1) The document describes an in silico study to identify potential inhibitors of DNA methyltransferase (DNMT1) through pharmacophore modeling.
2) Two pharmacophore models were generated based on features of compounds previously shown to bind DNMT1. These models were used to screen a database of over 150,000 compounds.
3) A total of 182 compounds were identified with predicted binding energies above -9.7 kcal/mol to DNMT1. The results provide support for further refinement of the pharmacophore models and experimental testing of top compounds as potential DNMT1 inhibitors.
In silico discovery of dna methyltransferase inhibitors (1)angelicagonzalez10
1) The document describes an in silico study to identify potential inhibitors of DNA methyltransferase (DNMT1) using pharmacophore modeling.
2) Two pharmacophore models were generated based on features of compounds previously shown to bind DNMT1. These models were used to screen a database of compounds.
3) A total of 182 compounds were identified with predicted binding energies over -9.7 kcal/mol to DNMT1. The results provide support for further refinement of the pharmacophore models and experimental testing of top compounds.
Architectures, mechanisms and molecular evolution of natural product methyltr...yangxiaolong2013
This document summarizes recent research on natural product methyltransferases (NPMTs). It discusses how methylation is a common biochemical modification in natural products, usually catalyzed by S-adenosyl-L-methionine (SAM)-dependent methyltransferases. The structural biology of over 50 NPMTs has provided insights into their catalytic mechanisms and substrate specificities. NPMTs are classified based on the atom (O, N, C, or S) that accepts the methyl group. They modify a wide range of substrates involved in signaling, defense, and specialized metabolism. Sequence analysis reveals conserved motifs in NPMTs related to SAM binding. Elucidating NPMT structures has advanced understanding of their evolution and
This document summarizes the synthesis and characterization of a novel ruthenium(II) complex containing 4-carboxy-N-ethylbenzamide (CNEB) as a ligand, and its potential as an inhibitor of lactate dehydrogenase (LDH). The CNEB ligand was synthesized and characterized using techniques such as X-ray crystallography. It was then complexed with cis-Ru(bpy)2Cl2 to form [Ru(CNEB)2(bpy)2]2PF6. The complex showed cytotoxic effects against cancer cells and interacted with LDH. In vitro and in tissue experiments demonstrated that the complex acts as a non-competitive inhibitor of LDH. Thus,
This study examines mutations to the bovine immunodeficiency virus (BIV) transactivator protein (Tat) and its interaction with the trans-activation response element (TAR) RNA. All-atom modeling of the wild-type and mutant Tat-TAR complexes showed that double glycine mutations at positions 75 and 78 of Tat decreased stability, while a single glycine mutation at position 75 increased stability. Coarse-grained lattice modeling of over 12 million structures supported these findings. The researchers are developing updated statistical potentials using a larger training set to better evaluate coarse-grained structures and calculate binding energies of the mutant complexes.
This document summarizes research testing the ability of eight diindolylmethane derivatives to induce apoptosis in murine L5178Y lymphoma cells. The derivatives were synthesized with different substituted phenyl groups attached to the methane carbon. Testing found compound 3a, with a meta-hydroxyl group, was the most active, inhibiting 93% of cell growth and inducing 71.04% apoptosis. In general, substituents able to form hydrogen bonds and in the meta position were most effective at arresting the cell cycle. The preliminary results provide insight into how the substituent and position impact potency against lymphoma cells.
The document discusses an overview of livestock metabolomics. It defines metabolomics as the large-scale study of small molecules present in cells, biofluids, tissues and organs. Various techniques for metabolomic analysis are described including mass spectrometry, NMR spectroscopy, GC-MS and LC-MS. Applications of metabolomics in livestock include disease diagnosis, biomarker identification, monitoring drug and surgical impacts, and understanding gene-environment interactions. Specific examples include identifying metabolic biomarkers for mastitis resistance in dairy cows and detection of milk fever in cattle. The challenges and future prospects of metabolomics research are also outlined.
PuneetJaju_SummerProjectReport_Univ. of CambridgePuneet Jaju
Puneet Jaju, under the supervision of Dr. Henrietta Venter, aimed to determine the stoichiometry of proteins in the multidrug efflux pump MexAB-OprM from the pathogen Pseudomonas aeruginosa. This pump contributes to the pathogen's drug resistance. Jaju cloned and purified the individual proteins MexA, MexB, and OprM, and attempted to cross-link them into a complex to analyze by mass spectrometry. Cross-linking the purified proteins yielded some high molecular weight complexes but was inefficient. Cross-linking proteins expressed in E. coli cells before purification yielded a higher molecular weight band corresponding to a cross-linked complex, though further optimization is needed to obtain sufficient yields
Chemically modified tetracycline- Dr. RohanjeetRohanjeet Dede
This document discusses chemically modified tetracyclines (CMTs) as host modulating agents for the treatment of periodontitis. It begins by providing background on periodontitis and the role of host inflammatory response. It then discusses tetracycline antibiotics and how their structure was chemically modified to develop CMTs, which lack antimicrobial properties but retain anti-collagenase effects. The document outlines several CMT structures and their mechanisms of action, including inhibition of matrix metalloproteinases and inflammatory mediators. It describes the pleiotropic host modulation effects of CMTs and their potential use in other conditions beyond periodontitis.
In silico discovery of dna methyltransferase inhibitors (1)angelicagonzalez10
1) The document describes an in silico study to identify potential inhibitors of DNA methyltransferase (DNMT1) using pharmacophore modeling.
2) Two pharmacophore models were generated based on features of compounds previously shown to bind DNMT1. These models were used to screen a database of compounds.
3) A total of 182 compounds were identified with predicted binding energies over -9.7 kcal/mol to DNMT1. The results provide support for further refinement of the pharmacophore models and experimental testing of top compounds.
Architectures, mechanisms and molecular evolution of natural product methyltr...yangxiaolong2013
This document summarizes recent research on natural product methyltransferases (NPMTs). It discusses how methylation is a common biochemical modification in natural products, usually catalyzed by S-adenosyl-L-methionine (SAM)-dependent methyltransferases. The structural biology of over 50 NPMTs has provided insights into their catalytic mechanisms and substrate specificities. NPMTs are classified based on the atom (O, N, C, or S) that accepts the methyl group. They modify a wide range of substrates involved in signaling, defense, and specialized metabolism. Sequence analysis reveals conserved motifs in NPMTs related to SAM binding. Elucidating NPMT structures has advanced understanding of their evolution and
This document summarizes the synthesis and characterization of a novel ruthenium(II) complex containing 4-carboxy-N-ethylbenzamide (CNEB) as a ligand, and its potential as an inhibitor of lactate dehydrogenase (LDH). The CNEB ligand was synthesized and characterized using techniques such as X-ray crystallography. It was then complexed with cis-Ru(bpy)2Cl2 to form [Ru(CNEB)2(bpy)2]2PF6. The complex showed cytotoxic effects against cancer cells and interacted with LDH. In vitro and in tissue experiments demonstrated that the complex acts as a non-competitive inhibitor of LDH. Thus,
This study examines mutations to the bovine immunodeficiency virus (BIV) transactivator protein (Tat) and its interaction with the trans-activation response element (TAR) RNA. All-atom modeling of the wild-type and mutant Tat-TAR complexes showed that double glycine mutations at positions 75 and 78 of Tat decreased stability, while a single glycine mutation at position 75 increased stability. Coarse-grained lattice modeling of over 12 million structures supported these findings. The researchers are developing updated statistical potentials using a larger training set to better evaluate coarse-grained structures and calculate binding energies of the mutant complexes.
