Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.

Protein-ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multitarget interactions are the first step in finding an effective therapeutic, while undesirable off-target interactions are the first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets and to project novel drugs into a hybrid protein-ligand feature space to identify their likely protein interactions.

Discovery of Small-Molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline.

A rapid response is necessary to contain emergent biological outbreaks before they can become pandemics. The novel coronavirus (SARS-CoV-2) that causes COVID-19 was first reported in December of 2019 in Wuhan, China and reached most corners of the globe in less than two months. In just over a year since the initial infections, COVID-19 infected almost 100 million people worldwide.

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.

Predicting accurate protein-ligand binding affinities is an important task in drug discovery but remains a challenge even with computationally expensive biophysics-based energy scoring methods and state-of-the-art deep learning approaches. Despite the recent advances in the application of deep convolutional and graph neural network-based approaches, it remains unclear what the relative advantages of each approach are and how they compare with physics-based methodologies that have found more mainstream success in virtual screening pipelines. We present fusion models that combine features and inference from complementary representations to improve binding affinity prediction.

System-level analysis of metabolic trade-offs during anaerobic photoheterotrophic growth in Rhodopseudomonas palustris.

Background: Living organisms need to allocate their limited resources in a manner that optimizes their overall fitness by simultaneously achieving several different biological objectives. Examination of these biological trade-offs can provide invaluable information regarding the biophysical and biochemical bases behind observed cellular phenotypes. A quantitative knowledge of a cell system's critical objectives is also needed for engineering of cellular metabolism, where there is interest in mitigating the fitness costs that may result from human manipulation.

Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study.

Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored.

Exon 14 Mutation Encodes an Actionable Therapeutic Target in Lung Adenocarcinoma.

Targeting somatically activated oncogenes has revolutionized the treatment of non-small cell lung cancer (NSCLC). Mutations in the gene mesenchymal-epithelial transition () near the exon 14 splice sites are recurrent in lung adenocarcinoma and cause exon skipping (Δ14). Here, we analyzed 4,422 samples from 12 different malignancies to estimate the rate of said exon skipping.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER.

A method to predict blood-brain barrier permeability of drug-like compounds using molecular dynamics simulations.

The blood-brain barrier (BBB) is formed by specialized tight junctions between endothelial cells that line brain capillaries to create a highly selective barrier between the brain and the rest of the body. A major problem to overcome in drug design is the ability of the compound in question to cross the BBB. Neuroactive drugs are required to cross the BBB to function.

Developing an approach for first-principles catalyst design: application to carbon-capture catalysis.

An approach to catalyst design is presented in which local potential energy surface models are first built to elucidate design principles and then used to identify larger scaffold motifs that match the target geometries. Carbon sequestration via hydration is used as the model reaction, and three- and four-coordinate sp(2) or sp(3) nitrogen-ligand motifs are considered for Zn(II) metals. The comparison of binding, activation and product release energies over a large range of interaction distances and angles suggests that four-coordinate short Zn(II)-Nsp(3) bond distances favor a rapid turnover for CO2 hydration.

Understanding a substrate's product regioselectivity in a family of enzymes: a case study of acetaminophen binding in cytochrome P450s.

Product regioselectivity as influenced by molecular recognition is a key aspect of enzyme catalysis. We applied large-scale two-dimensional (2D) umbrella sampling (USP) simulations to characterize acetaminophen (APAP) binding in the active sites of the family of Cytochrome P450 (CYP) enzymes as a case study to show the different regioselectivity exhibited by a single substrate in comparative enzymes. Our results successfully explain the experimentally observed product regioselectivity for all five human CYPs included in this study, demonstrating that binding events play an important role in determining regioselectivity.

Tricyclic GyrB/ParE (TriBE) inhibitors: a new class of broad-spectrum dual-targeting antibacterial agents.

Increasing resistance to every major class of antibiotics and a dearth of novel classes of antibacterial agents in development pipelines has created a dwindling reservoir of treatment options for serious bacterial infections. The bacterial type IIA topoisomerases, DNA gyrase and topoisomerase IV, are validated antibacterial drug targets with multiple prospective drug binding sites, including the catalytic site targeted by the fluoroquinolone antibiotics. However, growing resistance to fluoroquinolones, frequently mediated by mutations in the drug-binding site, is increasingly limiting the utility of this antibiotic class, prompting the search for other inhibitor classes that target different sites on the topoisomerase complexes.

Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment.

In this work we announce and evaluate a high throughput virtual screening pipeline for in-silico screening of virtual compound databases using high performance computing (HPC). Notable features of this pipeline are an automated receptor preparation scheme with unsupervised binding site identification. The pipeline includes receptor/target preparation, ligand preparation, VinaLC docking calculation, and molecular mechanics/generalized Born surface area (MM/GBSA) rescoring using the GB model by Onufriev and co-workers [J.

Molecular recognition of aromatic rings by flavin: electrostatics and dispersion determine ring positioning above isoalloxazine.

Aromatic stacking interactions between isoalloxazine (ISA) of flavin and three prototypical aromatics (benzene, pyridine, chlorobenzene) were investigated using electronic structure calculations with Monte Carlo simulated annealing. The Effective Fragment Potential (EFP) method was used to locate the low-energy equilibrium configurations for the three dimer systems. These structures were further characterized through DFT (M06-2X) and MP2 calculations.

Comparison and analysis of zinc and cobalt-based systems as catalytic entities for the hydration of carbon dioxide.

