CHDOCK: a hierarchical docking approach for(5)

Camacho C,Coulouris G,Avagyan V,Ma N,Papadopoulos J,Bealer K,Madden TL(2009)BLAST+∶architecture and Bioinform 10∶421

Chen R,Weng Z (2003) A novel shape complementarity scoring function for protein-protein 51∶397-408

Comeau SR,Gatchell DW,Vajda S,Camacho CJ (2004) ClusPro∶a fully automated algorithm for protein-protein Acids Res 32∶W96-W99

de Vries SJ,van Dijk M,Bonvin AM (2010) The HADDOCK web server for data-driven biomolecular Protoc 5∶883-897

de Vries SJ,Schindler CE,Chauvot de Beauchene I,Zacharias M(2015) A web interface for easy flexible protein-protein docking with J 108∶462-465

DiMaio F,Leaver-Fay A,Bradley P,Baker D,Andre I (2011)Modeling symmetric macromolecular structures in ONE 6∶e

Goodsell DS,Olson AJ (2000) Structural symmetry and protein Rev Biophys Biomol Struct 29∶105-153

Huang S-Y (2014) Search strategies and evaluation in proteinprotein docking∶principles,advances and Discov Today 19∶1081-1096

Huang S-Y,Zou X (2008) An iterative knowledge-based scoring function for protein-protein 72∶557-579

Katchalski-Katzir E,Shariv I,Eisenstein M,Friesem AA,Aflalo C,Vakser IA (1992) Molecular surface recognition∶determination of geometric fit between proteins and their ligands by correlation Natl Acad Sci USA 89∶2195-2199

Lee H,Park H,Ko J,Seok C(2013)GalaxyGemini∶a web server for protein homo-oligomer structure prediction based on 29∶1078-1080

Lensink MF,Velankar S,Kryshtafovych A,Huang SY,Schneidman-Duhovny D,Sali A,Segura J,Fernandez-Fuentes N,Viswanath S,Elber R (2016) Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling∶a CASP-CAPRI 84∶323-348

Lensink MF,Velankar S,Baek M,Heo L,Seok C,Wodak SJ (2018)The challenge of modeling protein assemblies∶the CASP12-CAPRI 86∶257-273

Li AJ,Nussinov R (1998) A set of van der Waals and coulombic radii of protein atoms for molecular and solvent-accessible surface calculation,packing evaluation,and 32∶111-127

Lo Conte L,Ailey B,Hubbard TJ,Brenner SE,Murzin AG,Chothia C(2000) SCOP∶a structural classification of proteins Acids Res 28∶257-259

Petsalaki E,Russell RB (2008) Peptide-mediated interactions in biological systems∶new discoveries and Opin Biotechnol 19∶344-350

Pierce B,Tong W,Weng Z(2005)M-ZDOCK∶a grid-based approach for Cnsymmetric multimer 21∶1472-1478

Poupon A,Janin J (2010) Analysis and prediction of protein quaternary ∶Data mining techniques for the life ,pp 349-364

Ritchie DW,Grudinin S(2016)Spherical polar Fourier assembly of protein complexes with arbitrary point group Appl Crystallogr 49∶158-167

Schneidman-Duhovny D,Inbar Y,Nussinov R,Wolfson HJ (2005)PatchDock and SymmDock∶servers for rigid and symmetric Acids Res 33∶W363-W367

Torchala M,Moal IH,Chaleil RA,Fernandez-Recio J,Bates PA(2013) SwarmDock∶ a server for flexible protein-protein 29∶807-809

Tovchigrechko A,Vakser IA (2006) GRAMM-X public web server for protein-protein Acids Res 34∶W310-W314

Yan Y,Huang S-Y (2018) Protein-protein docking with improved shape ∶ International conference on intelligent ,pp 600-605

Yan Y,Huang S-Y (2019) A non-redundant benchmark for symmetric protein Data Min Anal 2∶92-99

