The critical role of QM/MM X-ray refinement and accurate tautomer/protomer determination in structure-based drug design.
The critical role of QM/MM X-ray refinement and accurate tautomer/protomer determination in structure-based drug design.
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DOI：
10.1007/s10822-020-00354-6
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发表时间：
2021-04
影响因子：
3.5
通讯作者：
Westerhoff LM
中科院分区：
文献类型：
--
作者：
Borbulevych OY;Martin RI;Westerhoff LM
Conventional protein:ligand crystallographic refinement uses stereochemistry restraints coupled with a rudimentary energy functional to ensure the correct geometry of the model of the macromolecule—along with any bound ligand(s)—within the context of the experimental, X-ray density. These methods generally lack explicit terms for electrostatics, polarization, dispersion, hydrogen bonds, and other key interactions, and instead they use pre-determined parameters (e.g. bond lengths, angles, and torsions) to drive structural refinement. In order to address this deficiency and obtain a more complete and ultimately more accurate structure, we have developed an automated approach for macromolecular refinement based on a two layer, QM/MM (ONIOM) scheme as implemented within our DivCon Discovery Suite and "plugged in" to two mainstream crystallographic packages: PHENIX and BUSTER. This implementation is able to use one or more region layer(s), which is(are) characterized using linear-scaling, semi-empirical quantum mechanics, followed by a system layer which includes the balance of the model and which is described using a molecular mechanics functional. In this work, we applied our Phenix/DivCon refinement method—coupled with our XModeScore method for experimental tautomer/protomer state determination—to the characterization of structure sets relevant to structure-based drug design (SBDD). We then use these newly refined structures to show the impact of QM/MM X-ray refined structure on our understanding of function by exploring the influence of these improved structures on protein:ligand binding affinity prediction (and we likewise show how we use post-refinement scoring outliers to inform subsequent X-ray crystallographic efforts). Through this endeavor, we demonstrate a computational chemistry ↔ structural biology (X-ray crystallography) "feedback loop" which has utility in industrial and academic pharmaceutical research as well as other allied fields. The online version of this article (10.1007/s10822-020-00354-6) contains supplementary material, which is available to authorized users.
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DOI：
10.1016/j.str.2017.10.009
发表时间：
2017-12-05
期刊：
Structure (London, England : 1993)
影响因子：
--
作者：
Gore S;Sanz García E;Hendrickx PMS;Gutmanas A;Westbrook JD;Yang H;Feng Z;Baskaran K;Berrisford JM;Hudson BP;Ikegawa Y;Kobayashi N;Lawson CL;Mading S;Mak L;Mukhopadhyay A;Oldfield TJ;Patwardhan A;Peisach E;Sahni G;Sekharan MR;Sen S;Shao C;Smart OS;Ulrich EL;Yamashita R;Quesada M;Young JY;Nakamura H;Markley JL;Berman HM;Burley SK;Velankar S;Kleywegt GJ
通讯作者：
Kleywegt GJ
DOI：
10.1107/s2059798316002837
发表时间：
2016-04
期刊：
Acta crystallographica. Section D, Structural biology
影响因子：
--
作者：
Borbulevych O;Martin RI;Tickle IJ;Westerhoff LM
通讯作者：
Westerhoff LM
影响因子：
5.6
作者：
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Carlson HA
影响因子：
5.5
作者：
Fu, Zheng;Li, Xue;Merz, Kenneth M., Jr.
通讯作者：
Merz, Kenneth M., Jr.
DOI：
10.1107/s0907444909052925
发表时间：
2010-02
期刊：
Acta crystallographica. Section D, Biological crystallography
影响因子：
--
作者：
Adams PD;Afonine PV;Bunkóczi G;Chen VB;Davis IW;Echols N;Headd JJ;Hung LW;Kapral GJ;Grosse-Kunstleve RW;McCoy AJ;Moriarty NW;Oeffner R;Read RJ;Richardson DC;Richardson JS;Terwilliger TC;Zwart PH
通讯作者：
Zwart PH