Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods

DeltaGzip: Computing Biopolymer-Ligand Binding Affinity via Kolmogorov Complexity and Lossless Compression

The design of biosequences for biosensing and therapeutics is a challenging multistep search and optimization task. In principle, computational modeling may speed up the design process by virtual screening of sequences based on their binding affinities to target molecules. However, in practice, existing machine-learned models trained to predict binding affinities lack the flexibility with respect to reaction conditions, and molecular dynamics simulations that can incorporate reaction conditions suffer from high computational costs. Here, we describe a computational approach called DeltaGzip that evaluates the free energy of binding in biopolymer-ligand complexes from ultrashort equilibrium molecular dynamics simulations. The entropy of binding is evaluated using the Kolmogorov complexity definition of entropy and approximated using a lossless compression algorithm, Gzip. We benchmark the method on a well-studied data set of protein-ligand complexes comparing the predictions of DeltaGzip to the free energies of binding obtained using Jarzynski equality and experimental measurements.

Computational Investigation of the Covalent Inhibition Mechanism of Bruton's Tyrosine Kinase by Ibrutinib

Covalent inhibitors represent a promising class of therapeutic compounds. Nonetheless, rationally designing covalent inhibitors to achieve a right balance between selectivity and reactivity remains extremely challenging. To better understand the covalent binding mechanism, a computational study is carried out using the irreversible covalent inhibitor of Bruton tyrosine kinase (BTK) ibrutinib as an example. A multi-μs classical molecular dynamics trajectory of the unlinked inhibitor is generated to explore the fluctuations of the compound associated with the kinase binding pocket. Then, the reaction pathway leading to the formation of the covalent bond with the cysteine residue at position 481 via a Michael addition is determined using the string method in collective variables on the basis of hybrid quantum mechanical-molecular mechanical (QM/MM) simulations. The reaction pathway shows a strong correlation between the covalent bond formation and the protonation/deprotonation events taking place sequentially in the covalent inhibition reaction, consistent with a 3-step reaction with transient thiolate and enolates intermediate states. Two possible atomistic mechanisms affecting deprotonation/protonation events from the thiolate to the enolate intermediate were observed: a highly correlated direct pathway involving proton transfer to the Cα of the acrylamide warhead from the cysteine involving one or a few water molecules and a more indirect pathway involving a long-lived enolate intermediate state following the escape of the proton to the bulk solution. The results are compared with experiments by simulating the long-time kinetics of the reaction using kinetic modeling.

Two-Step Covalent Docking with Attracting Cavities

Due to their various advantages, interest in the development of covalent drugs has been renewed in the past few years. It is therefore important to accurately describe and predict their interactions with biological targets by computer-aided drug design tools such as docking algorithms. Here, we report a covalent docking procedure for our in-house docking code Attracting Cavities (AC), which mimics the two-step mechanism of covalent ligand binding. Ligand binding to the protein cavity is driven by nonbonded interactions, followed by the formation of a covalent bond between the ligand and the protein through a chemical reaction. To test the performance of this method, we developed a diverse, high-quality, openly accessible re-docking benchmark set of 95 covalent complexes bound by 8 chemical reactions to 5 different reactive amino acids. Combination with structures from previous studies resulted in a set of 304 complexes, on which AC obtained a success rate (rmsd ≤ 2 Å) of 78%, outperforming two state-of-the-art covalent docking codes, genetic optimization for ligand docking (GOLD (66%)) and AutoDock (AD (35%)). Using a more stringent success criterion (rmsd ≤ 1.5 Å), AC reached a success rate of 71 vs 55% for GOLD and 26% for AD. We additionally assessed the cross-docking performance of AC on a set of 76 covalent complexes of the SARS-CoV-2 main protease. On this challenging test set of mainly small and highly solvent-exposed ligands, AC yielded success rates of 58 and 28% for re-docking and cross-docking, respectively, compared to 45 and 17% for GOLD.