In nature, the zinc metalloenzyme carbonic anhydrase II (CAII) efficiently catalyzes the conversion of carbon dioxide (CO2) to bicarbonate under physiological conditions. Many research efforts have been directed towards the development of small molecule mimetics that can facilitate this process and thus have a beneficial environmental impact, but these efforts have met very limited success. Herein, we undertook quantum mechanical calculations of four mimetics, 1,5,9-triazacyclododedacane, 1,4,7,10-tetraazacyclododedacane, tris(4,5-dimethyl-2-imidazolyl)phosphine, and tris(2-benzimidazolylmethyl)amine, in their complexed form either with the Zn(2+) or the Co(2+) ion and studied their reaction coordinate for CO2 hydration.

Rapid catalytic template searching as an enzyme function prediction procedure.

We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues--The Catalytic Site Atlas (CSA).

Computational Analysis of a Zn-Bound Tris(imidazolyl) Calix[6]arene Aqua Complex: Toward Incorporating Second-Coordination Sphere Effects into Carbonic Anhydrase Biomimetics.

Molecular dynamics simulations and quantum-mechanical calculations were performed to characterize a supramolecular tris(imidazolyl) calix[6]arene Zn(2+) aqua complex, as a biomimetic model for the catalyzed hydration of carbon dioxide to bicarbonate, H2O + CO2 → H(+) + HCO3(-). On the basis of potential-of-mean-force (PMF) calculations, stable conformations had distorted 3-fold symmetry and supported either one or zero encapsulated water molecules. The conformation with an encapsulated water molecule is calculated to be lower in free energy than the conformation with an empty cavity (ΔG = 1.

Pyrrolopyrimidine inhibitors of DNA gyrase B (GyrB) and topoisomerase IV (ParE). Part I: Structure guided discovery and optimization of dual targeting agents with potent, broad-spectrum enzymatic activity.

The bacterial topoisomerases DNA gyrase (GyrB) and topoisomerase IV (ParE) are essential enzymes that control the topological state of DNA during replication. The high degree of conservation in the ATP-binding pockets of these enzymes make them appealing targets for broad-spectrum inhibitor development. A pyrrolopyrimidine scaffold was identified from a pharmacophore-based fragment screen with optimization potential.

Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines.

A mixed parallel scheme that combines message passing interface (MPI) and multithreading was implemented in the AutoDock Vina molecular docking program. The resulting program, named VinaLC, was tested on the petascale high performance computing (HPC) machines at Lawrence Livermore National Laboratory. To exploit the typical cluster-type supercomputers, thousands of docking calculations were dispatched by the master process to run simultaneously on thousands of slave processes, where each docking calculation takes one slave process on one node, and within the node each docking calculation runs via multithreading on multiple CPU cores and shared memory.

Pyrrolopyrimidine inhibitors of DNA gyrase B (GyrB) and topoisomerase IV (ParE), Part II: development of inhibitors with broad spectrum, Gram-negative antibacterial activity.

The structurally related bacterial topoisomerases DNA gyrase (GyrB) and topoisomerase IV (ParE) have long been recognized as prime candidates for the development of broad spectrum antibacterial agents. However, GyrB/ParE targeting antibacterials with spectrum that encompasses robust Gram-negative pathogens have not yet been reported. Using structure-based inhibitor design, we optimized a novel pyrrolopyrimidine inhibitor series with potent, dual targeting activity against GyrB and ParE.

Approaches to efficiently estimate solvation and explicit water energetics in ligand binding: the use of WaterMap.

Introduction: Water displacement plays critical role in several phases of drug discovery. Proper treatment of displacing water could improve enrichment in virtual screening and could lead to more successes in lead optimization. WaterMap has recently emerged as a promising approach in this regard; recent implementations of this protocol successfully explained various binding activity that were poorly understood previously, including the well-known super affinity associated with biotin binding to streptavidin.

Toward a small molecule, biomimetic carbonic anhydrase model: theoretical and experimental investigations of a panel of zinc(II) aza-macrocyclic catalysts.

A panel of five zinc-chelated aza-macrocycle ligands and their ability to catalyze the hydration of carbon dioxide to bicarbonate, H(2)O + CO(2) → H(+) + HCO(3)(–), was investigated using quantum-mechanical methods and stopped-flow experiments. The key intermediates in the reaction coordinate were optimized using the M06-2X density functional with aug-cc-pVTZ basis set. Activation energies for the first step in the catalytic cycle, nucleophilic CO(2) addition, were calculated from gas-phase optimized transition-state geometries.

Leveraging structural information for the discovery of new drugs: computational methods.

Escalating problems with drug resistance continue to compromise the effectiveness of commercial antibiotics, necessitating the search for novel classes of antimicrobial agents. To circumvent problems with resistance, a multitarget single-pharmacophore approach has been employed to discover inhibitors that possess balanced activity against multiple target enzymes. In this chapter, we examine the application of computational techniques, in particular, structure-based drug design approaches, to design new dual-targeting antibacterial agents against bacterial topoisomerases.

Effects of somatic mutations on CDR loop flexibility during affinity maturation.

Prior studies suggest that antibody affinity maturation is achieved, in part, via prearranging the CDRs for binding. The implication is that the entropy cost of binding is reduced and that this rigidification occurs as a consequence of somatic mutations during maturation. However, how these mutations modulate CDR flexibility is unclear.

Accounting for water molecules in drug design.

Importance Of The Field: Water molecules often appear around ligands in protein crystal structures. Reliable prediction of the effects of water on ligand binding remains a challenge. Solvation effects are crucial for lead optimization where a 100-fold difference in binding affinity is significant but correspond to only ∼3 kcal/mol in binding free energy.