Title:Design of Novel Acat Inhibitors as Potent Anti-Hyperlipidemic Agents Using Chemometric Approaches
Volume: 21
Issue: 1
Author(s): Shagufta Khan, Sarvesh Paliwal, Smita Jain and Pragya Sharma*
Affiliation:
- Department of Pharmacy, Banasthali Vidyapith, Banasthali, Rajasthan, 304022, India
- Amity Institute of Pharmacy, Amity University Rajasthan, Jaipur, Rajasthan, 303002, India
Keywords:
QSAR, ACAT, FFNN, MLR, PLS, hypercholesterolemia.
Abstract:
Aim: A 2D QSAR study of acyl-coenzyme A (CoA): cholesterol acyltransferase (ACAT)
inhibitors revealed that electronic, topological, and steric properties are important structural features
required for activity against ACAT.
Background: In order to interpret the evidence encrypted by the molecular structure of the compounds,
a standard physicochemical descriptors-centered, and Quantitative Structure-Activity Relationship
(QSAR) approach was implemented on a data set of Indoline derivatives were reported to be
acyl-coenzyme A (CoA): cholesterol acyltransferase ACAT inhibitors.
Objective: The ACAT enzyme plays an important role in the absorption of dietary cholesterol. Therefore,
the inhibition of ACAT is a key strategy or primary objective for the treatment of hypercholesterolemia
and atherosclerosis.
Methods: Chemo metric models were designed by inserting a battery of statistical techniques in the
current study that demonstrate the linear approaches of analysis, including multiple linear regression
(MLR), partial least square PLS, and non-linear methods such as artificial neural networks (ANN).
Results: The activity contributions of these molecules were analyzed through regression equation,
and the best QSAR model was created with an excellent correlative and predictive ability. Significant
statistical values S = 0.35, F = 60.30, r = 0.92, r² = 0.85, r² (CV) = 0.82 of the designed models were
obtained using stepwise MLR and a comparable PLS and FFNN model with r² (CV) = 0.82, 0.88 and
0.86 respectively and the relevant descriptors like inertia moment 1 size, Kier Chiv4 (cluster) index,
Kier Chiv6(ring) index offered important information regarding this model.
Conclusion: The model reveals that inertia moment 1 size, Kier Chiv4 (cluster) index, and Kier
Chiv6 (ring) index are prerequisite descriptors to determine other promising ACAT antagonists with
high and liable potency against the target. Therefore, these characteristics may be used efficiently for
the design and evaluation of active compounds as new ACAT inhibitors thanks to their utilization.