Recent advances in targeting the "undruggable" proteins: from drug discovery to clinical trials

Undruggable proteins are a class of proteins that are often characterized by large, complex structures or functions that are difficult to interfere with using conventional drug design strategies. Targeting such undruggable targets has been considered also a great opportunity for treatment of human diseases and has attracted substantial efforts in the field of medicine. Therefore, in this review, we focus on the recent development of drug discovery targeting "undruggable" proteins and their application in clinic. To make this review well organized, we discuss the design strategies targeting the undruggable proteins, including covalent regulation, allosteric inhibition, protein-protein/DNA interaction inhibition, targeted proteins regulation, nucleic acid-based approach, immunotherapy and others.

HCovDock: an efficient docking method for modeling covalent protein-ligand interactions

Covalent inhibitors have received extensive attentions in the past few decades because of their long residence time, high binding efficiency and strong selectivity. Therefore, it is valuable to develop computational tools like molecular docking for modeling of covalent protein-ligand interactions or screening of potential covalent drugs. Meeting the needs, we have proposed HCovDock, an efficient docking algorithm for covalent protein-ligand interactions by integrating a ligand sampling method of incremental construction and a scoring function with covalent bond-based energy. Tested on a benchmark containing 207 diverse protein-ligand complexes, HCovDock exhibits a significantly better performance than seven other state-of-the-art covalent docking programs (AutoDock, Cov_DOX, CovDock, FITTED, GOLD, ICM-Pro and MOE). With the criterion of ligand root-mean-squared distance < 2.0 Å, HCovDock obtains a high success rate of 70.5% and 93.2% in reproducing experimentally observed structures for top 1 and top 10 predictions. In addition, HCovDock is also validated in virtual screening against 10 receptors of three proteins. HCovDock is computationally efficient and the average running time for docking a ligand is only 5 min with as fast as 1 sec for ligands with one rotatable bond and about 18 min for ligands with 23 rotational bonds. HCovDock can be freely assessed at http://huanglab.phys.hust.edu.cn/hcovdock/.

Novel inhibitors and activity-based probes targeting serine proteases

Serine proteases play varied and manifold roles in important biological, physiological, and pathological processes. These include viral, bacterial, and parasitic infection, allergic sensitization, tumor invasion, and metastasis. The use of activity-based profiling has been foundational in pinpointing the precise roles of serine proteases across this myriad of processes. A broad range of serine protease-targeted activity-based probe (ABP) chemotypes have been developed and we have recently introduced biotinylated and "clickable" peptides containing P1 N-alkyl glycine arginine N-hydroxy succinimidyl (NHS) carbamates as ABPs for detection/profiling of trypsin-like serine proteases. This present study provides synthetic details for the preparation of additional examples of this ABP chemotype, which function as potent irreversible inhibitors of their respective target serine protease. We describe their use for the activity-based profiling of a broad range of serine proteases including trypsin, the trypsin-like protease plasmin, chymotrypsin, cathepsin G, and neutrophil elastase (NE), including the profiling of the latter protease in clinical samples obtained from patients with cystic fibrosis.

Novel Aurora A and Protein Kinase C (α, β1, β2, and θ) Multitarget Inhibitors: Impact of Selenium Atoms on the Potency and Selectivity

Aurora kinases and protein kinase C (PKC) have been shown to be involved in different aspects of cancer progression. To date, no dual Aurora/PKC inhibitor with clinical efficacy and low toxicity is available. Here, we report the identification of compound 2e as a potent small molecule capable of selectively inhibiting Aurora A kinase and PKC isoforms α, β1, β2 and θ. Compound 2e demonstrated significant inhibition of the colony forming ability of metastatic breast cancer cells in vitro and metastasis development in vivo. In vitro kinase screening and molecular modeling studies revealed the critical role of the selenium-containing side chains within 2e, where selenium atoms were shown to significantly improve its selectivity and potency by forming additional interactions and modulating the protein dynamics. In comparison to other H-bonding heteroatoms such as sulfur, our studies suggested that these selenium atoms also confer more favorable PK properties.

Docking Ligands into Flexible and Solvated Macromolecules. 8. Forming New Bonds─Challenges and Opportunities

Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.

