The results of the fifth blind test of crystal structure prediction, which show important success with more challenging large and flexible molecules, are presented and discussed.

We report on the organization and outcome of the fourth blind test of crystal structure prediction, an international collaborative project organized to evaluate the present state in computational methods of predicting the crystal structures of small organic molecules. There were 14 research groups which took part, using a variety of methods to generate and rank the most likely crystal structures for four target systems: three single-component crystal structures and a 1:1 cocrystal. Participants were challenged to predict the crystal structures of the four systems, given only their molecular diagrams, while the recently determined but as-yet unpublished crystal structures were withheld by an independent referee. Three predictions were allowed for each system. The results demonstrate a dramatic improvement in rates of success over previous blind tests; in total, there were 13 successful predictions and, for each of the four targets, at least two groups correctly predicted the observed crystal structure. The successes include one participating group who correctly predicted all four crystal structures as their first ranked choice, albeit at a considerable computational expense. The results reflect important improvements in modelling methods and suggest that, at least for the small and fairly rigid types of molecules included in this blind test, such calculations can be constructively applied to help understand crystallization and polymorphism of organic molecules.

Following the interest generated by two previous blind tests of crystal structure prediction (CSP1999 and CSP2001), a third such collaborative project (CSP2004) was hosted by the Cambridge Crystallographic Data Centre. A range of methodologies used in searching for and ranking the likelihood of predicted crystal structures is represented amongst the 18 participating research groups, although most are based on the global minimization of the lattice energy. Initially the participants were given molecular diagrams of three molecules and asked to submit three predictions for the most likely crystal structure of each. Unlike earlier blind tests, no restriction was placed on the possible space group of the target crystal structures. Furthermore, Z' = 2 structures were allowed. Part-way through the test, a partial structure report was discovered for one of the molecules, which could no longer be considered a blind test. Hence, a second molecule from the same category (small, rigid with common atom types) was offered to the participants as a replacement. Success rates within the three submitted predictions were lower than in the previous tests - there was only one successful prediction for any of the three ;blind' molecules. For the ;simplest' rigid molecule, this lack of success is partly due to the observed structure crystallizing with two molecules in the asymmetric unit. As in the 2001 blind test, there was no success in predicting the structure of the flexible molecule. The results highlight the necessity for better energy models, capable of simultaneously describing conformational and packing energies with high accuracy. There is also a need for improvements in search procedures for crystals with more than one independent molecule, as well as for molecules with conformational flexibility. These are necessary requirements for the prediction of possible thermodynamically favoured polymorphs. Which of these are actually realised is also influenced by as yet insufficiently understood processes of nucleation and crystal growth.

Recent improvements of a hierarchical ab initio or de novo approach for predicting both ␣ and ␤ structures of proteins are described. The united-residue energy function used in this procedure includes multibody interactions from a cumulant expansion of the free energy of polypeptide chains, with their relative weights determined by Z-score optimization. The critical initial stage of the hierarchical procedure involves a search of conformational space by the conformational space annealing (CSA) method, followed by optimization of an all-atom model. The procedure was assessed in a recent blind test of protein structure prediction (CASP4). The resulting lowest-energy structures of the target proteins (ranging in size from 70 to 244 residues) agreed with the experimental structures in many respects. The entire experimental structure of a cyclic ␣-helical protein of 70 residues was predicted to within 4.3 Å ␣-carbon (C ␣ ) rms deviation (rmsd) whereas, for other ␣-helical proteins, fragments of roughly 60 residues were predicted to within 6.0 Å C ␣ rmsd. Whereas ␤ structures can now be predicted with the new procedure, the success rate for ␣͞␤-and ␤-proteins is lower than that for ␣-proteins at present. For the ␤ portions of ␣͞␤ structures, the C ␣ rmsd's are less than 6.0 Å for contiguous fragments of 30 -40 residues; for one target, three fragments (of length 10, 23, and 28 residues, respectively) formed a compact part of the tertiary structure with a C ␣ rmsd less than 6.0 Å. Overall, these results constitute an important step toward the ab initio prediction of protein structure solely from the amino acid sequence. I mportant progress has been made in recent years toward the physics-based computation of protein structure based solely on knowledge of the amino acid sequence. This approach, commonly referred to as an ab initio or de novo method (1-3), is based on the thermodynamic hypothesis formulated by Anfinsen (4), according to which the native structure of a protein corresponds to the global minimum of its free energy under given conditions. Protein structure prediction by using ab initio methods is accomplished by a search for a conformation corresponding to the global-minimum of an appropriate potential energy function without use of secondary structure prediction, homology modeling, threading, etc.Until recently, ab initio protein structure prediction based solely on the thermodynamic hypothesis was considered unfeasible (5-7) mainly because of the inaccuracy of the potential functions used to describe protein conformational energy and the lack of powerful global optimization methods for exploring the energy landscapes represented by those functions. Other types of knowledge-based methodologies, such as homology modeling (8-13) or threading methods (9,12,14) have been considered to be the most successful approaches. However, the success of these methods depends on the presence of sequentially or structurally homologous proteins in the databases. Furthermore, they do not provide a general understanding of the...

