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The quest for novel chemical matter ~de novo drug design by sumiran

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This document discusses de novo drug design, which aims to design novel drug molecules from scratch computationally. It describes the basic steps of de novo design programs, including analyzing the target protein's active site, building molecules, and evaluating candidates. The key goals are to design molecules that fit the active site and form favorable interactions. Constraints like hydrogen bonding and hydrophobic regions are extracted from the target structure to guide molecule generation and scoring. The end goal is to produce new molecular scaffolds that can inspire medicinal chemistry efforts.

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THE QUEST FOR NOVEL CHEMICAL MATTER ~DE NOVO DRUG DESIGN
The quest for novel chemical matter ~de novo drug design by sumiran
The quest for novel chemical matter ~de novo drug design by sumiran
? De novo design aims to build in silico an entire molecule ¡®from scratch¡¯ ? De novo programs attempt to automate the process of structure-based drug design. ? More speci?cally, these programs design compounds to ?t in a particular active site, or conform to a particular pharmacophore model. ? This is an admirable goal, although it is also an extremely complex task. ? In practice, de novo programs have become part of the computational drug design tool box.
The quest for novel chemical matter ~de novo drug design by sumiran
? The artwork ¡®Development II¡¯ by M. C. Escher provides an illustration of the concept of chemical space ? There might exist several activity ¡®islands¡¯ in chemical space, represented by the well-shaped and formed ¡®lizards¡¯; that is, drug molecules with desired de novo design provides a method for lead identification. ? De novo design can therefore be regarded as a complement to other virtual techniques, such as database searching, and non-virtual techniques such as HTS.
The quest for novel chemical matter ~de novo drug design by sumiran
All of the current de novo programs follow three basic steps: 1. Analysis of the active site 2. Building molecules
The quest for novel chemical matter ~de novo drug design by sumiran
PRIMARY TARGET CONSTRAINTS ? All information that is related to the ligand¨Creceptor interaction forms the PRIMARY TARGET CONSTRAINTS for candidate compounds. ? Such constraints can be gathered both from the three- dimensional receptor structure and from known ligands of the particular target. ? If the former is consulted, the design strategy is receptor- based; in the latter case, it is ligand-based.
The quest for novel chemical matter ~de novo drug design by sumiran
? Receptor-based design starts with the determination of the binding site. ? As complementarities in molecular shape and submolecular physical and chemical properties are important for specific binding, the binding site is then examined to derive shape constraints for a ligand, as well as specific non-covalent ligand¨C receptor interactions in the form of hypothetical INTERACTION SITES. ? Interaction sites are typically subdivided into 1. hydrogen bonds 2. electrostatic 3. hydrophobic interactions.
? Receptor groups capable of hydrogen-bonding are of special interest owing to the strongly directional nature of the two interaction partners ¡ª hydrogen-bond acceptor and donor ¡ª and often form key interaction sites. ? They allow the assignation of ligand atom positions with a complementary hydrogen-bond type within a small region of space and a defined orientation. ? Key interaction sites have a major role in the effort to reduce the vast number of possible structures because they define strong and explicit requirements for successful receptor¨Cligand binding.
? Receptor-based de novo design uses a variety of methods to deduce interaction sites from the three dimensional structure of the binding pocket. ? HSITE, a rule-based method, was the first software specifically developed for the derivation of primary target constraints in an automated, de novo design approach. ? Only hydrogen-bond acceptors and donors are considered, but it attempted to identify intramolecular hydrogen bonds of the receptor. ? Other rule-based methods were developed later that added lipophilic interaction sites. ? HIPPO augmented this concept by including interaction sites of covalent bonds and bonds to metal ions.
? Some de novo design programs perform the calculations with the software GRID, whereas others contain their own implementation of this algorithm. ? LigBuilder carries out a statistical analysis after the grid-based calculations to extract the most promising interaction sites. ? Two de novo approaches use Multiple Copy Simultaneous Search (MCSS) for the generation of primary target constraints. ? MCSS determines energetically favourable positions and orientations of functional groups in the assembly ¡ª that is, favourable positions of specific functional groups in the binding site are not only indicated but are already placed at these positions. ? This placement of chemical groups provides a starting point for the next step in de novo design: the assembly of a complete ligand.
RECEPTOR-BASED SCORING ? The evaluation of candidate compounds with scoring functions is a central task in the design process. ? The application of a de novo design program yields more than one candidate compound. ? These structures can either emerge from a single run of the program or from several runs with one candidate compound per run. ? These quality-assessment approaches can be subdivided into three different types of receptor-based scoring functions: explicit force-field methods; empirical scoring functions; and knowledge-based scoring functions. ? All of these approaches attempt to approximate the binding free energy. ? Force fields are computationally more costly than the other two types of scoring functions. LEGEND was the first program that used a force field to evaluate candidate compounds. ? The first empirical scoring function in the field of de novo design was implemented in the program LUDI. ? Knowledge-based scoring functions have become popular in the field of docking during the past few years, yet to date there is only a single de novo design program, SmoG. ? Interactions found to occur more frequently than would be randomly expected are considered attractive; interactions that occur less frequently
The quest for novel chemical matter ~de novo drug design by sumiran
The quest for novel chemical matter ~de novo drug design by sumiran
The quest for novel chemical matter ~de novo drug design by sumiran
The quest for novel chemical matter ~de novo drug design by sumiran
LINK/GROW STRATEGY
The quest for novel chemical matter ~de novo drug design by sumiran
LATTICE STRATEGY
SECONDARY TARGET CONSTRAINTS ? An effectual drug molecule is subject to more objectives than the binding affinity. ? Essential drug properties, such as suitable absorption, distribution, metabolism, excretion and toxicity (the so-called ADMET properties), clearly emphasize the multi-dimensional optimization of drug development. ? Constraints other than the binding affinity are secondary constraints.
RECENT EXAMPLES OF DE NOVO DESIGN
The quest for novel chemical matter ~de novo drug design by sumiran
? An important goal of de novo design is to inspire medicinal chemists through the chemical motifs that are identified. ? Ultimately, the aim is to offer support for hit and lead identification and widen the chemical horizon.
REFERENCES ? Schneider G, Fechner U. Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov. 2005;4(8):649¨C 663. doi:10.1038/nrd1799 ? Pirard B. The quest for novel chemical matter and the contribution of computer-aided de novo design. Expert Opin Drug Discov. 2011;6(3):225¨C231. doi:10.1517/17460441.2011.554394 ? /SomasekharGupta/denovo- drug-design ? COMPUTATIONAL DRUG DESIGN BY DAVID C. YOUNG. Published by John Wiley & Sons, Inc., Hoboken, New Jersey
The quest for novel chemical matter ~de novo drug design by sumiran

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The quest for novel chemical matter ~de novo drug design by sumiran

  • 1. THE QUEST FOR NOVEL CHEMICAL MATTER ~DE NOVO DRUG DESIGN
  • 4. ? De novo design aims to build in silico an entire molecule ¡®from scratch¡¯ ? De novo programs attempt to automate the process of structure-based drug design. ? More speci?cally, these programs design compounds to ?t in a particular active site, or conform to a particular pharmacophore model. ? This is an admirable goal, although it is also an extremely complex task. ? In practice, de novo programs have become part of the computational drug design tool box.
  • 6. ? The artwork ¡®Development II¡¯ by M. C. Escher provides an illustration of the concept of chemical space ? There might exist several activity ¡®islands¡¯ in chemical space, represented by the well-shaped and formed ¡®lizards¡¯; that is, drug molecules with desired de novo design provides a method for lead identification. ? De novo design can therefore be regarded as a complement to other virtual techniques, such as database searching, and non-virtual techniques such as HTS.
  • 8. All of the current de novo programs follow three basic steps: 1. Analysis of the active site 2. Building molecules
  • 10. PRIMARY TARGET CONSTRAINTS ? All information that is related to the ligand¨Creceptor interaction forms the PRIMARY TARGET CONSTRAINTS for candidate compounds. ? Such constraints can be gathered both from the three- dimensional receptor structure and from known ligands of the particular target. ? If the former is consulted, the design strategy is receptor- based; in the latter case, it is ligand-based.
