over 25 unique protein-ligand complex structures were de- proach of Chothia and Lesk has proved particularly effective termined by X-ray crystallography, and the inhibition con- in predicting the conformations of five of the six hy- stants determined for these ligands and many other com- pervariable loops on the basis of homology, but has failed in pounds. We have used this information to test the predictive the case of the sixth loop, which is central to the antigen- capability of using the rather simple and approximate tech- binding site and is the most varied in conformation. In this niques of molecular mechanics minimization with an im- talk, we present a possible technique for the modeling of plicit aqueous solvation model and limited conformational such a loop. An algorithm for generating low-energy confor- searching. Thus, binding affinities were calculated using the mations for loop regions of a protein will be described. This energy-minimized crystal protein-ligand complexes and algorithm involves random pe~urbations to the backbone low-energy solution conformation structures of the unbound phi, psi torsion angles of the loop, folfowed by intelligent ligand. These results were ranked and compared to the alterations to these torsion angles in order to restore and inhibition constants. The program used was MacroModel maintain correct closure of the loop with the rest of the and the force field used was AMBER. protein.

Results

In all cases, the ligands were predicted to bind to the protein with high affinity, but the calculated “binding energies” were much larger than the free energies inferred from the inhibition constants. This discrepancy can be rationalized in terms of neglected unfavorable entropic effects.

Qualitative ranking within a homologous series is not possible for differences in experimental binding affinities less than c.a. 3 kcalimol but seems possible for differences larger than this.

It may be possible to calculate absolute binding affinities to within 3-4 kcallmol if one uses some simple approxima- tions regarding configu~tional entropy losses on binding.

Conclusion

Although still in the early stages of developments the method shows promise for calculating a binding affinity in a rapid and approximate manner, especially if entropic effects are considered. It may be useful as a tool for calculations involving molecules from a database docked into a protein structure, or for early evaluation of design ideas prior to synthesis.

A COMPUTATIONAL ALGORITHM FOR LOOP CLOSURE AND APPLICATION TO MODELING OF THE HYPERVARIABLE LOOPS IN ANTIBODIES

C.M. Venkatachalam, D.J. Edwards, E.A. Potterton, and R.E. Hubbard Molecular Simulations Inc., Burlington, MA, USA and Dept. of Chemistry, University of York, York, UK

Homology modeling is often employed to construct a struc- ture for a protein using information from homologous pro- teins of known three-dimensional structure. This has been widely used in the modeling of antibody structures where the major differences are changes in sequence and occur- rence of insertions or deletions in the ioop regions which form the antigen binding site. The canonical-structures ap-

After a reasonable backbone conformation is obtained, the side chains are placed using a side chain rotamer library. Finally, the loop is annealed by energy nlinimization using the CHARMm force field. The algorithm may be repeated successively to obtain a thorough sampling of the conforma- tional space of the loop. This is achieved without altering the coordinates of the residues outside the loop region,

Examples of the use of this algorithm and the efficiency of the procedure will be described. Clearly, such an algorithm is applicable to modeling loops in any protein.

THE INFORMATION EXPLOSION: HOW CAN WE COPE?

Peter Murray-Rust Protein Structure Group, GlaxoGroup Research, Greenford, Middlesex, UK

Data in structural biology (protein structure, sequence, and biological activity) are being published at a rate which dou- bles about every I8 months. With the recent advances in sequence determination and a steady advance in the hard- ware and software available to crystallographers this prob- lem is getting even more acute. Managing the information in this data requires different approaches than those that are common in the chemical information field. The data are “fuzzy,” and there are few standards, so that a conventional top-down approach is likely to be out of date by the time it is completed. The questions that scientists wish to ask are wide ranging and often boil down to “Here is a new sequence; what implications does it have for my project?”

I shall try to show some of the developments which offer constructive ways forward. The most important will be coi- laboration and communication between groups across the world, since most of the data will be in the public domain. It will be critical to provide navigation systems through the data, since users cannot be expected to know where they are or how to use them. This formidable challenge requires a new set of tools, among which are: managed libraries of data, data standards, probably cle fucro initially, flexible graphical interfaces (e.g., X-windows), object-based tools (probably C-+ + classes), and transparent, high band- width comms (for multimedia).

The Molecular Graphics Society has an excellent record of facilitating collaboration, and so wili have an important role in the future of bioinformatics.

268 J. Mol. Graphics, 1993$ Vol. 11, December