In search of new lead compounds for trypanosomiasis drug design: a protein structure-based linked-fragment approach

Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges

The emergence of drug-resistant mycobacteria, including Mycobacterium tuberculosis (Mtb) and non-tuberculous mycobacteria (NTM), poses an increasing global threat that urgently demands the development of new potent anti-mycobacterial drugs. One of the approaches toward the identification of new drugs is fragment-based drug discovery (FBDD), which is the most ingenious among other drug discovery models, such as structure-based drug design (SBDD) and high-throughput screening. Specialized techniques, such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and many others, are part of the drug discovery approach to combat the Mtb and NTM global menaces. Moreover, the primary drawbacks of traditional methods, such as the limited measurement of biomolecular toxicity and uncertain bioavailability evaluation, are successfully overcome by the FBDD approach. The current review focuses on the recognition of fragment-based drug discovery as a popular approach using virtual, computational, and biophysical methods to identify potent fragment molecules. FBDD focuses on designing optimal inhibitors against potential therapeutic targets of NTM and Mtb (PurC, ArgB, MmpL3, and TrmD). Additionally, we have elaborated on the challenges associated with the FBDD approach in the identification and development of novel compounds. Insights into the applications and overcoming the challenges of FBDD approaches will aid in the identification of potential therapeutic compounds to treat drug-sensitive and drug-resistant NTMs and Mtb infections.

Graph neural networks for automated de novo drug design

The goal of de novo drug design is to create novel chemical entities with desired biological activities and pharmacokinetics (PK) properties. Over recent years, with the development of artificial intelligence (AI) technologies, data-driven methods have rapidly gained in popularity in this field. Among them, graph neural networks (GNNs), a type of neural network directly operating on the graph structure data, have received extensive attention. In this review, we introduce the applications of GNNs in de novo drug design from three aspects: molecule scoring, molecule generation and optimization, and synthesis planning. Furthermore, we also discuss the current challenges and future directions of GNNs in de novo drug design.

The nature of ligand efficiency

Ligand efficiency is a widely used design parameter in drug discovery. It is calculated by scaling affinity by molecular size and has a nontrivial dependency on the concentration unit used to express affinity that stems from the inability of the logarithm function to take dimensioned arguments. Consequently, perception of efficiency varies with the choice of concentration unit and it is argued that the ligand efficiency metric is not physically meaningful nor should it be considered to be a metric. The dependence of ligand efficiency on the concentration unit can be eliminated by defining efficiency in terms of sensitivity of affinity to molecular size and this is illustrated with reference to fragment-to-lead optimizations. Group efficiency and fit quality are also examined in detail from a physicochemical perspective. The importance of examining relationships between affinity and molecular size directly is stressed throughout this study and an alternative to ligand efficiency for normalization of affinity with respect to molecular size is presented.

Homo- and Heterodimerization of Proteins in Cell Signaling: Inhibition and Drug Design

Protein dimerization controls many physiological processes in the body. Proteins form homo-, hetero-, or oligomerization in the cellular environment to regulate the cellular processes. Any deregulation of these processes may result in a disease state. Protein-protein interactions (PPIs) can be inhibited by antibodies, small molecules, or peptides, and inhibition of PPI has therapeutic value. PPI drug discovery research has steadily increased in the last decade, and a few PPI inhibitors have already reached the pharmaceutical market. Several PPI inhibitors are in clinical trials. With advancements in structural and molecular biology methods, several methods are now available to study protein homo- and heterodimerization and their inhibition by drug-like molecules. Recently developed methods to study PPI such as proximity ligation assay and enzyme-fragment complementation assay that detect the PPI in the cellular environment are described with examples. At present, the methods used to design PPI inhibitors can be classified into three major groups: (1) structure-based drug design, (2) high-throughput screening, and (3) fragment-based drug design. In this chapter, we have described some of the experimental methods to study PPIs and their inhibition. Examples of homo- and heterodimers of proteins, their structural and functional aspects, and some of the inhibitors that have clinical importance are discussed. The design of PPI inhibitors of epidermal growth factor receptor heterodimers and CD2-CD58 is discussed in detail.

