SmoothDock - Revision history

Christoph at 22:27, 15 March 2018

2018-03-15T22:27:08Z

Christoph: /* External links */

2012-02-18T18:07:11Z

‎External links

Christoph at 01:25, 17 December 2009

2009-12-17T01:25:21Z

Christoph: /* See also */

2008-12-01T05:43:09Z

‎See also

Christoph at 07:42, 9 May 2008

2008-05-09T07:42:49Z

Christoph: /* Technical details */

2008-05-09T07:42:07Z

‎Technical details

Christoph at 06:58, 9 May 2008

2008-05-09T06:58:46Z

Christoph: /* See also */

2008-05-09T06:56:40Z

‎See also

Christoph: /* See also */

2008-05-09T04:07:26Z

‎See also

Christoph at 04:04, 9 May 2008

2008-05-09T04:04:59Z

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-'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref><ref name="Kozakov2006">Kozakov D, Brenke R, Comeau SR, Vajda S (2006). PIPER: An FFT-based protein docking program with pairwise potentials. ''Proteins''.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).
+'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro'',<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref><ref name="Kozakov2006">Kozakov D, Brenke R, Comeau SR, Vajda S (2006). PIPER: An FFT-based protein docking program with pairwise potentials. ''Proteins''.</ref> developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).
-''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to [http://vakser.bioinformatics.ku.edu/resources/gramm/grammx GRAMM-X], and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.
+''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]],<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref> and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to [http://vakser.bioinformatics.ku.edu/resources/gramm/grammx GRAMM-X], and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.
 ==The ''SmoothDock'' algorithm==
@@ Line 16: / Line 16: @@
 ===Step 2: filtering decoys===
-Following the procedure detailed elsewhere<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref><ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref><ref>Camacho CJ, Weng Z, Vajda S, DeLisi C (1999). Free energy landscapes of encounter complexes in protein-protein association. ''Biophys J'', '''76''':1166-1178.</ref>, for each complex we compute the effective desolvation and electrostatic binding affinity between receptor and ligand. We then filter the 500 best desolvation energy<ref>Zhang C, Vasmatzis G, Cornette JL (1997). Determination of atomic desolvation energies from the structures of crystallized proteins. ''J Mol Biol'', '''267''':707-726.</ref> and 1,500 best electrostatic energy<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref> complexes for a total of 2,000 complex candidates.
+Following the procedure detailed elsewhere,<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref><ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref><ref>Camacho CJ, Weng Z, Vajda S, DeLisi C (1999). Free energy landscapes of encounter complexes in protein-protein association. ''Biophys J'', '''76''':1166-1178.</ref> for each complex we compute the effective desolvation and electrostatic binding affinity between receptor and ligand. We then filter the 500 best desolvation energy<ref>Zhang C, Vasmatzis G, Cornette JL (1997). Determination of atomic desolvation energies from the structures of crystallized proteins. ''J Mol Biol'', '''267''':707-726.</ref> and 1,500 best electrostatic energy<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref> complexes for a total of 2,000 complex candidates.
 ===Step 3: clustering decoys===
-We cluster the filtered complexes using a ''pairwise RMS deviation'' (RMSD) criterion (see below), and retain the twenty-five clusters with the highest number of neighbors<ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref>.
+We cluster the filtered complexes using a ''pairwise RMS deviation'' (RMSD) criterion (see below), and retain the twenty-five clusters with the highest number of neighbors.<ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref>
 The complexes are clustered in either of two ways:
@@ Line 28: / Line 28: @@
 ====Pairwise RMSD clustering====
-The top 2000 energetically favourable structures are then clustered on the basis of a pairwise binding site root mean squared deviation (RMSD) criterion. For each of the 2000 structures, the residues of the moving molecule (designated as the ligand) that have at least one atom within 10 Å of any atom of the still molecule (designated as the receptor) are recorded into a list. Then, the distance between the C&alpha; of each of those residues and the C&alpha; of the corresponding residues on each of the 2000 ligands is calculated and stored into a matrix. Clusters are then formed by selecting the ligand that has the most neighbours below a previously selected clustering radius. Each member within the cluster is then eliminated from the matrix to avoid overlaps between clusters. This is repeated until at least 30 clusters are formed. The ligand with the most neighbours is the cluster centre, and is the representative structure for the cluster. The top cluster centres are then minimized in CHARMM<ref>Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983). CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. ''J Comput Chem'', '''4''':187–217.</ref> in the presence of the receptor, and concatenated into a PDB in NMR format.
+The top 2,000 energetically favourable structures are then clustered on the basis of a pairwise binding site root mean squared deviation (RMSD) criterion. For each of the 2,000 structures, the residues of the moving molecule (designated as the ligand) that have at least one atom within 10 Å of any atom of the still molecule (designated as the receptor) are recorded into a list. Then, the distance between the C&alpha; of each of those residues and the C&alpha; of the corresponding residues on each of the 2,000 ligands is calculated and stored into a matrix. Clusters are then formed by selecting the ligand that has the most neighbours below a previously selected clustering radius. Each member within the cluster is then eliminated from the matrix to avoid overlaps between clusters. This is repeated until at least 30 clusters are formed. The ligand with the most neighbours is the cluster centre, and is the representative structure for the cluster. The top cluster centres are then minimized in CHARMM<ref>Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983). CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. ''J Comput Chem'', '''4''':187–217.</ref> in the presence of the receptor, and concatenated into a PDB in NMR format.
 ===Step 4: refinement and discrimination of native-like clusters===