Design, synthesis and in vitro evaluation of novel SARS-CoV-2 3CLpro covalent inhibitors

Severe diseases such as the ongoing COVID-19 pandemic, as well as the previous SARS and MERS outbreaks, are the result of coronavirus infections and have demonstrated the urgent need for antiviral drugs to combat these deadly viruses. Due to its essential role in viral replication and function, 3CL^pro (main coronaviruses cysteine-protease) has been identified as a promising target for the development of antiviral drugs. Previously reported SARS-CoV 3CL^pro non-covalent inhibitors were used as a starting point for the development of covalent inhibitors of SARS-CoV-2 3CL^pro. We report herein our efforts in the design and synthesis of submicromolar covalent inhibitors when the enzymatic activity of the viral protease was used as a screening platform.

Docking Paradigm in Drug Design

Docking is in demand for the rational computer aided structure based drug design. A review of docking methods and programs is presented. Different types of docking programs are described. They include docking of non-covalent small ligands, protein-protein docking, supercomputer docking, quantum docking, the new generation of docking programs and the application of docking for covalent inhibitors discovery. Taking into account the threat of COVID-19, we present here a short review of docking applications to the discovery of inhibitors of SARS-CoV and SARS-CoV-2 target proteins, including our own result of the search for inhibitors of SARS-CoV-2 main protease using docking and quantum chemical post-processing. The conclusion is made that docking is extremely important in the fight against COVID-19 during the process of development of antivirus drugs having a direct action on SARS-CoV-2 target proteins.

Cinnamide derived pyrimidine-benzimidazole hybrids as tubulin inhibitors: Synthesis, in silico and cell growth inhibition studies

An approach in modern medicinal chemistry to discover novel bioactive compounds is by mimicking diverse complementary pharmacophores. In extension of this strategy, a new class of piperazine-linked cinnamide derivatives of benzimidazole-pyrimidine hybrids have been designed and synthesized. Their in vitro cytotoxicity profiles were explored on selected human cancer cell lines. Specifically, structural comparison of target hybrids with tubulin-DAMA-colchicine and tubulin-nocodazole complexes has exposed a deep position of benzimidazole ring into the αT5 loop. All the synthesized compounds were demonstrated modest to interesting cytotoxicity against different cancer cell lines. The utmost cytotoxicity has shown with an amine linker of benzimidazole-pyrimidine series, with specificity toward A549 (lung cancer) cell line. The most potent compound in this series was 18i, which inhibited cancer cell growth at micromolar concentrations ranging 2.21-7.29 µM. Flow cytometry studies disclosed that 18i inhibited the cells in G2/M phase of cell cycle. The potent antitumor activity of 18i resulted from enhanced microtubule disruption at a similar level as nocodazole on β-tubulin antibody, explored using immunofluorescence staining. The most active compound 18i also inhibited tubulin polymerization with an IC₅₀ of 5.72 ± 0.51 µM. In vitro biological analysis of 18i presented apoptosis induction on A549 cells with triggering of ROS generation and loss of mitochondrial membrane potential, resulting in DNA injury. In addition, 18i displayed impairment in cellular migration and inhibited the colony formation. Notably, the safety profile of most potent compound 18i was revealed by screening against normal human pulmonary epithelial cells (L132: IC₅₀: 69.25 ± 5.95 μM). The detailed binding interactions of 18i with tubulin was investigated by employing molecular docking, superimposition and free energy analyses. Thus remarks made in this study established that pyrimidine-benzimidazole hybrids as a new class of tubulin polymerization inhibitors with significant anticancer activity.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

Microencapsulation of Coenzyme Q10 and bile acids using ionic gelation vibrational jet flow technology for oral delivery

Developing new delivery dosage forms with robust delivery and safety profiles remains a challenge to the pharmaceutical industry in terms of optimum gut absorption, consistent dosing and bioavailability; particularly for orally administered drugs that are poorly water soluble. Coenzyme Q10 is an example of a poorly water-soluble compound with low bioavailability, and significant inter-individual variation after oral administration; limiting its optimum efficacy, as a powerful antioxidant with significant promise in treating hearing disorders. Microencapsulation technology is one way to optimize drug bioavailability and absorption profile. One example is Ionic Gelation Vibrational Jet Flow techniques, using new encapsulating parameters to determine the nature of formed capsules. Bile acids are an example of an excipient that can be used to improve membrane permeability; and will be examined. This review addresses the applications of microencapsulation technology on oral delivery and efficacy profiles of poorly water-soluble drugs, focusing on Coenzyme Q10.

