Structure-based discovery of small molecule APC-Asef interaction inhibitors: In silico approaches and molecular dynamics simulations

Colorectal cancer, which is considered one of the leading causes of mortality worldwide, develops through the formation of benign polyps on the inner colon or rectum wall. Truncations in adenomatous polyposis coli (APC) gene lead to the spread of the disease in the entire colon region when combined with the guanine nucleotide exchange factor (GEF) Asef. A series of peptidomimetic agents were previously discovered as protein-protein interaction inhibitors that can target the APC-Asef interface. Structure-based virtual screening (SBVS), using a set of docking methods combined with molecular dynamics simulations, was carried out to identify new small drug-like agents. After the initial screening process, compounds with diverse chemical scaffolds and direct interaction with Arg549 and other active site residues were chosen and subjected to induce fit. The amide functional group found in the ligand hit structures showed strong interactions with Arg549, leading to observable conformational changes that allow suitable positioning within the peptide binding site. Furthermore, the pH-specific MD simulations of the top hit 838 within the APC-Asef binding site depicted significant interactions required for biochemical recognition in changing microenvironment. Predicted inhibitory constant (Ki) values and binding free energies of hits further described the significance of the amide group over the other chemical scaffolds. This combination of in silico approaches provides key insights for colorectal drug discovery programs targeting the APC-Asef interaction. [Figure not available: see fulltext.] © 2020, Springer-Verlag GmbH Germany, part of Springer Nature

Structural and Functional Analysis of Dengue Virus Non-Structural Protein 5 (NS5) Using Molecular Dynamics

Dengue is an infection transmitted by the Aedes mosquito and is considered a major public health concern in many tropical and Asian countries, including the Philippines. It is caused by the dengue virus (DENV) which belongs to the Flaviviridae family and has four serotypes. The non-structural protein 5 (NS5), which consists of an MTase domain and an RdRp domain, is the largest and most conserved protein among flaviviruses and thus a potential target against DENV. However, there are very limited studies on the functional homodimer structure of NS5. Through molecular dynamics, it was found that residues 458–470, 583–586, 630–637, 743–744, and 890–900 of monomer A and residues 14–24, 311–315, and 462–464 of monomer B undergo essential motions for the conformational changes in the RdRp template tunnel and GTP binding in the MTase domain. Through the analysis of these motions, it was also proposed that in the dimeric structure of NS5 only one pair of domains contribute to the function of the protein. Other essential residues, specifically A-ASP533, A-LYS689, A-ARG620, A-ARG688, A-SER710, B-ARG620, B-LYS689, A-GLU40, A-ARG262, A-GLU267, A-ARG673, and B-ARG673, were also identified to play important roles in the information flow necessary for the function of the protein. In particular, shortest paths analysis led to the identification of ARG673 as an essential residue for the communication between RdRp and MTase catalytic sites. Mutation of this residue led to changes in the conformational flexibility of the RdRp finger subdomain, which may influence the RdRp catalytic function. These findings serve as a basis for future studies on the mechanism and inhibition of the NS5 dimer for dengue drug discovery

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field

In silico strategies in tuberculosis drug discovery

© 2020 by the authors. Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their “undruggable” binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery

N-terminus-independent activation of c-Src via binding to a tetraspan(in) TM4SF5 in hepatocellular carcinoma is abolished by the TM4SF5 C-terminal peptide application

Active c-Src non-receptor tyrosine kinase localizes to the plasma membrane via N-terminal lipid modification. Membranous c-Src causes cancer initiation and progression. Even though transmembrane 4 L six family member 5 (TM4SF5), a tetraspan(in), can be involved in this mechanism, the molecular and structural influence of TM4SF5 on c-Src remains unknown. Methods: Here, we investigated molecular and structural details by which TM4SF5 regulated c-Src devoid of its N-terminus and how cell-penetrating peptides were able to interrupt c-Src activation via interference of c-Src-TM4SF5 interaction in hepatocellular carcinoma models. Results: The TM4SF5 C-terminus efficiently bound the c-Src SH1 kinase domain, efficiently to the inactively-closed form. The complex involved protein tyrosine phosphatase 1B able to dephosphorylate Tyr530. The c-Src SH1 domain alone, even in a closed form, bound TM4SF5 to cause c-Src Tyr419 and FAK Y861 phosphorylation. Homology modeling and molecular dynamics simulation studies predicted the directly interfacing residues, which were further validated by mutational studies. Cell penetration of TM4SF5 C-terminal peptides blocked the interaction of TM4SF5 with c-Src and prevented c-Src-dependent tumor initiation and progression in vivo. Conclusions: Collectively, these data demonstrate that binding of the TM4SF5 C-terminus to the kinase domain of inactive c-Src leads to its activation. Because this binding can be abolished by cell-penetrating peptides containing the TM4SF5 C-terminus, targeting this direct interaction may be an effective strategy for developing therapeutics that block the development and progression of hepatocellular carcinoma.Y