  • 12. ? Receptor-based design starts with the determination of the binding site. ? As complementarities in molecular shape and submolecular physical and chemical properties are important for specific binding, the binding site is then examined to derive shape constraints for a ligand, as well as specific non-covalent ligand¨C receptor interactions in the form of hypothetical INTERACTION SITES. ? Interaction sites are typically subdivided into 1. hydrogen bonds 2. electrostatic 3. hydrophobic interactions.
  • 13. ? Receptor groups capable of hydrogen-bonding are of special interest owing to the strongly directional nature of the two interaction partners ¡ª hydrogen-bond acceptor and donor ¡ª and often form key interaction sites. ? They allow the assignation of ligand atom positions with a complementary hydrogen-bond type within a small region of space and a defined orientation. ? Key interaction sites have a major role in the effort to reduce the vast number of possible structures because they define strong and explicit requirements for successful receptor¨Cligand binding.
  • 14. ? Receptor-based de novo design uses a variety of methods to deduce interaction sites from the three dimensional structure of the binding pocket. ? HSITE, a rule-based method, was the first software specifically developed for the derivation of primary target constraints in an automated, de novo design approach. ? Only hydrogen-bond acceptors and donors are considered, but it attempted to identify intramolecular hydrogen bonds of the receptor. ? Other rule-based methods were developed later that added lipophilic interaction sites. ? HIPPO augmented this concept by including interaction sites of covalent bonds and bonds to metal ions.
  • 15. ? Some de novo design programs perform the calculations with the software GRID, whereas others contain their own implementation of this algorithm. ? LigBuilder carries out a statistical analysis after the grid-based calculations to extract the most promising interaction sites. ? Two de novo approaches use Multiple Copy Simultaneous Search (MCSS) for the generation of primary target constraints. ? MCSS determines energetically favourable positions and orientations of functional groups in the assembly ¡ª that is, favourable positions of specific functional groups in the binding site are not only indicated but are already placed at these positions. ? This placement of chemical groups provides a starting point for the next step in de novo design: the assembly of a complete ligand.
  • 16. RECEPTOR-BASED SCORING ? The evaluation of candidate compounds with scoring functions is a central task in the design process. ? The application of a de novo design program yields more than one candidate compound. ? These structures can either emerge from a single run of the program or from several runs with one candidate compound per run. ? These quality-assessment approaches can be subdivided into three different types of receptor-based scoring functions: explicit force-field methods; empirical scoring functions; and knowledge-based scoring functions. ? All of these approaches attempt to approximate the binding free energy. ? Force fields are computationally more costly than the other two types of scoring functions. LEGEND was the first program that used a force field to evaluate candidate compounds. ? The first empirical scoring function in the field of de novo design was implemented in the program LUDI. ? Knowledge-based scoring functions have become popular in the field of docking during the past few years, yet to date there is only a single de novo design program, SmoG. ? Interactions found to occur more frequently than would be randomly expected are considered attractive; interactions that occur less frequently
  • 24. SECONDARY TARGET CONSTRAINTS ? An effectual drug molecule is subject to more objectives than the binding affinity. ? Essential drug properties, such as suitable absorption, distribution, metabolism, excretion and toxicity (the so-called ADMET properties), clearly emphasize the multi-dimensional optimization of drug development. ? Constraints other than the binding affinity are secondary constraints.
  • 25. RECENT EXAMPLES OF DE NOVO DESIGN
  • 27. ? An important goal of de novo design is to inspire medicinal chemists through the chemical motifs that are identified. ? Ultimately, the aim is to offer support for hit and lead identification and widen the chemical horizon.
  • 28. REFERENCES ? Schneider G, Fechner U. Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov. 2005;4(8):649¨C 663. doi:10.1038/nrd1799 ? Pirard B. The quest for novel chemical matter and the contribution of computer-aided de novo design. Expert Opin Drug Discov. 2011;6(3):225¨C231. doi:10.1517/17460441.2011.554394 ? /SomasekharGupta/denovo- drug-design ? COMPUTATIONAL DRUG DESIGN BY DAVID C. YOUNG. Published by John Wiley & Sons, Inc., Hoboken, New Jersey