Spectrofluorimetric analysis of the binding of a target molecule to serum albumin: tricky aspects and tips

Protein binding heavily modulates drug activity. Therefore, the binding features need to be elucidated when chemistry researchers study new molecules (metal complexes) to be used as drugs. This paper concerns the experimental and data treatment aspects of the mechanistic analysis of the binding to a fluorescent protein (the golden standard serum albumin) by using direct fluorescence titrations. Fluorescence data are not rarely only qualitatively used, neglecting further treatments which could offer a precious detailed picture of the behavior of the drug. We aim to spread a mechanistic approach, discussing the critical aspects for correctly designing the experiments and treating the data. The researcher may confirm adduct formation and evaluate binding constants (Stern-Volmer K_SV or other types of K). Also, we discuss here, with the help of literature examples, the correct use of temperature dependence of K to extract thermodynamic parameters, comment on enthalpy-entropy compensation, together with the use of synchronous spectra and exchange experiments to gain information on the binding type and site. We think that this tutorial/critical synopsis can be of help for the increasing community dealing with these experiments, which are valuable but often much more tricky than it might appear at first sight.

Mechanisms of Action for Small Molecules Revealed by Structural Biology in Drug Discovery

Small-molecule drugs are organic compounds affecting molecular pathways by targeting important proteins. These compounds have a low molecular weight, making them penetrate cells easily. Small-molecule drugs can be developed from leads derived from rational drug design or isolated from natural resources. A target-based drug discovery project usually includes target identification, target validation, hit identification, hit to lead and lead optimization. Understanding molecular interactions between small molecules and their targets is critical in drug discovery. Although many biophysical and biochemical methods are able to elucidate molecular interactions of small molecules with their targets, structural biology is the most powerful tool to determine the mechanisms of action for both targets and the developed compounds. Herein, we reviewed the application of structural biology to investigate binding modes of orthosteric and allosteric inhibitors. It is exemplified that structural biology provides a clear view of the binding modes of protease inhibitors and phosphatase inhibitors. We also demonstrate that structural biology provides insights into the function of a target and identifies a druggable site for rational drug design.

Biocatalytic synthesis of planar chiral macrocycles

Macrocycles can restrict the rotation of substituents through steric repulsions, locking in conformations that provide or enhance the activities of pharmaceuticals, agrochemicals, aroma chemicals, and materials. In many cases, the arrangement of substituents in the macrocycle imparts an element of planar chirality. The difficulty in predicting when planar chirality will arise, as well as the limited number of synthetic methods to impart selectivity, have led to planar chirality being regarded as an irritant. We report a strategy for enantio- and atroposelective biocatalytic synthesis of planar chiral macrocycles. The macrocycles can be formed with high enantioselectivity from simple building blocks and are decorated with functionality that allows one to further modify the macrocycles with diverse structural features.

Chemical Intuition in Drug Design and Discovery

The medicinal chemist plays the most important role in drug design, discovery and development. The primary goal is to discover leads and optimize them to develop clinically useful drug candidates. This process requires the medicinal chemist to deal with large sets of data containing chemical descriptors, pharmacological data, pharmacokinetics parameters, and in silico predictions. The modern medicinal chemist has a large number of tools and technologies to aid him in creating strategies and supporting decision-making. Alongside with these tools, human cognition, experience and creativity are fundamental to drug research and are important for the chemical intuition of medicinal chemists. Therefore, fine-tuning of data processing and in-house experience are essential to reach clinical trials. In this article, we will provide an expert opinion on how chemical intuition contributes to the discovery of drugs, discuss where it is involved in the modern drug discovery process, and demonstrate how multidisciplinary teams can create the optimal environment for drug design, discovery, and development.

