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"Discover the link between the latest chemical biology approaches and novel drug therapies! Protein Targeting with Small Molecules: Chemical Biology Techniques and Applications takes readers beyond the use of chemical biology in basic research, providing a highly relevant look at techniques that can address the challenges of biology and drug design and development. This indispensable bench companion features up-to-date coverage of advances in chemistry and assesses their impact on developing new therapeutics, making it ideal for chemical biologists and medicinal chemists who are developing small molecule drugs to target proteins and treat diseases. In addition, the book examines the full range of complex biological systems and their interrelationship with chemistry, from the interaction of biological response modifiers with proteins to the chemical biology of cell surface oligosaccharides. Distinguished by an overview of chemical biology that is reinforced and clarified by detailed examples and descriptions of techniques, Protein Targeting with Small Molecules: Chemical Biology Techniques and Applications:* Introduces key technologies and methods of chemical biology designed to detect the interactions of small molecules and proteins* Facilitates the discovery of small molecules that bind to proteins and describes the molecules' application in the investigation of biological processes* Presents timely coverage of the development of fluorescent probes for small molecules, as well as the generation of small molecule ligands and inhibitors* Reviews important techniques such as chemical genomics, target profiling, immobilization technology, detection methods, chemical inhibition, and structure-based targeting* Offers a compelling synopsis of data that underscores the recent progress made in the area of targeting proteins by small molecules"

"This book about protein-protein Interactions as drug targets, targeting the MDM2-p53 protein-protein interaction for new cancer therapeutics, the development of small-molecule IAP antagonists for the treatment of cancer, protein-protein interaction targets to inhibit HIV-1 infection, inhibitors of protein-protein interactions paramyxovirus fusion ? a focus on respiratory syncytial virus, rational design strategies for developing synthetic inhibitors of helical protein interfaces, and the discovery of navitoclax, a Bcl-2 family inhibitor."

"This dissertation comprehensively demonstrates how two universally conserved guanosine triphosphatases in the signal recognition particle and its membrane receptor maintain the efficiency and fidelity of the co-translational protein targeting process essential to all cells. A series of quantitative experiments reveal that the highly ordered and coordinated conformational states of the machinery are the key to their regulatory function. This dissertation also offers a mechanistic view of another fascinating system in which multistate protein machinery closely control critical biological processes."

"Penelitian ini bertujuan untuk mengetahui laju pertumbuhan maksimum mikroalga yang dikultivasi dalam medium NPK Urea dan kandungan protein pada sampel kering mikroalga dengan metode uji absorbansi spektrofotometri uv-visible. Jenis mikroalga yang digunakan dalam penelitian ini adalah Chlorella vulgaris dan Spirulina plantesis. Laju pertumbuhan maksimum diperoleh dari tiga metode hitung yaitu haemositometer, absorbansi dan kapasitansi. Laju pertumbuhan maksimum Chlorella vulgaris diperoleh pada hari ketujuh masa kultivasi dengan jumlah 4.752.000 sel/ml dan Spirulina plantesis pada hari keenam dengan jumlah 64.000 sel/ml. Pengujian kandungan protein menggunakan alkaline copper reagen (ACR) yang memanfaatkan reaksi antara larutan tembaga (Cu2+), NaOH dan sampel. Perubahan warna sampel menjadi ungu menandakan adanya reaksi antara Cu2+ dengan ikatan peptida atau protein. Besarnya konsentrasi protein dapat diketahui dengan melihat nilai serapan pada panjang gelombang 520 nm. Kandungan protein yang dihasilkan dari berat kering sampel (w/w) dalam penelitian ini sebesar 14,78% untuk Chlorella vulgaris dan 16,06% untuk Spirulina plantesis. Jenis asam amino yang teridentifikasi berdasarkan perbandingan grafik BSA dengan sampel adalah tyrosin, phenylalanine dan tryptophan.