This document summarizes research testing the ability of eight diindolylmethane derivatives to induce apoptosis in murine L5178Y lymphoma cells. The derivatives were synthesized with different substituted phenyl groups attached to the methane carbon. Testing found compound 3a, with a meta-hydroxyl group, was the most active, inhibiting 93% of cell growth and inducing 71.04% apoptosis. In general, substituents able to form hydrogen bonds and in the meta position were most effective at arresting the cell cycle. The preliminary results provide insight into how the substituent and position impact potency against lymphoma cells.
The document discusses an overview of livestock metabolomics. It defines metabolomics as the large-scale study of small molecules present in cells, biofluids, tissues and organs. Various techniques for metabolomic analysis are described including mass spectrometry, NMR spectroscopy, GC-MS and LC-MS. Applications of metabolomics in livestock include disease diagnosis, biomarker identification, monitoring drug and surgical impacts, and understanding gene-environment interactions. Specific examples include identifying metabolic biomarkers for mastitis resistance in dairy cows and detection of milk fever in cattle. The challenges and future prospects of metabolomics research are also outlined.
PuneetJaju_SummerProjectReport_Univ. of CambridgePuneet Jaju
Puneet Jaju, under the supervision of Dr. Henrietta Venter, aimed to determine the stoichiometry of proteins in the multidrug efflux pump MexAB-OprM from the pathogen Pseudomonas aeruginosa. This pump contributes to the pathogen's drug resistance. Jaju cloned and purified the individual proteins MexA, MexB, and OprM, and attempted to cross-link them into a complex to analyze by mass spectrometry. Cross-linking the purified proteins yielded some high molecular weight complexes but was inefficient. Cross-linking proteins expressed in E. coli cells before purification yielded a higher molecular weight band corresponding to a cross-linked complex, though further optimization is needed to obtain sufficient yields
Chemically modified tetracycline- Dr. RohanjeetRohanjeet Dede
This document discusses chemically modified tetracyclines (CMTs) as host modulating agents for the treatment of periodontitis. It begins by providing background on periodontitis and the role of host inflammatory response. It then discusses tetracycline antibiotics and how their structure was chemically modified to develop CMTs, which lack antimicrobial properties but retain anti-collagenase effects. The document outlines several CMT structures and their mechanisms of action, including inhibition of matrix metalloproteinases and inflammatory mediators. It describes the pleiotropic host modulation effects of CMTs and their potential use in other conditions beyond periodontitis.
1. The study characterized the aggregation of recombinant human Interleukin-1 receptor type II (rhuIL-1RII) using differential scanning calorimetry (DSC) and size exclusion chromatography (SEC).
2. A scan-rate dependence in the DSC experiment and a break from linearity in initial aggregation rates near the melting temperature (Tm) suggested that protein unfolding significantly contributes to the aggregation reaction pathway.
3. A mechanistic model was developed to extract meaningful thermodynamic and kinetic parameters from the irreversibly denatured aggregation process by simulating how unfolding properties could predict aggregation rates at different temperatures above and below the Tm.
This document discusses systems pharmacology and applying a systems-based approach to understanding drug action and effects. It begins by outlining some big questions in pharmacology research, such as predicting drug efficacy and toxicity. It then discusses concepts like polypharmacology, where one drug can have multiple targets, and how drug binding is a dynamic process. The document proposes using multiscale modeling to simulate these complex biological processes. It describes developing computational methods to explore the large conformational and functional spaces involved. Several applications of these approaches are mentioned, such as drug repositioning and designing personalized medicines. Overall, the document advocates applying systems-level modeling and simulations to better understand how drugs work in the body.
This document summarizes Philip Bourne's research using bioinformatics and systems biology approaches for early stage drug discovery. His approach involves characterizing known protein-ligand binding sites, searching for similar off-target binding sites across the proteome, and analyzing networks of potential drug-target interactions to understand drug polypharmacology and repurpose existing drugs. Examples are given of findings that explained drug side effects, identified possible drug repurposing opportunities, and informed multi-target drug strategies. The goal is to develop a high-throughput approach to rationally explore large networks of protein-ligand interactions.
1) The document discusses mitochondrial DNA (mtDNA) and its role in white adipose tissue. mtDNA encodes components of the mitochondrial respiratory chain and is important for mitochondrial function.
2) Alterations in mtDNA levels or mutations have been linked to obesity and other metabolic disorders. Studies show that mtDNA levels are reduced in obesity but may be more closely associated with diabetes.
3) Drugs that treat diabetes, like pioglitazone, have been found to increase mtDNA levels in white adipose tissue. Further research is needed to fully understand how mtDNA impacts white adipose tissue and metabolism.
This document provides an outline for a presentation on directed evolution. It discusses the process of directed evolution, which involves randomly introducing mutations at the genetic level followed by selection of variants with desired protein characteristics. The document also covers types of mutations, naturally evolutionary processes like random mutagenesis and gene recombination that directed evolution mimics, library size, selection and screening strategies, applications, and advantages of directed evolution over rational design.
This document summarizes research on sortase enzymes. Sortases are bacterial transpeptidase enzymes that covalently attach secreted proteins to the bacterial cell wall. They play important roles in virulence and pathogenesis. The document discusses various classes of sortases, their mechanisms of action, roles in antibiotic resistance and biofilm formation. It also outlines applications of sortases in areas like vaccine development, drug targeting, and protein immobilization. Overall, the document provides an overview of the sortase enzyme family and their significance in microbial physiology and disease.
NMR spectroscopy techniques including 2D TOCSY, ROESY, and STD NMR were used to analyze peptide epitopes and determine their binding to monoclonal antibodies. 2D NMR was used to assign proton signals in peptide epitopes. STD NMR showed that the peptide GVTSAX3D binds to antibody SM3 through interactions of the 3-aminobenzoate substitution and methyl groups of valine, threonine, and alanine residues. Mass spectrometry and NMR spectroscopy supported the successful synthesis and characterization of peptide epitopes for studying antibody binding.
Drug and gene delivery vehicles are biocompatible devices that can carry therapeutic components in the body. Synthetic vehicles include block copolymers, liposomes, dendrimers, and magnetic nanoparticles. Block copolymers form micelles with hydrophobic cores that can encapsulate drugs. Liposomes are phospholipid vesicles that can encapsulate both hydrophilic and hydrophobic drugs. Dendrimers are nanoscale polymers that can be functionalized to target drugs. Magnetic nanoparticles can be used for drug delivery, hyperthermia cancer treatment, and as MRI contrast agents. These vehicles aim to improve drug bioavailability and targeting while decreasing toxicity.
