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: Analysis Potency of Red Betel Active Compund as an Inhibitor of Acetylcholinesterase Enzyme Through In Silico
Abstrak: Alzheimer merupakan penyakit yang menyebabkan terjadinya penurunan fungsi kognitif dan merupakan penyebab kematian ketujuh terbesar di dunia. Inhibitor enzim asetilkolinesterase (AChE) merupakan pengobatan alzheimer yang paling banyak berkembang hingga saat ini, namun pengonsumsiannya masih memberikan banyak efek samping. Sirih merah, tanaman yang telah banyak digunakan dalam pengobatan herbal mengandung banyak senyawa aktif yang diharapkan dapat berpotensi sebagai inhibitor AChE. Penelitian ini bertujuan menemukan senyawa aktif sirih merah yang berpotensi dalam menginhibisi enzim AChE secara in silico menggunakan teknik penambatan molekuler. Potensi inhibisi terbaik dimiliki oleh copaene, auron, dan 1,1’-(6,6’-Dihydroxy-5,5’-dimethoxy3,3’-biphenyldiyl)di(1-propanone) dengan nilai ΔG dan Ki berturut-turut sebesar - 7,738; -7,658; dan -5,348 kkal/mol serta Ki 2,045; 2,498; dan 118,9 µM. Ketiga ligan tersebut juga berinteraksi dengan sisi aktif CAS (Catalytic Active Site) atau PAS (Peripheral Aromatic Site) yang berperan penting dalam penghambatan enzim AChE untuk terapi antialzheimer., Alzheimer is a disease that causes the decline of cognitive function and considered as the seventh biggest cause of death in the world. Acetylcholinesterase (AChE) enzyme inhibitors are the most established treatment for alzheimer until now despite its possible side effects. Red betel, a widely used plant in herbal medication, contains many active compounds which are expected to be potential for AChE inhibitors. The study aims to research the active compound of red betel that has the potential to inhibit the AChE enzyme in silico through molecular docking techniques. The finest inhibitory potentials were possessed by copaene, aurone, and 1,1’-(6,6’ -Dihydroxy- 5,5’ -dimethoxy- 3,3’ -biphenyldiyl)di(1- propanone) indicated correspondingly by the value of ΔG and Ki values -7.738; - 7,658; and -5.348 kcal/mol and Ki 2,045; 2,498; and 118,9 µM. Those three ligands also interacted with the active site CAS (Catalytic Active Site) or PAS (Peripheral Aromatic Site) that plays a fundamental role to inhibit the AChE enzyme for antialzheimer therapy.
Keyword: acetylcholinesterase, alzheimer, molecular docking, red betel

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