Challenges and opportunities for new protein crystallization strategies in structure-based drug design

Structure-based drug design (SBDD) has emerged as a valuable pharmaceutical lead discovery tool, showing potential for accelerating the discovery process, while reducing developmental costs and boosting potencies of the drug that is ultimately selected. SBDD is an iterative, rational, lead compound sculpting process that involves both the synthesis of new derivatives and the evaluation of their binding to the target structure either through computational docking or elucidation of the target structure as a complex with the lead compound. This method heavily relies on the production of high-resolution (< 2 Å) 3D structures of the drug target, obtained through X-ray crystallographic analysis, in the presence or absence of the drug candidate. The lack of generalized methods for high quality crystal production is still a major bottleneck in the process of macromolecular crystallization. This review provides a brief introduction to SBDD and describes several macromolecular crystallization strategies, with an emphasis on advances and challenges facing researchers in the field today. Recent trends in the development of more universal macromolecular crystallization techniques, particularly nucleation-based techniques that are applicable to both soluble and integral membrane proteins, are also discussed.     

Challenges and opportunities for new protein crystallization strategies in structure-based drug design

Structure-based drug design (SBDD) has emerged as a valuable pharmaceutical lead discovery tool, showing potential for accelerating the discovery process,while reducing developmental costs and boosting potencies of the drug that is ultimately selected. SBDD is an iterative, rational, lead compound sculpting process that involves both the synthesis of new derivatives and the evaluation of their binding to the target structure either through computational docking or elucidation of the target structure as a complex with the lead compound. This method heavily relies on the production of high resolution(< 2 ?) 3D structures of the drug target, obtained through X-ray crystallographic analysis, in the presence or absence of the drug candidate.The lack of generalized methods for high quality crystal production is still a major bottleneck in the process of macromolecular crystallization. This review provides a brief introduction to SBDD and describes several macromolecular crystallization strategies, with an emphasis on advances and challenges facing researchers in the field today. Recent trends in the development of more universal macromolecular crystallization techniques, particularly nucleation-based techniques that are applicable to both soluble and integral membrane proteins, are also discussed.     

Accommodating protein flexibility for structure-based drug design

Proper incorporation of protein flexibility for prediction of binding poses and affinities of small compounds has attracted increasing attention recently in computational drug design. Various approaches have been proposed to accommodate protein flexibility in the prediction of binding modes and the binding free energy of ligands in an efficient manner. In this review, the significance of incorporating protein flexibility is discussed from the structural biophysical point of view, and then various approaches of generating protein conformation ensembles, as well as their successes and limitations, are introduced and compared. Special emphasis is on how to generate a proper ensemble of conformation for a specific purpose, as well as the computational efficiency of various approaches. Different searching algorithms for the prediction of optimal binding poses of ligands, which are the core engines of docking programs, are accounted for. Scoring functions for evaluation of protein-ligand complexes are compared. Two end-point methods of free energy calculation, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Linear Interaction Energy (LIE) method, are briefly reviewed. Finally, we also provide an example for the extension of the conventional protein-ligand docking algorithm for prediction of multiple binding sites and ligand translocation pathways.     

Learning from structure-based drug design and new antivirals targeting the ribonucleoprotein complex for the treatment of influenza

Introduction: Influenza viruses are a threat to human health. There are presently only two methods for treating influenza: vaccines, which require yearly updates, and two classes of antivirals that suffer with the problem of resistance by current human influenza viruses; this is especially the case with amantadine and rimantadine. Consequently, there is an urgent need for the development of new antivirals with new mechanisms of action.

Areas covered: In this review, the authors focus on viral protein domains, their associated activity and their inhibition by small molecules defined by a structure-based design with a special emphasis on the ribonucleoprotein complex and its inhibitors. Several new classes of antiviral candidates targeting viral replication through individual domains of the polymerase and the nucleoprotein (NP) have been developed through structure-based design.

Expert opinion: To date, the antivirals targeting neuraminidase are by far the most developed and potent. Antiviral candidates targeting the NP and polymerase domains are in the pipeline but their pharmacokinetics needs further studies. The recently published structures of the polymerase expand the possibilities for development of new antivirals. Combination therapies targeting conserved viral targets and new cellular proteins or exploiting drug promiscuity hold promises to fight against the emergence of resistance.     

Antibacterial drug discovery and structure-based design

Bacterial resistance continues to develop and pose a significant threat, both in hospitals and, more recently, in the community. A focus on other therapeutic areas by the larger pharmaceutical companies has left a shortfall in the pipeline of novel antibacterials. Recently, many new structures have been studied by structure-genomics initiatives, delivering a wealth of targets to consider. Using the tools of structure-based design, antibacterial discovery must exploit these targets to accelerate the process of drug discovery.     

A critical appraisal of structure-based drug design

Even though conceptually started in the early 1980s, the use of protein structure information in drug discovery has never reached the current level of significance, nor has it experienced the revolutionary development that it is currently undergoing. Initially used for lead optimization, structure-based drug design (SBDD) now covers and supports virtually all steps in the drug- discovery pipeline. This commentary is a critical appraisal of the current state of the art, examining both successes and failures. Future directions in SBDD are also discussed.     