Yan Y,Wen Z,Wang X,Huang SY(2017)Addressing recent docking challenges∶a hybrid strategy to integrate template-based and free protein-protein 85∶497-512

INTRODUCTIONProtein-protein interactions are crucial in many biological processes like signal transduction,intracellular trafficking,and immune all proteinprotein interactions,a significant portion is formed by symmetric homo-oligomers(Andre et al.2008;Goodsell and Olson 2000; Poupon and Janin 2010).According to the Protein Data Bank(PDB)(Berman et al.2000),more than one third of the proteins have some types of example,many transmembrane proteins like ion channels are formed by symmetric homooligomer symmetry of homo-oligomeric proteins is thought to be associated with many potential benefits like greater stability,reduced aggregation,and robustness to errors in synthesis (Andre et al.2008;Goodsell and Olson 2000).The interface between symmetric homo-oligomers is often the targeting site for regulating the biological processes (Petsalaki and Russell 2008).Therefore,determining the complex structure of symmetric proteins is important (Lensink et al.2016,2018).Theoretically,one can use a general protein-protein docking approach to predict the complex structure of symmetric homo-oligomers by docking one monomer against the other(Comeau et al.2004;de Vries et al.2010,2015; Torchala et al.2013; Tovchigrechko and Vakser 2006).However,such a general docking strategy is not efficient for symmetric one hand,the general protein-protein docking approach treats two interacting partners as different proteins and therefore often don’t generate the complex structures with strict symmetry; On the other hand,general protein-protein docking normally don’t consider the symmetry restraints during the docking process,and therefore is not computationally ,specialized protein-protein docking algorithms are needed for predicting the complex structure of symmetric protein important symmetry in proteins is cyclic symmetry (Cn),for which the oligomeric structure can be constructed by n consecutive rotations of 360°/n around a single rotational axis of one subunit (Andre et al.2008).Despite the importance of symmetric protein homo-oligomers,only a few algorithms have been developed for symmetric protein et a fast docking algorithm for cyclically symmetric complexes through local feature matching,which is referred to as SymmDock(Schneidman-Duhovny et al.2005).SymmDock constructs the symmetric homooligomer complexes by restricting the search to symmetric cyclic Weng group developed an FFT-based algorithm for symmetric protein-protein docking by restricting the search space with cyclic symmetry (M-ZDOCK) (Pierce et al.2005).Based on the symmetric protein complexes in the PDB,several web servers that use template-based methods like ROBETTA (DiMaio et al.2011),SWISS-MODEL (Biasini et al.2014),and GalaxyGemini (Lee et al.2013)have also been proposed to predict the homo-oligomeric addition,Ritchie and Grudinin presented a fast docking algorithm,which is named SAM,for predicting the symmetrical models of protein complexes with arbitrary point group symmetry through a spherical polar FFT-based algorithm (Ritchie and Grudinin 2016).Very recently,the Seok group has developed a combination modeling approach,GalaxyHomomer,for homo-oligomer structure prediction from a monomer sequence or structure by template-based modeling if homologous complexes are available in the PDB or ab initio docking (Baek et al.2017).However,despite the significant progress in the development of symmetric docking algorithms,there is still much room in improving the docking ,we have developed a new pairwise shapebased scoring approach to consider long-range interactions(LSC)of protein atoms by an exponential form in FFT-based protein-protein on general protein-protein complexes,our LSC approach showed a significant advantage over the traditional grid-based method (Yan and Huang 2018).Extending the LSC approach to symmetric complexes,we have here developed a fast ab initio docking approach for the symmetric docking of homo-oligomers with Cnsymmetry by an FFT-based search algorithm with LSC,which is referred to as AND DISCUSSIONComparison with other programsWe have tested our symmetric docking algorithm CHDOCK on the bound and unbound structures of our symmetric protein docking benchmark of 212 Cntargets (Yan and Huang 2019).Table 1 lists the success rates of CHDOCK in binding mode predictions for bound and unbound docking on the 212 cases with Cnsymmetry when the top 1,10,and 100 predictions are corresponding results are also shown in comparison,Table 1 and Fig.1 also give the corresponding results of three other Cnsymmetric docking algorithms,M-ZDOCK (Pierce et al.2005),SymmDock (Schneidman-Duhovny et al.2005),and SAM(Ritchie and Grudinin 2016),on this benchmark,in which the same clustering criteria have been applied to their final binding modes during the calculation of success rates.It can be seen from Table 1 and Fig.1 that CHDOCK obtained a significantly better performance than the other three docking methods for bound docking and achieved a success rate of 55.19%,72.17%,and 90.57% for top 1,10,and 100 predictions,respectively,in comparison to those of 45.76%,65.09%,and 89.15%for M-ZDOCK,38.85%,54.25%,and 84.91% for SAM,and 16.04% 31.60%,and 67.45% for trends can also be observed in the results for unbound docking,though the performance differences among different algorithms are not as much as those for bound docking due to the impact of conformational changes in the unbound ,CHDOCK also performed significantly better than the other three methods for unbound docking and obtained a success rate of 30.66%,44.81%,and 68.40% for top 1,10,and 100 predictions,respectively,in comparison to those of 26.42%,36.79%,and 66.51% for M-ZDOCK,19.34%,31.60%,and 63.68%for SAM,and 11.79%,30.66%,and 58.49% for SymmDock (Table 1 and Fig.1).Besides the success rate of docking,we have also compared the average root mean square deviation(RMSD) of ‘hit(s)’ (i.e.,successful binding mode predictions) for both bound docking and unbound docking with the other three programs when the top 1,10,100 predictions were results are listed in Table 2 and the corresponding results are shown in Table 2 and Fig.2,we can see that CHDOCK also performed much better and obtained moreaccurate binding modes than the other three programs for both bound docking and unbound bound docking,CHDOCK obtained an average RMSD of 1.10,1.51 and 2.11 ? for top 1,10 and 100 predictions,respectively,in comparison to those of 2.27,2.80 and 3.46 ? for the second-best method for unbound docking,similar results can also be obtained an average RMSD of 2.54,3.12 and 4.07 ? for top 1,10,100 predictions,respectively,while M-ZDOCK obtained a higher RMSD of 3.26,3.86 and 5.07 ?.Interestingly,one can also note that among the four docking programs,if a method performs better in the success rate of binding mode prediction,it also performs better in the average RMSD of ‘hits’.That means,the performance comes from both the number and the quality of successful 1 The success rates (%) predicted by our CHDOCK and three other symmetric docking programs on our protein docking benchmark of 212 Cnsymmetric complexes when the top 1,10,and 100 predictions were consideredBound docking Unbound docking Method Top 1 Top 10 Top 100 Top 1 Top 10 Top 100 CHDOCK 55.19 72.17 90.57 30.66 44.81 68.40 M-ZDOCK 45.76 65.09 89.15 26.42 36.79 66.51 SAM 35.85 54.25 84.91 19.34 31.60 63.68 SymmDock 16.04 31.60 67.45 11.79 30.66 The success rates of our CHDOCK and three other symmetric docking methods in binding mode predictions on our protein docking benchmark of 212 Cnsymmetric complexes for bound docking(A)and unbound docking(B).For each method,from left to right are for the results of top 100,10,and 1 prediction,respectivelyTable 2 The average LRMSD(?)of ‘hit(s)’predicted by our CHDOCK and three other symmetric docking programs on our protein docking benchmark of 212 Cnsymmetric complexes when the top 1,10,and 100 predictions were consideredBound docking Unbound docking Method Top 1 Top 10 Top 100 Top 1 Top 10 Top 100 CHDOCK 1.10 1.51 2.11 2.54 3.12 4.07 M-ZDOCK 2.27 2.80 3.46 3.26 3.86 5.07 SAM 2.28 2.88 4.10 3.43 4.03 5.48 SymmDock 3.40 4.42 5.72 5.15 5.61 of scoring The average RMSD of first ‘hit(s)’ of our CHDOCK and three other symmetric docking methods tested on our protein docking benchmark of 212 Cnsymmetric complexes for bound docking(A)and unbound docking(B).For each method,from left to right are for the results of top 100,10,and 1 prediction,respectivelyTo investigate the performance of our scoring function,we also tested our pure FFT-based docking,named CHDOCK_lite,on the benchmark,which only uses the shape complementarity to filter and sort docking docking results for bound docking and unbound docking are shown in Fig.3.It can be seen from the figure that CHDOCK performed much better than CHDOCK_ the help of our scoring function ITScorePP (Huang and Zou 2008),the success rate of bound docking for top 1 prediction increased from 21.70% to 55.19% and for unbound docking,the success rate increased from 11.32% to 30.66%.The great improvement of CHDOCK compared to CHDOCK_lite demonstrates the important role of our scoring and M-ZDOCK are both the three-dimensional(3D) FFT-based docking algorithms and adopt the similar sampling ,the difference between CHDOCK and M-ZDOCK is that CHDOCK adopts a better shape complementarity score LSC (Yan and Huang 2018) and a more powerful scoring function ITScorePP(Huang and Zou 2008).In our previous study on hetero protein complexes (Yan and Huang 2018),LSC has shown its better performance than PSC(Chen and Weng 2003) used in also showed a better performance in scoring decoys and finding the near native structures (Huang and Zou 2008).Therefore,the better performance of CHDOCK than M-ZDOCK would be attributed to both the shape complementarity score LSC and our scoring function CHDOCK has achieved better performance than the other three docking programs,the success rate for top 1 prediction is still not high,especially for unbound are much room to improve the existing methods and develop new docking programs in the The success rate as a function of the number of top predictions for our CHDOCK and CHDOCK_lite tested on our protein docking benchmark of 212 Cnsymmetric complexes for bound docking (A) and unbound docking (B)Examples of the docking modelFigure 4 shows the top binding modes predicted by our CHDOCK for both bound and unbound docking on three example can be seen from the figure that the predicted complexes overlap well with the experimental native structures,and give a ligand RMSD of 0.42 and 4.03 ? for C2symmetric target 1MSC,0.92 and 3.38 ? for C4symmetric target 1OVO,and 0.95 and 1.20 ? for C6symmetric target 1KQ1, good consistency between the predicted and native structures in both bound and unbound docking demonstrates the reliability of our have developed a hierarchical docking algorithm for predicting the complex structures of homo-oligomers with Cnsymmetry,which referred to as Cnsymmetric binding modes were first generated by an FFT-based docking algorithm,in which a shape complementarity scoring function was used to consider long-range ,the binding modes with best shape complementarity were optimized with our iterative scoring function for protein-protein symmetric docking algorithm CHDOCK was evaluated on a diverse benchmark of 212 Cnsymmetric protein complexes from the PDB,and was compared with three state-of-the-art symmetric docking approaches including M-ZDOCK,SAM,and shows that CHDOCK achieved a significantly better performance than the other three docking methods in both the number and the quality of successful predictions for bound docking and unbound results demonstrate the strong predictive power of our hierarchical docking algorithm CHDOCK in modeling Cnsymmetric protein AND METHODSFFT-based translational Comparisons