← Older revision		Revision as of 18:07, 18 February 2012
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	[[Category:Academic Research]]		[[Category:Academic Research]]
	[[Category:Bioinformatics]]		[[Category:Bioinformatics]]
		+	[[Category:Portfolio]]

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 ===Step 2: filtering decoys===
-Following the procedure detailed elsewhere<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref><ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref><ref>Camacho CJ, Weng Z, Vajda S, DeLisi C (1999). Free energy landscapes of encounter complexes in protein-protein association. ''Biophys J'', '''76''':1166-1178.</ref>, for each complex we comput the effective desolvation and electrostatic binding affinity between receptor and ligand. We then filter the 500 best desolvation energy<ref>Zhang C, Vasmatzis G, Cornette JL (1997). Determination of atomic desolvation energies from the structures of crystallized proteins. ''J Mol Biol'', '''267''':707-726.</ref> and 1,500 best electrostatic energy<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref> complexes for a total of 2,000 complex candidates.
+Following the procedure detailed elsewhere<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref><ref>Gatchell D, Vajda S, Camacho CJ. Sampling, clustering, refinement and discrimination of protein interactions using SmoothDock. ''To be Submitted''.</ref><ref>Camacho CJ, Weng Z, Vajda S, DeLisi C (1999). Free energy landscapes of encounter complexes in protein-protein association. ''Biophys J'', '''76''':1166-1178.</ref>, for each complex we compute the effective desolvation and electrostatic binding affinity between receptor and ligand. We then filter the 500 best desolvation energy<ref>Zhang C, Vasmatzis G, Cornette JL (1997). Determination of atomic desolvation energies from the structures of crystallized proteins. ''J Mol Biol'', '''267''':707-726.</ref> and 1,500 best electrostatic energy<ref>Camacho C, Gatchell D, Kimura R, Vajda S (2000). Scoring docked conformations generated by rigid body protein-protein docking. ''Proteins'', '''40''':525-537.</ref> complexes for a total of 2,000 complex candidates.
 ===Step 3: clustering decoys===
@@ Line 25: / Line 25: @@
 # using a C&alpha; binding site RMSD criterion and a cutoff radius of 7 Å.
-All clustering is done in a hierarchical manner such that no overlaps occurred between distinct clusters.
+All clustering is done in a hierarchical manner such that no overlaps occur between distinct clusters.
 ====Pairwise RMSD clustering====
-The top 2000 energetically favourable structures are then clustered on the basis of a pairwise binding site root mean squared deviation (RMSD) criterion. For each of the 2000 structures, the residues of the moving molecule (designated as the ligand) that have at least one atom within 10 Å of any atom of the still molecule (designated as the receptor) are recorded into a list. Then, the distance between the C&alpha; of each of those residues and the C&alpha; of the corresponding residues on each of the 2000 ligands is calculated and stored into a matrix. Clusters are then formed by selecting the ligand that has the most neighbours below a previously selected clustering radius. Each member within the cluster is then eliminated from the matrix to avoid overlaps between clusters. This is repeated until at least 30 clusters are formed. The ligand with the most neighbours is the cluster centre, and is the representative structure for the cluster. The top cluster centres are then CHARMM<ref>Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983). CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. ''J Comput Chem'', '''4''':187–217.</ref> minimized in the presence of the receptor, and concatenated into PDB NMR format.
+The top 2000 energetically favourable structures are then clustered on the basis of a pairwise binding site root mean squared deviation (RMSD) criterion. For each of the 2000 structures, the residues of the moving molecule (designated as the ligand) that have at least one atom within 10 Å of any atom of the still molecule (designated as the receptor) are recorded into a list. Then, the distance between the C&alpha; of each of those residues and the C&alpha; of the corresponding residues on each of the 2000 ligands is calculated and stored into a matrix. Clusters are then formed by selecting the ligand that has the most neighbours below a previously selected clustering radius. Each member within the cluster is then eliminated from the matrix to avoid overlaps between clusters. This is repeated until at least 30 clusters are formed. The ligand with the most neighbours is the cluster centre, and is the representative structure for the cluster. The top cluster centres are then minimized in CHARMM<ref>Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983). CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. ''J Comput Chem'', '''4''':187–217.</ref> in the presence of the receptor, and concatenated into a PDB in NMR format.
 ===Step 4: refinement and discrimination of native-like clusters===