Phasins promote bacterial growth and PHA synthesis and affect the number, size, and distribution. Due to their amphiphilic nature, these proteins play an important structural function, forming an interphase between the hydrophobic content of PHA granules and the hydrophilic cytoplasm content. Phasins have been observed to affect both PHA accumulation and utilization. Apart from their role as granule structural proteins, phasins have a remarkable variety of additional functions which might play an active role in PHA-related stress protection and fitness enhancement. Due to their granule binding capacity and structural flexibility, several biotechnological applications have been developed using different phasins, increasing the interest in the study of these remarkable proteins.
Proteins perform many functions in living organisms and differ based on their amino acid sequence. Affinity chromatography uses the interaction between proteins and ligands to separate proteins, and magnetic nanoparticles can be used to make this process faster and more efficient. In this experiment, magnetic nanoparticles were prepared and bound to tissue plasminogen activator to isolate it using affinity chromatography, washing and eluting steps. Absorbance readings would then indicate if proteins were successfully isolated.
Cross-linking is a technique used to study protein structure and interactions. It involves using bifunctional reagents containing two reactive groups to form covalent bonds between amino acid residues, either within or between proteins. This captures transient or conditional interactions and provides structural data at higher resolution than other methods. The most common cross-linking reagents react with amino acids like cysteine, tyrosine, and lysine. Cross-linking has provided important insights into protein structure-function relationships and molecular interactions.
This document discusses peptidomimetics, which are small protein-like chains designed to mimic peptides while having no peptide bonds and a molecular weight under 700 Daltons. Peptidomimetics are derived from bioactive peptides and aim to improve stability, transport properties, and activity while reducing degradation. They are classified based on their modifications from the original peptide. Common modification methods include cyclization, retro-inverso design, and restricting conformations through disulfide bonds or metal chelation. Peptidomimetics have therapeutic value as they can overcome issues like poor oral bioavailability that limit peptide drugs, as demonstrated for somatostatin analogs. Recent advances include using peptidomimetics to enhance peptide vaccines
Characterization of mg state of mb in presence of peg 10 (z a parray) originalZahoor Parray
This document summarizes a study that characterized the intermediate state of myoglobin (Mb) in the presence of polyethylene glycol 10 (PEG 10) under physiological conditions. The researchers found that PEG 10 perturbed the tertiary structure of Mb but did not significantly change its secondary structure. PEG 10 was found to induce a molten globule state in Mb, where the intermediate state had hydrophobic patches and a larger hydrodynamic volume than the native protein. Isothermal titration calorimetry showed strong binding between Mb and PEG 10 at physiological pH. The researchers hypothesize that PEG 10 induces a molten globule conformation in Mb by interacting with its heme group. They conclude that protein-crowder interactions need careful
Research Summary of Laura J. Donahue, Ph.D.Laura Donahue
Laura J. Donahue conducted research on photodynamic therapy including:
1. Synthesizing two phenothiazine trimers and studying their ability to absorb light and potential for PDT, with one trimer showing promise after oxidation.
2. Conjugating chlorin e6 to PEG-folic acid and finding it had higher phototoxicity than chlorin e6 alone in killing HeLa cells, suggesting targeted delivery.
3. Reviewing the literature on photodynamic therapy to provide background information for her dissertation.
The document discusses proteomics, which is the study of the proteome or total protein complement of a biological system. Proteomics aims to understand protein expression, functions, interactions, and modifications through various analytical techniques and faces many challenges due to the complexity of proteins. Key approaches in proteomics include expression profiling to compare protein levels between healthy and disease states, structural analysis to determine protein structures, and network mapping to study protein interactions. Mass spectrometry and bioinformatics tools play important roles in proteomic studies, which have applications in characterizing protein complexes and identifying disease biomarkers.
This document describes the identification of a novel selective serotonin reuptake inhibitor (SSRI) through a process combining virtual screening and rational molecular hybridization. Virtual screening of a compound library using a monoamine transporter model identified a hit compound, MI-17, with modest serotonin transporter affinity. Comparison to a known SSRI led to the design of a molecular hybrid, DJLDU-3-79, combining structural elements of MI-17 and the known SSRI. Pharmacological evaluation found DJLDU-3-79 displayed improved serotonin transporter selectivity and binding affinity compared to MI-17. In mice, DJLDU-3-79 decreased immobility in a test of antidepressant-like activity comparable to
This document discusses intrinsically disordered proteins (IDPs), which lack a fixed three-dimensional structure under physiological conditions and instead exist as dynamic ensembles. It notes that IDPs challenge the traditional view that proteins require a well-defined structure to function. The document also mentions that IDPs often gain structure upon binding to their protein partners, and that their flexible, disordered state allows for low affinity but high specificity interactions optimal for regulation. Finally, it suggests intrinsic disorder may have evolved to allow for extended interaction surfaces and efficient signal processing.
The document discusses metabolomics data analysis and issues for biostatistics. It describes the metabolomics pipeline from experimental design and data acquisition to statistical analysis and biological interpretation. Key aspects covered include data preprocessing methods, exploratory and supervised multivariate analysis, and biological interpretation tools like metabolic network inference and pathway analysis. Specific statistical challenges in metabolomics like handling non-detects and exploring variable importance are also addressed.
Machine Learning Applications at Bell Labs, HolmdelAaron Schumacher
A presentation from Larry Jackel (North-C, Toyota Research Institute, NVIDIA) at the Neural Nets Back to the Future workshop (https://sites.google.com/site/nnb2tf/) at ICML 2016 (http://icml.cc/2016/) covering the fascinating and human history of neural net and deep learning technology that brings us to the present day.
1. The study characterized the aggregation of recombinant human Interleukin-1 receptor type II (rhuIL-1RII) using differential scanning calorimetry (DSC) and size exclusion chromatography (SEC).
2. A scan-rate dependence in the DSC experiment and a break from linearity in initial aggregation rates near the melting temperature (Tm) suggested that protein unfolding significantly contributes to the aggregation reaction pathway.
3. A mechanistic model was developed to extract meaningful thermodynamic and kinetic parameters from the irreversibly denatured aggregation process by simulating how unfolding properties could predict aggregation rates at different temperatures above and below the Tm.
This document discusses systems pharmacology and applying a systems-based approach to understanding drug action and effects. It begins by outlining some big questions in pharmacology research, such as predicting drug efficacy and toxicity. It then discusses concepts like polypharmacology, where one drug can have multiple targets, and how drug binding is a dynamic process. The document proposes using multiscale modeling to simulate these complex biological processes. It describes developing computational methods to explore the large conformational and functional spaces involved. Several applications of these approaches are mentioned, such as drug repositioning and designing personalized medicines. Overall, the document advocates applying systems-level modeling and simulations to better understand how drugs work in the body.
