Introducing the Automated Ligand Searcher.

The Automated Ligand Searcher (ALISE) is designed as an automated computational drug discovery tool. To approximate the binding free energy of ligands to a receptor, ALISE includes a three-stage workflow, with each stage involving an increasingly sophisticated computational method: molecular docking, molecular dynamics, and free energy perturbation, respectively. To narrow the number of potential ligands, poorly performing ligands are gradually segregated out. The performance and usability of ALISE are benchmarked for a case study containing known active ligands and decoys for the HIV protease. The example illustrates that ALISE filters the decoys successfully and demonstrates that the automation, comprehensiveness, and user-friendliness of the software make it a valuable tool for improved and faster drug development workflows.

ATP-Bound State of the Uncoupling Protein 1 (UCP1) from Molecular Simulations.

The uncoupling protein 1 (UCP1) dissipates the transmembrane (TM) proton gradient in the inner mitochondrial membrane (IMM) by leaking protons across the membrane and producing heat in the process. Such a nonshivering production of heat in the brown adipose tissue can combat obesity-related diseases. UCP1-associated proton leak is activated by free fatty acids and inhibited by purine nucleotides. The mechanism of proton leak and the binding sites of the activators (fatty acids) remain unknown, while the binding site of the inhibitors (nucleotides) was described recently. Using molecular dynamics simulations, we generated a conformational ensemble of UCP1. Using metadynamics-based free energy calculations, we obtained the most likely ATP-bound conformation of UCP1. Our conformational ensemble provides a molecular basis for a breadth of prior biochemical data available for UCP1. Based on the simulations, we make the following testable predictions about the mechanisms of activation of proton leak and proton leak inhibition by ATP: (1) R277 plays the dual role of stabilizing ATP at the binding site for inhibition and acting as a proton surrogate for D28 in the absence of a proton during proton transport, (2) the binding of ATP to UCP1 is mediated by residues R84, R92, R183, and S88, (3) R92 shuttles ATP from the E191-R92 gate in the intermembrane space to the nucleotide binding site and serves to increase ATP affinity, (4) ATP can inhibit proton leak by controlling the ionization states of matrix facing lysine residues such as K269 and K56, and (5) fatty acids can bind to UCP1 from the IMM either via the cavity between TM1 and TM2 or between TM5 and TM6. Our simulations set the platform for future investigations into the proton transport and inhibition mechanisms of UCP1.

The molecular basis of the antidepressant action of the magic mushroom extract, psilocin.

Magic mushrooms, and their extract psilocybin, are well-known for their psychedelic properties and recreational use. Psilocin, the bio-active form of psilocybin, can potentially treat various psychiatric diseases. Psilocin putatively exerts its psychedelic effect as an agonist to the serotonin 2A receptor (5-HT2AR), which is also the receptor for the neurological hormone serotonin. The two key chemical differences between the two molecules are first, that the primary amine in serotonin is replaced with a tertiary amine in psilocin, and second, the hydroxyl group is substituted differently on the aromatic ring. Here, we find that psilocin can bind to 5-HT2AR with an affinity higher than serotonin, and provide the molecular logic behind the higher binding affinity of psilocin using extensive molecular dynamics simulations and free energy calculations. The binding free energy of psilocin is dependent upon the protonation states of the ligands, as well as that of the key residue in the binding site: Aspartate 155. We find that the tertiary amine of psilocin, and not the altered substitution of the hydroxyl group in the ring is responsible for the increased affinity of psilocin. We propose design rules for effective antidepressants based on molecular insights from our simulations.

Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations.

Drug design is a time-consuming and cumbersome process due to the vast search space of drug-like molecules and the difficulty of investigating atomic and electronic interactions. The present paper proposes a computational drug design workflow that combines artificial intelligence (AI) methods, i.e., an evolutionary algorithm and artificial neural network model, and molecular dynamics (MD) simulations to design and evaluate potential drug candidates. For the purpose of illustration, the proposed workflow was applied to design drug candidates against the main protease of severe acute respiratory syndrome coronavirus 2. From the ∼140,000 molecules designed using AI methods, MD analysis identified two molecules as potential drug candidates.

Inhibition Mechanism of Antimalarial Drugs Targeting the Cytochrome bc1 Complex.

Plasmodium falciparum (P. falciparum) is the main parasite known to cause malaria in humans. The antimalarial drug atovaquone is known to inhibit the Qo-site of the cytochrome bc1 complex of P. falciparum, which ultimately blocks ATP synthesis, leading to cell death. Through the years, mutations of the P. falciparum cytochrome bc1 complex, causing resistance to atovaquone, have emerged. The present investigation applies molecular dynamics (MD) simulations to study how the specific mutations Y279S and L282V, known to cause atovaquone resistance in malarial parasites, affect the inhibition mechanism of two known inhibitors. Binding free energy estimates were obtained through free energy perturbation calculations but were unable to confidently resolve the effects of mutations due to the great complexity of the binding environment. Meanwhile, basic mechanistic considerations from the MD simulations provide a detailed characterization of inhibitor binding modes and indicate that the Y279S mutation weakens the natural binding of the inhibitors, while no conclusive effect of the L282V mutation could be observed.