@@ Line 48: / Line 48: @@
 *[[CAPRI]]
 *[http://cluspro.bu.edu/ ClusPro]
 *[http://dock.compbio.ucsf.edu/Contributed_Code/index.htm Official UCSF DOCK Web-site]
 *[http://wiki.compbio.ucsf.edu/wiki/index.php/Main_Page Dockumentation] &mdash; a community-driven project to document the UCSF DOCK program.
@@ Line 54: / Line 55: @@
 *[http://vakser.bioinformatics.ku.edu/resources/gramm/grammx GRAMM-X] &mdash; by the Ilya A. Vakser Lab
 *[http://dockground.bioinformatics.ku.edu/ Dockground] &mdash; an integrated system of databases for protein recognition studies.
 ===Concepts===
 *[[wikipedia:Electrostatics]]

@@ Line 1: / Line 1: @@
 '''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref><ref name="Kozakov2006">Kozakov D, Brenke R, Comeau SR, Vajda S (2006). PIPER: An FFT-based protein docking program with pairwise potentials. ''Proteins''.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).
-''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to GRAMM-X, and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.
+''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to [http://vakser.bioinformatics.ku.edu/resources/gramm/grammx GRAMM-X], and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.
 ==The ''SmoothDock'' algorithm==

@@ Line 37: / Line 37: @@
 The algorithm described above is implemented through a combination of Fortran77 and C code. The initial data (input) and results (output) are sent through multiple pipes as a series of I/O streams using [[Perl]], [[awk]], [[sed]], and [[bash]] scripts. They are all controlled via [[make|makefiles]] and use extensive [[regular expression]]s.
-Since billions of calculations (a minimum of 2.7 x 10<sup>10</sup>) are needed for ''each'' receptor/ligand complex, the main (C) code was optimised to run in parallel on a dedicated cluster of 256 CPUs (using the MPICH compiler).
+Since billions of calculations (a minimum of 128<sup>3</suP>*13000 ≈ 2.7 x 10<sup>10</sup>) are needed for ''each'' receptor/ligand complex, the main (C) code was optimised to run in parallel on a dedicated cluster of 256 CPUs (using the MPICH compiler).
 ==The ''SmoothDock'' Server==

← Older revision		Revision as of 06:58, 9 May 2008
Line 1:		Line 1:
−	'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory\|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).	+	'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory\|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref><ref name="Kozakov2006">Kozakov D, Brenke R, Comeau SR, Vajda S (2006). PIPER: An FFT-based protein docking program with pairwise potentials. ''Proteins''.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).

	''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to GRAMM-X, and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.		''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to GRAMM-X, and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.

@@ Line 51: / Line 51: @@
 *[http://bioinfo3d.cs.tau.ac.il/PatchDock/index.html PatchDock]
 *[http://bioinfo3d.cs.tau.ac.il/SymmDock/index.html SymmDock]
 *[http://dockground.bioinformatics.ku.edu/ Dockground] &mdash; an integrated system of databases for protein recognition studies.
 ===Concepts===

← Older revision		Revision as of 04:04, 9 May 2008
Line 1:		Line 1:
	'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory\|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).		'''''SmoothDock''''' is a fully automated algorithm for finding physical interactions between proteins involved in common cellular functions. It was developed by [[Dr. Carlos J. Camacho Laboratory\|Carlos J. Camacho]] and [[Christoph Champ]] at the University of Pittsburgh. It is based upon a previous algorithm, ''ClusPro''<ref>Comeau SR, Gatchell DW, Vajda S, Camacho CJ (2004). ClusPro: a fully automated algorithm for protein-protein docking. ''Nucleic Acids Res'', '''32''':W96-9.</ref>, developed by Camacho and Steven R. Comeau at Boston University (note: ''ClusPro'' is also based on a previous algorithm, ''Consensus''<ref>Prasad JC, Vajda S, Camacho CJ (2004). Consensus alignment server for reliable comparative modeling with distant templates. ''Nucleic Acids Res'', '''32''':W50-4.</ref>).
		+
		+	''SmoothDock'' starts from around 20,000 predictions obtained from FFT-based global search program [[DOT]]<ref name="Mandell2001">Mandell JG, Roberts VA, Pique ME, Kotlovyi V, Mitchell JC, Tsigelny NE I, Ten Eyck LF (2001). Protein docking using continuum electrostatics and geometric fit. ''Protein Eng, 14:105–113''.</ref>, and then employs a rigid body minimization with a combination of empirical and standard force field energy terms and clustering. In general outline, ''ClusPro'' and ''SmoothDock'' are similar to GRAMM-X, and all use FFT-based initial global search, but the refinement/re-scoring protocols and potential terms differ in each case.

	==The ''SmoothDock'' algorithm==		==The ''SmoothDock'' algorithm==