between the top predicted binding modes and native structures for three targets 1MSC (C2 symmetry) (A),1OVO(C4 symmetry)(B)and 1KQ1(C6 symmetry)(C).The native structure is colored in pink and the predicted structure is colored by each column,the upper and lower ones are for bound docking and unbound docking,respectivelyThe putative symmetrical complexes were constructed from a monomer or subunit in 3D translational space by a modified version of our general FFT-based docking algorithm (Yan et al.2017; Yan and Huang 2018).Specifically,we first made two copies of the subunit or was called ‘receptor’ subunit and the other ‘ligand’’ docking with Cnsymmetry,the receptor subunit was fixed and the ligand subunit was rotated by an angle of 360°/n around the perform an FFT-based search,both the receptor and ligand subunits needed to be mapped onto a 3D grid of N×N×N grid points (Chen and Weng 2003;Katchalski-Katzir et al.1992).The grid points within the VDW radius of any protein atoms were considered inside the molecule,and the others were considered as outside the ,the VDW radii for standard protein atoms were taken from the study by Li and Nussinov (1998).Then,the inside-protein grid points were divided into three parts∶ surface layer,nearsurface layer,and core is defined that a grid point belonged to the surface layer if any of its neighboring grid points is outside the ,a grid point belonged to the near-surface layer if any of its neighbors is in the surface the other grid points except the surface and near-surface layers inside the protein were defined as the core to the above definitions,one can see that the nearsurface layer and core region were normally occupied by the protein atoms,and the surface layer separated the inside protein from the outside ,each grid point for the receptor (R) and ligand (L) subunits was assigned a complex value as∶andwhere J2=-1,l,m,and n are the indices of the 3D grid(l，m，n=1，???，N),and r is the distance between the grid points of(i,j,k)and(l,m,n).Here,i ∈[l -3，l+3],j ∈[m-3，m+3] and k ∈[n-3，n+3] for the surface layer,and i ∈[l -1，l+1],j ∈[m-1，m+1] and k ∈[n-1，n+1] for the near-surface layer, also,the grid point (i,j,k) should belong to nearsurface layer or protein the above mapping of the proteins on the grid,the shape complementarity score between two neighboring subunits of a symmetric complex around the zaxis can be generally expressed by the following equation (Chen and Weng 2003; Katchalski-Katzir et al.1992)∶where o and p are the number of grid points by which the ligand (L) is shifted with respect to the receptor(R)in the x-y plane,re is no shift in the z-axis because the rotational axis is parallel to the z-axis,which reduces the sampling space in one translational correlation of Eq.3 can be calculated by an FFT-based higher correlation score means a better shape complementarity between two grids for a relative translation of (o,p) (Katchalski-Katzir et al.1992).Rotational sampling strategyTo perform a global sampling approach for putative binding modes,one needs to search the six-dimensional(i.e.,3 translational + 3 rotational) exhaustive search in 3D translational space can be performed by an FFT-based approach,as described in the previous exhaustive search in the rotational space will be conducted in the space of Euler angles by taking into the Cnsymmetry restriction ,the monomer subunit is rotated by an interval of Euler angles (φ=0,Δθ,Δψ) in the rotational space,where the angular definition is based on the so-called ‘x-axis convention’.Namely,φ is the first rotation about the zaxis,θ ∈0，π/2[ ]is the second rotation about the former x-axis (now x′),and ψ ∈(0,2π] is the third rotation about the former z-axis (now z′).It is unnecessary to sample the φ angles as the rotational axis is addition,θ only needs to be sampled within 0，π/2[ ]instead of 0，π[ ] because of the rotational these reduce the sampling space in the rotational ,for each rotation of the monomer subunit,an FFT-based algorithm