This document summarizes Philip Bourne's research using bioinformatics and systems biology approaches for early stage drug discovery. His approach involves characterizing known protein-ligand binding sites, searching for similar off-target binding sites across the proteome, and analyzing networks of potential drug-target interactions to understand drug polypharmacology and repurpose existing drugs. Examples are given of findings that explained drug side effects, identified possible drug repurposing opportunities, and informed multi-target drug strategies. The goal is to develop a high-throughput approach to rationally explore large networks of protein-ligand interactions.
1) The document discusses mitochondrial DNA (mtDNA) and its role in white adipose tissue. mtDNA encodes components of the mitochondrial respiratory chain and is important for mitochondrial function.
2) Alterations in mtDNA levels or mutations have been linked to obesity and other metabolic disorders. Studies show that mtDNA levels are reduced in obesity but may be more closely associated with diabetes.
3) Drugs that treat diabetes, like pioglitazone, have been found to increase mtDNA levels in white adipose tissue. Further research is needed to fully understand how mtDNA impacts white adipose tissue and metabolism.
This document provides an outline for a presentation on directed evolution. It discusses the process of directed evolution, which involves randomly introducing mutations at the genetic level followed by selection of variants with desired protein characteristics. The document also covers types of mutations, naturally evolutionary processes like random mutagenesis and gene recombination that directed evolution mimics, library size, selection and screening strategies, applications, and advantages of directed evolution over rational design.
This document summarizes research on sortase enzymes. Sortases are bacterial transpeptidase enzymes that covalently attach secreted proteins to the bacterial cell wall. They play important roles in virulence and pathogenesis. The document discusses various classes of sortases, their mechanisms of action, roles in antibiotic resistance and biofilm formation. It also outlines applications of sortases in areas like vaccine development, drug targeting, and protein immobilization. Overall, the document provides an overview of the sortase enzyme family and their significance in microbial physiology and disease.
NMR spectroscopy techniques including 2D TOCSY, ROESY, and STD NMR were used to analyze peptide epitopes and determine their binding to monoclonal antibodies. 2D NMR was used to assign proton signals in peptide epitopes. STD NMR showed that the peptide GVTSAX3D binds to antibody SM3 through interactions of the 3-aminobenzoate substitution and methyl groups of valine, threonine, and alanine residues. Mass spectrometry and NMR spectroscopy supported the successful synthesis and characterization of peptide epitopes for studying antibody binding.
Drug and gene delivery vehicles are biocompatible devices that can carry therapeutic components in the body. Synthetic vehicles include block copolymers, liposomes, dendrimers, and magnetic nanoparticles. Block copolymers form micelles with hydrophobic cores that can encapsulate drugs. Liposomes are phospholipid vesicles that can encapsulate both hydrophilic and hydrophobic drugs. Dendrimers are nanoscale polymers that can be functionalized to target drugs. Magnetic nanoparticles can be used for drug delivery, hyperthermia cancer treatment, and as MRI contrast agents. These vehicles aim to improve drug bioavailability and targeting while decreasing toxicity.
Phasins promote bacterial growth and PHA synthesis and affect the number, size, and distribution. Due to their amphiphilic nature, these proteins play an important structural function, forming an interphase between the hydrophobic content of PHA granules and the hydrophilic cytoplasm content. Phasins have been observed to affect both PHA accumulation and utilization. Apart from their role as granule structural proteins, phasins have a remarkable variety of additional functions which might play an active role in PHA-related stress protection and fitness enhancement. Due to their granule binding capacity and structural flexibility, several biotechnological applications have been developed using different phasins, increasing the interest in the study of these remarkable proteins.
Proteins perform many functions in living organisms and differ based on their amino acid sequence. Affinity chromatography uses the interaction between proteins and ligands to separate proteins, and magnetic nanoparticles can be used to make this process faster and more efficient. In this experiment, magnetic nanoparticles were prepared and bound to tissue plasminogen activator to isolate it using affinity chromatography, washing and eluting steps. Absorbance readings would then indicate if proteins were successfully isolated.
Cross-linking is a technique used to study protein structure and interactions. It involves using bifunctional reagents containing two reactive groups to form covalent bonds between amino acid residues, either within or between proteins. This captures transient or conditional interactions and provides structural data at higher resolution than other methods. The most common cross-linking reagents react with amino acids like cysteine, tyrosine, and lysine. Cross-linking has provided important insights into protein structure-function relationships and molecular interactions.
This document discusses peptidomimetics, which are small protein-like chains designed to mimic peptides while having no peptide bonds and a molecular weight under 700 Daltons. Peptidomimetics are derived from bioactive peptides and aim to improve stability, transport properties, and activity while reducing degradation. They are classified based on their modifications from the original peptide. Common modification methods include cyclization, retro-inverso design, and restricting conformations through disulfide bonds or metal chelation. Peptidomimetics have therapeutic value as they can overcome issues like poor oral bioavailability that limit peptide drugs, as demonstrated for somatostatin analogs. Recent advances include using peptidomimetics to enhance peptide vaccines
Characterization of mg state of mb in presence of peg 10 (z a parray) originalZahoor Parray
This document summarizes a study that characterized the intermediate state of myoglobin (Mb) in the presence of polyethylene glycol 10 (PEG 10) under physiological conditions. The researchers found that PEG 10 perturbed the tertiary structure of Mb but did not significantly change its secondary structure. PEG 10 was found to induce a molten globule state in Mb, where the intermediate state had hydrophobic patches and a larger hydrodynamic volume than the native protein. Isothermal titration calorimetry showed strong binding between Mb and PEG 10 at physiological pH. The researchers hypothesize that PEG 10 induces a molten globule conformation in Mb by interacting with its heme group. They conclude that protein-crowder interactions need careful
Research Summary of Laura J. Donahue, Ph.D.Laura Donahue
Laura J. Donahue conducted research on photodynamic therapy including:
1. Synthesizing two phenothiazine trimers and studying their ability to absorb light and potential for PDT, with one trimer showing promise after oxidation.
2. Conjugating chlorin e6 to PEG-folic acid and finding it had higher phototoxicity than chlorin e6 alone in killing HeLa cells, suggesting targeted delivery.
3. Reviewing the literature on photodynamic therapy to provide background information for her dissertation.
The document discusses proteomics, which is the study of the proteome or total protein complement of a biological system. Proteomics aims to understand protein expression, functions, interactions, and modifications through various analytical techniques and faces many challenges due to the complexity of proteins. Key approaches in proteomics include expression profiling to compare protein levels between healthy and disease states, structural analysis to determine protein structures, and network mapping to study protein interactions. Mass spectrometry and bioinformatics tools play important roles in proteomic studies, which have applications in characterizing protein complexes and identifying disease biomarkers.
