Judul: Meniran (Phyllanthus niruri) Potential as an Antivirus  against Foot and Mouth Disease In Silico
Abstrak: Penyakit mulut dan kuku (PMK) merupakan penyakit infeksius yang dapat menjangkiti hewan ternak sehingga mampu menyebabkan kerugian ekonomi yang masif. Meniran hijau (Phyllanthus niruri) diketahui memiliki aktivitas antivirus, sehingga dapat dijadikan salah satu alternatif antivirus PMK untuk diuji secara in silico. Penelitian diawali dengan berbagai analisis struktural dan fungsional reseptor target, penambatan molekuler dengan YASARA Structure, dan seleksi senyawa metabolit sekunder meniran hijau. Senyawa dengan nilai ΔG paling negatif dan Kd terkecil dikatakan memiliki ikatan terkuat, ini dapat dijumpai pada phyllanthenol dengan nilai ΔG dan Kd berturut-turut adalah -7.526 kkal/mol dan 2.261 μM. Namun, jika dilihat dari kemiripan letak pengikatan ligan pada struktur protein dengan rupintrivir sebagai ligan pembanding, kemungkinan besar eriodictin dan diosgenin dapat menjadi senyawa paling potensial. Berdasarkan pendekatan secara in silico pada penelitian ini, senyawa metabolit sekunder meniran hijau dapat dikatakan potensial sebagai antivirus PMK dengan metode kerja inhibisi protease 3Cnya., Foot and mouth disease (FMD) is an infectious disease that can infect livestock, causing massive economic losses. Green meniran (Phyllanthus niruri) is known to have antiviral activity, so it can be used as an alternative for FMD antiviral to be tested in silico. The research began with various structural and functional analyzes of target receptors, molecular docking with YASARA Structure, and selection of green meniran secondary metabolites. The compound with the most negative ΔG value and the smallest Kd is said to have the strongest bond, this can be found in phyllanthenol with ΔG and Kd values of -7.526 kcal/mol and 2.261 μM, respectively. However, judging from the similarity in the location of the binding of the ligand in the protein structure to that of rupintrivir as the comparison ligand, it is very likely that eriodictin and diosgenin could be the most potent compounds. Based on the in silico approach in this study, the secondary metabolites of green meniran can be said to be potential as FMD antivirals with their protease 3C inhibition method.
Keyword: antivirus, FMDV, inhibitor, green meniran, molecular docking

Judul: Analysis of Active Compounds in Phyllanthus niruri L. as  potential inhibitors to SARS-CoV-2 3CLpro EPI_ISL_576383 with Molecular  Docking
Abstrak: Coronavirus disease 2019 (COVID- 19) merupakan penyakit yang disebabkan oleh infeksi virus corona SARS-CoV-2. Enzim 3-Chymotrypsin-Like Protease (3CLpro) berperan dalam siklus hidup SARS-CoV-2 sebagai enzim kunci dalam replikasi dan transkripsi virus. Penelitian ini bertujuan menganalisis interaksi molekuler senyawa aktif meniran terhadap reseptor 3CLpro dari SARS-CoV-2 asal Indonesia EPI_ISL_576383 dan menentukan senyawa aktif meniran sebagai inhibitor enzim 3CLpro SARS-CoV-2. Metode yang digunakan dalam penelitian ini yaitu penambatan molekuler menggunakan aplikasi YASARA Structure. Hasil penelitian menunjukkan dari 49 senyawa aktif meniran terdapat tujuh senyawa aktif yang memiliki afinitas pengikatan terhadap 3CLpro antara lain ellagic acid, lupeol, hinokinin, hypophyllanthin, methyl brevifolincarboxylate, quercetin dan niranthin. Senyawa aktif ellagic acid menjadi ligan terbaik dengan energi bebas ikatan (∆G) -4.296 kkal/mol yang berinteraksi dengan 13 residu asam amino. Hasil penelitian dapat digunakan sebagai acauan dalam studi in vitro dan in vivo terhadap enzim 3- Chymotrypsin-Like Protease (3CLpro) SARS-CoV-2., Coronavirus disease 2019 (COVID-19) is a disease caused by infection of coronavirus, SARS-CoV-2. The 3-Chymotrypsin-Like Protease (3CLpro) acts as a key enzyme in the replication and transcription of SARS-CoV-2 virus life cycle. This study aims to analyze the molecular interaction and determine the best ligand from the active compounds in Phyllanthus niruri L. against the 3CLpro receptor from Indonesian EPI_ISL_576383 in SARS-CoV-2 coronavirus. Molecular docking was conducted using YASARA Structure application. The results from 49 active compounds showed seven active compounds that exhibit affinity binding to 3CLpro, such as ellagic acid, lupeol, hinokinin, hypophyllanthin, methyl brevifolincarboxylate, quercetin and niranthin. Ellagic acid is determined as the best ligand out of all the active compounds with free energies of binding (∆G) - 4,296 kcal/mol and shown interaction with 13 amino acid residues. These results can be further used as a reference for in vitro and in vivo studies of SARS-CoV-2 3-Chymotrypsin-Like Protease (3CLpro).
Keyword: 3CLpro inhibitor, molecular docking, Phyllanthus niruri L

Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm