scholarly journals An automated protocol for modelling peptide substrates to proteases

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Rodrigo Ochoa ◽  
Mikhail Magnitov ◽  
Roman A. Laskowski ◽  
Pilar Cossio ◽  
Janet M. Thornton
Keyword(s):  
Substrate Recognition ◽  
Accessible Surface Area ◽  
Conformational Sampling ◽  
Structural Determinants ◽  
Peptide Substrates ◽  
The Family ◽  
Protease Substrate ◽  
Peptide Complexes ◽  
Accessible Surface ◽  
Automated Protocol

Abstract Background Proteases are key drivers in many biological processes, in part due to their specificity towards their substrates. However, depending on the family and molecular function, they can also display substrate promiscuity which can also be essential. Databases compiling specificity matrices derived from experimental assays have provided valuable insights into protease substrate recognition. Despite this, there are still gaps in our knowledge of the structural determinants. Here, we compile a set of protease crystal structures with bound peptide-like ligands to create a protocol for modelling substrates bound to protease structures, and for studying observables associated to the binding recognition. Results As an application, we modelled a subset of protease–peptide complexes for which experimental cleavage data are available to compare with informational entropies obtained from protease–specificity matrices. The modelled complexes were subjected to conformational sampling using the Backrub method in Rosetta, and multiple observables from the simulations were calculated and compared per peptide position. We found that some of the calculated structural observables, such as the relative accessible surface area and the interaction energy, can help characterize a protease’s substrate recognition, giving insights for the potential prediction of novel substrates by combining additional approaches. Conclusion Overall, our approach provides a repository of protease structures with annotated data, and an open source computational protocol to reproduce the modelling and dynamic analysis of the protease–peptide complexes.

scholarly journals Molecular Determinants of the Kinetic Binding Properties of Antihistamines at the Histamine H1 Receptors

2021 ◽  
Vol 22 (5) ◽  
pp. 2400
Author(s):  
Hayato Akimoto ◽  
Yoshihiro Uesawa ◽  
Shigeru Hishinuma
Keyword(s):  
Surface Area ◽  
Accessible Surface Area ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Surface ◽  
Structural Determinants ◽  
Binding Properties ◽  
Duration Of Action ◽  
Accessible Surface ◽  
Binding Enthalpy ◽  
Histamine H1 Receptors

The binding affinity of ligands for their receptors is determined by their kinetic and thermodynamic binding properties. Kinetic analyses of the rate constants of association and dissociation (kon and koff, respectively) of antihistamines have suggested that second-generation antihistamines have a long duration of action owing to the long residence time (1/koff) at the H1 receptors. In this study, we examined the relationship between the kinetic and thermodynamic binding properties of antihistamines, followed by an evaluation of the structural determinants responsible for their kinetic binding properties using quantitative structure–activity relationship (QSAR) analyses. We found that whereas the binding enthalpy and entropy might contribute to the increase and decrease, respectively, in the koff values, there was no significant relationship with the kon values. QSAR analyses indicated that kon and koff values could be determined by the descriptors FASA_H (water-accessible surface area of all hydrophobic atoms divided by total water-accessible surface area) and vsurf_CW2 (a 3D molecular field descriptor weighted by capacity factor 2, the ratio of the hydrophilic surface to the total molecular surface), respectively. These findings provide further insight into the mechanisms by which the kinetic binding properties of antihistamines are regulated by their thermodynamic binding forces and physicochemical properties.

scholarly journals Identifying signatures of proteolytic stability and monomeric propensity in O-glycosylated insulin using molecular simulation

2021 ◽  
Author(s):  
Wei-Tse Hsu ◽  
Dominique Ramirez ◽  
Tarek Sammakia ◽  
Zhongping Tan ◽  
Michael Shirts
Keyword(s):  
Molecular Design ◽  
Experimental Studies ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Structural Determinants ◽  
Rational Molecular Design ◽  
Proteolytic Stability ◽  
Accessible Surface ◽  
Solvent Accessible Surface ◽  
Type Crystal

Insulin has been commonly adopted as a peptide drug to treat diabetes given its ability to facilitate the uptake of glucose from the blood. The development of oral insulin remains elusive over decades owing to its susceptibility to the enzymes in the gastrointestinal tract and poor permeability through the intestinal epithelium upon dimerization. Recent experimental studies have revealed that certain O-linked glycosylation patterns could enhance insulin’s proteolytic stability and reduce its dimerization propensity, but the understanding of such phenomena at the molecular level is still evasive. To address this challenge, we propose and test several structural determinants that could potentially in uence insulin’s proteolytic stability and dimerization propensity. We used these as the metrics to assess the properties of interest from 10  s aggregate molecular dynamics of each of 12 targeted insulin glyco-variants from multiple wild-type crystal structures. We found that glycan-involved hydrogen bonds and glycan-dimer occlusion were useful metrics predicting the proteolytic stability and dimerization propensity of insulin, as was in part the solvent accessible surface area of proteolytic sites, while other plausible metrics were not generally predictive. This work helps better explain how O-linked glycosylation in uences the proteolytic stability and monomeric propensity of insulin, illuminating a path towards rational molecular design of insulin glycoforms.

scholarly journals Identifying signatures of proteolytic stability and monomeric propensity in O-glycosylated insulin using molecular simulation

2021 ◽  
Author(s):  
Wei-Tse Hsu ◽  
Dominique Ramirez ◽  
Tarek Sammakia ◽  
Zhongping Tan ◽  
Michael Shirts
Keyword(s):  
Molecular Design ◽  
Experimental Studies ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Structural Determinants ◽  
Rational Molecular Design ◽  
Proteolytic Stability ◽  
Accessible Surface ◽  
Solvent Accessible Surface ◽  
Type Crystal

Insulin has been commonly adopted as a peptide drug to treat diabetes given its ability to facilitate the uptake of glucose from the blood. The development of oral insulin remains elusive over decades owing to its susceptibility to the enzymes in the gastrointestinal tract and poor permeability through the intestinal epithelium upon dimerization. Recent experimental studies have revealed that certain O-linked glycosylation patterns could enhance insulin’s proteolytic stability and reduce its dimerization propensity, but the understanding of such phenomena at the molecular level is still evasive. To address this challenge, we propose and test several structural determinants that could potentially in uence insulin’s proteolytic stability and dimerization propensity. We used these as the metrics to assess the properties of interest from 10  s aggregate molecular dynamics of each of 12 targeted insulin glyco-variants from multiple wild-type crystal structures. We found that glycan-involved hydrogen bonds and glycan-dimer occlusion were useful metrics predicting the proteolytic stability and dimerization propensity of insulin, as was in part the solvent accessible surface area of proteolytic sites, while other plausible metrics were not generally predictive. This work helps better explain how O-linked glycosylation in uences the proteolytic stability and monomeric propensity of insulin, illuminating a path towards rational molecular design of insulin glycoforms.

Application of the ESMACS Binding Free Energy Protocol to a Highly Varied Ligand Dataset: Lactate Dehydogenase A

2019 ◽  
Author(s):  
David Wright ◽  
Fouad Husseini ◽  
Shunzhou Wan ◽  
Christophe Meyer ◽  
Herman Van Vlijmen ◽  
...  
Keyword(s):  
Free Energy ◽  
Surface Area ◽  
Binding Free Energy ◽  
Normal Mode Analysis ◽  
Binding Mode ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Mode Analysis ◽  
Energy Calculation ◽  
Accessible Surface

<div>Here, we evaluate the performance of our range of ensemble simulation based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) for use in fragment based drug design scenarios. ESMACS is designed to generate reproducible binding affinity predictions from the widely used molecular mechanics Poisson-Boltzmann surface area (MMPBSA) approach. We study ligands designed to target two binding pockets in the lactate dehydogenase A target protein, which vary in size, charge and binding mode. When comparing to experimental results, we obtain excellent statistical rankings across this highly diverse set of ligands. In addition, we investigate three approaches to account for entropic contributions not captured by standard MMPBSA calculations: (1) normal mode analysis, (2) weighted solvent accessible surface area (WSAS) and (3) variational entropy. </div>

scholarly journals Interaction of Temporin-L Analogues with the E. coli FtsZ Protein

Antibiotics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 704
Author(s):  
Angela Di Somma ◽  
Carolina Canè ◽  
Antonio Moretta ◽  
Angela Duilio
Keyword(s):  
Protein Interactions ◽  
Bacterial Infections ◽  
Antibacterial Properties ◽  
Bacterial Cell Division ◽  
Structural Determinants ◽  
E Coli ◽  
Functional Studies ◽  
Division Process ◽  
Z Ring ◽  
Peptide Complexes