This document describes the identification of a novel selective serotonin reuptake inhibitor (SSRI) through a process combining virtual screening and rational molecular hybridization. Virtual screening of a compound library using a monoamine transporter model identified a hit compound, MI-17, with modest serotonin transporter affinity. Comparison to a known SSRI led to the design of a molecular hybrid, DJLDU-3-79, combining structural elements of MI-17 and the known SSRI. Pharmacological evaluation found DJLDU-3-79 displayed improved serotonin transporter selectivity and binding affinity compared to MI-17. In mice, DJLDU-3-79 decreased immobility in a test of antidepressant-like activity comparable to
This document discusses intrinsically disordered proteins (IDPs), which lack a fixed three-dimensional structure under physiological conditions and instead exist as dynamic ensembles. It notes that IDPs challenge the traditional view that proteins require a well-defined structure to function. The document also mentions that IDPs often gain structure upon binding to their protein partners, and that their flexible, disordered state allows for low affinity but high specificity interactions optimal for regulation. Finally, it suggests intrinsic disorder may have evolved to allow for extended interaction surfaces and efficient signal processing.
The document discusses metabolomics data analysis and issues for biostatistics. It describes the metabolomics pipeline from experimental design and data acquisition to statistical analysis and biological interpretation. Key aspects covered include data preprocessing methods, exploratory and supervised multivariate analysis, and biological interpretation tools like metabolic network inference and pathway analysis. Specific statistical challenges in metabolomics like handling non-detects and exploring variable importance are also addressed.
Machine Learning Applications at Bell Labs, HolmdelAaron Schumacher
A presentation from Larry Jackel (North-C, Toyota Research Institute, NVIDIA) at the Neural Nets Back to the Future workshop (https://sites.google.com/site/nnb2tf/) at ICML 2016 (http://icml.cc/2016/) covering the fascinating and human history of neural net and deep learning technology that brings us to the present day.
Washington, DC Economic Partnership’s Doing Business in DC program on Recent Developments in Labor and Employment Laws featuring Grace Lee from Venable, LLP.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document outlines various engineering projects focused on assistive devices and vehicle modifications for physically challenged individuals, including an aircraft flat bed seat, gravity-assisted power generator still in development, and a sprag clutch gear box. It also mentions general vehicle layout and mechanical systems like a screw bolt mechanism, double drive screwdriver, gear box to increase motor speed, fly wheel, and gear system.
The DC Development Report is a summary of the major development and construction projects in the District of Columbia. The Washington, DC Economic Partnership (WDCEP) began tracking development activity in 2001 with the hope of creating a comprehensive database that would answer a number of questions in regards to the construction activity in the city. The Report summarizes our entire database of projects, highlights major projects and what lies ahead for development in the District of Columbia.
This update of the DC Development Report is an overview of development activity and of the expansion occurring in DC. As a resource book, it is a compilation of nearly 14 years of data collection and research that provides an overview of an ever-changing development and construction cycle.
The WDCEP performs an annual “development census” in the month of September and receives contributions from more than 100 developers, architects, contractors and economic development organizations. This outreach results in updates to more than 350 projects. While our database of projects is constantly being updated, for the purposes of this publication all data reflects project status, design and information as of September 2014.
In 2014 the WDCEP partnered with CBRE to provide an economic overview of DC and in-depth analysis of the office, retail and residential markets. Although every attempt was made to ensure the quality of the information contained in this document, the WDCEP and CBRE makes no warranty or guarantee as to its accuracy, completeness or usefulness for any given purpose.
Toura is a platform that allows content providers to create scalable mobile strategies and applications across different operating systems. It provides tools to upload, organize, and format content. Publishers can then build mobile apps intuitively with layouts and custom design elements. The built apps can be compiled and submitted to app stores, and monetized through various models like paid apps, advertising, and sponsorships. Analytics tools also allow monitoring performance and optimizing content. Toura aims to make it simple for publishers to execute multi-platform mobile strategies and experiments without extensive development resources.
The Department of Small and Local Business Development (DSLBD) manages the Certified Business Enterprise (CBE) Program. The CBE Program provides certification and contracting preferences to local businesses. Businesses must meet criteria to be certified in categories like Local Business Enterprise, Small Business Enterprise, or Disadvantaged Business Enterprise. The certification process involves attending an orientation, applying online, and submitting supplemental documents. DSLBD assists businesses and ensures CBE utilization on government contracts.
The Office of Partnerships and Grants Services (OPGS) enhances the capacity of DC government agencies, nonprofits, and community groups to identify and secure resources that advance the Mayor's priorities. OPGS provides grant assistance, acts as the District's liaison for federal grants, offers training, and builds partnerships. It informs groups of funding opportunities through alerts and a resource center. Recently, the One City Fund was established with $15 million in competitive grants for nonprofits. OPGS advises nonprofits on organizing documentation and developing competitive grant proposals.
The document provides specifications for Carrier Asia Co., Ltd.'s single effect hot water and steam absorption chillers. It includes performance data such as cooling capacity, dimensions, weight, and inlet/outlet temperatures for chilled water, cooling water, and hot water or steam. Key features listed are that the chillers use lithium bromide and water as natural refrigerants, require low maintenance due to few moving parts, and offer cost-effective cooling as an alternative to electric chillers.
Virtual meetings allow team members in different locations to interact without travel costs through tools like instant messaging, telephone conferences, and video conferencing. Video conferencing combines live video and audio so participants can see each other, demonstrate products, and share visual information. There are two types of video conferencing systems: room systems for larger meetings that require specialized equipment, and desktop systems that use webcams and monitors for smaller individual or group meetings. Web-based meetings combine instant messaging, shared workspaces, video conferencing, and tools like virtual whiteboards in one sophisticated system, allowing attendees to participate from any device anywhere in the world.
1) The study aimed to identify a drug that could inhibit the Dengue virus methyltransferase enzyme from binding to GTP, disrupting the virus. 2) Using computer modeling, researchers identified the binding pocket of the methyltransferase and placed benzene rings there to define the pharmacophore. 3) Over 60,000 potential compounds were identified from a database that fit this pharmacophore. The top 25 compounds with highest affinity were selected, with DENV-M2_1 having the highest affinity of -10.4.
This document describes research into developing a drug to inhibit the Dengue virus. Researchers used a computer model of the virus's methyltransferase enzyme, which transfers methyl groups and requires GTP for energy. They positioned benzene rings in the GTP-binding pocket to create a pharmacophore model. This model was used to search a database of over 60,000 compounds, identifying 25 with highest affinity. The compound with highest affinity, DENV-M2_1, was placed in the pocket and fit similarly to the benzene rings, suggesting it could inhibit GTP binding and prevent viral development. Further testing of this compound is needed to validate it as a potential Dengue treatment.
In silico discovery of histone methyltranferase 1juancarlosrise
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DNA methylation is a biological process where methyl groups are added to DNA, changing gene expression without altering the DNA sequence. It is essential for normal development in mammals and is associated with processes like genomic imprinting, carcinogenesis, and aging. DNA methyltransferases are enzymes that catalyze the addition of methyl groups to DNA from S-adenosylmethionine. DNA methylation plays important roles in gene silencing, X-chromosome inactivation, and suppressing viral genomes and repetitive elements incorporated into the host genome. Aberrant DNA methylation is also involved in cancer by transcriptionally silencing tumor suppressor genes.
