Editorial

3 pages, 168 KiB

Open AccessEditorial

Special Issue on “Computational Approaches for Protein Dynamics and Function”

by Domenico Scaramozzino and Robert L. Jernigan

Appl. Sci. 2023, 13(14), 8522; https://0-doi-org.brum.beds.ac.uk/10.3390/app13148522 - 24 Jul 2023

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Proteins are fundamental macromolecules that sustain living organisms by performing an astonishingly wide variety of tasks [...] Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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17 pages, 4879 KiB

Open AccessArticle

Information Transfer in Active States of Human β₂-Adrenergic Receptor via Inter-Rotameric Motions of Loop Regions

by Nuray Sogunmez and Ebru Demet Akten

Appl. Sci. 2022, 12(17), 8530; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178530 - 26 Aug 2022

Cited by 2 | Viewed by 1145

Abstract

Two independent 1.5 μs long MD simulations were conducted for the fully atomistic model of the human beta2-adrenergic receptor (β₂AR) in a complex with a G protein to investigate the signal transmission in a fully active state via mutual information and [...] Read more.

Two independent 1.5 μs long MD simulations were conducted for the fully atomistic model of the human beta2-adrenergic receptor (β₂AR) in a complex with a G protein to investigate the signal transmission in a fully active state via mutual information and transfer entropy based on α-carbon displacements and rotameric states of backbone and side-chain torsion angles. Significant correlations between fluctuations in α-Carbon displacements were mostly detected between transmembrane (TM) helices, especially TM5 and TM6 located at each end of ICL3 and TM7. Signal transmission across β₂-AR was quantified by shared mutual information; a high amount of correspondence was distinguished in almost all loop regions when rotameric states were employed. Moreover, polar residues, especially Arg, made the most contribution to signal transmission via correlated side-chain rotameric fluctuations as they were more frequently observed in loop regions than hydrophobic residues. Furthermore, transfer entropy identified all loop regions as major entropy donor sites, which drove future rotameric states of torsion angles of residues in transmembrane helices. Polar residues appeared as donor sites from which entropy flowed towards hydrophobic residues. Overall, loops in β₂AR were recognized as potential allosteric hot spot regions, which play an essential role in signal transmission and should likely be used as potential drug targets. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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17 pages, 32669 KiB

Open AccessArticle

Free-Energy Landscape Analysis of Protein-Ligand Binding: The Case of Human Glutathione Transferase A1

by Adrien Nicolaï, Nicolas Petiot, Paul Grassein, Patrice Delarue, Fabrice Neiers and Patrick Senet

Appl. Sci. 2022, 12(16), 8196; https://0-doi-org.brum.beds.ac.uk/10.3390/app12168196 - 16 Aug 2022

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Abstract

Glutathione transferases (GSTs) are a superfamily of enzymes which have in common the ability to catalyze the nucleophilic addition of the thiol group of reduced glutathione (GSH) onto electrophilic and hydrophobic substrates. This conjugation reaction, which occurs spontaneously but is dramatically accelerated by [...] Read more.

Glutathione transferases (GSTs) are a superfamily of enzymes which have in common the ability to catalyze the nucleophilic addition of the thiol group of reduced glutathione (GSH) onto electrophilic and hydrophobic substrates. This conjugation reaction, which occurs spontaneously but is dramatically accelerated by the enzyme, protects cells against damages caused by harmful molecules. With some exceptions, GSTs are catalytically active as homodimers, with monomers generally constituted of 200 to 250 residues organized into two subdomains. The first is the N-terminal subdomain, which contains an active site named G site, where GSH is hosted in catalytic conformation and which is generally highly conserved among GSTs. The second subdomain, hydrophobic, which binds the substrate counterpart (H site), can vary from one GST to another, resulting in structures able to recognize different substrates. In the present work, we performed all-atom molecular dynamics simulations in explicit solvent of human GSTA1 in its APO form, bound to GSH ligand and bound to GS-conjugated ligand. From MD, two probes were analyzed to (i) decipher the local conformational changes induced by the presence of the ligand and (ii) map the communication pathways involved in the ligand-binding process. These two local probes are, first, coarse-grained angles

(θ

,

γ)

, representing the local conformation of the protein main chain and, second, dihedral angles