Structure-based drug design: aiming for a perfect fit

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit.

Software for molecular docking: a review

Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate.

Six Biophysical Screening Methods Miss a Large Proportion of Crystallographically Discovered Fragment Hits: A Case Study

Fragment-based lead discovery (FBLD) has become a pillar in drug development. Typical applications of this method comprise at least two biophysical screens as prefilter and a follow-up crystallographic experiment on a subset of fragments. Clearly, structural information is pivotal in FBLD, but a key question is whether such a screening cascade strategy will retrieve the majority of fragment-bound structures. We therefore set out to screen 361 fragments for binding to endothiapepsin, a representative of the challenging group of aspartic proteases, employing six screening techniques and crystallography in parallel. Crystallography resulted in the very high number of 71 structures. Yet alarmingly, 44% of these hits were not detected by any biophysical screening approach. Moreover, any screening cascade, building on the results from two or more screening methods, would have failed to predict at least 73% of these hits. We thus conclude that, at least in the present case, the frequently applied biophysical prescreening filters deteriorate the number of possible X-ray hits while only the immediate use of crystallography enables exhaustive retrieval of a maximum of fragment structures, which represent a rich source guiding hit-to-lead-to-drug evolution.

Fragment screening using X-ray crystallography

The fragment-based approach is now well established as an important component of modern drug discovery. A key part in establishing its position as a viable technique has been the development of a range of biophysical methodologies with sufficient sensitivity to detect the binding of very weakly binding molecules. X-ray crystallography was one of the first techniques demonstrated to be capable of detecting such weak binding, but historically its potential for screening was under-appreciated and impractical due to its relatively low throughput. In this chapter we discuss the various benefits associated with fragment-screening by X-ray crystallography, and describe the technical developments we have implemented to allow its routine use in drug discovery. We emphasize how this approach has allowed a much greater exploitation of crystallography than has traditionally been the case within the pharmaceutical industry, with the rapid and timely provision of structural information having maximum impact on project direction.

Protein pockets: inventory, shape, and comparison

The shape of the protein surface dictates what interactions are possible with other macromolecules, but defining discrete pockets or possible interaction sites remains difficult. First, there is the problem of defining the extent of the pocket. Second, one has to characterize the shape of each pocket. Third, one needs to make quantitative comparisons between pockets on different proteins. An elegant solution to these problems is to sort all surface and solvent points by travel depth and then collect a hierarchical tree of pockets. The connectivity of the tree is determined via the deepest saddle points between each pair of neighboring pockets. The resulting pocket surfaces tessellate the entire protein surface, producing a complete inventory of pockets. This method of identifying pockets also allows one to easily compute important shape metrics, including the problematic pocket volume, surface area, and mouth size. Pockets are also annotated with their lining residue lists and polarity and with other residue-based properties. Using this tree and the various shape metrics pockets can be merged, grouped, or filtered for further analysis. Since this method includes the entire surface, it guarantees that any pocket of interest will be found among the output pockets, unlike all previous methods of pocket identification. The resulting hierarchy of pockets is easy to visualize and aids users in higher level analysis. Comparison of pockets is done by using the shape metrics, avoiding the complex shape alignment problem. Example applications show that the method facilitates pocket comparison along mutational or time-dependent series. Pockets from families of proteins can be examined using multiple pocket tree alignments to see how ligand binding sites or how other pockets have changed with evolution. Our method is called CLIPPERS for complete liberal inventory of protein pockets elucidating and reporting on shape.