DNA methylation is a biological process where methyl groups are added to DNA, changing gene expression without altering the DNA sequence. It is essential for normal development in mammals and is associated with processes like genomic imprinting and carcinogenesis. DNA methyltransferases are enzymes that catalyze the addition of methyl groups to DNA from S-adenosyl methionine. DNA methylation plays important roles in gene silencing, X-chromosome inactivation, and suppressing viral genomes and repetitive elements incorporated into the host genome. Abnormal DNA methylation is also associated with cancer by transcriptionally silencing tumor suppressor genes.
This document summarizes a presentation on discovering inhibitors for the histone-lysine N-methyltransferase SETD2 using an in silico approach. It discusses methyltransferases and histone methyltransferases as a potential target. The hypothesis is that selective, high-affinity SETD2 inhibitors can be identified by targeting its SAM binding site. The methodology involves generating pharmacophore models using software and screening databases of compounds. Results show two pharmacophore models and top-hit compounds identified. The conclusions are that the SETD2 binding site is a potential drug target and compounds with high predicted binding energies were identified. Future work involves refining models and testing top compounds in assays.
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This document discusses non-viral gene transfer methods. It describes various techniques for direct delivery of naked DNA including electroporation, gene guns, sonoporation, magnetofection, hydrodynamic delivery, and microinjections. It also discusses various non-viral vectors for gene delivery including oligonucleotides, liposomes, lipoplexes, polymersomes, polyplexes, dendrimers, inorganic nanoparticles, and cell-penetrating peptides. Each method is described in terms of its mechanism of delivery, advantages, disadvantages and suitable target tissues. The document provides an overview of non-viral gene expression systems and delivery methods.
This doctoral research used single-molecule imaging techniques to study DNA replication in live E. coli cells. Endogenous replication proteins like β2-clamps were labeled with fluorescent proteins using genome engineering. Observations found β2-clamps accumulate on DNA after initiation and remain bound for minutes. Experiments also examined how replisomes encounter natural Tus-Ter roadblocks and determined replication speed decreases but is not stalled. Further work aimed to study primase dynamics and localization of Tus proteins during the cell cycle but faced challenges in strain engineering. The research demonstrated applications of in vivo single-molecule imaging while also highlighting ongoing difficulties in the field.
Epigenetics- Transcription regulation of gene expressionakash mahadev
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This document summarizes recent research on the role of epigenetic regulation in human cancers. It discusses how epigenetic mechanisms like DNA methylation and histone modifications can disrupt gene expression and lead to tumorigenesis. Specifically, it describes how hypermethylation of CpG islands can silence tumor suppressor genes, and how certain histone modifications are associated with transcriptional activation or repression. The document also reviews emerging epigenetic therapies and challenges in the field, such as a lack of predictive biomarkers and unclear mechanisms of response/resistance.
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Epigenetics is the study of alterations in gene expression that occur without changes to the underlying DNA sequence. Some key mechanisms of epigenetics include DNA methylation, histone modifications, and microRNAs. DNA methylation involves the addition of methyl groups to cytosine bases and typically inhibits gene transcription. Histone modifications like acetylation and deacetylation alter chromatin structure and gene accessibility. MicroRNAs regulate gene expression through RNA interference. Epigenetic factors can be influenced by environmental exposures and differ even between identical twins, helping to explain phenotypic differences. Epigenetics also provides insights into disease development and may be modulated by nutrients.
DNA methylation is an epigenetic mechanism where a methyl group is added to DNA nucleotides, most commonly to the 5-carbon position of cytosine. This methylation can alter gene expression and affect cellular processes. DNA methyltransferases (DNMTs) establish and maintain DNA methylation patterns, while Ten-Eleven Translocation (TET) enzymes can remove methyl groups through a process called active DNA demethylation. Abnormal DNA methylation is associated with diseases like cancer, where tumor suppressor genes are often silenced by hypermethylation while genomes are globally hypomethylated.
The document summarizes recent research on DNA mismatch repair (MMR) in eukaryotic cells. MMR plays critical roles in maintaining genome stability by correcting replication errors. While prokaryotic MMR is well understood, the mechanism in eukaryotes is more complex and questions remain about strand discrimination, essential components, and how MMR interacts with other pathways. The document reviews current understanding and debates around how eukaryotic MMR distinguishes the parental and daughter strands to ensure errors are repaired accurately.
DNA MISMATCH REPAIR HAPPENS ONLY DURING A BRIEF WINDOW OF OPPORTUNITYANDMET...Jorge Rico
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A comparative study using different measure of filterationpurkaitjayati29
This document presents a study comparing different scoring functions used in filter-based feature selection methods for microarray gene expression data. Chapter 1 introduces gene expression, DNA microarrays, and the goals of classification and feature selection. Chapter 2 provides background on bioinformatics, molecular biology, and the central dogma. Chapter 3 describes DNA microarray technology and gene expression data. Chapter 4 reviews literature on feature selection techniques applied to microarray data, discussing filter, wrapper, embedded, hybrid, and ensemble methods. Chapter 5 proposes using a scoring function-based filter method to select relevant genes, focusing on mutual information, symmetric uncertainty, information gain, and Chi-square scoring functions.
This document discusses plant epigenetics and its potential for crop improvement. It begins by defining epigenetics as heritable changes in gene expression that do not involve changes to the underlying DNA sequence. It then discusses several epigenetic mechanisms including DNA methylation, histone modifications, and RNA interference. DNA methylation and histone modifications can alter gene expression patterns without changing the DNA sequence. RNA interference is a post-transcriptional gene silencing mechanism. Understanding these epigenetic processes may help improve crops through epigenetic breeding or biotechnology approaches.
4) Describe the role of methylation in regulating gene expression. (.pdfshanhairstonkirui643
4) Describe the role of methylation in regulating gene expression. (In other words, does it
promote or inhibit gene expression, what is methylated, and what proteins add or remove the
methylation groups (as applicable)?).
5) Describe the role of acetylation in control of gene expression. (In other words, does it promote
or inhibit gene expression, what is acetylated, and what enzymes add or remove the acetylation
groups?).
6) How does the charge of the histones within a nucleosome affect a cell’s transcriptional
activity? In other words, does making a histone octomer more or less positively charged have an
effect?
Solution
Answer:
4. DNA methylation is an epigenetic mechanism and involves the modifcation of DNA that
occurs through the addition of a methyl group to DNA strand itself. DNA methylation occurs at
the cytosine bases of eukaryotic DNA, which are converted to 5-methylcytosine by DNA
methyltransferase (DNMT) enzymes.
DNA methylation plays a crucial role in repressing gene expression, perhaps by blocking the
promoters at which activating transcription factors should bind. It appears that proper DNA
methylation is essential for cell differentiation and embryonic development.
