Literature DB >> 27110726

Protein Binding Pocket Dynamics.

Antonia Stank1, Daria B Kokh1, Jonathan C Fuller1, Rebecca C Wade1,2.   

Abstract

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

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Year:  2016        PMID: 27110726     DOI: 10.1021/acs.accounts.5b00516

Source DB:  PubMed          Journal:  Acc Chem Res        ISSN: 0001-4842            Impact factor:   22.384


  56 in total

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2.  Methods for Molecular Modelling of Protein Complexes.

Authors:  Tejashree Rajaram Kanitkar; Neeladri Sen; Sanjana Nair; Neelesh Soni; Kaustubh Amritkar; Yogendra Ramtirtha; M S Madhusudhan
Journal:  Methods Mol Biol       Date:  2021

3.  Binding site matching in rational drug design: algorithms and applications.

Authors:  Misagh Naderi; Jeffrey Mitchell Lemoine; Rajiv Gandhi Govindaraj; Omar Zade Kana; Wei Pan Feinstein; Michal Brylinski
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

4.  POVME 3.0: Software for Mapping Binding Pocket Flexibility.

Authors:  Jeffrey R Wagner; Jesper Sørensen; Nathan Hensley; Celia Wong; Clare Zhu; Taylor Perison; Rommie E Amaro
Journal:  J Chem Theory Comput       Date:  2017-08-30       Impact factor: 6.006

5.  Design and Applications of Water-Soluble Coordination Cages.

Authors:  Edmundo G Percástegui; Tanya K Ronson; Jonathan R Nitschke
Journal:  Chem Rev       Date:  2020-11-25       Impact factor: 60.622

6.  BionoiNet: ligand-binding site classification with off-the-shelf deep neural network.

Authors:  Wentao Shi; Jeffrey M Lemoine; Abd-El-Monsif A Shawky; Manali Singha; Limeng Pu; Shuangyan Yang; J Ramanujam; Michal Brylinski
Journal:  Bioinformatics       Date:  2020-05-01       Impact factor: 6.937

7.  Discovery of Novel Cyclic Salt Bridge in Thermophilic Bacterial Protease and Study of its Sequence and Structure.

Authors:  Debanjan Mitra; Pradeep K Das Mohapatra
Journal:  Appl Biochem Biotechnol       Date:  2021-03-08       Impact factor: 2.926

8.  Understanding the enzyme-ligand complex: insights from all-atom simulations of butyrylcholinesterase inhibition.

Authors:  Walter Alvarado; Parker Ladd Bremer; Angela Choy; Helen N Dinh; Aingty Eung; Jeannette Gonzalez; Phillippe Ly; Trina Tran; Kensaku Nakayama; Jason P Schwans; Eric J Sorin
Journal:  J Biomol Struct Dyn       Date:  2019-04-07

9.  Systematic Dissociation Pathway Searches Guided by Principal Component Modes.

Authors:  Zhiye Tang; Chia-En A Chang
Journal:  J Chem Theory Comput       Date:  2017-05-01       Impact factor: 6.006

10.  Full-Length P2X7 Structures Reveal How Palmitoylation Prevents Channel Desensitization.

Authors:  Alanna E McCarthy; Craig Yoshioka; Steven E Mansoor
Journal:  Cell       Date:  2019-10-03       Impact factor: 41.582

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