The multiple roles of computational chemistry in fragment-based drug design

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Docking for fragment inhibitors of AmpC beta-lactamase

Fragment screens for new ligands have had wide success, notwithstanding their constraint to libraries of 1,000-10,000 molecules. Larger libraries would be addressable were molecular docking reliable for fragment screens, but this has not been widely accepted. To investigate docking's ability to prioritize fragments, a library of >137,000 such molecules were docked against the structure of beta-lactamase. Forty-eight fragments highly ranked by docking were acquired and tested; 23 had K(i) values ranging from 0.7 to 9.2 mM. X-ray crystal structures of the enzyme-bound complexes were determined for 8 of the fragments. For 4, the correspondence between the predicted and experimental structures was high (RMSD between 1.2 and 1.4 A), whereas for another 2, the fidelity was lower but retained most key interactions (RMSD 2.4-2.6 A). Two of the 8 fragments adopted very different poses in the active site owing to enzyme conformational changes. The 48% hit rate of the fragment docking compares very favorably with "lead-like" docking and high-throughput screening against the same enzyme. To understand this, we investigated the occurrence of the fragment scaffolds among larger, lead-like molecules. Approximately 1% of commercially available fragments contain these inhibitors whereas only 10(-7)% of lead-like molecules do. This suggests that many more chemotypes and combinations of chemotypes are present among fragments than are available among lead-like molecules, contributing to the higher hit rates. The ability of docking to prioritize these fragments suggests that the technique can be used to exploit the better chemotype coverage that exists at the fragment level.

Rational design of a beta-lactamase inhibitor achieved via stabilization of the trans-enamine intermediate: 1.28 A crystal structure of wt SHV-1 complex with a penam sulfone

beta-Lactamases are one of the major causes of antibiotic resistance in Gram negative bacteria. The continuing evolution of beta-lactamases that are capable of hydrolyzing our most potent beta-lactams presents a vexing clinical problem, in particular since a number of them are resistant to inhibitors. The efficient inhibition of these enzymes is therefore of great clinical importance. Building upon our previous structural studies that examined tazobactam trapped as a trans-enamine intermediate in a deacylation deficient SHV variant, we designed a novel penam sulfone derivative that forms a more stable trans-enamine intermediate. We report here the 1.28 A resolution crystal structure of wt SHV-1 in complex with a rationally designed penam sulfone, SA2-13. The compound is covalently bound to the active site of wt SHV-1 similar to tazobactam yet forms an additional salt-bridge with K234 and hydrogen bonds with S130 and T235 to stabilize the trans-enamine intermediate. Kinetic measurements show that SA2-13, once reacted with SHV-1 beta-lactamase, is about 10-fold slower at being released from the enzyme compared to tazobactam. Stabilizing the trans-enamine intermediate represents a novel strategy for the rational design of mechanism-based class A beta-lactamase inhibitors.

Multiple solvent crystal structures: probing binding sites, plasticity and hydration

Multiple solvent crystal structures (MSCS) of porcine pancreatic elastase were used to map the binding surface the enzyme. Crystal structures of elastase in neat acetonitrile, 95% acetone, 55% dimethylformamide, 80% 5-hexene-1,2-diol, 80% isopropanol, 80% ethanol and 40% trifluoroethanol showed that the organic solvent molecules clustered in the active site, were found mostly unclustered in crystal contacts and in general did not bind elsewhere on the surface of elastase. Mixtures of 40% benzene or 40% cyclohexane in 50% isopropanol and 10% water showed no bound benzene or cyclohexane molecules, but did reveal bound isopropanol. The clusters of organic solvent probe molecules coincide with pockets occupied by known inhibitors. MSCS also reveal the areas of plasticity within the elastase binding site and allow for the visualization of a nearly complete first hydration shell. The pattern of organic solvent clusters determined by MSCS for elastase is consistent with patterns for hot spots in protein-ligand interactions determined from database analysis in general. The MSCS method allows probing of hot spots, plasticity and hydration simultaneously, providing a powerful complementary strategy to guide computational methods currently in development for binding site determination, ligand docking and design.