was used to calculate the shape complementarity between the grids of the receptor and the ligand in the translational the docking calculation,an angle interval of 10° was used for rotational sampling,and a spacing of 1.2 ? was adopted in discretizing proteins onto grids for FFT-based translational distributed Euler angles were used for the rotational search,resulting in a total of 360 orientations in the rotational each rotation,up to the top 100 translations with best shape complementarities were kept and optimized by our scoring function ITScorePP(Huang and Zou 2008).The binding mode that corresponds to the best energy score in an FFT-based translational search was kept for each rotation of the ligand subunit,yielding a total of 360 ligand binding modes for a docking run.Our FFT-based docking algorithm is computationally efficient and on average can complete a full docking calculation in 30 min on a 2.6 GHZ Intel CPU functionAll the binding modes generated from the initial stage were evaluated by ITScorePP (Huang and Zou 2008)and minimized according to their binding scores by a SIMPLEX optimization binding energy score is a summation of the binding scores over all the interfaces between the subunits of the predicted final ranked binding modes were clustered with an RMSD cutoff of 5 ?,where the RMSD was calculated using the backbone atoms.If two binding modes have a ligand RMSD of ＜5 ?,the one with the better score is on the protein complexes in the PDB,we have also constructed a non-redundant benchmark for our symmetric protein-protein ,all the homo-oligomeric protein complexes with Cnsymmetry were collected from the crystal structures with resolution better than 2.5 ?.The symmetry type of a complex was determined by its biological unit.The symmetric homo-oligomer complexes were then clustered according to their SCOP (version 1.75) family IDs (Lo Conte et al.2000).For the complexes belonging to the same family,the one with the best resolution was selected as the representative,corresponding to a bound case of our benchmark,in which each subunit was called the bound structure of the the bound structure in each bound case,the unbound structure was identified by searching against the PDB database for the asymmetric structures using the BLASTP (proteinprotein BLAST) algorithm of the BLAST package (Camacho et al.2009).If an asymmetric structure had＞95% sequence identity with the bound structure and covered ＞95% of the sequence alignment,the asymmetric structure was regarded as a candidate of the unbound there were multiple unbound structures for a subunit protein,the one with the high resolution was selected as the yielded a total of 212 homo-oligomeric protein complexes with Cnsymmetry (http∶///SDBenchmark/) (Yan and Huang 2019).All the structures in the benchmark have their original coordinates without any random criteriaThe quality of a predicted binding mode was measured by the ligand RMSD (LRMSD).Here,the RMSD was calculated based on the backbone atoms of the ligand subunit after optimal superimposition of the receptor subunit and the native docking performance was evaluated by the success rate,i.e.,the fraction of the targets with at least one hit in the test set when a certain number of top predictions were ,a hit is a prediction with a ligand RMSD of＜10 ? (Huang 2014).AcknowledgementsThis work was supported by the National Key Research and Development Program of China(2016YFC and 2016YFC),the National Natural Science Foundation of China(),and the startup grant of Huazhong University of Science and Technology ().Compliance with Ethical StandardsConflict of interestYumeng Yan,Sheng-You Huang declare that they have no conflict of and animal rights and informed consentThis article does not contain any studies with human or animal subjects performed by any of the AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http∶///licenses/by/4.0/),which permits unrestricted use,distribution,and reproduction in any medium,provided