χ

representing the local conformation of the amino-acid side chains. From the local probes time series, effective free-energy landscapes along the amino-acid sequence were analyzed and compared between the three different forms of GSTA1. This methodology allowed us to extract a network of 33 key residues, some of them being located in the experimentally well-known binding sites G and H of GSTA1 and others being located as far as 30Å from the original binding sites. Finally, the collective motions associated with the network of key residues were established, showing a strong dynamical coupling between residues Gly14-Arg15 and Gln54-Val55, both in the same binding site (intrasite) but also between binding sites of each monomer (intersites). Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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19 pages, 3823 KiB

Open AccessArticle

In-Silico Characterization of von Willebrand Factor Bound to FVIII

by Valentina Drago, Luisa Di Paola, Claire Lesieur, Renato Bernardini, Claudio Bucolo and Chiara Bianca Maria Platania

Appl. Sci. 2022, 12(15), 7855; https://0-doi-org.brum.beds.ac.uk/10.3390/app12157855 - 04 Aug 2022

Cited by 1 | Viewed by 1898

Abstract

Factor VIII belongs to the coagulation cascade and is expressed as a long pre-protein (mature form, 2351 amino acids long). FVIII is deficient or defective in hemophilic A patients, who need to be treated with hemoderivatives or recombinant FVIII substitutes, i.e., biologic drugs. [...] Read more.

Factor VIII belongs to the coagulation cascade and is expressed as a long pre-protein (mature form, 2351 amino acids long). FVIII is deficient or defective in hemophilic A patients, who need to be treated with hemoderivatives or recombinant FVIII substitutes, i.e., biologic drugs. The interaction between FVIII and von Willebrand factor (VWF) influences the pharmacokinetics of FVIII medications. In vivo, full-length FVIII (FL-FVIII) is secreted in a plasma-inactive form, which includes the B domain, which is then proteolyzed by thrombin protease activity, leading to an inactive plasma intermediate. In this work, we analyzed through a computational approach the binding of VWF with two structure models of FVIII (secreted full-length with B domain, and B domain-deleted FVIII). We included in our analysis the atomic model of efanesoctocog alfa, a novel and investigational recombinant FVIII medication, in which the VWF is covalently linked to FVIII. We carried out a structural analysis of VWF/FVIII interfaces by means of protein–protein docking, PISA (Proteins, Interfaces, Structures and Assemblies), and protein contact networks (PCN) analyses. Accordingly, our computational approaches to previously published experimental data demonstrated that the domains A3-C1 of B domain-deleted FVIII (BDD-FVIII) is the preferential binding site for VWF. Overall, our computational approach applied to topological analysis of protein–protein interface can be aimed at the rational design of biologic drugs other than FVIII medications. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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17 pages, 6419 KiB

Open AccessArticle

In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins

by Thomas Tarenzi, Giovanni Mattiotti, Marta Rigoli and Raffaello Potestio

Appl. Sci. 2022, 12(14), 7157; https://0-doi-org.brum.beds.ac.uk/10.3390/app12147157 - 15 Jul 2022

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Abstract

The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. [...] Read more.

The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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18 pages, 4203 KiB

Open AccessArticle

Protein Fluctuations in Response to Random External Forces

by Domenico Scaramozzino, Pranav M. Khade and Robert L. Jernigan

Appl. Sci. 2022, 12(5), 2344; https://0-doi-org.brum.beds.ac.uk/10.3390/app12052344 - 23 Feb 2022

Cited by 1 | Viewed by 2216

Abstract

Elastic network models (ENMs) have been widely used in the last decades to investigate protein motions and dynamics. There the intrinsic fluctuations based on the isolated structures are obtained from the normal modes of these elastic networks, and they generally show good agreement [...] Read more.

