Implementation of gradient gravitational search algorithm towards conformational search

Conformational Search for the Building Block of Proteins Based on the Gradient Gravitational Search Algorithm (ConfGGS) Using Force Fields: CHARMM, AMBER, and OPLS-AA

“…The computed MSD values are obtained to be 0.31, 0.24, and 0.30 using the CHARMM, AMBER, and OPLS-AA force fields, respectively. It has been mentioned earlier that the GGS algorithm outperforms the considered algorithms based on the lowest MAE and MSD values computed for the dihedral angle of the respective near-optimal solution . In line with the efficiency of the GGS algorithm toward conformational search, the present investigation of the ConfGGS technique using three different force fields also provide good results compared to other considered simulation methods with regard to a small number of iteration steps, low computational cost, and low MAE and MSD values.…”

“…It has been mentioned earlier that the GGS algorithm outperforms the considered algorithms based on the lowest MAE and MSD values computed for the dihedral angle of the respective near-optimal solution. 14 In line with the efficiency of the GGS algorithm toward conformational search, the present investigation of the ConfGGS technique using three different force fields also provide good results compared to other considered simulation methods with regard to a small number of iteration steps, low computational cost, and low MAE and MSD values. The possible explanation of the performance of different force field parameters may be the complexity and accuracy of parameterized individual data sets.…”

“…), or coupled cluster methods (e.g., CCSD­(T)). Contradictorily, force fields are currently the alternative and reliable methods to be implemented with efficient optimization algorithms that can be invariably used for conformational searches within a practical time frame , toward protein structure prediction, since they ignore electronic motions and compute the energy of the considered system as a function of the nuclear coordinates only, based on the Born–Oppenheimer approximation. The contributions due to bonded and nonbonded interactions within the systems such as bond stretching, bending of angles and rotations about single bonds, which alters the dihedral angles, electrostatic interactions, and van der Waals interactions are included in the potential energy function.…”

In-silico approaches towards development of model irreversible HIV-1 protease inhibitors

“…The in-silico approaches include (i) minimization of structure for the considered model aziridine based inhibitors by using ConfGGS/CHARMM [44,45]. Such techniques considered energy minimization using Cartesian coordinates along with their respective connectivity through bonds, angles and dihedral angles in the potential energy function.…”

“…The in-silico approaches in the present investigation includes, (i) ConfGGS [44,45] towards structure minimization of model aziridine based inhibitors (ii) Molecular Docking towards predicting the best match between model aziridine based inhibitors and HIV-1 PR, (iii) Covalent Docking towards exploring the binding affinity for the covalent interaction between model aziridine based inhibitors and HIV-1 PR (iv) MD Simulation of free enzyme HIV-1 PR and complex with the model aziridine based inhibitors to test and check the quality for the description of inhibition process (v) QM/MM computation to understand the inhibition potency and inhibition reaction at molecular level. Furthermore, ConfGGS/CHARMM has also been used to optimize the reactants and products, obtained from QM/MM computations.…”