Driving affinity selection by centrifugal force

We describe a new approach to affinity selection based on the application of centrifugal force to macromolecules in solution. The method relies on the well known macromolecular hydrodynamic principles of centrifugation. It can be automated and operated in a centralized fashion, or it can be decentralized and used by single researchers or networks of researchers with a minimal additional capital investment. In this method, a centrifugal driving force is used to establish a differential and selective concentration gradient between a therapeutic target and potential ligands in compound libraries. This concentration gradient, in turn, drives the binding of ligands. Once formed, the differential concentration gradient of target macromolecules and ligands is fractionated to capture the self-sorting binding events. Ligand binding is defined by the individual ligand binding constants, so tight binding ligands will essentially distribute identically with the protein target, and weaker binding ligands will not. The level of affinity needed to operationally define tight binding can be adjusted by selecting the initial concentration conditions or centrifugal force. A variety of rapid, commonly available, detection methods can be used to assess binding in the fractionated samples. The method can be broadly applied in drug discovery efforts to examine most types of cell-cell, protein-protein, and protein-small molecule interactions. We describe the application of this method to systems of small molecule interactions with several macromolecules of therapeutic interest.

Computational mapping identifies the binding sites of organic solvents on proteins

Computational mapping places molecular probes--small molecules or functional groups--on a protein surface to identify the most favorable binding positions. Although x-ray crystallography and NMR show that organic solvents bind to a limited number of sites on a protein, current mapping methods result in hundreds of energy minima and do not reveal why some sites bind molecules with different sizes and polarities. We describe a mapping algorithm that explains the origin of this phenomenon. The algorithm has been applied to hen egg-white lysozyme and to thermolysin, interacting with eight and four different ligands, respectively. In both cases the search finds the consensus site to which all molecules bind, whereas other positions that bind only certain ligands are not necessarily found. The consensus sites are pockets of the active site, lined with partially exposed hydrophobic residues and with a number of polar residues toward the edge. These sites can accommodate each ligand in a number of rotational states, some with a hydrogen bond to one of the nearby donor/acceptor groups. Specific substrates and/or inhibitors of hen egg-white lysozyme and thermolysin interact with the same side chains identified by the mapping, but form several hydrogen bonds and bind in unique orientations.

Glycolysis as a target for the design of new anti-trypanosome drugs

Glycolysis is perceived as a promising target for new drugs against parasitic trypanosomatid protozoa because this pathway plays an essential role in their ATP supply. Trypanosomatid glycolysis is unique in that it is compartmentalized, and many of its enzymes display unique structural and kinetic features. Structure- and catalytic mechanism-based approaches are applied to design compounds that inhibit the glycolytic enzymes of the parasites without affecting the corresponding proteins of the human host. For some trypanosomatid enzymes, potent and selective inhibitors have already been developed that affect only the growth of cultured trypanosomatids, and not mammalian cells.

Discovering novel ligands for macromolecules using X-ray crystallographic screening

The need to decrease the time scale for clinical compound discovery has led to innovations at several stages in the process, including genomics/proteomics for target identification, ultrahigh-throughput screening for lead identification, and structure-based drug design and combinatorial chemistry for lead optimization. A critical juncture in the process is the identification of a proper lead compound, because a poor choice may generate costly difficulties at later stages. Lead compounds are commonly identified from high-throughput screens of large compound libraries, derived from known substrates/inhibitors, or identified in computational prescreeusing X-ray crystal structures. Structural information is often consulted to efficiently optimize leads, but under the current paradigm, such data require preidentification and confirmation of compound binding. Here, we describe a new X-ray crystallography-driven screening technique that combines the steps of lead identification, structural assessment, and optimization. The method is rapid, efficient, and high-throughput, and it results in detailed crystallographic structure information. The utility of the method is demonstrated in the discovery and optimization of a new orally available class of urokinase inhibitors for the treatment of cancer.

Structural chemistry and therapeutic intervention of protein-protein interactions in immune response, human immunodeficiency virus entry, and apoptosis

Protein-protein interactions involved in diverse biological functions are largely unexplored therapeutic targets, and present a major challenge and opportunity for drug design research. Encouraging new approaches to this problem recently have emerged from studies of small molecule regulators of protein-protein complexes. This review outlines the basic concepts for two of these approaches, based on structural and chemical strategies, by illustrating their application in the design of small molecule inhibitors for three biological systems: (1) cell surface molecules CD4 and CD8 involved in immune response, (2) chemokine receptor-ligand interactions implicated in human immunodeficiency virus entry, and (3) B-cell leukemia/lymphoma-2 family proteins essential for regulation of programmed cell death or apoptosis. The design and discovery of these novel reagents provide valuable tools to probe fundamental questions about a particular protein-protein complex, and may lead to a new generation of potential therapeutic agents. Furthermore, these studies suggest a framework for chemical intervention of other protein-protein interactions involved in many pathological processes.