Predicting Positions of Bridging Water Molecules in Nucleic Acid-Ligand Complexes

Over the past two decades, interests in DNA and RNA as drug targets have been growing rapidly. Following the trends observed with protein drug targets, computational approaches for drug design have been developed for this new class of molecules. Our efforts toward the development of a universal docking program, Fitted, led us to focus on nucleic acids. Throughout the development of this docking program, efforts were directed toward displaceable water molecules which must be accurately located for optimal docking-based drug discovery. However, although there is a plethora of methods to place water molecules in and around protein structures, there is, to the best of our knowledge, no such fully automated method for nucleic acids, which are significantly more polar and solvated than proteins. We report herein a new method, Splash'Em (Solvation Potential Laid around Statistical Hydration on Entire Macromolecules) developed to place water molecules within the binding cavity of nucleic acids. This fast method was shown to have high agreement with water positions in crystal structures and will therefore provide essential information to medicinal chemists.

Chemoproteomic Selectivity Profiling of PIKK and PI3K Kinase Inhibitors

Chemical proteomic approaches utilizing immobilized, broad-selective kinase inhibitors (Kinobeads) have proven valuable for the elucidation of a compound's target profile under close-to-physiological conditions and often revealed potentially synergistic or toxic off-targets. Current Kinobeads enrich more than 300 native protein kinases from cell line or tissue lysates but do not systematically cover phosphatidylinositol 3-kinases (PI3Ks) and phosphatidylinositol 3-kinase-related kinases (PIKKs). Some PIKKs and PI3Ks show aberrant activation in many human diseases and are indeed validated drug targets. Here, we report the development of a novel version of Kinobeads that extends kinome coverage to these proteins. This is achieved by inclusion of two affinity probes derived from the clinical PI3K/MTOR inhibitors Omipalisib and BGT226. We demonstrate the utility of the new affinity matrix by the profiling of 13 clinical and preclinical PIKK/PI3K inhibitors. The large discrepancies between the PI3K affinity values obtained and reported results from recombinant assays led us to perform a phosphoproteomic experiment showing that the chemoproteomic assay is the better approximation of PI3K inhibitor action in cellulo. The results further show that NVP-BEZ235 is not a PI3K inhibitor. Surprisingly, the designated ATM inhibitor CP466722 was found to bind strongly to ALK2, identifying a new chemotype for drug discovery to treat fibrodysplasia ossificans progressiva.

Challenges and current status of computational methods for docking small molecules to nucleic acids

Since the development of the first docking program in 1982, the use of docking-based in silico screening for potentially bioactive molecule discovery has become a common strategy in academia and pharmaceutical industry. Up until recently, application of docking programs has largely focused on drugs binding to proteins. However, with the discovery of promising drug targets in nucleic acids, including RNA riboswitches, DNA G-quadruplexes, and extended repeats in RNA, there has been greater interests in developing drugs for nucleic acids. However, due to major biochemical and physical differences in charges, binding pockets, and solvation, existing docking programs, developed for proteins, face difficulties when adopted directly for nucleic acids. In this review, we cover the current field of in silico docking to nucleic acids, available programs, as well as challenges faced in the field.

In search of constrained FTY720 and phytosphingosine analogs as dual acting anticancer agents targeting metabolic and epigenetic pathways

A series of compounds containing pyrrolidine and pyrrolizidine cores with appended hydrophobic substituents were prepared as constrained analogs of FTY720 and phytosphingosine. The effect of these compounds on the viability of cancer cells, on downregulation of the nutrient transport systems, and on their ability to cause vacuolation was studied. An attempt to inhibit HDACs with some phosphate esters of our analogs was thwarted by our failure to reproduce the reported inhibitory action of FTY720-phosphate.

Docking of Covalent Ligands: Challenges and Approaches

Covalent ligands have recently regained considerable attention in drug discovery. The rational design of such ligands, however, is still faced with particular challenges, mostly related to the fact that covalent bond formation is a quantum mechanical phenomenon which cannot adequately be handled by the force fields or empirical approaches typically used for noncovalent protein-ligand interactions. Although the necessity for quantum chemical approaches is clear, they cannot yet routinely be applied on large data sets of ligands or for a broader exploration of binding modes in docking calculations. On the other hand, technical solutions for performing docking calculations with covalent ligands are available, but their scope is normally quite limited. Scoring functions typically neglect the contribution from covalent bond formation completely. In this situation, the question arises how to approach covalent ligands and which methods to choose for their docking and design.

