Pengaruh Minimisasi Energi MMFF94 dengan MarvinSketch dan Open Babel PyRx pada Penambatan Molekular Turunan Oksindola Tersubstitusi

In silico technique is widely used for drug discovery because it can predict the conformation of ligands in protein macromolecules and it can calculate the binding affinity. The energy minimization is carried out to make the ligand more stable near the initial state during molecular docking process. The Merck Molecular Force Field (MMFF94) is one type of energy minimization process often used in organic compounds. The molecular docking of substituted oxindole derivatives on indoleamine macromolecules 2,3-dioxygenase (IDO-1, PDB: 2D0T) by MMFF94 minimization operated by MarvinSketch and Open Babel in PyRx showed different results. The binding affinity energy obtained was also quite different, but the ligands have the same conformation and bind the same residue with slightly different bond distances. Keywords: Molecular docking, energy minimization, substituted oxindole, Merck Molecular Force Field 94 Teknik in silico banyak digunakan untuk penemuan senyawa obat karena dapat memprediksi konformasi suatu ligan dalam makromolekul protein dan mampu menghitung nilai afinitas ikatan. Proses minimisasi energi dilakukan untuk menjadikan ligan lebih stabil mendekati keadaan awal selama penambatan molekular berlangsung. Merck Molecular Force Field (MMFF94) adalah salah satu jenis persamaan minimisasi energi yang sering digunakan pada senyawa organik. Hasil pengujian pengaruh minimisasi energi dengan MMFF94 menggunakan program MarvinSketch dan Open Babel dalam PyRx pada turunan oksindola tersubstitusi alkil terhadap makromolekul 2,3-dioxygenase indoleamine (IDO-1, PDB: 2D0T) menunjukkan hasil dengan nilai yang berbeda. Energi afinitas ikatan yang didapatkan juga cukup berbeda, namun ligan memiliki konformasi yang sama dan mengikat residu yang sama dengan jarak ikatan yang sedikit berbeda. Kata kunci: Penambatan molekular, minimisasi energi, oksindola tersubstitusi, Merck Molecular Force Field 94

A Molecular Force Field-Based Optimal Deployment Algorithm for UAV Swarm Coverage Maximization in Mobile Wireless Sensor Network

In the mobile wireless sensor network (MWSN) field, there exists an important problem—how can we quickly form an MWSN to cover a designated working area on the ground using an unmanned aerial vehicle (UAV) swarm? This problem is of significance in many military and civilian applications. In this paper, inspired by intermolecular forces, a novel molecular force field-based optimal deployment algorithm for a UAV swarm is proposed to solve this problem. A multi-rotor UAV swarm is used to carry sensors and quickly build an MWSN in a designated working area. The necessary minimum number of UAVs is determined according to the principle that the coverage area of any three UAVs has the smallest overlap. Based on the geometric properties of a convex polygon, two initialization methods are proposed to make the initial deployment more uniform, following which, the positions of all UAVs are subsequently optimized by the proposed molecular force field-based deployment algorithm. Simulation experiment results show that the proposed algorithm, when compared with three existing algorithms, can obtain the maximum coverage ratio for the designated working area thanks to the proposed initialization methods. The probability of falling into a local optimum and the computational complexity are reduced, while the convergence rate is improved.

ESTUDO TEÓRICO DO ÁCIDO GIBERÉLICO: CARACTERIZAÇÃO CONFORMACIONAL, ELETRÔNICA E ADME

A indústria moderna utiliza-se dos produtos naturais para diversos fins, desde os alimentícios até os farmacêuticos. Muitas vezes a própria indústria é interessada na biossíntese de determinados compostos naturalmente disponíveis, sendo que certas propriedades físico-químicas não estão reportadas. Uma dessas biomoléculas é o ácido giberélico (GA3), que atua modificando a forma de vegetais e acelerando seu metabolismo, cuja biossíntese tem baixo rendimento. Nesse contexto, as técnicas computacionais auxiliam na predição de propriedades físico-químicas, dentre elas a técnica do campo de força clássico MMFF94 (do inglês Merck Molecular Force Field 94). Desse modo, o presente trabalho tem como objetivo realizar um estudo inicial de caracterização eletrônica e estrutural do GA3 através do método dos cálculos de campo de força clássico MMFF94. Os cálculos de química computacional realizados foram determinantes na obtenção das propriedades físico-químicas do GA3, além do cálculo do coeficiente de partição log P, cálculos esses essenciais para futuros testes de docking molecular ou dinâmica molecular. A otimização eletrônica e estrutural do GA3 atingiu o ponto de menor energia potencial mais estável de valor 100,087 kJ mol-1 através do algoritmo MMFF94. Deste modo, propõe-se uma metodologia de otimização molecular para futuras simulações in silico para docking molecular.