Thrombin inhibitor design: X-ray and solution studies provide a novel P1 determinant

The crystal structures of proflavin and 6-fluorotryptamine thrombin have been completed showing binding of both ligands at the active site S1 pocket. The structure of proflavin:thrombin was confirmatory, while the structure of 6-fluorotryptamine indicated a novel binding mode at the thrombin active site. Furthermore, speculation that the sodium atom identified in an extended solvent channel beneath the S pocket may play a role in binding of these ligands was investigated by direct proflavin titrations as well as chromogenic activity measurements as a function of sodium concentration at constant ionic strength. These results suggested a linkage between the sodium site and the S1 pocket. This observation could be due to a simple ionic interaction between Asp189 and the sodium ion or a more complicated structural rearrangement of the thrombin S1 pocket. Finally, the unique binding mode of 6-fluorotryptamine provides ideas toward the design of a neutrally charged thrombin inhibitor.

Discovering high-affinity ligands for proteins: SAR by NMR

A nuclear magnetic resonance (NMR)-based method is described in which small organic molecules that bind to proximal subsites of a protein are identified, optimized, and linked together to produce high-affinity ligands. The approach is called "SAR by NMR" because structure-activity relationships (SAR) are obtained from NMR. With this technique, compounds with nanomolar affinities for the FK506 binding protein were rapidly discovered by tethering two ligands with micromolar affinities. The method reduces the amount of chemical synthesis and time required for the discovery of high-affinity ligands and appears particularly useful in target-directed drug research.

Empirical free energy as a target function in docking and design: application to HIV-1 protease inhibitors

Structure-based drug design requires the development of efficient computer programs for exploring the structural compatibility of various flexible ligands with a given receptor. While various algorithms are available for finding docked conformations, selecting a target function that can reliably score the conformations remains a serious problem. We show that the use of an empirical free energy evaluation method, originally developed to characterize protein-protein interactions, can substantially improve the efficacy of search algorithms. In addition to the molecular mechanics interaction energy, the function takes account of solvation and side chain conformational entropy, while remaining simple enough to replace the incomplete target functions used in many drug docking and design procedures. The free energy function is used here in conjunction with a simple site mapping-fragment assembly algorithm, for docking the MVT-101 non-peptide inhibitor to HIV-1 protease. In particular, we predict the bound structure with an all atom RMSD of 1.21 A, compared to 1.69 A using an energy target function, and also accurately predict the free energy shifts obtained with a series of five trimeric hydroxyethylene isostere analogs.

Identification of a peptide inhibitor against glycosomal phosphoglycerate kinase of Trypanosoma brucei by a synthetic peptide library approach

A synthetic peptide library, composed of 2.5 million L-amino acid pentapeptides anchored on polystyrene beads was prepared with each bead bearing a single pentapeptide sequence. This library was screened for interaction with glycosomal phosphoglycerate kinase (gPGK) of Trypanosoma brucei labelled with fluorescein or with biotin. Affinity beads that bound the enzyme were selected with a pipette or with streptavidin coated magnetic beads. The beads that bound to the enzyme were individually subjected to Edman microsequence analysis to determine the sequence of the corresponding peptide ligands. The corresponding peptide-sequences were synthesised as free peptide acids and evaluated for enzyme activity inhibition. The pentapeptide NWMMF was able to selectively inhibit gPGK with an IC50 of approximately 80 microM.