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This study has purpose to determine the maximum growth rate of microalgae cultivation in the NPK Urea medium and protein content on a dry microalgae sample with UV-visible absorbance spectrophotometry assay method. Type of microalgae used in this study was Chlorella vulgaris and Spirulina plantesis. The maximum growth rate is calculated using three methods: haemocytometer, absorbance and capacitance. Chlorella vulgaris maximum growth rate obtained on the seventh day of cultivation period with the number 4.752.000 cells/ml and Spirulina plantesis on the sixth day with the number 64.000 cells/ml. The protein content was tested using alkaline copper reagent (ACR) which utilizes the reaction between copper (Cu2+), NaOH and samples. The color change of samples turn to purple indicates there are reaction between Cu2+ and peptide bonds or protein. The amount of protein concentration can be determined by looking the absorption value at 520 nm wavelength. The result of protein content of the dry sample weight (w/w) in this study amounted to 14.78% for Chlorella vulgaris and 16.06% for Spirulina plantesis. Types of amino acid were identified by comparison with a standart BSA is tyrosine, phenylalanine and tryptophan."

"Methicillin-resistant Staphylococcus aureus (MRSA) telah menyebar luas dan menjadi penyebab utama infeksi, baik di masyarakat maupun rumah sakit. MRSA tidak hanya berdampak bagi kesehatan, tetapi juga menimbulkan implikasi ekonomi serius dengan perkiraan kontribusi yang signifikan terhadap kematian dalam dekade mendatang. Penicillin-binding Protein 2a (PBP2a) merupakan protein tambahan pada membran bakteri Staphylococcus aureus yang bertanggung jawab atas resistensinya terhadap antibiotik β-laktam, termasuk metisilin. Dalam penelitian ini, senyawa yang diketahui memiliki aktivitas sebagai inhibitor PBP2a digunakan sebagai training set dan active set. Training set digunakan untuk membuat model farmakofor menggunakan metode shared dan merged pada perangkat lunak LigandScout. Model dari metode shared menghasilkan skor tertinggi sebesar 0,8525 dengan fitur dua daerah hidrofobik (H) dan satu akseptor ikatan hidrogen (HBA). Sementara itu, Model dari metode merged menghasilkan skor tertinggi sebesar 0,8053 dengan fitur empat akseptor ikatan hidrogen (HBA). Setelah dilakukan optimasi dan validasi menggunakan active set dan decoy set, model farmakofor terbaik berasal dari model yang dibangun menggunakan metode shared dengan penurunan weight sebesar 0,1 pada fitur farmakofor H1. Parameter analisis yang diperoleh adalah AUC100%; EF1%; EF5%; sensitivitas; dan spesifisitas yang berturut-turut senilai 0,67; 3,9; 3,1; 0,65; dan 0,60. Model farmakofor terbaik digunakan untuk melakukan penapisan virtual pada pangkalan data HerbalDB. Pemeringkatan senyawa kandidat dilakukan berdasarkan pharmacophore-fit score tertinggi. Senyawa kandidat yang termasuk dalam peringkat sepuluh tertinggi adalah Trigonelloside C, (S)-6-Gingerol, Epicatechin-(4β→6)-epicatechin-(4β→8)-catechin, Mesuol, Scutellarein 7-glucosyl-(1→4)-rhamnoside, trans-p-Ferulyl alcohol 4-O-[6-(2-methyl-3-hydroxypropionyl)] glucopyranoside, 3’-Deoxymaysin, 15-HETE, Proanthocyanidin A1, dan Anhydrosafflor yellow B.

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Methicillin-resistant Staphylococcus aureus (MRSA) has spread widely and become a major cause of infections in both the community and hospitals. MRSA not only impacts health but also has serious economic implications, with a significant contribution to mortality expected in the coming decade. Penicillin-binding Protein 2a (PBP2a) is an additional protein on the membrane of the Staphylococcus aureus responsible for its resistance to β-lactam antibiotics, including methicillin. In this study, compounds known to have activity as PBP2a inhibitors were used as the training set and active set. The training set was used to create pharmacophore models using the shared and merged methods in the LigandScout software. The model from the shared method achieved the highest score of 0.8525 with features of two hydrophobic regions (H) and one hydrogen bond acceptor (HBA). Meanwhile, the model from the merged method achieved the highest score of 0.8053 with features of four hydrogen bond acceptors (HBA). After validation and optimization using the active set and decoy set, the best pharmacophore model was obtained from the shared method with a weight reduction of 0.1 on the H1 pharmacophore feature. The analysis parameters obtained were AUC100%; EF1%; EF5%; sensitivity; and specificity which score were 0,67; 3,9; 3,1; 0,65; dan 0,60 respectively. The best pharmacophore model was used for virtual screening on the HerbalDB database. Candidate compounds were ranked based on the highest pharmacophore-fit score, with the top ten candidate compounds being Trigonelloside C, (S)-6-Gingerol, Epicatechin-(4β→6)-epicatechin-(4β→8)-catechin, Mesuol, Scutellarein 7-glucosyl-(1→4)-rhamnoside, trans-p-Ferulyl alcohol 4-O-[6-(2-methyl-3-hydroxypropionyl)] glucopyranoside, 3’-Deoxymaysin, 15-HETE, Proanthocyanidin A1, dan Anhydrosafflor yellow B."