In some cases, methylation has observed to play a role in mediating gene expression. Evidence
of this has been found in studies that show that methylation near gene promoters varies
considerably depending on cell type, with more methylation of promoters correlating with low or
no transcription. While overall methylation levels and completeness of methylation of particular
promoters are similar in individual humans, there are significant differences in overall and
specific methylation levels between different tissue types and between normal cells and cancer
cells from the same tissue.
The demethylation process is necessary for epigenetic reprogramming of genes and is also
directly involved in many important disease mechanisms such as tumor progression.
Demethylation of DNA can either be passive or active, or a combination of both.
Passive DNA demethylation usually takes place on newly synthesized DNA strands via DNMT1
during replication rounds. Active DNA demethylation mainly occurs by the removal of 5-
methylcytosine via the sequential modification of cytosine bases..
Similar to Angelica and khrystall written report research project (20)
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This document discusses preparing a receptor/target for docking simulations by cleaning a protein, setting a grid configuration file, and running Vina docking with benzenes. It also mentions converting and separating benzenes for use in a molecular model.
Gel electrophoresis is a method used to separate biomolecules like DNA, RNA, and proteins based on their size and charge. There are two main types of gels used: agarose gels separate larger DNA and RNA fragments, while polyacrylamide gels are better for separating smaller proteins. DNA or proteins are loaded onto the gel and an electric current is applied, causing the molecules to migrate through the gel at different rates depending on their size and charge. The results can then be visualized to analyze samples.
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In silico discovery of dna methyltransferase inhibitors 05 05 (1) (1)khrystallramos
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Angelica and khrystall written report research project
1. In silico discovery of DNA methyltransferase inhibitors.
Angélica M. González-Sánchez[1][2], Khrystall K. Ramos-Callejas[1][2] , Adriana O. Diaz-
Quiñones[2] and Héctor M. Maldonado, Ph.D.[3].
[1]RISE students [2]University of Puerto Rico at Cayey [3] Pharmacology Department UCC, Medical School
______________________________________________________________________
Abstract
DNA Methyltransferases are a type of transferase enzymes that add methyl groups to cyto-
sine bases in newly replicated DNA. In mammals this process is necessary for a normal de-
velopment of cell’s functions as well as for growth of the organism. Recent studies have
shown that, under pathological conditions, there is a close relationship between the meth-
ylation of tumor suppressor genes and cancer development. This project, which derives
from a previous research made by the In silico drug discovery team, was therefore intended
to identify specific, high-affinity inhibitors for the DNA Methyltransferase by using an In
silico approach. We used several databases and software that allowed us to identify poten-
tial new targets in DNA Methyltransferase, to create two pharmacophore models for the
identified target and to identify compounds from a database that suited both the size of the
target and the features of the model. A total of 182 compounds were obtained in this study
with predicted binding energies of more than -9.7 kilocalories per mole. These results are
quite significant given the relatively small portion of the database that was evaluated.
Therefore, the pharmacophore model that allowed identifying the compounds with the
highest binding energies, which was Model 2, will be refined further on.
Keywords: DNA methyltransferase/ methyl group/ In silico/ pharmacophore model/ bind-
ing energy.
Introduction other is called methylation. In living or-
Methyltransferases are a type of ganisms it mainly occurs in reactions re-
transferase enzyme that transfers a me- lated to the DNA or to proteins. That’s
thyl group from a donor molecule to an why methylation most often takes place
acceptor. A methyl group is composed of in the nucleic bases in DNA or in amino
one carbon atom bonded to 3 hydrogen acids in protein structures.
atoms (refer to Figure 1). It is the group
Figure 1: Chem-
that the methyltransferase transfers. By
ical structure of
transferring this methyl group from one a Methyl group
molecule to another, the methyltransfer-
ase is in charge of catalyzing certain reac- To function as a methyl group
tions in the body. The transfer of this transporter, the methyltransferase carries
methyl group from one compound to an- with itself a compound named S-
2. In Silico discovery of DNA methyltransferase inhibitors.
adenosylmethionine, also called SAM, and to control expression of genes in dif-
which functions as a methyl donor ferent types of cells (Goodsell, 2011).
(Malygin and Hattman, 2012). This dona-
In humans, as in other mammals, a
tion occurs due to the fact that SAM has a
normal regulation of DNA Methyltrans-
sulfur atom bound to a reactive methyl
ferases in the cells is essential for embry-
group that is willing to break off and react
onic development, as well as for other
(refer to Figure 2).
processes of growth (Goodsell, 2011).
Figure 2: Chemical structure of the methyl do-
However, in cancer cells, DNA methyl-
nor S-adenosylmethionine.
transferases have been shown to be over-
produced, to work faster and to function
at greater rates (Perry et al., 2010). A link
has also been found between the methyla-
tion of the tumor suppressor genes and
There are several types of methyl- tumorigenesis, which is the process by
transferases (Fandy, 2009). For this par- which normal cells are transformed into
ticular research we decided to focus on cancer cells, as well as with metastasis,
DNA’s methyltransferase. DNA methyl- which is the process by which cancer cells
transferase also has several subtypes, spread from one organ to another. This
from which we chose the DNA methyl- means that the methylation of these tu-
transferase 1, or DNMT1 (refer to Figure mor suppressor genes promotes cancer
3). This one is in charge of adding methyl development (Chik and Szyf, 2010).
groups to cytosine bases in newly repli-
cated DNA (Fandy, 2009). This has sever- Figure 3: Struc-
al implications. In order for a cell to be ture of human
capable of doing a specific function it DNMT1 (residues
600-1600) in
must encode certain genes to produce
complex with
specific proteins. For this process, meth- Sinefungin.
ylation of the DNA is essential because it
adds methyl groups to genes in the DNA, Pdb: 3SWR
shutting off some and activating others
(Goodsell, 2011). In order for cell’s speci-
ficity to be maintained, methyltransferas-
es have to methylate DNA strands so that
this genetic information will be transmit- Given this, it has been decided to
ted as DNA replicates. Therefore, the me- investigate about a way of finding specific
thyl groups that are added to the DNA inhibitors to decrease this type of methyl-
strands are important to modify how DNA ation that can lead to cancer develop-
bases are read during protein synthesis ment. That’s the reason why we have
derived the hypothesis that specific, high-
May 2012. 2
3. In Silico discovery of DNA methyltransferase inhibitors.
affinity inhibitors of DNA methyltransfer- tential new target (or site of interaction)
ase (DNMT1) can be identified via an In in that protein. For this, a compound that
Silico approach. was downloaded with the structure of the
protein, called Sinefungin, was very useful
Materials and Methods
because it served as a guide to identify
In order to reach our objectives
where there is more probability of inter-
and test our hypothesis, we followed an In
action of that protein with other com-
silico approach. Therefore, our materials
pounds. Then, by using the server
were mainly databases and software that
NanoBio and the software AutoDock Vina
will be described further on. First, the
we started to make a benzene mapping by
structure of the methyltransferase
identifying benzenes that had a high bind-
DNMT1 was downloaded from the data-
ing energy in their interaction with the
base www.pdb.org by entering the acces-
protein. From this benzene mapping we
sion code of the desired protein
were supposed to develop a pharmaco-
(3SWR.pdb). The structure of the DNMT1
phore model, but by recommendation of
was then opened with the software
our mentor, we decided to develop it by
PyMOL Molecular Grpahics System v1.3
using a different strategy. Therefore, we
(www.pymol.org). There, the protein was
took 2 compounds that have already been
cleaned from drugs and water molecules
studied in a research made by the In silico
that were not useful for this study (refer
drug discovery team about Dengue’s Me-
to Figure 4).