Chemical probes and drug leads from advances in synthetic planning and methodology

Screening of small-molecule libraries is a productive method for identifying both chemical probes of disease-related targets and potential starting points for drug discovery. In this article, we focus on strategies such as diversity-oriented synthesis that aim to explore novel areas of chemical space efficiently by populating small-molecule libraries with compounds containing structural features that are typically under-represented in commercially available screening collections. Drawing from more than a decade's worth of examples, we highlight how the design and synthesis of such libraries have been enabled by modern synthetic chemistry, and we illustrate the impact of the resultant chemical probes and drug leads in a wide range of diseases.

Covalent inhibitors design and discovery

In the history of therapeutics, covalent drugs occupy a very distinct category. While representing a significant fraction of the drugs on the market, very few have been deliberately designed to interact covalently with their biological target. In this review, the prevalence of covalent drugs will first be briefly covered, followed by an introduction to their mechanisms of action and more detailed discussions of their discovery and the development of safe and efficient covalent enzyme inhibitors. All stages of a drug discovery program will be covered, from target considerations to lead optimization, strategies to tune reactivity and computational methods. The goal of this article is to provide an overview of the field and to outline good practices that are needed for the proper assessment and development of covalent inhibitors as well as a good understanding of the potential and limitations of current computational methods for the design of covalent drugs.

Modeling covalent-modifier drugs

In this review, we present a summary of how computer modeling has been used in the development of covalent-modifier drugs. Covalent-modifier drugs bind by forming a chemical bond with their target. This covalent binding can improve the selectivity of the drug for a target with complementary reactivity and result in increased binding affinities due to the strength of the covalent bond formed. In some cases, this results in irreversible inhibition of the target, but some targeted covalent inhibitor (TCI) drugs bind covalently but reversibly. Computer modeling is widely used in drug discovery, but different computational methods must be used to model covalent modifiers because of the chemical bonds formed. Structural and bioinformatic analysis has identified sites of modification that could yield selectivity for a chosen target. Docking methods, which are used to rank binding poses of large sets of inhibitors, have been augmented to support the formation of protein-ligand bonds and are now capable of predicting the binding pose of covalent modifiers accurately. The pK_a's of amino acids can be calculated in order to assess their reactivity towards electrophiles. QM/MM methods have been used to model the reaction mechanisms of covalent modification. The continued development of these tools will allow computation to aid in the development of new covalent-modifier drugs. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Quality by design (QbD) approach of pharmacogenomics in drug designing and formulation development for optimization of drug delivery systems

Conventional approaches of drug discovery are very complex, costly and time consuming. But after the completion of human genome project, applications of pharmacogenomics in this area completely revolutionize the drug discovery and development process to produce a quality by design (QbD) approach based products. The applications of two areas of pharmacogenomics i.e. structural and functional pharmacogenomics excel the drug discovery process by employing genomic data in drug target identification and evaluation, lead optimization via high throughput screening, evaluation of drug metabolizing enzymes, drug transporters and drug receptors using computer aided technique and bioinformatics library data base. Pharmacogenomics also provides an important and reliable basis for evaluation and optimization of the dosage forms as well as repositioning of failed drugs for the treatment of new disease. Various dosage forms of category of drugs such as anticancer drugs, vaccines, gene and DNA delivery systems and immunological agents can be easily evaluated based on the genetic markers of the related disease. The effect of different formulation polymers on pharmacokinetic and pharmacodynamic properties of drugs can be assessed easily and therefore it plays an important role in formulation optimization. However, current applications of pharmacogenomics in drug discovery and formulation optimization are very limited because of costly and non accessible techniques for everyone, but in future, with the advancement in the technology; the application of genomic data in drug discovery will provide us with innovative, safer and more efficacious medicines.