between membrane transporters of the gut microbiome and intestinal epithelium of the host might play an important role in drug absorbance by gut microbes in an in vivo condition.

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A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

Cancers ◽

10.3390/cancers13092111 ◽

2021 ◽

Vol 13 (9) ◽

pp. 2111

Author(s):

Bo-Wei Zhao ◽

Zhu-Hong You ◽

Lun Hu ◽

Zhen-Hao Guo ◽

Lei Wang ◽

...

Keyword(s):

Drug Target ◽

Large Scale ◽

Computational Models ◽

Structural Information ◽

Characteristic Curve ◽

Representation Learning ◽

Graph Representation ◽

Convolutional Network ◽

Novel Method

Identification of drug-target interactions (DTIs) is a significant step in the drug discovery or repositioning process. Compared with the time-consuming and labor-intensive in vivo experimental methods, the computational models can provide high-quality DTI candidates in an instant. In this study, we propose a novel method called LGDTI to predict DTIs based on large-scale graph representation learning. LGDTI can capture the local and global structural information of the graph. Specifically, the first-order neighbor information of nodes can be aggregated by the graph convolutional network (GCN); on the other hand, the high-order neighbor information of nodes can be learned by the graph embedding method called DeepWalk. Finally, the two kinds of feature are fed into the random forest classifier to train and predict potential DTIs. The results show that our method obtained area under the receiver operating characteristic curve (AUROC) of 0.9455 and area under the precision-recall curve (AUPR) of 0.9491 under 5-fold cross-validation. Moreover, we compare the presented method with some existing state-of-the-art methods. These results imply that LGDTI can efficiently and robustly capture undiscovered DTIs. Moreover, the proposed model is expected to bring new inspiration and provide novel perspectives to relevant researchers.

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Formulation and evaluation of effervescent floating tablets of tizanidine hydrochloride

Acta Pharmaceutica ◽

10.2478/v10007-011-0015-5 ◽

2011 ◽

Vol 61 (2) ◽

pp. 217-226 ◽

Cited By ~ 7

Author(s):

Komuravelly Someshwar ◽

Kalyani Chithaluru ◽

Tadikonda Ramarao ◽

K. Kumar

Keyword(s):

Drug Release ◽

Residence Time ◽

Release Kinetics ◽

Hydroxypropyl Methylcellulose ◽

Matrix Tablets ◽

Physical Parameters ◽

Floating Tablets ◽

Gastric Residence Time

Formulation and evaluation of effervescent floating tablets of tizanidine hydrochloride Tizanidine hydrochloride is an orally administered prokinetic agent that facilitates or restores motility through-out the length of the gastrointestinal tract. The objective of the present investigation was to develop effervescent floating matrix tablets of tizanidine hydrochloride for prolongation of gastric residence time in order to overcome its low bioavailability (34-40 %) and short biological half life (4.2 h). Tablets were prepared by the direct compression method, using different viscosity grades of hydroxypropyl methylcellulose (HPMC K4M, K15M and K100M). Tablets were evaluated for various physical parameters and floating properties. Further, tablets were studied for in vitro drug release characteristics in 12 hours. Drug release from effervescent floating matrix tablets was sustained over 12 h with buoyant properties. DSC study revealed that there is no drug excipient interaction. Based on the release kinetics, all formulations best fitted the Higuchi, first-order model and non-Fickian as the mechanism of drug release. Optimized formulation (F9) was selected based on the similarity factor (f2) (74.2), dissolution efficiency at 2, 6 and 8 h, and t50 (5.4 h) and was used in radiographic studies by incorporating BaSO4. In vivo X-ray studies in human volunteers showed that the mean gastric residence time was 6.2 ± 0.2 h.

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Preclinical Assessment of Nanostructured Liquid Crystalline Particles for the Management of Bacterial Keratitis: in-vivo and Pharmacokinetics Study

10.21203/rs.3.rs-481365/v1 ◽

2021 ◽

Author(s):

Shreya Kaul ◽

Upendra Nagaich ◽

Navneet Verma

Keyword(s):

Residence Time ◽

Liquid Crystalline ◽

Ex Vivo ◽

Research Work ◽

Poloxamer 407 ◽

Pharmacokinetic Studies ◽

Eye Drops ◽

Statistical Experimental Design ◽

Bacterial Keratitis

Abstract The research work was driven to develop novel nanostructured liquid crystalline particles of vancomycin for its improved pre-ocular residence time, ocular bio-availability, enhanced targeting, increased permeability, reduced dosing frequency, controlled drug release and reduced systemic side-effects. Formulation was developed by fragmenting cubic crystalline phase of glycerol monooleate, water and poloxamer 407. A four-factor, three-level Taguchi statistical experimental design was constructed to optimize the formulation. Formulations exhibited internal-cubic structure of the vesicles with particle size in the range of 51.11 ± 0.96 nm to 158.73 ± 0.46 nm and negative zeta potential. Ex-vivo transcorneal permeation studies demonstrated that the optimized cubosomes had 2.4-fold increase in apparent permeability co-efficient as compared to vancomycin solution. Whereas, in-vivo studies in rabbits demonstrated that the severity of keratitis was considerably lowered in day 3 with optimized cubosomes. Ocular pharmacokinetic studies evaluated level of drug in aqueous humor and results revealed that the time to peak concentration (Tmax) of vancomycin loaded cubosomal formulation was about 1.9-fold higher and mean residence time was 2.2-fold greater than vancomycin solution. Furthermore, histological examination revealed that the corneal layers displayed well-maintained morphology without any stromal swelling, consequently indicating safety of formulation. In conclusion, results manifested that the developed vancomycin loaded cubosomes could be a promising novel ocular carrier and an ideal substitute for conventional eye-drops for the management of bacterial-keratitis.

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Single molecule tracking of Ace1p in Saccharomyces cerevisiae defines a characteristic residence time for non-specific interactions of transcription factors with chromatin

Nucleic Acids Research ◽

10.1093/nar/gkw744 ◽

2016 ◽

Vol 44 (21) ◽

pp. e160-e160 ◽

Cited By ~ 23

Author(s):

David A Ball ◽

Gunjan D Mehta ◽

Ronit Salomon-Kent ◽

Davide Mazza ◽

Tatsuya Morisaki ◽

...

Keyword(s):

Transcription Factors ◽

Residence Time ◽

Single Molecule ◽

Specific Binding ◽

Underlying Mechanism ◽

Specific Interactions ◽

Single Molecule Tracking ◽

Reliable Performance ◽

Transient Interactions

Abstract In vivo single molecule tracking has recently developed into a powerful technique for measuring and understanding the transient interactions of transcription factors (TF) with their chromatin response elements. However, this method still lacks a solid foundation for distinguishing between specific and non-specific interactions. To address this issue, we took advantage of the power of molecular genetics of yeast. Yeast TF Ace1p has only five specific sites in the genome and thus serves as a benchmark to distinguish specific from non-specific binding. Here, we show that the estimated residence time of the short-residence molecules is essentially the same for Hht1p, Ace1p and Hsf1p, equaling 0.12–0.32 s. These three DNA-binding proteins are very different in their structure, function and intracellular concentration. This suggests that (i) short-residence molecules are bound to DNA non-specifically, and (ii) that non-specific binding shares common characteristics between vastly different DNA-bound proteins and thus may have a common underlying mechanism. We develop new and robust procedure for evaluation of adverse effects of labeling, and new quantitative analysis procedures that significantly improve residence time measurements by accounting for fluorophore blinking. Our results provide a framework for the reliable performance and analysis of single molecule TF experiments in yeast.

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