Judul: Molecular Docking of the Active Compound of Red Betel (Piper crocatum) on Butyrylcholinesterase as an Antialzheimer's Candidate
Abstrak: Jenis demensia yang sering dialami oleh orang lanjut usia (lansia), salah satunya yaitu penyakit Alzheimer. Penderita penyakit Alzheimer ditandai dengan penurunan fungsi kognitif, memori, dan perubahan perilaku secara permanen. Komponen aktif yang terkandung dalam daun sirih merah memiliki keterkaitan dalam menghambat enzim butirilkolinesterase (BChE). BChE adalah salah satu enzim yang berperan penting dalam penanganan penyakit Alzheimer yang dikaitkan dengan patologis Alzheimer, yaitu hipotesis kolinergik. Penelitian ini bertujuan menguji daya inhibisi senyawa aktif yang terkandung dalam daun sirih merah terhadap aktivitas enzim BChE melalui pendekatan simulasi penambatan molekuler. Metode yang digunakan pada penelitian melalui penggabungan metode penapisan virtual dan penambatan molekuler sebagai tahapan awal pengembangan daun sirih merah melalui penghambatan enzim BChE. Hasil yang telah diperoleh pada penelitian ini, yaitu daya inhibisi terbaik dimiliki oleh 1,2,3,4,5,6,7- heptazacycloicosane sebesar 0,4888 µM dan diperoleh energi bebas pengikatan sebesar -8,6 kkal mol-1 . Residu yang terlibat pada pengikatan substrat oleh ligan uji dengan enzim BChE, yaitu Tyr-332 dan Trp-82., Alzheimer’s disease is a type of dementia experienced by a significant portion of the world’s population. Alzheimer’s is characterized by a permanent decline in cognitive function, memory, and behavioral changes. The active components contained in red betel leaf are linked to inhibiting the butyrylcholinesterase (BChE) enzyme. According to the cholinergic hypothesis, BChE is an enzyme that may play an important role in the etiology and treatment of Alzheimer’s disease. The aim of the study was to test the inhibitory power of the active compound contained in red betel leaf against BChE through a molecular docking simulation approach. The method used in this research was a combination of virtual screening and molecular docking. The result obtained with the best inhibition were 1,2,3,4,5,6,7-heptazacycloicosane of 0,4888 µM and a binding free energy of -8,6 kkal mol-1. The amino acids involved in binding the substrate by the test ligand to BChE were Tyr-332 and Trp-82.
Keyword: antialzheimer, butirilkolinesterase, sirih merah, antialzheimer, butyrylcholinesterase, Piper crocatum

Judul: Molecular Docking of Black Cumin Active Compound to Inhibits Cholinesterase Enzyme in the Development of Alzheimer’s Therapy
Abstrak: Asetilkolinesterase (AChE) dan Butirilkolinesterase (BChE) merupakan dua jenis enzim kolinesterase yang berperan dalam penurunan kadar asetilkolin sebagai gejala khas penyakit alzheimer. Jintan hitam memiliki beragam senyawa aktif yang berpotensi menghambat aktivitas kedua enzim. Penelitian ini bertujuan menganalisis interaksi beberapa senyawa aktif penting dari jintan hitam dalam menghambat aktivitas kedua enzim. Senyawa uji terbaik dipilih berdasar analisis sifat kemiripan obat yang memenuhi kriteria dalam bioavailabilitas, toksisitas dan aspek farmakokinetik sebagai obat. Analisis penambatan molekul dilakukan dengan perangkat lunak komputer PyRx Virtual Screening dan YASARA Structure. Hasil penelitian menunjukkan 7 dari 25 senyawa uji diduga memiliki aktivitas penghambatan pada enzim AChE dan BChE. Senyawa nigelicin berpotensi sebagai inhibitor terbaik AChE (ΔG -7,74 kcal/mol; %BSS 69,23%). Senyawa nigelidin berpotensi sebagai inhibitor terbaik BChE (ΔG -6,73 kcal/mol; %BSS 33,33%). Ikatan inhibitor dan enzim pada keduanya didominasi interaksi hidrofobik dengan cincin aromatik berjajar. Kedua senyawa tergolong kelompok alkaloid jintan hitam yang berpotensi dikembangkan sebagai herbal terapi alzheimer., Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE) are two types of cholinesterase enzyme that plays important role in reducing acetylcholine as a symptom of alzheimer. Black cumin has a variety of active compounds and the potential to inhibit the activity of both enzymes. This study aims to analyze interaction of some crucial active compounds of black cumin in inhibiting AChE and BChE enzymes. Active compounds selected through drugs-likeness analysis that in compliance with bioavailability, toxicity and pharmacocinetics aspect. Docking simulation doing by the Pyrx Virtual Screening software and the YASARA Structure software. As a result, 7 of the 25 analyze compounds have the potential to inhibit activity of both enzymes. Nigelicin is the best compound that inhibits AChE (ΔG -7,74 kcal/mol; %BSS 69,23%). Nigelidin is the best compound that inhibits BChE (ΔG -6.73 kcal/mol; %BSS 33,33%). Both inhibitor and enzyme complex dominated by hydrophobic with lined aromatic structure. Both compounds are classified as alkaloid of black cumin that potential as alzheimer’s therapy.
Keyword: alzheimer’s disease, acetylcholinesterase, butyrylcholinesterase, black cumin, molecular docking

Judul: 3D model reconstruction using aerial photo to measure object height
Abstrak: 3D reconstruction, especially for height extraction, using digital aerial photos taken from a non-metric camera and Unmanned Aerial Vehicle (UAV) is a challenging study. The purposes of the study are to determine the factors affect the accuracy of an object’s height reveal from a 3D model and establish procedures to deliver the optimal result. Two or more overlapping aerial photos can be constructed into the 3D model by applying the principles of collinearity and epipolar geometry using 3D reconstruction algorithm. Due to the instability of non-metric digital camera, the camera must be calibrated before 3D reconstruction is processed, in that way the quality of spatial extraction can be then measured. The study is conducted using 24 megapixels resolution Sony NEX7 digital camera and Hexacopter UAV. UAV was flown to a height of 50 m, 60 m and 70 m and placed at a certain position in order to get some height variations of camera. Camera Calibration Toolbox is utilized to calculate intrinsik parameters of the camera and a specific program is developed using MATLAB in order to build the 3D model and to obtain the object’s height. The result validation is done by comparing the height from 3D model with that one measured using Electronic Total Station. The accuracy of the object’s height up to 1 mm successfully achieved, with the largest height prediction error reaches 15.2 cm at 70 m flying height above ground level and average percentage error 4.07 for 20 objects.
Keyword: 3D reconstruction, collinearity, epipolar geometry, UAV