PMID- 8951649
OWN - NLM
STAT- MEDLINE
DCOM- 19970328
LR  - 20191101
IS  - 0920-654X (Print)
IS  - 0920-654X (Linking)
VI  - 10
IP  - 5
DP  - 1996 Oct
TI  - Computational combinatorial ligand design: application to human alpha-thrombin.
PG  - 372-96
AB  - A new method is presented for computer-aided ligand design by combinatorial 
      selection of fragments that bind favorably to a macromolecular target of known 
      three-dimensional structure. Firstly, the multiple-copy simultaneous-search 
      procedure (MCSS) is used to exhaustively search for optimal positions and 
      orientations of functional groups on the surface of the macromolecule (enzyme or 
      receptor fragment). The MCSS minima are then sorted according to an approximated 
      binding free energy, whose solvation component is expressed as a sum of separate 
      electrostatic and nonpolar contributions. The electrostatic solvation energy is 
      calculated by the numerical solution of the linearized Poisson-Boltzmann 
      equation, while the nonpolar contribution to the binding free energy is assumed 
      to be proportional to the loss in solvent-accessible surface area. The program 
      developed for computational combinatorial ligand design (CCLD) allows the fast 
      and automatic generation of a multitude of highly diverse compounds, by 
      connecting in a combinatorial fashion the functional groups in their minimized 
      positions. The fragments are linked as two atoms may be either fused, or 
      connected by a covalent bond or a small linker unit. To avoid the combinatorial 
      explosion problem, pruning of the growing ligand is performed according to the 
      average value of the approximated binding free energy of its fragments. The 
      method is illustrated here by constructing candidate ligands for the active site 
      of human alpha-thrombin. The MCSS minima with favorable binding free energy 
      reproduce the interaction patterns of known inhibitors. Starting from these 
      fragments, CCLD generates a set of compounds that are closely related to 
      high-affinity thrombin inhibitors. In addition, putative ligands with novel 
      binding motifs are suggested. Probable implications of the MCSS-CCLD approach for 
      the evolving scenario of drug discovery are discussed.
FAU - Caflisch, A
AU  - Caflisch A
AD  - Department of Biochemistry, University of Zurich, Switzerland.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - Netherlands
TA  - J Comput Aided Mol Des
JT  - Journal of computer-aided molecular design
JID - 8710425
RN  - 0 (Enzyme Inhibitors)
RN  - 0 (Ligands)
RN  - 0 (Macromolecular Substances)
RN  - 0 (Pyrrolidines)
RN  - 5L0H5Q9VAG (Methylguanidine)
RN  - EC 3.4.21.5 (Thrombin)
SB  - IM
MH  - Binding Sites
MH  - *Computer-Aided Design
MH  - *Drug Design
MH  - Enzyme Inhibitors/chemistry
MH  - Humans
MH  - Ligands
MH  - Macromolecular Substances
MH  - Methylguanidine/chemistry
MH  - Models, Molecular
MH  - Molecular Structure
MH  - Protein Conformation
MH  - Pyrrolidines/chemistry
MH  - Software
MH  - Static Electricity
MH  - Thermodynamics
MH  - Thrombin/antagonists & inhibitors/*chemistry
EDAT- 1996/10/01 00:00
MHDA- 1996/10/01 00:01
CRDT- 1996/10/01 00:00
PHST- 1996/10/01 00:00 [pubmed]
PHST- 1996/10/01 00:01 [medline]
PHST- 1996/10/01 00:00 [entrez]
AID - 10.1007/BF00124471 [doi]
PST - ppublish
SO  - J Comput Aided Mol Des. 1996 Oct;10(5):372-96. doi: 10.1007/BF00124471.