Application of molecular docking and PSO-SVR intelligent approaches in antimalarial activity prediction of enantiomeric cycloguanil analogues

Structure- and ligand-based drug design methods for the modeling of antimalarial agents: a review of updates from 2012 onwards

Malaria still persists as one of the deadliest infectious disease having a huge morbidity and mortality affecting the higher population of the world. Structure and ligand-based drug design methods like molecular docking and MD simulations, pharmacophore modeling, QSAR and virtual screening are widely used to perceive the accordant correlation between the antimalarial activity and property of the compounds to design novel dominant and discriminant molecules. These modeling methods will speed-up antimalarial drug discovery, selection of better drug candidates for synthesis and to achieve potent and safer drugs. In this work, we have extensively reviewed the literature pertaining to the use and applications of various ligand and structure-based computational methods for the design of antimalarial agents. Different classes of molecules are discussed along with their target interactions pattern, which is responsible for antimalarial activity. Communicated by Ramaswamy H. Sarma.

Recent advances in quantitative structure-activity relationship models of antimalarial drugs

INTRODUCTION

Due to emerging resistance to the first-line artemisinin-based antimalarials and lack of efficient vaccines and limited chemotherapeutic alternatives, there is an urgent need to develop new antimalarial compounds. In this regard, quantitative structure-activity relationship (QSAR) modeling can provide essential information about required physicochemical properties and structural parameters of antimalarial drug candidates.

AREAS COVERED

The authors provide an overview of recent advances of QSAR models covering different classes of antimalarial compounds as well as molecular docking studies of compounds acting on different antimalarial targets reported in the last 5 years (2015-2019) to explore the mode of interactions between the molecules and the receptors. We have tried to cover most of the QSAR models of antimalarials (along with results from some other related computational methods) reported during 2015-2019.

EXPERT OPINION

Many QSAR reports for antimalarial compounds are based on small number of data points. This review infers that most of the present work deals with analog-based QSAR approach with a limited applicability domain (a very few cases with wide domain) whereas novel target-based computational approach is reported in very few cases, which leads to huge voids of computational work based on novel antimalarial targets.

Toxicity profiling and prioritization of plant-derived antimalarial agents

Human malaria is the most widespread mosquito-borne life-threatening disease worldwide. In the absence of effective vaccines, prevention and treatment of malaria only depend on prophylaxis and drug-based therapy either in monotherapy or in combination. Unfortunately, the number of available antimalarial drugs presenting different mechanisms of action is rather limited. In addition, the appearance of drug-resistance in the parasite strains impacts the efficacy of the treatments. As a result, there is a crucial need to find new drugs to circumvent resistance problems. In the quest to identify new antimalarial agents a huge number of plant-derived compounds (PDCs) have been investigated. Surprisingly in the in silico PDC screening programs, toxicity filters are either never used or so simple that their interest is limited. In this context, the goal of this study was to show how to take advantage of validated toxicity QSAR models for refining the selection of PDCs. From an original data set of 507 PDCs collected from the literature, the use of toxicity filters for endocrine disruption, developmental toxicity, and hepatotoxicity in conjunction with classical pharmacokinetic filters allowed us to obtain a list of 31 compounds of potential interest. The pros and cons of such a strategy have been discussed.

Molecular docking, design, synthesis and biological evaluation of novel 2,3-aryl-thiazolidin-4-ones as potent NNRTIs

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) remain the most promising anti-AIDS agents that target the HIV-1 reverse transcriptase enzyme (RT). However, the efficiency of approved NNRTI drugs has decreased by the appearance of drug-resistant viruses and side effects upon long-term usage. Thus, there is an urgent need for developing new, potent NNRTIs with broad spectrum against HIV-1 virus and with improved properties. In this study, a series of thiazolidinone derivatives was designed based on a butterfly mimicking scaffold consisting of a substituted benzothiazolyl moiety connected with a substituted phenyl ring via a thiazolidinone moiety. The most promising derivatives were selected using molecular docking analysis and PASS prediction program, synthesized and evaluated for HIV-1 RT inhibition. Five out of fifteen tested compounds exhibited good inhibitory action. It was observed that the presence of Cl or CN substituents at the position 6 of the benzothiazole ring in combination with two fluoro atoms at the ortho-positions or a hydrogen acceptor substituent at the 4-position of the phenyl ring are favourable for the HIV RT inhibitory activity.