PURPOSE OF REVIEW: We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development. RECENT FINDINGS: Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates. SUMMARY: Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.
PURPOSE OF REVIEW: We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development. RECENT FINDINGS: Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates. SUMMARY: Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.
Authors: Bart Alewijnse; Alun W Ashton; Melissa G Chambers; Songye Chen; Anchi Cheng; Mark Ebrahim; Edward T Eng; Wim J H Hagen; Abraham J Koster; Claudia S López; Natalya Lukoyanova; Joaquin Ortega; Ludovic Renault; Steve Reyntjens; William J Rice; Giovanna Scapin; Raymond Schrijver; Alistair Siebert; Scott M Stagg; Valerie Grum-Tokars; Elizabeth R Wright; Shenping Wu; Zhiheng Yu; Z Hong Zhou; Bridget Carragher; Clinton S Potter Journal: J Struct Biol Date: 2017-08-04 Impact factor: 2.867
Authors: Brian Jiménez-García; Jorge Roel-Touris; Miguel Romero-Durana; Miquel Vidal; Daniel Jiménez-González; Juan Fernández-Recio Journal: Bioinformatics Date: 2018-01-01 Impact factor: 6.937
Authors: Marc F Lensink; Sameer Velankar; Andriy Kryshtafovych; Shen-You Huang; Dina Schneidman-Duhovny; Andrej Sali; Joan Segura; Narcis Fernandez-Fuentes; Shruthi Viswanath; Ron Elber; Sergei Grudinin; Petr Popov; Emilie Neveu; Hasup Lee; Minkyung Baek; Sangwoo Park; Lim Heo; Gyu Rie Lee; Chaok Seok; Sanbo Qin; Huan-Xiang Zhou; David W Ritchie; Bernard Maigret; Marie-Dominique Devignes; Anisah Ghoorah; Mieczyslaw Torchala; Raphaël A G Chaleil; Paul A Bates; Efrat Ben-Zeev; Miriam Eisenstein; Surendra S Negi; Zhiping Weng; Thom Vreven; Brian G Pierce; Tyler M Borrman; Jinchao Yu; Françoise Ochsenbein; Raphaël Guerois; Anna Vangone; João P G L M Rodrigues; Gydo van Zundert; Mehdi Nellen; Li Xue; Ezgi Karaca; Adrien S J Melquiond; Koen Visscher; Panagiotis L Kastritis; Alexandre M J J Bonvin; Xianjin Xu; Liming Qiu; Chengfei Yan; Jilong Li; Zhiwei Ma; Jianlin Cheng; Xiaoqin Zou; Yang Shen; Lenna X Peterson; Hyung-Rae Kim; Amit Roy; Xusi Han; Juan Esquivel-Rodriguez; Daisuke Kihara; Xiaofeng Yu; Neil J Bruce; Jonathan C Fuller; Rebecca C Wade; Ivan Anishchenko; Petras J Kundrotas; Ilya A Vakser; Kenichiro Imai; Kazunori Yamada; Toshiyuki Oda; Tsukasa Nakamura; Kentaro Tomii; Chiara Pallara; Miguel Romero-Durana; Brian Jiménez-García; Iain H Moal; Juan Férnandez-Recio; Jong Young Joung; Jong Yun Kim; Keehyoung Joo; Jooyoung Lee; Dima Kozakov; Sandor Vajda; Scott Mottarella; David R Hall; Dmitri Beglov; Artem Mamonov; Bing Xia; Tanggis Bohnuud; Carlos A Del Carpio; Eichiro Ichiishi; Nicholas Marze; Daisuke Kuroda; Shourya S Roy Burman; Jeffrey J Gray; Edrisse Chermak; Luigi Cavallo; Romina Oliva; Andrey Tovchigrechko; Shoshana J Wodak Journal: Proteins Date: 2016-06-01