Protein crystallography and infectious diseases

The current rapid growth in the number of known 3-dimensional protein structures is producing a database of structures that is increasingly useful as a starting point for the development of new medically relevant molecules such as drugs, therapeutic proteins, and vaccines. This development is beautifully illustrated in the recent book, Protein structure: New approaches to disease and therapy (Perutz, 1992). There is a great and growing promise for the design of molecules for the treatment or prevention of a wide variety of diseases, an endeavor made possible by the insights derived from the structure and function of crucial proteins from pathogenic organisms and from man. We present here 2 illustrations of structure-based drug design. The first is the prospect of developing antitrypanosomal drugs based on crystallographic, ligand-binding, and molecular modeling studies of glycolytic glycosomal enzymes from Trypanosomatidae. These unicellular organisms are responsible for several tropical diseases, including African and American trypanosomiases, as well as various forms of leishmaniasis. Because the target enzymes are also present in the human host, this project is a pioneering study in selective design. The second illustrative case is the prospect of designing anti-cholera drugs based on detailed analysis of the structure of cholera toxin and the closely related Escherichia coli heat-labile enterotoxin. Such potential drugs can be targeted either at inhibiting the toxin's receptor binding site or at blocking the toxin's intracellular catalytic activity. Study of the Vibrio cholerae and E. coli toxins serves at the same time as an example of a general approach to structure-based vaccine design. These toxins exhibit a remarkable ability to stimulate the mucosal immune system, and early results have suggested that this property can be maintained by engineered fusion proteins based on the native toxin structure. The challenge is thus to incorporate selected epitopes from foreign pathogens into the native framework of the toxin such that crucial features of both the epitope and the toxin are maintained. That is, the modified toxin must continue to evoke a strong mucosal immune response, and this response must be directed against an epitope conformation characteristic of the original pathogen.

Galactose-binding site in Escherichia coli heat-labile enterotoxin (LT) and cholera toxin (CT)

The galactose-binding site in cholera toxin and the closely related heat-labile enterotoxin (LT) from Escherichia coli is an attractive target for the rational design of potential anti-cholera drugs. In this paper we analyse the molecular structure of this binding site as seen in several crystal structures, including that of an LT:galactose complex which we report here at 2.2 A resolution. The binding surface on the free toxin contains several tightly associated water molecules and a relatively flexible loop consisting of residues 51-60 of the B subunit. During receptor binding this loop becomes tightly ordered by forming hydrogen bonds jointly to the GM1 pentasaccharide and to a set of water molecules which stabilize the toxin:receptor complex.

Crystal structure of recombinant human triosephosphate isomerase at 2.8 A resolution. Triosephosphate isomerase-related human genetic disorders and comparison with the trypanosomal enzyme

The crystal structure of recombinant human triosephosphate isomerase (hTIM) has been determined complexed with the transition-state analogue 2-phosphoglycolate at a resolution of 2.8 A. After refinement, the R-factor is 16.7% with good geometry. The asymmetric unit contains 1 complete dimer of 53,000 Da, with only 1 of the subunits binding the inhibitor. The so-called flexible loop, comprising residues 168-174, is in its "closed" conformation in the subunit that binds the inhibitor, and in the "open" conformation in the other subunit. The tips of the loop in these 2 conformations differ up to 7 A in position. The RMS difference between hTIM and the enzyme of Trypanosoma brucei, the causative agent of sleeping sickness, is 1.12 A for 487 C alpha positions with 53% sequence identity. Significant sequence differences between the human and parasite enzymes occur at about 13 A from the phosphate binding site. The chicken and human enzymes have an RMS difference of 0.69 A for 484 equivalent residues and about 90% sequence identity. Complementary mutations ensure a great similarity in the packing of side chains in the core of the beta-barrels of these 2 enzymes. Three point mutations in hTIM have been correlated with severe genetic disorders ranging from hemolytic disorder to neuromuscular impairment. Knowledge of the structure of the human enzyme provides insight into the probable effect of 2 of these mutations, Glu 104 to Asp and Phe 240 to Ile, on the enzyme. The third mutation reported to be responsible for a genetic disorder, Gly 122 to Arg, is however difficult to explain. This residue is far away from both catalytic centers in the dimer, as well as from the dimer interface, and seems unlikely to affect stability or activity. Inspection of the 3-dimensional structure of trypanosomal triosephosphate isomerase, which has a methionine at position 122, only increased the mystery of the effects of the Gly to Arg mutation in the human enzyme.