Recent progress in structure-based anti-influenza drug design

Seasonal and pandemic influenza have caused high morbidity and mortality worldwide. Recent emergence of influenza A H5N1 and H1N1 strains has heightened concern, especially as a result of their drug resistance. The life cycle of influenza viruses has been well studied and nearly all the viral proteins are becoming potential therapeutic targets. In this review, we present an overview of recent progress in structure-based anti-influenza drug design, paying close attention to the increasing role of computation and strategies for overcoming drug resistance.     

LEA3D: a computer-aided ligand design for structure-based drug design

We present an improved version of the program LEA developed to design organic molecules. Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a tool for the investigation of such problems. New software, called LEA3D, is now able to conceive organic molecules by combining 3D fragments. Fragments were extracted from both biological compounds and known drugs. A fitness function guides the search process in optimizing the molecules toward an optimal value of the properties. The fitness function is build up by combining several independent property evaluations, including the score provided by the FlexX docking program. One application in de novo drug design is described. The example makes use of the structure of Mycobacterium tuberculosis thymidine monophosphate kinase to generate analogues of one of its natural substrates. Among 22 tested compounds, 17 show inhibitory activity in the micromolar range.     

The role of quantum mechanics in structure-based drug design

Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate problems from scoring protein-ligand poses to building QM QSAR models. Through the variational principle of QM we know that we can obtain a more accurate representation of molecular systems than classical models, and while this is not a matter of debate, it still has not been shown that the expense of QM approaches is offset by improved accuracy in DD applications. Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to protein-ligand complexes.     

The bacterial ribosome,a promising focus for structure-based drug design

Recent crystal structures of the bacterial ribosome have identified the complex molecular interactions involved in antibiotic-ribosome recognition. Insights into the binding of aminoglycosides, macrolides, tetracyclines and other antibiotics provide opportunities for computational, structure-based approaches to be used in the design of appropriate modifications to existing antibiotics as well as in the discovery of completely new drug classes.     

The application of quantum mechanics in structure-based drug design

Introduction: Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein–ligand recognition.

Areas covered: In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein–ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein–ligand docking, protein–ligand binding affinities and ligand strain on binding.

Expert opinion: Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.     

Progress in structure-based drug design against influenza A virus

Introduction: The 2009-H1N1 influenza pandemic has prompted new global efforts to develop new drugs and drug design techniques to combat influenza viruses. While there have been a number of attempts to provide drugs to treat influenza, drug resistance has been a major problem with only four drugs currently approved by the FDA for its treatment. Areas covered: In this review, the drug-resistant problem of influenza A viruses is discussed and summarized. The article also introduces the experimental and computational structures of drug targeting proteins, neuraminidases, and of the M2 proton channel. Furthermore, the article illustrates the latest drug candidates and techniques of computer-aided drug design with examples of their application, including virtual in silico screening and scoring, AutoDock and evolutionary technique AutoGrow. Expert opinion: Structure-based drug design is the inventive process for finding new drugs based on the structural knowledge of the biological target. Computer-aided drug design strategies and techniques will make drug discovery more effective and economical. It is anticipated that the recent advances in structure-based drug design techniques will greatly help scientists to develop more powerful and specific drugs to fight the next generation of influenza viruses.     

Progress in structure-based drug design against influenza A virus

Introduction: The 2009-H1N1 influenza pandemic has prompted new global efforts to develop new drugs and drug design techniques to combat influenza viruses. While there have been a number of attempts to provide drugs to treat influenza, drug resistance has been a major problem with only four drugs currently approved by the FDA for its treatment.

Areas covered: In this review, the drug-resistant problem of influenza A viruses is discussed and summarized. The article also introduces the experimental and computational structures of drug targeting proteins, neuraminidases, and of the M2 proton channel. Furthermore, the article illustrates the latest drug candidates and techniques of computer-aided drug design with examples of their application, including virtual in silico screening and scoring, AutoDock and evolutionary technique AutoGrow.

Expert opinion: Structure-based drug design is the inventive process for finding new drugs based on the structural knowledge of the biological target. Computer-aided drug design strategies and techniques will make drug discovery more effective and economical. It is anticipated that the recent advances in structure-based drug design techniques will greatly help scientists to develop more powerful and specific drugs to fight the next generation of influenza viruses.     

Incorporating protein flexibility into docking and structure-based drug design

The use of structure in drug design has become widespread, mainly thanks to recent advances in crystallography. Nevertheless, biological macromolecules are intrinsically flexible and it is increasingly evident that their function depends critically on both their structure and dynamics. In this review the authors discuss the implications of protein flexibility for drug design and review recent progress in incorporating protein flexibility into docking and structure-based drug design.     

Targeting protein multiple conformations: a structure-based strategy for kinase drug design

Multiple conformations of a protein kinase target offer an opportunity to design small-molecule inhibitors with distinct but clinically useful profiles. This article analyzes and classifies the binding pockets in the kinase catalytic cleft in different conformational states. Targeting kinase multiple conformations as an emerging strategy in the field is exemplified with important small-molecule agents in the clinic. The structure-based analysis in the paper provides a rationale for thwarting the development of drug-resistant mutations in antikinase therapy.     

Cambridge Healthtech Institute fourth annual conference in structure-based drug design

The CHI-sponsored fourth annual meeting, held at the Sheraton hotel in Boston, USA, was attended by approximately 120 delegates, mainly from the pharmaceutical and biotechnology industries. The theme of the conference focused on new developments and validation of current techniques in structure-based drug design, as well as the successful application of these methods in drug development.