The research of new therapeutic agents to fight bacterial infections has recently focused on the investigation of antimicrobial peptides (AMPs), the most common weapon that all organisms produce to prevent invasion by external pathogens. Among AMPs, the amphibian Temporins constitute a well-known family with high antibacterial properties against Gram-positive and Gram-negative bacteria. In particular, Temporin-L was shown to affect bacterial cell division by inhibiting FtsZ, a tubulin-like protein involved in the crucial step of Z-ring formation at the beginning of the division process. As FtsZ represents a leading target for new antibacterial compounds, in this paper we investigated in detail the interaction of Temporin L with Escherichia coli FtsZ and designed two TL analogues in an attempt to increase peptide-protein interactions and to better understand the structural determinants leading to FtsZ inhibition. The results demonstrated that the TL analogues improved their binding to FtsZ, originating stable protein-peptide complexes. Functional studies showed that both peptides were endowed with a high capability of inhibiting both the enzymatic and polymerization activities of the protein. Moreover, the TL analogues were able to inhibit bacterial growth at low micromolar concentrations. These observations may open up the way to the development of novel peptide or peptidomimetic drugs tailored to bind FtsZ, hampering a crucial process of bacterial life that might be proposed for future pharmaceutical applications.

scholarly journals PAMAM dendrimer: a pH-controlled nanosponge

2017 ◽  
Vol 95 (9) ◽  
pp. 991-998 ◽  
Author(s):  
Prabal K. Maiti
Keyword(s):  
Accessible Surface Area ◽  
Pamam Dendrimer ◽  
Low Ph ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Water Molecules ◽  
Accessible Volume ◽  
Accessible Surface ◽  
Solvent Accessible Surface ◽  
Ph Controlled

Using fully atomistic molecular dynamics simulation that are several hundred nanoseconds long, we demonstrate the pH-controlled sponge action of PAMAM dendrimer. We show how at varying pH levels, the PAMAM dendrimer acts as a wet sponge; at neutral or low pH levels, the dendrimer expands noticeably and the interior of the dendrimer opens up to host several hundreds to thousands of water molecules depending on the generation number. Increasing the pH (i.e., going from low pH to high pH) leads to the collapse of the dendrimer size, thereby expelling the inner water, which mimics the ‘sponge’ action. As the dendrimer size swells up at a neutral pH or low pH due to the electrostatic repulsion between the primary and tertiary amines that are protonated at this pH, there is dramatic increase in the available solvent accessible surface area (SASA), as well as solvent accessible volume (SAV).

PUTRACER: A NOVEL METHOD FOR IDENTIFICATION OF CONTINUOUS-DOMAINS IN MULTI-DOMAIN PROTEINS

2013 ◽  
Vol 11 (01) ◽  
pp. 1340012 ◽  
Author(s):  
SEYED SHAHRIAR ARAB ◽  
MOHAMMADBAGHER PARSA GHARAMALEKI ◽  
ZAIDDODINE PASHANDI ◽  
REZVAN MOBASSERI
Keyword(s):  
Protein Structures ◽  
Three Dimensional ◽  
Accessible Surface Area ◽  
Computer Assisted ◽  
Correct Assignment ◽  
Critical Boundary ◽  
Novel Method ◽  
Accessible Surface ◽  
A Chain

Computer assisted assignment of protein domains is considered as an important issue in structural bioinformatics. The exponential increase in the number of known three dimensional protein structures and the significant role of proteins in biology, medicine and pharmacology illustrate the necessity of a reliable method to automatically detect structural domains as protein units. For this aim, we have developed a program based on the accessible surface area (ASA) and the hydrogen bonds energy in protein backbone (HBE). PUTracer (Protein Unit Tracer) is built on the features of a fast top-down approach to cut a chain into its domains (contiguous domains) with minimal change in ASA as well as HBE. Performance of the program was assessed by a comprehensive benchmark dataset of 124 protein chains, which is based on agreement among experts (e.g. CATH, SCOP) and was expanded to include structures with different types of domain combinations. Equal number of domains and at least 90% agreement in critical boundary accuracy were considered as correct assignment conditions. PUTracer assigned domains correctly in 81.45% of protein chains. Although low critical boundary accuracy in 18.55% of protein chains leads to the incorrect assignments, adjusting the scales causes to improve the performance up to 89.5%. We discuss here the success or failure of adjusting the scales with provided evidences. Availability: PUTracer is available at http://bioinf.modares.ac.ir/software/PUTracer/

Sign in / Sign up

Export Citation Format

Share Document