Target the More Druggable Protein States in a Highly Dynamic Protein--Protein Interaction System

Identification of novel compounds and repurposing of FDA drugs for 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme of Plasmodium falciparum to combat malaria resistance

The rise of Plasmodium falciparum resistance to Artemisinin-based combination therapies (ACTs) is a significant concern in the fight against malaria. This situation calls for the search for novel anti-malarial candidates. 1-deoxy-D-xylulose 5-phosphate reductoisomerase (IspC) is a potential target involved in various cellular processes in P. falciparum (Pf). We screened ∼0.69 billion novel compounds from the ZINC20 library and repurposed ∼1400 FDA drugs using computational drug discovery methods against PfIspC. Following our computational pipeline, we found five novel ZINC20 compounds (Z-2, Z-3, Z-10, Z-13, and Z-14) and three FDA drugs (Aliskiren, Ceftolozane, and Ombitasvir) that showed striking docking energy (ranging from -8.405 to -10.834 kcal/mol), and strong interactions with key binding site residues (Ser269, Ser270, Ser306, Asn311, Lys312, and Met360) of PfIspC. The novel anti-malarial compounds also exhibited favorable pharmacokinetics and physicochemical properties. Furthermore, through molecular dynamics simulation, we observed the stable dynamics of PfIspC-inhibitor complexes and the influence of inhibitor binding on the protein's conformational arrangements. Notably, the binding free energy estimation confirmed high binding affinity (varied from -11.68 to -33.16 kcal/mol) of these compounds for PfIspC. Our findings could contribute to the ongoing efforts in combating malaria and invite experimental-lab researchers for validation.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.

Revisiting biomolecular NMR spectroscopy for promoting small-molecule drug discovery

Recently, there has been increasing interest in new modalities such as therapeutic antibodies and gene therapy at a number of pharmaceutical companies. Moreover, in small-molecule drug discovery at such companies, efforts have focused on hard-to-drug targets such as inhibiting protein-protein interactions. Biomolecular NMR spectroscopy has been used in drug discovery in a variety of ways, such as for the reliable detection of binding and providing three-dimensional structural information for structure-based drug design. The advantages of using NMR spectroscopy have been known for decades (Jahnke in J Biomol NMR 39:87-90, (2007); Gossert and Jahnke in Prog Nucl Magn Reson Spectrosc 97:82-125, (2016)). For tackling hard-to-drug targets and increasing the success in discovering drug molecules, in-depth analysis of drug-target protein interactions performed by biophysical methods will be more and more essential. Here, we review the advantages of NMR spectroscopy as a key technology of biophysical methods and also discuss issues such as using cutting-edge NMR spectrometers and increasing the demand of utilizing conformational dynamics information for promoting small-molecule drug discovery.

Impact of lymphoma-linked Asn11Tyr point mutation on the interaction between Bcl-2 and a BH3 mimetic: Insights from molecular dynamics simulation

Frequent mutations in the Bcl-2 anti-apoptotic protein are often implicated in diffuse large B-cell lymphoma (DLBCL), a disease profoundly resistant to drugs. Bcl-2-competitive inhibitors, "BH3 mimetics," activate apoptosis by interfering with the interactions between pro-apoptotic BH3 domains and the hydrophobic groove of Bcl-2. The aim of our research is to determine the potential of DLBCL-linked N11Y mutation to facilitate resistance against a "BH3 mimetic" using molecular dynamics simulation. Binding free energy calculations suggest a significant decrease in the binding affinity in the mutant model. In-depth analysis of the models using residue interaction network, dynamic cross-correlation, and free energy landscape approaches reveal that the mutation modifies the conformations of key residues, thereby altering the shape of the hydrophobic groove. This subsequently changes the ligand orientation and counteracts the phenomenon of LB region unwinding, a crucial event observed in the wild-type model. Lowest frequency motions captured by principal component analysis reflect the stretching of the groove for efficient ligand accommodation in the wild-type complex but not in the mutant model. This is the first in silico study that unravels the mechanism of drug resistance induced by a Bcl-2 mutation, which could be of great relevance while designing and tailoring therapeutics.

Regulator of G-protein signaling (RGS) proteins as drug targets: Progress and future potentials

G protein-coupled receptors (GPCRs) play critical roles in regulating processes such as cellular homeostasis, responses to stimuli, and cell signaling. Accordingly, GPCRs have long served as extraordinarily successful drug targets. It is therefore not surprising that the discovery in the mid-1990s of a family of proteins that regulate processes downstream of GPCRs generated great excitement in the field. This finding enhanced the understanding of these critical signaling pathways and provided potentially new targets for pharmacological intervention. These regulators of G-protein signaling (RGS) proteins were viewed by many as nodes downstream of GPCRs that could be targeted with small molecules to tune signaling processes. In this review, we provide a brief overview of the discovery of RGS proteins and of the gradual and continuing discovery of their roles in disease states, focusing particularly on cancer and neurological disorders. We also discuss high-throughput screening efforts that have led to the discovery first of peptide-based and then of small-molecule inhibitors targeting a subset of the RGS proteins. We explore the unique mechanisms of RGS inhibition these chemical tools have revealed and highlight the most up-to-date studies using these tools in animal experiments. Finally, we discuss the future opportunities in the field, as there are clearly more avenues left to be explored and potentials to be realized.

Protein ensembles link genotype to phenotype

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.

Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein

High-risk strains of human papillomavirus (HPV) have been identified as the etiologic agent of some anogenital tract, head, and neck cancers. Although prophylactic HPV vaccines have been approved; it is still necessary a drug-based treatment against the infection and its oncogenic effects. The E6 oncoprotein is one of the most studied therapeutic targets of HPV, it has been identified as a key factor in cell immortalization and tumor progression in HPV-positive cells. E6 can promote the degradation of p53, a tumor suppressor protein, through the interaction with the cellular ubiquitin ligase E6AP. Therefore, preventing the formation of the E6-E6AP complex is one of the main strategies to inhibit the viability and proliferation of infected cells. Herein, we propose an in silico pipeline to identify small-molecule inhibitors of the E6-E6AP interaction. Virtual screening was carried out by predicting the ADME properties of the molecules and performing ensemble-based docking simulations to E6 protein followed by binding free energy estimation through MM/PB(GB)SA methods. Finally, the top-three compounds were selected, and their stability in the E6 docked complex and their effect in the inhibition of the E6-E6AP interaction was corroborated by molecular dynamics simulation. Therefore, this pipeline and the identified molecules represent a new starting point in the development of anti-HPV drugs.

Rational design and structure–activity relationship studies of quercetin–amino acid hybrids targeting the anti-apoptotic protein Bcl-xL

Anti-apoptotic proteins, like the Bcl-2 family proteins, present an important therapeutic cancer drug target.