thyltransferase (refer to Figure 5). In that
Figure 4: Clean structure of the DMNT1
previous research these compounds
(pdb: 3SWR)
showed a great binding energy with the
DNA Methyltransferase. Two pharmaco-
phore models were created by combining
the most prominent features of those two
compounds. For the generation of this
model we took advantage of the unique
features of the software LigandScout
(www.inteligand.com). We came up with
two pharmacophore models that are hy-
brids of the two compounds previously
identified and which have 3 basic fea-
tures: hydrophobic centroids, an aromatic
ring and exclusion volumes (refer to Fig-
ure 6).
Further on, by using the software
AutoDock (protein docking software) we Those two pharmacophore models
were able to make a grid and configura- generated were then used to "filter" rela-
tion file, that allowed us to identify a po- tively large databases of small chemical
May 2012. 3
4. In Silico discovery of DNA methyltransferase inhibitors.
compounds (drug-like or lead-like) by us- Figure 6: The two generated pharmacophore
models.
ing the Terminal of the server NanoBio
and LigandScout. A smaller database with
Figure 5: Compounds that showed great affinity
with the DNA Methyltransferase on a previous
Dengue’s Methyltransferase research.
Results
Lead-like compounds are mole-
cules that serve as the starting point for
the development of a drug, typically by
the compounds presenting characteristics variations in structure for optimal effica-
imposed by the model was generated. cy. From a database of about 1.7 million
Therefore, the developed pharmacophore lead-like compounds we evaluated more
models helped to reduce significantly the than 150,000 of them, divided into 5 piec-
results of compounds from the database es of the database, each one with more
to be evaluated. This smaller database of than twenty five thousand drugs. Twen-
compounds was screened by docking ty-seven thousand two hundred and
analysis against the originally selected eighty four drugs which were suitable
target. This docking analysis consisted of with the features of the first model were
separating the smaller filtered database obtained. The average binding energy for
into files of individual drugs to then be these drugs in the first hundred top hits
able to observe the characteristics of each was 9.86 kilocalories per mole. On the
drug, including their affinity with the pro- other hand, we also acquired thirty-nine
tein. This was also done by using Lig- thousand five hundred and thirty-five
andScout. Further on, results were drugs that suited the features of the se-
combined and ranked according to pre- cond model. The average binding energy
dicted binding energies, from the greatest for the first hundred top hits of this model
affinity to the weakest one. From this, was 9.94 kilocalories per mole. This is
drugs with the greatest affinity, also quite significant for a relatively small
called potential top-hits, were identified. piece of the database evaluated. A total of
Finally, results were analyzed by observ- 182 compounds with predicted binding
ing the interactions of each of the top hit energies equal or higher than -9.7 kilocal-
drugs with the protein and identifying ories per mol were found between the
which sites of interaction, or features, two models used in this pilot project (re-
were more common, whether the ones of fer to Figure 7).
Model 1 or the ones of Model 2. These
results will also be used for further re-
finement of the pharmacophore model.
May 2012. 4
5. In Silico discovery of DNA methyltransferase inhibitors.
Model 2 are superior to the results ob-
Figure 7: Distribution of selected compounds
with predicted binding energies equal or high- tained with Model 1. This is because they
er than -9.7 kcal/mol. show higher affinity with the protein and
also because many drugs identified by the
first model resulted to be suitable with
the second one as well. Although close to
Along with the great binding ener-
gies that these models evidenced, there
was also a very significant finding that
demonstrated that 27% of the chosen
drugs fulfilled requirements of both mod-
els. These results are outstanding in
terms of the drugs’ affinity for the methyl-
transferase, which was higher mostly on
drugs from the second model (refer to
Figure 8).
Discussion
From these results we are able to
develop several conclusions. First of all,
we generated two Pharmacophore mod-
els by using information obtained from
the interaction of two previously identi-
fied compounds with the DNA methyl-
transferase as target. This 27% of the compounds obtained where
pharmacophore models allowed us to selected by both models, a significant
identify compounds that had a significant number of compounds with predicted
interaction with the DNA methyltransfer- high binding energies were also obtained
ase 1. Also, from analysis of the results with Model 1. Therefore, it can be con-
and ranking of predicted top-hits, it can cluded that Model 1 was noteworthy as
be concluded that results obtained by well. As a whole, we proved our hypothe-
May 2012. 5
6. In Silico discovery of DNA methyltransferase inhibitors.
sis because we demonstrated that by us- discovery team for guiding us in this in-
ing an In Silico approach we were able to credible journey. We would also like to
identify several drugs, which are potential thank the RISE Program for giving us the
candidates for the development of a spe- opportunity of participating in this re-
cific, high affinity inhibitor of DNA Me- search experience.
thyltransferase.
Furthermore, the acquired results Literature Cited
will definitely be useful for future studies. Chik F, Szyf M. 2010. Effects of specific
On these future studies, the In silico drug DMNT gene depletion on cancer cell trans-
discovery team will complete the analysis formation and breast cancer cell invasion;
of the interactions between the top-hits toward selective DMNT inhibitors. Carcino-
and the target and evaluate the possibility genesis. 32(2):224-232.
of refining the pharmacophore model. Fandy T. 2009. Development of DNA Me-
The sample of the evaluated compound thyltransferase Inhibitors for the Treatment
of Neoplastic Diseases. Current Medicinal
database should also be broaden to in-
Chemistry. 16(17):2075-2085.
clude a larger number of drugs. The goal
Goodsell, D. 2011. Molecule of the month:
would be to evaluate 1.7 million lead-like
DNA Methyltransferases. RCBS Protein
compounds, which represent the whole Data-
database. After several refinements of the Bank.http://www.pdb.org/pdb/101/motm.do
model along with their respective screen- ?momID=139
ings we should identify top-hits and test a Malygin EG, Hattman S. 2012. DNA me-
group of these compounds in a bioassay. thyltransferases: mechanistic models derived
from kinetic analysis. Critical reviews in
Acknowledgements Biochemistry and Molecular Biology.
We would like to acknowledge the
Perry A, Watson W, Lawler M, Hollywood
great contribution of our mentor Dr. Hec- D. 2010. The epigenome as a therapeutic
tor Maldonado, our student assistant target in prostate cancer. Nature Reviews on
Adriana Diaz and the whole In Silico drug Urology. 7(1):668-680.
May 2012. 6