Elastic network models (ENMs) have been widely used in the last decades to investigate protein motions and dynamics. There the intrinsic fluctuations based on the isolated structures are obtained from the normal modes of these elastic networks, and they generally show good agreement with the B-factors extracted from X-ray crystallographic experiments, which are commonly considered to be indicators of protein flexibility. In this paper, we propose a new approach to analyze protein fluctuations and flexibility, which has a more appropriate physical basis. It is based on the application of random forces to the protein ENM to simulate the effects of collisions of solvent on a protein structure. For this purpose, we consider both the C^α-atom coarse-grained anisotropic network model (ANM) and an elastic network augmented with points included for the crystallized waters. We apply random forces to these protein networks everywhere, as well as only on the protein surface alone. Despite the randomness of the directions of the applied perturbations, the computed average displacements of the protein network show a remarkably good agreement with the experimental B-factors. In particular, for our set of 919 protein structures, we find that the highest correlation with the B-factors is obtained when applying forces to the external surface of the water-augmented ANM (an overall gain of 3% in the Pearson’s coefficient for the entire dataset, with improvements up to 30% for individual proteins), rather than when evaluating the fluctuations obtained from the normal modes of a standard C^α-atom coarse-grained ANM. It follows that protein fluctuations should be considered not just as the intrinsic fluctuations of the internal dynamics, but also equally well as responses to external solvent forces, or as a combination of both. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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16 pages, 16476 KiB

Open AccessArticle

Identification of Novel Inhibitors of Type-I Mycobacterium Tuberculosis Fatty Acid Synthase Using Docking-Based Virtual Screening and Molecular Dynamics Simulation

by Nidhi Singh, Shi-Qing Mao and Wenjin Li

Appl. Sci. 2021, 11(15), 6977; https://0-doi-org.brum.beds.ac.uk/10.3390/app11156977 - 29 Jul 2021

Cited by 2 | Viewed by 1737

Abstract

Mycobacterial fatty acid synthase type-I (FAS-I) has an important role in the de novo synthesis of fatty acids, which constitute a major component of the cell wall. The essentiality of FAS-I in the survival and growth of mycobacterium makes it an attractive drug [...] Read more.

Mycobacterial fatty acid synthase type-I (FAS-I) has an important role in the de novo synthesis of fatty acids, which constitute a major component of the cell wall. The essentiality of FAS-I in the survival and growth of mycobacterium makes it an attractive drug target. However, targeted inhibitors against Mycobacterial FAS-I have not been reported yet. Recently, the structure of FAS-I from Mycobacterium tuberculosis was solved. Therefore, in a quest to find potential inhibitors against FAS-I, molecular docking-based virtual screening and molecular dynamics simulation were done. Subsequently, molecular dynamic simulations based on binding free energy calculations were done to gain insight into the predicted binding mode of putative hits. The detailed analysis resulted in the selection of four putative inhibitors. For compounds BTB14738, RH00608, SPB02705, and CD01000, binding free energy was calculated as −72.27 ± 12.63, −68.06 ± 11.80, −63.57 ± 12.22, and −51.28 ± 13.74 KJ/mol, respectively. These compounds are proposed to be promising pioneer hits. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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14 pages, 2372 KiB

Open AccessPerspective

Are Protein Shape-Encoded Lowest-Frequency Motions a Key Phenotype Selected by Evolution?

by Laura Orellana

Appl. Sci. 2023, 13(11), 6756; https://0-doi-org.brum.beds.ac.uk/10.3390/app13116756 - 01 Jun 2023

Cited by 1 | Viewed by 1246

Abstract

At the very deepest molecular level, the mechanisms of life depend on the operation of proteins, the so-called “workhorses” of the cell. Proteins are nanoscale machines that transform energy into useful cellular work, such as ion or nutrient transport, information processing, or energy [...] Read more.

At the very deepest molecular level, the mechanisms of life depend on the operation of proteins, the so-called “workhorses” of the cell. Proteins are nanoscale machines that transform energy into useful cellular work, such as ion or nutrient transport, information processing, or energy transformation. Behind every biological task, there is a nanometer-sized molecule whose shape and intrinsic motions, binding, and sensing properties have been evolutionarily polished for billions of years. With the emergence of structural biology, the most crucial property of biomolecules was thought to be their 3D shape, but how this relates to function was unclear. During the past years, Elastic Network Models have revealed that protein shape, motion and function are deeply intertwined, so that each structure displays robustly shape-encoded functional movements that can be extraordinarily conserved across the tree of life. Here, we briefly review the growing literature exploring the interplay between sequence evolution, protein shape, intrinsic motions and function, and highlight examples from our research in which fundamental movements are conserved from bacteria to mammals or selected by cancer cells to modulate function. Full article

(This article belongs to the Special Issue Computational Approaches for Protein Dynamics and Function)

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