SPROUT: a program for structure generation

SPROUT is a new computer program for constrained structure generation that is designed to generate molecules for a range of applications in molecular recognition. It uses artificial intelligence techniques to moderate the combinatorial explosion that is inherent in structure generation. The program is presented here for the design of enzyme inhibitors. Structure generation is divided into two phases: (i) primary structure generation to produce molecular graphs to fit the steric constraints; and (ii) secondary structure generation which is the process of introducing appropriate functionality to the graphs to produce molecules that satisfy the secondary constraints, e.g., electrostatics and hydrophobicity. Primary structure generation has been tested on two enzyme receptor sites; the p-amidino-phenyl-pyruvate binding site of trypsin and the acetyl pepstatin binding site of HIV-1 protease. The program successfully generates structures that resemble known substrates and, more importantly, the predictive power of the program has been demonstrated by its ability to suggest novel structures.

FOUNDATION: a program to retrieve all possible structures containing a user-defined minimum number of matching query elements from three-dimensional databases

A program is described that searches three-dimensional, structural databases, given a user-defined query, in order to retrieve all structures that contain any combination of a user-specified minimum number of matching elements. Queries consist of three-dimensional coordinates of atoms and/or bonds. Numerous query constraints are described which allow the investigator to define the chemical nature of the desired structures as well as the environment within which these structures must reside. They include: (1) Bonded vs. isolated atom distinction; (2) Atom type designation; (3) Definition of subsets with occupancy specification (>, =, < X atoms); (4) RMS-fit; (5) Active site volume accessibility of atoms linking query elements; (6) Number, atom type, and cyclic structure constraints for atoms linking pharmacophoric elements; (7) Automatic error boundary adjustment--ad infinitum constraint. To illustrate the capabilities of this program, queries based on the crystal structure of a thermolysin-inhibitor complex were tested against a subset of the Cambridge Crystallographic Database. Several compounds were returned which satisfied various aspects of the query, including fitting within the active site. Combination of segments of compounds which satisfy partial queries should provide a method for generating unique compounds with affinity for sites of known three-dimensional structure.

Computer-aided drug design: getting the best results

There are two major stages in the design of drug molecules: lead-molecule development and lead-molecule optimization. Whereas a variety of computational chemistry and molecular modeling (CC/MM) techniques are now routinely and successfully applied to the optimization stage of drug design, the generation of initial lead compounds has proven a more difficult problem for the CC/MM approach. Only recently has the design of lead molecules by this route become a subject of active research. This article looks at the factors which must be considered carefully when incorporating CC/MM methods into different aspects of drug-design strategies.

Structure of the complex between trypanosomal triosephosphate isomerase and N-hydroxy-4-phosphono-butanamide: binding at the active site despite an "open" flexible loop conformation

The structure of triosephosphate isomerase from Trypanosoma brucei complexed with the competitive inhibitor N-hydroxy-4-phosphono-butanamide was determined by X-ray crystallography to a resolution of 2.84 A. Full occupancy binding of the inhibitor is observed only at one of the active sites of the homodimeric enzyme where the flexible loop is locked in a completely open conformation by crystal contacts. There is evidence that the inhibitor also binds to the second active site of the enzyme, but with low occupancy. The hydroxamyl group of the inhibitor forms hydrogen bonds to the side chains of Asn 11, Lys 13, and His 95, whereas each of its three methylene units is involved in nonpolar interactions with the side chain of the flexible loop residue Ile 172. Interactions between the hydroxamyl and the catalytic base Glu 167 are absent. The binding of this phosphonate inhibitor exhibits three unusual features: (1) the flexible loop is open, in contrast with the binding mode observed in eight other complexes between triosephosphate isomerase and various phosphate and phosphonate compounds; (2) compared with these complexes the present structure reveals a 1.5-A shift of the anion-binding site; (3) this is the first phosphonate inhibitor that is not forced by the enzyme into an eclipsed conformation about the P-CH2 bond. The results are discussed with respect to an ongoing drug design project aimed at the selective inhibition of glycolytic enzymes of T. brucei.