you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons license,and indicate if changes were I,Strauss CE,Kaplan DB,Bradley P,Baker D (2008)Emergence of symmetry in homooligomeric biological Natl Acad Sci USA 105∶-Baek M,Park T,Heo L,Park C,Seok C (2017) GalaxyHomomer∶a web server for protein homo-oligomer structure prediction from a monomer sequence or Acids Res 45∶W320-W324Berman HM,Westbrook J,Feng Z,Gilliland G,Bhat TN,Weissig H,Shindyalov IN,Bourne PE (2000) The protein data Acids Res 28∶235-242Biasini M,Bienert S,Waterhouse A,Arnold K,Studer G,Schmidt T,Kiefer F,Gallo Cassarino T,Bertoni M,Bordoli L,Schwede T(2014) SWISS-MODEL∶modelling protein tertiary and quaternary structure using evolutionary Acids Res 42∶W252-W258Camacho C,Coulouris G,Avagyan V,Ma N,Papadopoulos J,Bealer K,Madden TL(2009)BLAST+∶architecture and Bioinform 10∶421Chen R,Weng Z (2003) A novel shape complementarity scoring function for protein-protein 51∶397-408Comeau SR,Gatchell DW,Vajda S,Camacho CJ (2004) ClusPro∶a fully automated algorithm for protein-protein Acids Res 32∶W96-W99de Vries SJ,van Dijk M,Bonvin AM (2010) The HADDOCK web server for data-driven biomolecular Protoc 5∶883-897de Vries SJ,Schindler CE,Chauvot de Beauchene I,Zacharias M(2015) A web interface for easy flexible protein-protein docking with J 108∶462-465DiMaio F,Leaver-Fay A,Bradley P,Baker D,Andre I (2011)Modeling symmetric macromolecular structures in ONE 6∶eGoodsell DS,Olson AJ (2000) Structural symmetry and protein Rev Biophys Biomol Struct 29∶105-153Huang S-Y (2014) Search strategies and evaluation in proteinprotein docking∶principles,advances and Discov Today 19∶1081-1096Huang S-Y,Zou X (2008) An iterative knowledge-based scoring function for protein-protein 72∶557-579Katchalski-Katzir E,Shariv I,Eisenstein M,Friesem AA,Aflalo C,Vakser IA (1992) Molecular surface recognition∶determination of geometric fit between proteins and their ligands by correlation Natl Acad Sci USA 89∶2195-2199Lee H,Park H,Ko J,Seok C(2013)GalaxyGemini∶a web server for protein homo-oligomer structure prediction based on 29∶1078-1080Lensink MF,Velankar S,Kryshtafovych A,Huang SY,Schneidman-Duhovny D,Sali A,Segura J,Fernandez-Fuentes N,Viswanath S,Elber R (2016) Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling∶a CASP-CAPRI 84∶323-348Lensink MF,Velankar S,Baek M,Heo L,Seok C,Wodak SJ (2018)The challenge of modeling protein assemblies∶the CASP12-CAPRI 86∶257-273Li AJ,Nussinov R (1998) A set of van der Waals and coulombic radii of protein atoms for molecular and solvent-accessible surface calculation,packing evaluation,and 32∶111-127Lo Conte L,Ailey B,Hubbard TJ,Brenner SE,Murzin AG,Chothia C(2000) SCOP∶a structural classification of proteins Acids Res 28∶257-259Petsalaki E,Russell RB (2008) Peptide-mediated interactions in biological systems∶new discoveries and Opin Biotechnol 19∶344-350Pierce B,Tong W,Weng Z(2005)M-ZDOCK∶a grid-based approach for Cnsymmetric multimer 21∶1472-1478Poupon A,Janin J (2010) Analysis and prediction of protein quaternary ∶Data mining techniques for the life ,pp 349-364Ritchie DW,Grudinin S(2016)Spherical polar Fourier assembly of protein complexes with arbitrary point group Appl Crystallogr 49∶158-167Schneidman-Duhovny D,Inbar Y,Nussinov R,Wolfson HJ (2005)PatchDock and SymmDock∶servers for rigid and symmetric Acids Res 33∶W363-W367Torchala M,Moal IH,Chaleil RA,Fernandez-Recio J,Bates PA(2013) SwarmDock∶ a server for flexible protein-protein 29∶807-809Tovchigrechko A,Vakser IA (2006) GRAMM-X public web server for protein-protein Acids Res 34∶W310-W314Yan Y,Huang S-Y (2018) Protein-protein docking with improved shape ∶ International conference on intelligent ,pp 600-605Yan Y,Huang S-Y (2019) A non-redundant benchmark for symmetric protein Data Min Anal 2∶92-99Yan Y,Wen Z,Wang X,Huang SY(2017)Addressing recent docking challenges∶a hybrid strategy to integrate template-based and free protein-protein 85∶497-512

文章来源：《科学学研究》 网址: http://www.kxxyj.cn/qikandaodu/2020/0925/391.html