Databases of ligand-binding pockets and protein-ligand interactions

被引：8

作者：

Carpenter, Kristy A. ^{[1
]}

Altman, Russ B. ^{[1
,2
,3
,4
]}

机构：

[1] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA

[3] Stanford Univ, Dept Genet, Stanford, CA 94305 USA

[4] Stanford Univ, Dept Med, Stanford, CA 94305 USA

来源：

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | 2024年 / 23卷

关键词：

Binding sites; Protein-ligand interaction; Pocket detection; Databases; Protein structure; Structural bioinformatics; INHIBITOR STARTING POINTS; MACHINE LEARNING APPROACH; DRUGGABILITY PREDICTION; IMPORTANT RESIDUES; SITE PREDICTION; FOLD SPACE; HOT-SPOTS; MOLECULES; TARGETS; IDENTIFICATION;

D O I：

10.1016/j.csbj.2024.03.015

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket -finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

引用

页码：1320 / 1338

页数：19

共 212 条

[1] Structural database resources for biological macromolecules [J].

Abriata, Luciano A. .

BRIEFINGS IN BIOINFORMATICS, 2017, 18 (04) :659-669

[2] The Biomolecular Interaction Network Database and related tools 2005 update [J].

Alfarano, C ;

Andrade, CE ;

Anthony, K ;

Bahroos, N ;

Bajec, M ;

Bantoft, K ;

Betel, D ;

Bobechko, B ;

Boutilier, K ;

Burgess, E ;

Buzadzija, K ;

Cavero, R ;

D'Abreo, C ;

Donaldson, I ;

Dorairajoo, D ;

Dumontier, MJ ;

Dumontier, MR ;

Earles, V ;

Farrall, R ;

Feldman, H ;

Garderman, E ;

Gong, Y ;

Gonzaga, R ;

Grytsan, V ;

Gryz, E ;

Gu, V ;

Haldorsen, E ;

Halupa, A ;

Haw, R ;

Hrvojic, A ;

Hurrell, L ;

Isserlin, R ;

Jack, F ;

Juma, F ;

Khan, A ;

Kon, T ;

Konopinsky, S ;

Le, V ;

Lee, E ;

Ling, S ;

Magidin, M ;

Moniakis, J ;

Montojo, J ;

Moore, S ;

Muskat, B ;

Ng, I ;

Paraiso, JP ;

Parker, B ;

Pintilie, G ;

Pirone, R .

NUCLEIC ACIDS RESEARCH, 2005, 33 :D418-D424

[3] Accurate prediction of protein structures and interactions using a three-track neural network [J].

Baek, Minkyung ;

DiMaio, Frank ;

Anishchenko, Ivan ;

Dauparas, Justas ;

Ovchinnikov, Sergey ;

Lee, Gyu Rie ;

Wang, Jue ;

Cong, Qian ;

Kinch, Lisa N. ;

Schaeffer, R. Dustin ;

Millan, Claudia ;

Park, Hahnbeom ;

Adams, Carson ;

Glassman, Caleb R. ;

DeGiovanni, Andy ;

Pereira, Jose H. ;

Rodrigues, Andria V. ;

van Dijk, Alberdina A. ;

Ebrecht, Ana C. ;

Opperman, Diederik J. ;

Sagmeister, Theo ;

Buhlheller, Christoph ;

Pavkov-Keller, Tea ;

Rathinaswamy, Manoj K. ;

Dalwadi, Udit ;

Yip, Calvin K. ;

Burke, John E. ;

Garcia, K. Christopher ;

Grishin, Nick V. ;

Adams, Paul D. ;

Read, Randy J. ;

Baker, David .

SCIENCE, 2021, 373 (6557) :871-+

[4]

Bagherian M, 2021, BRIEF BIOINFORM, V22, P247, DOI 10.1093/bib/bbz157

[5] Polypharmacy side-effect prediction with enhanced interpretability based on graph feature attention network [J].

Bang, Sunjoo ;

Jhee, Jong Ho ;

Shin, Hyunjung .

BIOINFORMATICS, 2021, 37 (18) :2955-2962

[6] Analysis of water patterns in protein kinase binding sites [J].

Barillari, Caterina ;

Duncan, Anna L. ;

Westwood, Isaac M. ;

Blagg, Julian ;

van Montfort, Rob L. M. .

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 (07) :2109-2121

[7] Domain-ligand mapping for enzymes [J].

Bashton, Matthew ;

Thornton, Janet M. .

JOURNAL OF MOLECULAR RECOGNITION, 2010, 23 (02) :194-208

[8] UniProt: the Universal Protein Knowledgebase in 2023 [J].

Bateman, Alex ;

Martin, Maria-Jesus ;

Orchard, Sandra ;

Magrane, Michele ;

Ahmad, Shadab ;

Alpi, Emanuele ;

Bowler-Barnett, Emily H. ;

Britto, Ramona ;

Cukura, Austra ;

Denny, Paul ;

Dogan, Tunca ;

Ebenezer, ThankGod ;

Fan, Jun ;

Garmiri, Penelope ;

Gonzales, Leonardo Jose da Costa ;

Hatton-Ellis, Emma ;

Hussein, Abdulrahman ;

Ignatchenko, Alexandr ;

Insana, Giuseppe ;

Ishtiaq, Rizwan ;

Joshi, Vishal ;

Jyothi, Dushyanth ;

Kandasaamy, Swaathi ;

Lock, Antonia ;

Luciani, Aurelien ;

Lugaric, Marija ;

Luo, Jie ;

Lussi, Yvonne ;

MacDougall, Alistair ;

Madeira, Fabio ;

Mahmoudy, Mahdi ;

Mishra, Alok ;

Moulang, Katie ;

Nightingale, Andrew ;

Pundir, Sangya ;

Qi, Guoying ;

Raj, Shriya ;

Raposo, Pedro ;

Rice, Daniel L. ;

Saidi, Rabie ;

Santos, Rafael ;

Speretta, Elena ;

Stephenson, James ;

Totoo, Prabhat ;

Turner, Edward ;

Tyagi, Nidhi ;

Vasudev, Preethi ;

Warner, Kate ;

Watkins, Xavier ;

Zellner, Hermann .

NUCLEIC ACIDS RESEARCH, 2023, 51 (D1) :D523-D531

[9]

Bates PA, 2001, PROTEINS, P39

[10] Molmil: a molecular viewer for the PDB and beyond [J].

Bekker, Gert-Jan ;

Nakamura, Haruki ;

Kinjo, Akira R. .

JOURNAL OF CHEMINFORMATICS, 2016, 8

← 1 2 3 4 5 6 7 8 9 10 →