Ramaswamy Nilakantan

New method for rapid characterization of molecular shapes: applications in drug design

We present a method for the rapid quantitative shape match between two molecules or a molecule and a template, using atom triplets as descriptors. This technique can be used either as a rapid screen preceding the computationally expensive shape-based docking method developed by Kuntz and co-workers or as a stand-alone method to rank compounds in a large database for their fit to a shape template. The merits and limitations of this method are discussed in detail with examples.

Database diversity assessment: New ideas, concepts, and tools

We present some new ideas for characterizing and comparing largechemical databases. The comparison of the contents of large databases is nottrivial since it implies pairwise comparison of hundreds of thousands ofcompounds. We have developed methods for categorizing compounds into groupsor series based on their ring-system content, using precalculatedstructure-based hashcodes. Two large databases can then be compared bysimply comparing their hashcode tables. Furthermore, the number of distinctring-system combinations can be used as an indicator of database diversity.We also present an indepen- dent technique for diversity assessment calledthe ’saturation diversity‘ approach. This method is based on picking as manymutually dissimilar compounds as possible from a database or a subsetthereof. We show that both methods yield similar results. Since the twomethods measure very different properties, this probably says more about theproperties of the databases studied than about the methods.

CONFIRM: connecting fragments found in receptor molecules

A novel algorithm for the connecting of fragment molecules is presented and validated for a number of test systems. Within the CONFIRM (Connecting Fragments Found in Receptor Molecules) approach a pre-prepared library of bridges is searched to extract those which match a search criterion derived from known experimental or computational binding information about fragment molecules within a target binding site. The resulting bridge ‘hits’ are then connected, in an automated fashion, to the fragments and docked into the target receptor. Docking poses are assessed in terms of root-mean-squared deviation from the known positions of the fragment molecules, as well as docking score should known inhibitors be available. The creation of the bridge library, the full details and novelty of the CONFIRM algorithm, and the general applicability of this approach within the field of fragment-based de novo drug design are discussed.

A Novel Approach to Combinatorial Library Design

We address the problem of designing a general-purpose combinatorial library to screen for pharmaceutical leads. Conventional approaches focus on diversity as the primary factor in designing such libraries. We suggest making screening libraries out of a set of pharmaceutically relevant scaffolds, with multiple analogs per scaffold. The rationale for this rests on the fact that even though the hit-rate in active series is much higher than in the database as a whole, often a large fraction of the compounds in active series are inactive. This is especially true when the series has not been optimized for the target under study. We introduce the concept of hit-rate within a series and use historic screening data to arrive at a crude estimate for it. We then use simple probability arguments to show that 50-100 compounds are required in each series in order to be nearly certain of finding at least one active compound in each true active series for any given target.

A method for automatic generation of novel chemical structures and its potential applications to drug discovery

A novel method for generation of chemical structures of potential pharmaceutical interest is presented. Structures are generated by random combination of known fragments and selected by statistical topological techniques. The power of the method lies in the great profusion of candidates generated together with the extremely high selectivity imposed by the techniques of selection.

A family of ring system-based structural fragments for use in structure-activity studies: database mining and recursive partitioning.

In earlier work from our laboratory, we have described the use of the ring system and ring scaffold as descriptors. We showed that these descriptors could be used for fast compound clustering, novelty determination, compound acquisition, and combinatorial library design. Here we extend the concept to a whole family of structural descriptors with the ring system as the centerpiece. We show how this simple idea can be used to build powerful search tools for mining chemical databases in useful ways. We have also built recursive partition trees using these fragments as descriptors. We will discuss how these trees can help in analyzing complex structure-activity data.

A structural informatics approach to mine kinase knowledge bases

In this paper, we describe a combination of structural informatics approaches developed to mine data extracted from existing structure knowledge bases (Protein Data Bank and the GVK database) with a focus on kinase ATP-binding site data. In contrast to existing systems that retrieve and analyze protein structures, our techniques are centered on a database of ligand-bound geometries in relation to residues lining the binding site and transparent access to ligand-based SAR data. We illustrate the systems in the context of the Abelson kinase and related inhibitor structures.

A Protein Relational Database and Protein Family Knowledge Bases to Facilitate Structure-Based Design Analyses

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom–atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid–centroid and centroid–atom distances and angles have also been included permitting queries for π‐stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

A New Method for Unbiased Comparison of Protein Structures

While there exist several excellent algorithms for protein sequence comparison, the comparison of protein structures is more difficult This paper presents a method for a sequence-independent, unbiased comparison of protein structures. The method treats each protein as a collection of a carbons without any regard to sequence or chain-connectivity. Heuristics are used to select a series of subsets of atoms in each of the protein structures. These subsets of atoms are then compared using a subgraph-isomorphism search technique. Partial matches thus obtained are then used to superpose one protein onto the other. A simple scoring function is then used to determine the validity of the match This method has been applied to a set of about 100 diverse proteins. Several proteins known to have similar structures were identified by the method A few protein-pairs not widely recognized to have structural similarities were also identified.