A method is proposed to determine the fraction of the tautomeric forms of the imidazole ring of histidine in proteins as a function of pH, provided that the observed 13 C γ and 13 C δ2 chemical shifts and the protein structure, or the fraction of H þ form, are known. This method is based on the use of quantum chemical methods to compute the 13 C NMR shieldings of all the imidazole ring carbons ( 13 C γ , 13 C δ2 , and 13 C ϵ1 ) for each of the two tautomers, N δ1 -H and N ϵ2 -H, and the protonated form, H þ , of histidine. This methodology enabled us (i) to determine the fraction of all the tautomeric forms of histidine for eight proteins for which the 13 C γ and 13 C δ2 chemical shifts had been determined in solution in the pH range of 3.2 to 7.5 and (ii) to estimate the fraction of tautomeric forms of eight histidine-containing dipeptide crystals for which the chemical shifts had been determined by solid-state 13 C NMR. Our results for proteins indicate that the protonated form is the most populated one, whereas the distribution of the tautomeric forms for the imidazole ring varies significantly among different histidines in the same protein, reflecting the importance of the environment of the histidines in determining the tautomeric forms. In addition, for ∼70% of the neutral histidine-containing dipeptides, the method leads to fairly good agreement between the calculated and the experimental tautomeric form. Coexistence of different tautomeric forms in the same crystal structure may explain the remaining 30% of disagreement.histidine protonation | histidine tautomers | pH effect | side-chain conformation A mong all 20 naturally occurring amino acids, histidine (His) is a unique residue for a number of reasons, among others because ∼50% of all enzymes use His in their active sites (1). This is mainly because of the chemical versatility of its imidazole ring, which includes two neutral, chemically distinct forms, and a protonated form, referred to as N δ1 -H and N ϵ2 -H tautomers, and H þ , respectively, with one form favored over the other by the protein environment and pH. Moreover, His with a pK°of 6.6 (2) titrates around neutral pH, allowing the deprotonated nitrogen of its imidazole ring to serve as an effective ligand for metal binding (3). In particular, it has been suggested that tautomerization and variations of χ1 of His are crucial parts of the proton-transfer process (4). In addition, it has also been recognized (5) that many imidazole-containing ligands could exhibit large chemical-shift variations when bound to a molecular target, such as a protein, offering valuable information about changes in the local structure of the ligand or target. Hence, characterization of the tautomers of drug molecules could have important consequence in the pharmaceutical industry. It is particularly interesting that the most abundant type of tautomers in the Cambridge Structural Database (CSD) correspond to derivatives of azoles, such as pyrazoles, imidazoles, etc. (6).Since chemical shifts were first observed by Ar...