"MRSA (Methicillin-Resistant Staphylococcus aureus) adalah jenis spesies bakteri S. aureus yang resisten terhadap antibiotik metisilin dan antibiotik beta laktam lainnya. Infeksi MRSA menjadi salah satu penyebab utama infeksi nosokomial dan sering kali terkait dengan tingkat kesakitan, kematian, durasi rawat inap yang panjang, dan beban biaya yang substansial. Resistensi MRSA dikaitkan dengan produksi jenis enzim PBP2 baru yaitu PBP2a yang memiliki afinitas yang rendah terhadap β-laktam. Penelitian ini bertujuan untuk mendapatkan parameter optimum untuk penapisan virtual dengan metode penambatan molekular senyawa inhibitor PBP2a menggunakan AutoDock Vina serta mendapatkan 10 kandidat senyawa yang berpotensi sebagai inhibitor PBP2a dari hasil penambatan menggunakan parameter optimum. Pada penelitian ini dilakukan penapisan virtual kandidat inhibitor penicillin-binding protein 2a (PBP2a dari pangkalan data HerbalDB menggunakan penambatan molekuler. Proses optimasi dan validasi menghasilkan parameter terbaik adalah ukuran gridbox 20,625Å x 20,625Å x 20,625Å dengan exhaustiveness 16 menggunakan Autodock Vina yang menghasilkan nilai EF1% 0 dan AUC 0,6428. Berdasarkan hasil penapisan diperoleh 10 peringkat senyawa terbaik menggunakan Autodock Vina yaitu, 7-(2''-p-coumaroylglucoside), 2’’-o-galloylisovitexin, Prunin 6’’-p-coumarate, Withanolide D, Epigallocatechin , 6-methoxypulcherrimin, Beta-cyclanoline, Artonin S, Quercetin 3-rhamnoside-7-glucoside, dan Epicatechin 3, 5-di-o-gallate.

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MRSA (Methicillin-Resistant Staphylococcus aureus) is a type of S. aureus bacterial species that is resistant to the antibiotic methicillin and other beta lactam antibiotics. MRSA infection is one of the main causes of nosocomial infections and is often associated with high levels of morbidity, mortality, long duration of hospitalization, and substantial cost burden. MRSA resistance is associated with the production of a new type of PBP2 enzyme, namely PBP2a, which has a low affinity for β-lactams. This study aims to obtain optimum parameters for virtual screening using the molecular docking method for PBP2a inhibitor compounds using AutoDock Vina and to obtain 10 candidate compounds that have the potential to act as PBP2a inhibitors from the docking results using optimum parameters. In this study, virtual screening of penicillin-binding protein 2a (PBP2a) inhibitor candidates was carried out from the HerbalDB database using molecular docking. The optimization and validation process resulted in the best parameters being a gridbox size of 20.625Å x 20.625Å x 20.625Å with exhaustiveness of 16 using Autodock Vina which resulted an EF1% value 0 and AUC 0.6428. Based on the screening results, the 10 best compound rankings were obtained using Autodock Vina, namely, 7-(2''-p-coumaroylglucoside), 2’’-o-galloylisovitexin, Prunin 6’’-p-coumarate, Withanolide D, Epigallocatechin , 6-methoxypulcherrimin, Beta-cyclanoline, Artonin S, Quercetin 3-rhamnoside-7-glucoside, and Epicatechin 3, 5-di-o-gallate."

"The lock-and-key principle formulated by Emil Fischer as early as the end of the 19th century has still not lost any of its significance for the life sciences. The basic aspects of ligand-protein interaction may be summarized under the term 'molecular recognition' and concern the specificity as well as stability of ligand binding. Molecular recognition is thus a central topic in the development of active substances, since stability and specificity determine whether a substance can be used as a drug. Nowadays, computer-aided prediction and intelligent molecular design make a large contribution to the constant search for, e. g., improved enzyme inhibitors, and new concepts such as that of pharmacophores are being developed."