Mutational fitness landscape and drug resistance.
Mutational fitness landscape and drug resistance.
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突变适应度景观和耐药性。
DOI：
10.1016/j.sbi.2022.102525
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发表时间：
2023
影响因子：
6.8
通讯作者：
Bolon,DanielNA
中科院分区：
文献类型：
--
作者：
Flynn,Julia;Samant,Neha;Schneider-Nachum,Gily;Tenzin,Tsepal;Bolon,DanielNA
已经开发了强大的技术来系统地量化健康状况，这为改善我们对耐药性的理解提供了宝贵的机会，并确定了开发降低耐药性敏感性的药物的新途径。我们概述了耐药性研究的关键重要性，以及健身景观方法为这一努力做出贡献的潜力。我们描述了突变扫描的主要技术进步，突变扫描是用于量化蛋白质适应度的主要方法。在计划和执行突变扫描项目时，有许多复杂的步骤需要考虑，包括制定选择方案、生成突变库、使用下一代测序跟踪变异频率以及处理和解释数据。对影响每个步骤的关键实验参数进行了讨论，以帮助规划健身景观研究。人们迫切需要更好地了解耐药性，而健身环境提供了一种很有希望的新方法。
Robust technology has been developed to systematically quantify fitness landscapes that provide valuable opportunities to improve our understanding of drug resistance and define new avenues to develop drugs with reduced resistance susceptibility. We outline the critical importance of drug resistance studies and the potential for fitness landscape approaches to contribute to this effort. We describe the major technical advancements in mutational scanning, which is the primary approach used to quantify protein fitness landscapes. There are many complex steps to consider in planning and executing mutational scanning projects including developing a selection scheme, generating mutant libraries, tracking the frequency of variants using next-generation sequencing, and processing and interpreting the data. Key experimental parameters impacting each of these steps are discussed to aid in planning fitness landscape studies. There is a strong need for improved understanding of drug resistance, and fitness landscapes provide a promising new approach.
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影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
影响因子：
7.7
作者：
Chen, John Z.;Fowler, Douglas M.;Tokuriki, Nobuhiko
通讯作者：
Tokuriki, Nobuhiko
影响因子：
8.8
作者：
Brenan L;Andreev A;Cohen O;Pantel S;Kamburov A;Cacchiarelli D;Persky NS;Zhu C;Bagul M;Goetz EM;Burgin AB;Garraway LA;Getz G;Mikkelsen TS;Piccioni F;Root DE;Johannessen CM
通讯作者：
Johannessen CM
影响因子：
7.7
作者：
Flynn, Julia M.;Samant, Neha;Schneider-Nachum, Gily;Barkan, David T.;Yilmaz, Nese Kurt;Schiffer, Celia A.;Moquin, Stephanie A.;Dovala, Dustin;Bolon, Daniel N. A.
通讯作者：
Bolon, Daniel N. A.
影响因子：
7.7
作者：
David Mavor;Kyle A. Barlow;Samuel Thompson;B. Barad;Alain R. Bonny;Clinton L. Cario;Garrett Gaskins;Zairan Liu;Laura Deming;S. Axen;Elena L. Cáceres;Weilin Chen;A. Cuesta;Rachel E. Gate;E. Green;Kaitlin R Hulce;Weiyue Ji;L. Kenner;Bruk Mensa;L. Morinishi;Steven M. Moss;M. Mravic;Ryan K Muir;Stefan Niekamp;C. Nnadi;Eugene Palovcak;E. Poss;T. Ross;Eugenia C. Salcedo;Stephanie K. See;Meena Subramaniam;A. Wong;Jennifer Li;K. Thorn;S. Conchúir;Benjamin P. Roscoe;E. Chow;J. Derisi;T. Kortemme;Daniel N. A. Bolon;J. Fraser
通讯作者：
David Mavor;Kyle A. Barlow;Samuel Thompson;B. Barad;Alain R. Bonny;Clinton L. Cario;Garrett Gaskins;Zairan Liu;Laura Deming;S. Axen;Elena L. Cáceres;Weilin Chen;A. Cuesta;Rachel E. Gate;E. Green;Kaitlin R Hulce;Weiyue Ji;L. Kenner;Bruk Mensa;L. Morinishi;Steven M. Moss;M. Mravic;Ryan K Muir;Stefan Niekamp;C. Nnadi;Eugene Palovcak;E. Poss;T. Ross;Eugenia C. Salcedo;Stephanie K. See;Meena Subramaniam;A. Wong;Jennifer Li;K. Thorn;S. Conchúir;Benjamin P. Roscoe;E. Chow;J. Derisi;T. Kortemme;Daniel N. A. Bolon;J. Fraser